By: Kristina Feghali and Douglas A. Granger

If you are interested in the relationship between stress, biology, and behavior, you are probably aware of how salivary cortisol has been integrated into applied research to represent the activity of the hypothalamic-pituitary-adrenal axis (HPA) component of the psychobiology of the stress response. Generally summarizing, cortisol levels increase in response to novelty when situations are unfamiliar, and the individual has minimal prior experience to respond and adapt. Higher cortisol levels are also associated with social withdrawal, negative affect, and psychological distress. The literature documenting these associations is extensive.

So much research effort has been focused on cortisol as a measure of stress that the key role cortisol plays in metabolism has been overlooked in many of these publications. Cortisol’s role in metabolism provides important mechanistic connectivity to health and disease. Incorporating these relationships into studies of salivary cortisol, stress, and behavior translates basic descriptive work into high-impact, meaningful outcomes.


Any search engine will summarize these relationships, so only a short teaser is provided here. Cortisol’s primary role in physiology is to mobilize glucose into the circulation from energy stores. Cortisol provides the body with glucose through the process of gluconeogenesis in the liver. Indeed, when cortisol rises in response to stress, the primary reason is to raise glucose levels that enable the individual to have the energy to respond to the immediate challenge. Having chronically high cortisol levels can reduce the effectiveness of insulin in lowering blood sugar and lead to insulin resistance, hyperglycemia, and risk for type 2 diabetes. Including measures of glucose and insulin in studies of salivary cortisol reactivity and recovery from stress seems well justified.

The main function of insulin is to enable cells to absorb glucose from the blood. The development of insulin resistance necessitates an increase in insulin production to sustain healthy blood sugar levels.

Figure 1: Healthy salivary insulin reactivity and recovery to ingestion of 35g sugar. Timing started immediately after glucose was ingested.

Insulin functions to store and use energy, while cortisol functions to rapidly gain access to energy. Cortisol can reduce the effectiveness of insulin, which makes sense because the body is working to create energy, and the last thing it needs is insulin to reduce it. Lowering cortisol through stress management and other methods may help regulate insulin secretion and blood glucose levels.


Does anybody suspect that the cognitive and behavioral correlates of cortisol responses to stress might be mediated by cortisol-induced changes in glucose? Has anyone considered that the magnitude of the cortisol response to a stressor might be moderated by glucose levels or insulin levels pre-challenge? Has anybody included hyper or hypo-glycemia or -insulinemia as blocking or exclusionary variables in their studies of salivary cortisol reactivity and recovery to stress?

For the past five years, Salimetrics has been working on methods to enable the measurement of glucose and insulin in saliva. Our goal is to enable the integration of these measures in future studies in an effort to advance our understanding of the literature linking stress, salivary cortisol, and behavior in important ways. For instance, this literature consistently reveals that individual differences are the norm rather than the exception. We hypothesize this is partially due to incomplete operationalization of cortisol biology. Incorporating insulin and glucose in the next generation of our measurement models should enable us to test links between salivary cortisol and specific and important issues (i.e., diabetes) affecting human health and development.

Is it possible that the salivary cortisol literature has focused too narrowly on cortisol as an index of stress? We encourage research teams to think so, and we encourage integrating a more comprehensive understanding of cortisol biology into the next generation of studies.


Let us share our expertise with you. Let us connect you to others who are already engaged in this effort. Let us provide the tools and support you need to develop and test research questions related to this important issue. Take a minute and explore the wide range of funding opportunities, public and private, afforded to you by expanding your research focus in this direction.


By: Kristina Feghali and Douglas A. Granger

Commentary from Douglas Granger

How many times has your attention been drawn to a headline about a new scientific discovery or a solution to a salient societal or health problem? It happens so frequently that I can’t even recall the exact number. Yet, each time, I find myself eagerly tuning in to hear scientists expound on their ideas, methodologies, and findings. The research enterprise is so important, and it’s the engine for advancing theory, building knowledge, developing plans and policies, and solving problems.


During my recent commute, I was caught off guard when a story I was listening to ended with the statement by the scientist being interviewed, which was repeated by the journalist, that “more research is needed.” Since then, I’ve noticed that this phrase is frequently used, and headlines often overstate scientific conclusions.

On the headline-generating side of this story, perhaps this is a function of the era we live in. The headline is a tool to capture our attention. These days, academics are even coached by campus personnel in ways to showcase their findings with journalists who influence the content of these headlines in the popular press and social media.

More often than not, these interviews or podcasts end with the scientist or the interviewer mentioning multiple caveats that qualify any conclusions. In contrast to the headline, the concluding statements are more tentative, less definitive, and qualified by study limitations. They are often followed by the interviewer or scientist announcing, “More research is needed.”

Scientifically, this seems appropriate. It’s not really a “bait and switch” operation. The scientist is being cautious not to over-interpret the observations. Scientists must be cautious about over-interpreting the findings of any single study because the next study may reveal evidence to the contrary. This is the world of academia where more research will always be needed because each major advance reveals the next set of important questions to address.


Consider how refreshing it would be if study outcomes enabled definitive conclusions, clearly answered the questions they set out to study, and made specific recommendations that were generalizable.

When investigators can do so, it enables them to efficiently move on to the next step in the process of developing knowledge in the field. When they cannot, it’s a bit like an academic treadmill or perhaps similar to the progress afforded in the “one-step forward, two-step back” scenario. When observations answer questions clearly, the publications that present these findings are high-impact. When the outcomes are clear, the observations tee up the next specific aims and research questions that build the foundation of the next grant proposals. When the outcomes are clear, fellows and post-docs move ahead in their career trajectories toward being independent investigators.

When studies do not do so, the discussion sections of the publications list a series of limitations of the method used (i.e.., problems with recruitment and retention of participants, caveats associated with logistic difficulties collecting data) and mention that future studies need to repeat the work and perhaps with a larger sample size. Have you noticed that if you attend the same scientific meeting year after year, you see that the topics researched and presented are repeated by the next generation of scientists?


Over the past 25 years, Salimetrics has published best practices and recommendations for collecting, handling, storing, and assaying saliva samples in the context of biobehavioral research. Structures were built to enable broad access to the tools developed in this work. We have also created systems to share this expertise with the scientific community and have enabled researchers to use these tools, including our top-tier SalivaLab that delivers excellent results every time.

In our scientific bones, we believe that by providing access to these tools, services, and knowledge, research that employs salivary bioscience measures will advance at a more efficient and effective pace. The effort, of course, is to push the field from discovery to method development, to exploration of applications, to translation. It is especially timely now to move the field from descriptive and method-focused work to translation.

We invite you and your team to join us on this quest. Regardless of whether you have saliva experience or not, and regardless of your stage in your scientific career, use Salimetrics and their experts to advance your research efforts so that you can address your projects’ specific aims and answer your research questions decisively.

Let us share our experience and knowledge with you; it will strengthen the significance, innovation, and methods of the studies you propose. We believe it will raise the impact of your scholarship and will accelerate your work in ways you may not imagine. We believe it will increase your priority scores and increase the chance of external funding. We believe it will maximize scientific value, minimize your costs, save you time, and enable you to focus on your science without distractions.

Reflecting on the statement “More research is needed,” wouldn’t it be fantastic if that phrase meant “because we are now looking at the next important piece of the puzzle” rather than “because our conclusions weren’t definitive, and our methods weren’t sufficient to clearly answer the hypotheses we tested.”

*Note: Salimetrics provides this information for research use only (RUO). Information is not provided to promote off-label use of medical devices. Please consult the full-text article.


In the biobehavioral sciences, one of the most challenging issues is estimating statistical power. The underlying question is:

“Does the study design include enough participants to rule out the possibility that observations made would be unlikely to have occurred by chance?”

This issue is center stage in the peer review of grant proposals as well as manuscripts submitted for publication.

Most salivary bioscience studies employ models that involve multi-method or -modal assessments in an effort to explain individual differences. Here, the task of estimating statistical power becomes even more daunting. The integration of biological and behavioral measures increases the potential for variables included to have different distributional properties and measurement errors. Moreover, the exploration of individual differences often demands analytical tactics that subgroup participants by key variables. Without guard rails or guidelines, investigators are making decisions about sample size based on a combination of opinions, assumptions, and budget restrictions. These choices directly impact whether proposals are funded, and if the resulting manuscripts are accepted for publication in top journals.

Over 25 years, we have engaged hundreds of investigators from the proposal planning through the publication and presentation of study findings. An anecdotal observation is that sometimes the number of participants included in project proposals is less than optimal from the outset, and/or at the end-line, investigators may not have a sufficient sample size (N, the number of participants) to analyze subgroup differences and test compelling secondary or tertiary research questions.

Our experience suggests that it would be helpful to investigators in the study planning stage to raise awareness of these specialized issues and start a dialogue that encourages consideration of best practice recommendations.


To begin, we take a data-driven approach. We asked a simple question: In the published literature, what is the distribution of N for studies that explore relationships with salivary bioscience measurements? Our assumption was that to pass peer review, studies in the literature had to include a sufficient N to reveal at least one statistically significant finding. So, we searched PubMed (since 2017) using specific keywords for three different common salivary bioscience study designs, listed the studies in descending order, and summarized our observations. We selected 101 qualified studies, blind to N, that focused on the Cortisol Awakening Response (i.e., keywords were “CAR”, “Saliva”, and “Cortisol Awakening Response”), 101 qualified studies on the Cortisol Diurnal (i.e., keywords were “saliva” and “diurnal sampling”), and 101 qualified studies that employed the Trier Social Stress Test (i.e., keywords” TSST” and “Saliva”).

In summary, our analysis of the 303 studies revealed a median value of 90 participants. Furthermore, we observed that 51 studies had a sample size of 39 participants or fewer, suggesting a potential limitation in their ability to detect a statistically significant correlation of moderate size at a significance level of p < 0.05. Figure 1. below shows the number of studies with various numbers of participants.

Additional in-depth additional figures for each study type. Each graph depicts the distributions of N for each study type: Cortisol Awakening Response, Cortisol Diurnal, and Trier Social Stress Test. You’ll notice the distributions are non-normal, and for this reason, we draw the reader’s attention to the median as the measure of central tendency.

Each graph portrays the distribution of salivary Coritsol Awakening Response, Cortisol Diurnal, and Trier Social Stress Test, searched from PubMed, based on the number of participants involved in each study. You’ll notice the distributions are non-normal and for this reason, we draw the reader’s attention to the median as the measure of central tendency.




Table 1. N by study type: percentiles, mean, median, standard deviation, and range

It’s our expectation that these tabled values will serve as general guidelines regarding the number of participants investigators should plan to include in their proposals. Since the studies included in this summary have each passed through the peer review process, we argue these figures have internal and external validity and can be used to complement more technically derived estimates of statistical power.

Moreover, we anticipate that despite the best of intentions that it is more common than not that at the end-line, studies fall short of the projected sample size due to unanticipated issues with the execution of recruitment and participant dropout/retention. Therefore, we forward these figures to frame estimates of sample size in completed studies after recruitment and retention issues that have had an impact. Investigators should consider accommodation of recruitment and retention problems in their project plans and projections.

These data suggest that a considerable number of studies in this literature may be underpowered. An observation often corroborated by the authors themselves. Many of these studies mention sample size as a limitation in their discussions and recommend a larger sample size in future studies.


Budget ceilings almost certainly impact project plans related to sample size. The cost of analytical services for testing salivary samples is a significant contributor to most proposed budgets. It is logical to think that larger sample size is prohibitive because they generate more samples, which are directly tied to increased expenses. We recently showed that this doesn’t necessarily have to be the case. Our prior effort emphasizes prioritizing biological replicates over technical replicates. Please see Riis, Jenna L et al. “The case for the repeatability intra-class correlation as a metric of precision for salivary bioscience data: Justification, assessment, application, and implications.” Psychoneuroendocrinology vol. 128 (2021): 105203, and see the commentary in Maximizing the Scientific Value of Saliva as a Biospecimen: A Guide for Research for additional details.


By considering these specialized issues, researchers can enhance the rigor and quality of their salivary bioscience studies. Salimetrics is committed to supporting researchers and encouraging ongoing dialogue and collaboration to advance the field of salivary bioscience.

For more information, researchers are encouraged to connect with an expert at Salimetrics. Additionally, researchers in the planning stages of their study can utilize the project summary, a resource available on the website to develop their study plan, including the option to input their desired sample and participant type and size.

Another resource available to salivary bioscience researchers is the Collaboratory which offers an opportunities for researchers to discuss and develop grant proposal and innovative ideas with salivary experts


Riis, J. L., Ahmadi, H., Hamilton, K. R., Bryce, C. I., Blair, C., & Granger, D. A. (2021). “The case for the repeatability intra-class correlation as a metric of precision for salivary bioscience data: Justification, assessment, application, and implications.” Psychoneuroendocrinology vol. 128 (2021): 105203.


*Note: Salimetrics provides this information for research use only (RUO). Information is not provided to promote off-label use of medical devices. Please consult the full-text article.


Kristina Feghali and Douglas Granger

There is a natural ebb and flow to activity in research groups that apply biobehavioral assessments. Work phases through proposing, awaiting funding decisions, project management, data collection, laboratory analyses, data analyses, and eventually scholarship. Each phase has a different interval and focus, and phases may overlap. At the level of operations, research labs are subject to somewhat of a boom-and-bust business cycle. Notice of award can come somewhat unexpectedly, requiring the investigator to hire staff quickly and hit the ground running. Notice of award can be delayed, making it difficult to plan. At the end of the project period, project staff are reassigned to a new project or let go if future project funding is uncertain. This seasonality makes it challenging to hire and retain staff, maintain consistency in operating procedures over time, and support the salaries of specialized technical personnel that maintain laboratory equipment.
One approach to reducing the burden of the boom-or-bust cycle on the individual investigator is the shared resource model or core lab. Shared resources work well when there are enough local investigators cycling in and out of funding to collectively financially support a core staff and equipment infrastructure.

Unfortunately, when the collective does not have enough funding, the financial burden falls back on the unit’s home department or school. Given the financial strains on academic units, that burden has become less and less likely to be picked up by the department or school. Consequently, staffing is reduced, equipment is not maintained, calibrated, and certified. When the next award is received, the cycle has to be started over again from ‘go’, likely with a compromise in the accuracy and quality of the data that would be generated by a trained and experienced staff. As you can see, this cycle creates inefficiencies at several levels and distracts investigators from the most important thing: the science.

Figure 1, inefficiency and ineffectiveness when research activity misaligns with resources. The orange area represents inefficiency when the research activity exceeds the available resources, leading to constraints and inefficiencies. The blue area reveals when research activity is below capacity, resulting in unused or underutilized resources

In our experience, salivary bioscience labs are examples of the boom-and-bust cycle. Only a few labs, operated by individual investigators, can consistently generate a funding stream to support sustained and consistent operations. Consequently, they are often staffed by students or temporary technicians. It’s also true that in our experience, efforts to create and maintain salivary bioscience core labs have not been able to support themselves, even when the local community of scholars is somewhat grant active. Budgets allocated for assay work are typically a small fraction of the overall project budget, and indirect costs returned to departments are often only a small fraction of the overall budget. The funds, are more often than not, insufficient to provide adequate support for a professional staff.

A Solution for Sustainable, Consistent High-Impact Research

To create a sustainable, best-in-class system with professionally staffed, high-quality equipment, and consistently applied operating procedures, we created the ultimate shared lab.

Salimetrics serves, in many respects, as an inter-institutional shared resource. Investigators have access to professional staff and best-in-class infrastructure when their projects are cycling through the phases needing these specialized services. Collaborating with investigators across institutions ensures that funding is consistent and steady, so when an individual investigator is ready, the unit can efficiently and effectively fulfill their needs. This system is ideal for small pilot studies as well as the largest nationwide surveys. It is able to quickly scale and return results rapidly, ensuring the highest quality by maintaining industry-standard quality control and assurance systems.

For 25 years, Salimetrics has operated in this manner and provided a resource to help investigators manage the boom-and-bust cycle of research. At its core is an assumption: investigators have precious time, which should be focused on the science. When investigators devote their time to operational details of this type, they are not devoting the time and attention needed for their science and scholarship.

Live the search for better science. Use this strategy to sustain quality and advance your science to the highest possible level of discovery and impact.

*Note: Salimetrics provides this information for research use only (RUO). Information is not provided to promote off-label use of medical devices. Please consult the full-text article.

Saliva attributes as a biospecimen include versatility, cost-effectiveness, ease of use, and low participant burden. Not surprisingly, oral fluid has rapidly become a research specimen of interest.

This is especially true in protocols requiring multiple sample collections within short time periods or for participant retention over longer periods across longitudinal studies. As the number of studies utilizing saliva samples has increased, so too has our specialized understanding of how sampling schemes can best be designed and applied to maximize scientific value and impact.


In a recent paper published in Psychoneuroendocrinology, Riis and colleagues (2021) discussed the case that salivary testing has advanced to a level of precision where it is now appropriate to pose an important question:

Is it less important to test samples in duplicate (technical replicates) and more important to invest in sampling more often (biological replicates) to produce the most valuable data?

The study observed that less than 5% of the variation in salivary analyte levels was attributable to laboratory-based measurement error in qualified labs (Riis et al 2021). In contrast, the variation in salivary analyte levels can differ dramatically from time to time. These results suggest that resources spent towards understanding variation in analyte levels within person from time to time can be a greater beneficial investment than expensing those resources to document technical errors observed between duplicate tests of the same samples.

Increasing the number of sampling time points within subject creates the opportunity to model intra-individual change in important ways, and the gain in statistical power this achieves will advance our understanding of the correlates and concomitants of individual differences in analyte levels.


By implementing this strategy, researchers can also take advantage of other potential benefits that come with collecting and analyzing a larger sample size. For example, tactical benefits could include piloting and testing a subset of samples for biomarkers that are exploratory and novel to your research. Moreover, with additional sampling time points, investigators may choose to assay some samples for their immediate research purposes, but also archive other samples for future laboratory analysis.

These advanced, data-informed tactics can be adapted to your study in ways that empower your project to maximize the value added by the inclusion and integration of salivary bioscience. Data-informed tactics backed by statistical proof further enable confidence in researchers who select a qualified lab to test a subset of additional samples.


Researchers looking to apply this strategy should consider a few factors. Collecting a subset of your samples and choosing a qualified lab to assay the samples is important. Qualified labs will need to have statistical proof that they have the ability to test specific analytes in singlet rather than duplicate. The SalivaLab possesses data that can instill confidence in researchers to test a subset of samples in singlet.

Considering that principal investigators have already invested in recruiting participants and obtaining resources for their studies, the cost-to-benefit ratio of the inclusion of more sampling time points is favorable. This is especially true when compared to the cost of conducting an entirely new study.

Lastly, Institutional Review Boards (IRB) have different policies for additional testing of biological specimens. Contact your IRB for recommendations and guidelines on consenting participants, archiving samples, and future analysis.


The Salimetrics’ ground-breaking salivary oxytocin assay was designed specifically for saliva with Salimetrics’ unique knowledge and experience. Early results are in – not only does the assay range span the levels appropriate in saliva, but researchers can also differentiate small, meaningful changes in salivary oxytocin levels that were not detectable before.

Researchers now have the ability to measure early indicators with a sensitivity so low that minute changes in oxytocin biology can be seen. Since the launch of the new Salimetrics assay, more than 300 researchers have requested information on how to incorporate salivary oxytocin into their grants, and early adopters are now publishing their research. While oxytocin levels have been previously measured in blood, breast milk, urine, and CSF, each of these fluids have limitations when appreciating a differential induction of oxytocin. Saliva has the distinct advantages of being both non-invasive and readily accessible, allowing for in-depth monitoring of peripheral oxytocin levels under basal and stimulated conditions. This makes saliva the right choice for oxytocin research.

Previously, the science behind oxytocin testing was limited by the differing methods used to measure it. While debate still exists regarding the forms of oxytocin detected by each method, research using plasma and serum established that oxytocin exists both as a cyclic molecule and complexed with other disulfide containing proteins (Brandtzaeg et al., 2016; Martin, 2016). This natural tendency of oxytocin to covalently adhere to proteins through disulfide exchange results in free and bound oxytocin pools. Therefore, levels measured by methods that only detect the free form may underestimate the total amount of oxytocin present. Based on this concept, some researchers believe pre-processing of the saliva sample is required. However, pre-processing, such as using Solid Phase Extraction (SPE), was shown to significantly reduce measurable oxytocin levels, and recent LC-MS evidence supports the conclusion that samples with low levels of oxytocin were simply due to the inability to detect oxytocin molecules when bound to plasma proteins (Brandtzaeg et al., 2016; Martin and Carter, 2013; Szeto, et al., 2011; Martin, 2016). In practice, most researchers publishing in the literature today choose to concentrate saliva samples, emphasizing the need for well-validated controls and methods in order to avoid the risk of discarding oxytocin and misrepresenting detectable levels.

With salivary oxytocin, investigators can achieve biological evidence to define attachment, pair-bonding, and social behavior in more detail with high ecological value. Using well-validated controls and methods, the Salimetrics’ salivary oxytocin assay detects oxytocin in whole, non-extracted saliva using low test volumes, and does not require additional sample manipulation. Salimetrics has rigorously validated this assay based on well-defined product development procedures and assay validation criteria that exceeds the industry standard for assay validation. Further, applied depletion studies have provided an extra level of robustness to give researchers the highest level of confidence in their results. The table below, featuring key improvements with Salimetrics, illustrates the average results of specific methods from Salimetrics’ validation criteria (full validation report available on request).

Oxytocin Validation Summary

Functional (LLOQ)8 pg/mL
Analytical (LLOD)4 pg/mL
Intra-Assay PrecisionCV= 16.03% (N=45)
Inter-Assay PrecisionCV= 3.9% (N=45)
Spike and Recovery16.3 pg/mL Recovery=109% (N=15)
Sample TypeWhole Saliva (no extraction/concentration)
Approved Collection Method(s)Passive Drool

Understanding the different methods available to researchers and subsequently choosing a method that meets rigorous validation criteria will enable researchers to pioneer an increased understanding of oxytocin regulated biological processes. Based on this solid foundation of rigor and reproducibility, the increased analytical sophistication, and robust validation of this assay opens a wide window for piloting different sample sets and stimuli for the salivary bioscience community.


  1. Brandtzaeg, O.K., Johnsen, E., Roberg-Larsen, H., Seip, K.F., MacLean, E.L., Gesquiere, L.R., Leknes, S., Lundanes, E., and Wilson, S.R. (2016). Proteomics tools reveal startlingly high amounts of oxytocin in plasma and serum. Sci Rep 6, 31693.
  2. Martin, W.L. (2016). Measurement of Oxytocin and Vasopressin (US20160377635A1)
  3. Martin, W. L., and Carter, C. S. (2013). Oxytocin and vasopressin are sequestered in plasma. Presented at the 10th World Congress on Neurohypophysial Hormones. Bristol, England.
  4. Carter, C.S., Pournajafi-Nazarloo, H., Kramer, K.M., Ziegler, T.E., White-Traut, R., Bello, D., and Schwertz, D. (2007). Oxytocin: behavioral associations and potential as a salivary biomarker. Annals of the New York Academy of Sciences 1098, 312-322.
  5. Szeto A, McCabe PM, Nation DA, Tabak BA, Rossetti MA, McCullough ME, Schneiderman N, Mendez AJ. ( 2011). Evaluation of enzyme immunoassay and radioimmunoassay methods for the measurement of plasma oxytocin. Psychosom Med 73(5):393-400.
    *Note: Salimetrics provides this information for research use only (RUO). Information is not provided to promote off-label use of medical devices. Please consult the full-text article.

*Note: Salimetrics provides this information for research use only (RUO). Information is not provided to promote off-label use of medical devices. Please consult the full-text article.


DHEA and cortisol are both hormones produced by the adrenal glands. While DHEA and cortisol are often measured independently as biomarkers, measuring the two hormones together can offer advanced insights for continued stress research.

As salivary cortisol becomes more widespread, researchers can increase innovation and have a better picture of behavioral problems by assessing multiple salivary analytes (Chen 2015). Assessing DHEA/DHEA(S) together with cortisol exemplifies this advantage. Strong evidence suggests that DHEA and DHEA(S) influence stress and behavior through anti-glucocorticoid effects. Early observations of this include below normal DHEA(S) levels observed in patients with Cushing’s syndrome. However, blocking glucocorticoid production results in an increase in DHEA levels (Kalimi 1994).

Although the underlying mechanism is still unclear, DHEA is believed to indirectly regulate glucocorticoid activation. DHEA indirectly increases levels of type 2 11β-HSD, causing greater conversion of glucocorticoids to the inactive state and decreasing overall glucocorticoid activity (Balazs 2008). Thus, the anti-glucocorticoid effects of DHEA indicate that there is an indirect relationship between cortisol and DHEA. This is illustrated by numerous studies of behavioral disorders that have found the ratio of cortisol to DHEA to be a useful predictor of symptoms and identifier of risk.

The DHEA and cortisol relationship is also useful when studying behavioral disorders, like depression and PTSD. A study focusing on attachment behaviors in adolescents found that fear of separation predicts higher waking cortisol/DHEA ratios as well (Oskis 2015). It is suggested that the high cortisol levels associated with anxious attachment styles result in a shift towards glucocorticoid synthesis, which, without buffering from DHEA, causes increased vulnerability to negative psychological outcomes. High cortisol levels can also impact other compounds leading to a reduction in immune and inflammatory response as well as cognitive dysfunction (Chen 2015).

PTSD has been previously linked to high DHEA levels, but a study of veterans with and without the disorder revealed that this relationship also involves cortisol. High DHEA levels relative to cortisol are indicative of greater adversity experienced and risk factors for PTSD. High DHEA levels alone suggest increased severity of PTSD symptoms (Yehuda 2006). A study of PTSD in women supported these findings. Women with PTSD show higher DHEA/cortisol ratios compared to those without, and furthermore, those with both PTSD and depression display lower ratios than women with PTSD but not depression (Gill 2008).

Salivary DHEA(S) also shows a diurnal rhythm and awakening response that may help pinpoint distinct biological conditions in opposition of salivary cortisol. The cortisol to DHEA(S) ratio, for example, is also considered a ratio of catabolic to anabolic activity and can be useful for predicting HPA axis dysfunction (Guilliams 2015). While DHEA and DHEA(S) are both promising biomarkers for continued research and development, DHEA(S) exists at much higher levels and is considered a more stable biomarker for measuring stress-related conditions.

Both the cortisol to DHEA(S) ratio and cortisol to DHEA ratio have been a growing trend in clinical research to better understand the significance of measuring these two biomarkers together. When studying either cortisol or DHEA/DHEA(S), it’s a good idea to take the other into consideration as well as to account for any interactions between these prominent salivary analytes.


  1. Kalimi, Mohammed, et al. (1994). “Anti-glucocorticoid effects of dehydroepiandrosterone (DHEA).” Molecular and Cellular Biochemistry. 131.2:99-104.
  2. Balazs, Zoltan, et al. (2008). “DHEA induces 11β-HSD2 by acting on CCAAT/enhancer-binding proteins.” Journal of the American Society of Nephrology. 19.1:92-101.
  3. Kimonis, ER., et al. (2019). “Dehydroepiandrosterone (DHEA) and its ratio to cortisol moderate associations between maltreatment and psychopathology in male juvenile offenders.” Psychoneuroendocrinology 101:263 – 271.
  4. Goodyer, I. M., J. Herbert, and A. Tamplin. (2003). “Psychoendocrine antecedents of persistent first-episode major depression in adolescents: a community-based longitudinal enquiry.” Psychological Medicine. 33.460:1-610.
  5. Oskis, Andrea, et al. (2015). “Biological stress regulation in female adolescents: a key role for confiding.” Journal of Youth and Adolescence. 44.5:1066-1077.
  6. Chen, F.R., et al. (2015). “Tactics for modeling multiple salivary analyte data in relation to behavior problems: Additive, ratio, and interaction effects.” Psychoneuroendocrinology. 51:188-200.
  7. Gill, Jessica, Meena Vythilingam, and Gayle G. Page. (2008). “Low cortisol, high DHEA, and high levels of stimulated TNF‐α, and IL‐6 in women with PTSD.” Journal of Traumatic Stress. 21.6:530-539.
  8. Guilliams, Thomas G. “The Role of Stress and the HPA Axis in Chronic Disease Management.” N.p.: Point Institute, 2015. Print.
  9. Orta, OR,. Et al. (2020). “The association between abuse history in childhood and salivary rhythms of coristiol and DHEA in postmenopausal women.”  Psychoneuroendocrinology. 112:104515
  10. Yehuda, R., et al. (2006). “Clinical correlates of DHEA associated with post‐traumatic stress disorder.” Acta Psychiatrica Scandinavica. 114.3:187-193.
  11. Granger, D., Kivlighan, K. ( 2003). “Integrating biological, behavioral, and social levels of analysis in early child development.” Child Development. 74(4): 1058-63.

*Note: Salimetrics provides this information for research use only (RUO). Information is not provided to promote off-label use of medical devices. Please consult the full-text article.


Although the state of the pandemic still seems to fluctuate from one day to the next, one thing remains clear: COVID-19 has shown us the benefits of saliva as a sample type are unprecedented for infectious disease research.

Now, investigators are needed to build on this foundation and further define how saliva, as a serum alternative in epidemiological seroprevalence and surveillance studies, is beneficial for large-scale, population-based studies. Saliva sampling is easy to access through central collection sites and home collection, enabling high-quality samples with better participant compliance and facilitating increased testing capacity – all at critical economies of scale. In this bulletin, we have summarized the current state of the industry, how you can apply the latest tools to support new, innovative research programs, and how our team is here to assist in the next chapter of discovery.


Saliva and other oral fluid collections contain readily measurable pathogen-specific antibodies whose reactivities mirror that found in the blood. These include antibodies of the Immunoglobulin A (IgA), Immunoglobulin G (IgG), and Immunoglobulin M (IgM) isotype. Secretory IgA is assembled into dimers associated with an additional protein (the J chain) when secreted into mucosal fluids (including saliva), while the oral source of IgG and IgM is from serum diffusing into saliva through the capillary beds of the gingival space between the gums and teeth. Enriched oral fluids such as gingival crevicular fluid (GCF) or oral mucosal transudate (OMT) have even higher concentrations of both IgG and IgM. Importantly, these antibody-rich samples can be self-collected efficiently with the proper collection methods and protocols. This enables efficient surveying of pathogen-specific antibodies in saliva, which will allow for tracking pathogen or vaccine exposure with differentiation between recent (IgM) or historical (IgG) exposure.

For an in-depth review of studies involving salivary pathogen-specific antibody makers, see table 13.1, in Chapter 13 of Salivary Bioscience: Foundations (1).


Evidence is building that shows saliva can facilitate population-level seroprevalence. Pairing this information with identifying risk factors for exposure and transmission, researchers can lead effective strategies for preventing and monitoring disease spread and containment.

A 2017 publication from Augustine et al. (2), explored the utility of saliva for epidemiological studies by investigating if visitors at Boquerón Beach in Puerto Rico were exposed to waterborne pathogens. Due to the ease of collection, visitors were able to collect saliva on-site. Results of the study indicated that more than “two-thirds of beachgoers were previously infected by at least one of the included waterborne pathogens” (2). Knowing this information can help determine exposure to specific detectable antibodies over a specific community or population.

In 2021, Salimetrics released the SARS-CoV-2 IgG Antibody Assay Panel 3-Plex (S-Protein, N-Protein, & RBD), featuring a 98.8% specificity and a 96.5% specificity, as part of their laboratory testing offering. This assay was specifically validated for use without specialized collection devices. The SARS-CoV-2 IgG Antibody Panel can also effectively track the antibody response to the vaccine or a natural infection over time and provides relative levels by including a reference standard. Below are representative performance data from individuals starting on the first day of immunization with the Moderna vaccine through a week after receiving their second dose of the vaccine. The lack of N-protein reactivity (shown in green) distinguishes the SARS-CoV-2 vaccination since the vaccine does not encode N-protein. In the graph below, you can see a moderate increase in Spike/RBD reactivity up to the second immunization (indicated by arrow) and the exponential increase in reactivity post-second immunization.

Saliva can also be used to monitor seroconversion, not just seroprevalence. For example, with COVID-19, investigators can observe patients post-infection to determine if they begin making antibodies to SARS-CoV-2, and which antigen specific antibodies are made – which is a factor in determining disease prognosis (3).


Most notably, saliva can be used to inform disease control strategies and guide immunization programs. When a disease presents itself at varying levels of intensity, such as observed with COVID-19, relying on the presentation of clinical symptoms is insufficient to monitor the spread of disease exposure. In this case, saliva represents an unprecedented ability to evaluate large-scale surveys of historical exposure through pathogen-specific IgG. At home, self-collection and the use of drop-off or mail-in sample returns to a central testing site differentiates saliva from serum or plasma by minimizing exposure to health care workers at collection sites and enabling a geographical scale of magnitude that is difficult to achieve with traditional central collection sites. These benefits are realized, for instance, when monitoring vaccination campaigns and routine immunizations or seroprevalence during outbreaks.

For example, Morris Cunnington completed a national study for hepatitis A virus (HAV) surveillance using oral fluid as a sample type (4). The findings showed that self-collection of oral fluids for serology was a practical way of sampling, and HAV-specific IgG can be used to accurately evaluate the exposure of a population when compared to blood. In this publication, applying specific demographic and social data measurements along with the antibody data provided strong epidemiological associations.

Another example of the utility of saliva for surveillance was to track the progression of Hepatitis A, B, and C. In a 2007 publication, a cross-sectional study investigated the prevalence of hepatitis compared to previous studies. “The 2003 findings of the cross-sectional oral fluid IgG survey in Belgium, was compared to a previous study 10 years earlier and indicated that Hep A and C may have been less of a burden than estimated in 1993” (5).

The staggering benefits of saliva can also be noted from a study that analyzed rubella cases in 2010. “For rubella, the incidence of rubella cases increased from 0.5 to 0.77 per 1,000,000 population when oral fluid testing was added” (6). In this study, oral fluid provided researchers with more specific information for those who had confirmed rubella cases, and allowed researchers to form strategies that would be effective for eliminating rubella in the UK based on their results.

In all cases, saliva can be collected safely in population-based settings without exposure risk and with less chance of participant error using self-collected specimens. Utilizing this methodology, investigators can operate on a large scale with increased participant compliance over blood-based sampling.


The utility of saliva as a diagnostic specimen is continuously evolving. As antibodies in saliva originate in blood, they are bioidentical to their serum counterparts and therefore, can be utilized in a diagnostic capacity. Most current salivary testing under this umbrella is captured as a method to screen high-risk participants or monitor active treatments and therapies. While epidemiological surveys generally do not require FDA approval, saliva will play a unique role in future diagnostics as the accuracy of saliva continues to improve with new collection techniques and a broadening understanding of saliva’s biological capacity. This advancement will soon lead to the development of precision Point of Care devices and saliva-based companion diagnostics.

Generally, in diagnostic applications, one limiting factor in successful testing is how the sample is collected. Due to the heterogeneous nature of saliva, particular attention must be placed on collecting the right sample for analysis. For antibody testing, this may require collecting an antibody enriched sample such as Gingival Crevicular Fluid (GCF) or Oral Mucosal Transudate (OMT). Salimetrics, in collaboration with SalivaBio, has focused on addressing sample collection concerns to enable a new wave of possibilities by facilitating better results through qualified and validated collection methods. Through this initiative, new methods for specific sample collection applications are on the horizon.


Salimetrics has developed and optimized tools required for use in epidemiological research and surveillance and has validated these tools to provide researchers a ready-to-use platform for infectious disease research. With the recent introduction of the Salimetrics Salivary Total Human IgG ELISA Kit and the Salivary Total Human IgM ELISA Kit, a new suite of tools is now available for researchers. Combined with Salimetrics Salivary Human SIgA ELISA Kit, this line of infectious disease research tools has been optimized to improve the specificity and sensitivity of corresponding pathogen-specific serological assays. Specifically, these assay tools minimize false negative determinations in pathogen-specific serological assays by excluding samples that have insufficient total antibody levels. In the current state of the pandemic, researchers can take advantage of this opportunity to understand the impact of COVID-19 on a biological level. Researchers can more fully understand the impact of COVID-19 in their study population with Salimetrics SARS-CoV-2 (IgG) Antibody Assay, 3-Plex (S-Protein, N-Protein, & RBD) – or with the Salivary SARS-CoV-2, N Antibody ELISA Kit.

If you’re exploring the next generation of infectious disease research with saliva or capturing the impact of COVID-19 stress-related exposure, Salimetrics is here to support your research and help you find solutions to your research challenges. For more in-depth information, the full scope of antibodies in saliva for infectious disease research can be found in Salivary Bioscience: Foundations, Chapter 13: The Utility of Antibodies in Saliva to Measure Pathogen Exposure and Infection.


For over 20 years, the Salimetrics saliva testing laboratory has remained a pillar of standardized methods for the salivary bioscience community, representing much more than just high-quality results.

The scientific impact has been phenomenal and the collaborative environment, equal access, pay only when you need it strategy has allowed academics throughout the world to focus on what they do best while being backed by a team of salivary bioscience experts. This approach has saved institutions from building, maintaining, and decommissioning labs as resources and scientific foci change over time.

As a current or future principal investigator, it can be a major inefficiency (and distraction) to manage the “hidden costs” (time, effort, equipment maintenance, staffing, and local politics) associated with large, project-specific analytical laboratories. Organizing and maintaining operations of this scale may seem aspirational, but they can also hinder an investigator’s ability to focus on their research program deliverables (i.e., high impact novel scientific observations) and departmental expectations for service, teaching, and mentoring. It is also problematic when such a facility and staff are underutilized. That is, the costs to maintain a laboratory are perpetual, but the research activity is constantly transitioning between stages such as the project launch, data collection, laboratory analyses, interpretation, and scholarships.

In the beginning, the Salimetrics saliva testing laboratory was established to support and assist principal investigators. The purpose was to serve a community of scholars with common interests by establishing a shared, equal access facility that would be available to all, regardless of their specific academic affiliation or whether they were in-network with the laboratory’s lead scientist. The goal was to make the highest quality professionals, equipment, and knowledge available to all, as a consistent resource that would facilitate advancing the field by raising quality standards and minimizing inconsistencies between studies due to idiosyncratic methods.

Today, we still honor that mission. We also realize that it is hard to fully appreciate the Salimetrics laboratory experience without sending samples yourself, so we thought you might benefit from knowing just five of the many value-added features of the Salimetrics saliva testing laboratory.


Salimetrics embodies these seven attributes of a high-quality salivary bioscience laboratory. In fact, Salimetrics pioneered the application of these criteria in saliva testing. The Salimetrics team is experienced and organized in handling even the most complex study designs. This experience has equipped us with a distinguished depth of knowledge in specific and specialized checks and balances that are designed to protect you and your research.


It’s not us, it’s you. We are fortunate to be invited to play a specific, supportive role for research teams. The focus on collaboration and team science has helped launch hundreds of investigators’ careers and forms a strong network of interdisciplinary researchers worldwide. While it is very common that study designs are built off of previous work, there are regularly significant advances in the field. This knowledge is critical to designing an effective study that meets the current community guidelines and expectations. Imagine being backed by the latest collection, handling, transport, and testing protocols in less time than it takes you to do a single literature search! The Salimetrics team is always at the forefront of Salivary Bioscience so that you can feel confident in your collection, handling, transport, and testing methods.


Deadlines are important and the Salimetrics lab’s track record confirms that we can deliver results on time. Researchers won’t ever experience year-long turnaround times, broken freezers, improperly stored or misplaced samples, or even disappearing samples (We’ve heard a lot of crazy stories!). This can be especially vital to meet project deadlines, so you can reach the next stage of your research efficiently. You can rest easy knowing your samples are in safe hands here.


For projects that require significant management or focus heavily on fieldwork, the Salimetrics laboratory is a well-trusted choice for researchers because it enables them to focus on the high-value inputs without the burden of monitoring, maintaining, resourcing, or transitioning lab staff and testing progress. At the Salimetrics lab, we employ only professional lab technicians, and each must adhere to strict GLP guidelines to ensure that each assay is properly run. Investigators don’t need to worry about changes in personnel, budget, experience, protocols, or capacity. This allows investigators to focus on details that make a study more credible, and not whether the lab staff ordered enough assay kits to properly run the samples, or if the kits they are using are expired (It happens more often than you would think!).


With over 5,000 studies serviced, there is no study too big or too small. Whether there are 30 samples from one collection site or 10,000 samples from 24 collection sites, your project manager has seen it all before and can recommend logistical options to help you get your samples to the lab on time. In-person sample drop-off and rush testing are also available if you need results fast, and investigators can easily archive remaining samples for future testing on request. Salimetrics has also designed new programs to enable the exploration of novel salivary biomarkers through validated, early-stage methods which leverage know-how from Salimetrics to break new ground in salivary bioscience. If you want to know more about what’s new, connect with an expert!


In the end, Salimetrics saves investigators both time and money. In such a complex field, it is important to explore your project workflow from multiple perspectives to ensure that it fits with your research goals. Plus, if you ever need to connect with an expert, we’re here to help. While we recognize that there are times when a researcher may need to select a different lab, we highly recommend choosing a lab that is established, high quality, and has been properly vetted to comply with at least these seven attributes of a high-quality salivary bioscience laboratory.

*Note: Salimetrics provides this information for research use only (RUO). Information is not provided to promote off-label use of medical devices. Please consult the full-text article.


1. Guarantee Time Point Accuracy for Saliva Sample Collection

OnTimePoint’s core functionality allows researchers to design and customize their study while minimizing participant and sample collection error. OnTimePoint™ guarantees time point accuracy by managing sample collection time points through smart barcode scanning and timepoint questionnaires. This system provides transparent communication between the researcher and their participants. Researchers can know the exact time and duration of each sample collection time point and thus decide whether it meets their study specifications. Using OnTimePoint™ will give researchers confidence in their results by standardizing protocols and collection times across participant groups.

2. Flexible Sample Scheduling, Notifications, and Error-Proofing

The ability to schedule samples and send sample collection notification reminders to a participant’s mobile device is a crucial tool. Researchers can also set a designated time (for example, 5 or 10 minutes before) to send reminder notifications to participants for upcoming samples, so that they can be prepared to collect on time. In addition, OnTimePoint™ allows awakening samples to be taken prior to their scheduled awakening time for individuals who may wake up early. Samples can also be set up as “On Demand” samples, allowing participants to initiate a sample collection in real-time at awakening, bedtime, during an event, or at random. This added feature gives participants an opportunity to collect samples based on an unscheduled triggering event, adding to the biological accuracy of the sample. OnTimePoint™ also supports scheduling sample collections before or after the previous or next sample, before or after events, and/or around awakening and bedtime. Once participants are ready to collect a sample, they simply scan the QR barcode found on the vial which pairs that sample to that participant, enhancing sample collection transparency.

Error proofing is vital to improving the quality of samples in a study. There are times when, even with the best intentions, participants produce non-compliant samples. OTP provides researchers the ability to flag these samples as they are occurring, and then choose whether to add additional samples or recollect samples from the participant and, as a result, researchers avoid having incomplete or erroneous biological data which may be critical to their findings. With this combination of sampling options, it is now possible to keep participants on time and fix previous sampling errors before it is too late.

3. Easy to Manage Study Dashboard

Real-time feedback on the researcher dashboard lets investigators view the overall progress of their study, evaluate and make potential adjustments to keep their study on track. You can add participants, schedule notifications, change their SalivaBio sampling method or volume requirements, and set sample collection schedules, even after the study has started. The best study outcomes have great study visibility and coordination, and the OTP dashboard, with its drill-down features, makes this easier and available all the time.

4. Intuitive Participant App

For participants, a free mobile app (compatible with both iOS and Android devices) can be downloaded through the Play or App Store. Within the app, participants can view the remaining number of samples and collection days, as well as a “to-do” list for required study inputs. The app then notifies participants of sample collection times, with optional content such as pre- or post-sample collection instructions and/or late sample reminders. The interactive framework also includes optional time-based questionnaire inputs such that researchers can qualify the sample pedigree – think about it: real-time answers to real-time questions right during sample collection.

5. User-Customizable Features for Added Flexibility

  • Sleep/Wake/Event Timing: Collect critical samples on time
  • Fitbit Integration: Backup/validation for wake and sleep times
  • Daily Questionnaires: Researchers can compose and change up to 8 daily multiple-choice questions, which are scheduled to appear once per day
  • TimePoint Questionnaires: Researchers can compose up to 4 multiple choice questions for participants to answer while collecting samples, which encourages participant compliance and engagement
  • Sample Alerts: If sample collections are out of specification, an alert will be sent to the researcher’s email and displayed on the study dashboard
  • Customizable Content Screens: For welcome text, sample collection instructions, post collection instructions, missed collection notifications, closing text, and more…
  • Provided Excel Template: Seamlessly import all participants and groups in a few clicks
  • Study or Participant Data Export: You can view or export (spreadsheet) data for a single or all participants quickly
  • Multi-Study Support: Coordinate multiple studies at the same time
  • Merit Badges: Encourage increased participant compliance

Every Study Will Benefit From OnTimePoint™

The OnTimePoint™ Saliva Collection Management System is priced at a low-cost so that every study benefits, no matter how straightforward or complex the sample collection protocol and participant data seem. Two-tiered pricing is based on a per-study basis. For Salimetrics, high-quality research starts with high-quality best practice methods, and creating these methods for the Salivary Bioscience community is our primary focus.


Salimetrics recently released the OnTimePoint™ (OTP) Saliva Collection Management System, a tool created to improve how researchers manage their study and obtain accurate, reliable, and reproducible results.

Our team at Salimetrics focused on the methods for Salivary Bioscience and has once again created a new method that improves sample integrity and participant compliance, and in the process, now provides an easy, low-cost way to increase rigor and reproducibility. This parallels the call to increase rigor and reproducibility in research from the NIH and publications from the research community such as: Schlotz (2018), Hulett (2019), and Benz (2019). For Salimetrics, high-quality research starts with high-quality best practice methods; and concentrating on sample integrity and participant compliance is a critical aspect of rigor and reproducibility that was putting research studies at risk. To achieve better compliance, the Salimetrics team addressed five key elements of successful saliva collection: (1) time-point accuracy; (2) flexible sample scheduling and notifications; (3) study dashboards for real-time visibility; (4) intuitive participant engagement; and (5) flexible questionnaires.



With the increased clinical focus on the science of sleep as it relates to human health and performance, salivary melatonin and more specifically, “Dim Light Melatonin Onset” or DLMO, continues to serve as a preferred, reliable tool to assess circadian rhythm sleep disorders and associated health concerns.

Melatonin (N-acetyl-5-methoxytryptamine) is the sleep-promoting neurohormone and circadian biomarker that serves as a master regulator of circadian rhythm, and measuring DLMO provides the most biologically accurate, evidence-based mechanism to assess circadian rhythm sleep disorders. Using saliva provides the opportunity for a non-invasive sample that does not disrupt a person’s normal sleep cycle, thereby making it a valid gold-standard in circadian rhythm sleep assessment.

Due to the circadian system’s propensity to be modulated by important environmental cues including exposure to bright light, eating, social behavior, exercising and activity schedules, DLMO patterns have been shown to reliably predict circadian timing and help clinicians more accurately assess sleep behavior and sleep phase shifts that can result in poor concentration, development, productivity, and diminished cognitive performance (Murray et al., 2017), (Burgess et al., 2016; Burgess et al., 2015). Determining DLMO is also relevant in discriminating circadian rhythm related sleep issues from other non-circadian related sleep disorders or establishing the timing of exogenous melatonin administration when treating delayed sleep phase disorders (Lewy et al., 1995).


DLMO profiles were originally facilitated in a sleep lab and determined by measuring serum melatonin levels over numerous time-points with serial blood draws in patients that have been cannulated. In modern research, the preferred DLMO method measures salivary melatonin levels over multiple time-points prior to and just after habitual bedtime. By utilizing saliva as a biological sample, researchers can significantly expand the number of participants that can cost-effectively be included in their study. Saliva also maintains a higher-level of participant recruitment and compliance. Salivary melatonin concentrations are accurate, reliable and highly correlated with levels in blood (Nagtegaal et al., 1998). Unlike serum, frequent saliva sampling for DLMO estimation can be performed in the comfort of one’s home and does not require an overnight stay at a sleep lab (Burgess et al., 2016). Saliva samples can be provided over 7-10 hours (as opposed to a 24-hour polysomnogram) and researchers can non-invasively monitor melatonin levels.


Figure 1. Example Phase Shifts – This figure represents examples of normal, advanced, and delayed phase shifts, observed through salivary melatonin analysis.


Scientific literature, confirmed by Salimetrics, generally recommends a 7-point sample collection (samples collected every hour beginning 5 hours before normal bedtime, through one hour past bedtime) to provide a reliable DLMO estimation. However, in severely phase shifted individuals, additional samples may need to be collected over a longer period, as well as in totally blind individuals with a non-24-hour sleep-wake disorder (Keijzer et al., 2014). This protocol was first developed by the Dutch National Referral Center for Sleep-Wake Disturbances and Chronobiology. Samples can be collected with Passive Drool, and typically 0.5 mL is more than sufficient for duplicate melatonin measurements.

For advanced precision in calculating DLMO measurements, a 13-point collection (samples collected every half hour, five hours before habitual bedtime, through one hour past bedtime) is recommended. However, the sample numbers required for this method may be excessive due to increased cost and participant burden. In most studies, the difference in DLMO estimation was not significant between half-hourly and hourly sampling (Molina and Burgess, 2011).

The complete sample collection instructions can be modeled from Salimetrics’ Salivary Melatonin for DLMO Collection Protocol.


In practice, accurate and reliable DLMO profiles come from high-quality and experienced laboratories using high quality melatonin assays. Qualified diagnostic and clinical labs adhere to CLIA and GLP regulated standards, and qualified research labs follow NIH requirements for rigor and reproducibility. Finding a lab that adheres to these Seven Attributes of High-Quality Lab provides investigators confidence in the data received. Researchers without access to their own high-quality lab can depend on the Salimetrics’ SalivaLab – the most qualified and experienced salivary research lab available. Salimetrics also provides a Center of Excellence (COE) Certification Program for salivary bioscience research labs that meet strict Center of Excellence requirements. Whether performing diagnostic or research testing, the lab should rely on the Salimetrics’ Melatonin Assay Kit as the best choice to ensure accurate and reliable salivary melatonin results.


To achieve the most reliable and consistent salivary DLMO measures, a highly sensitive and specific salivary melatonin assay is required. The Salimetrics Melatonin Assay is the preferred kit for fast and sensitive measurements of salivary melatonin without the use of radioactivity or needing a time and labor-intensive extraction protocol. Sample measurements show leading reproducibility when run as duplicate measurements (low CVs), so although we recommend samples be run in duplicate, there is a high level of confidence in measurements obtained when run in singlicate (see example data below).

Assay TypeCompetitive ELISA, colorimetric detection
Antibody usedRabbit Monoclonal Antibody
Sensitivity1.37 pg/mL
Assay Range0.78 – 50 pg/mL
Assay Time3.5 hours
Sample ExtractionNo
Sample Volume100 µL per well
Number of samples38 samples in duplicate, 76 in singlica


Clinicians and sleep experts routinely calculate DLMO using either the variable threshold method, aka “3k method”, or the fixed threshold method. The fixed threshold method is based on the time at which rising melatonin levels cross a previously determined threshold, typically set at 3 or 4 pg/mL for saliva. However, this method risks missing DLMO for individuals that are low melatonin producers, a common problem in an aging population. Salimetrics recommends using the 3k method to calculate DLMO (Voultsios et al., 1997, Molina and Burgess, 2011). This method establishes the mean of the first three low day-time samples and sets the threshold as 2 Standard Deviations above this mean for each person’s own measurements. The 3k method benefits DLMO determinations by including both individuals that are ‘low secretors’ who do not make sufficient melatonin to reach the fixed threshold values and allows for DLMO estimation in individuals who have daytime melatonin levels above the fixed threshold.


Data from 13 half-hourly saliva samples were used to estimate DLMO in the following Phase Response Curve. Using the variable threshold 3k method described above, the time of DLMO was estimated for the following sample profiles. Each line in the graph represents one set of singlicate measurements.


  1. Burgess, H.J., Park, M., Wyatt, J.K., and Fogg, L.F. (2016). Home dim light melatonin onsets with measures of compliance in delayed sleep phase disorder. Journal of sleep research 25, 314-317.
  2. Burgess, H.J., Wyatt, J.K., Park, M., and Fogg, L.F. (2015). Home Circadian Phase Assessments with Measures of Compliance Yield Accurate Dim Light Melatonin Onsets. Sleep 38, 889-897.
  3. Challet, E. (2015). Keeping circadian time with hormones. Diabetes Obes Metab 17 Suppl 1, 76-83.
  4. Keijzer, H., Smits, M.G., Duffy, J.F., and Curfs, L.M. (2014). Why the dim light melatonin onset (DLMO) should be measured before treatment of patients with circadian rhythm sleep disorders. Sleep Med Rev 18, 333-339.
  5. Lewy, A.J., Sack, R.L., Blood, M.L., Bauer, V.K., Cutler, N.L., and Thomas, K.H. (1995). Melatonin marks circadian phase position and resets the endogenous circadian pacemaker in humans. Ciba Found Symp 183, 303-317; discussion 317-321.
  6. Molina, T.A., and Burgess, H.J. (2011). Calculating the dim light melatonin onset: the impact of threshold and sampling rate. Chronobiol Int 28, 714-718.
  7. Murray, J.M., Sletten, T.L., Magee, M., Gordon, C., Lovato, N., Bartlett, D.J., Kennaway, D.J., Lack, L.C., Grunstein, R.R., Lockley, S.W., et al. (2017). Prevalence of Circadian Misalignment and Its Association With Depressive Symptoms in Delayed Sleep Phase Disorder. Sleep 40.
  8. Nagtegaal, E., Peeters, T., Swart, W., Smits, M., Kerkhof, G., and van der Meer, G. (1998). Correlation between concentrations of melatonin in saliva and serum in patients with delayed sleep phase syndrome. Ther Drug Monit 20, 181-183.
  9. Voultsios, A., Kennaway, D.J., and Dawson, D. (1997). Salivary melatonin as a circadian phase marker: validation and comparison to plasma melatonin. J Biol Rhythms 12, 457-466.
  10. Zelinski, E.L., Deibel, S.H., and McDonald, R.J. (2014). The trouble with circadian clock dysfunction: multiple deleterious effects on the brain and body. Neurosci Biobehav Rev 40, 80-101.
    *Note: Salimetrics provides this information for research use only (RUO). Information is not provided to promote off-label use of medical devices. Please consult the full-text article.


Salivary Bioscience study designs can take advantage of a participant baseline index for Cortisol available from the study’s saliva samples. In addition to the empirical measurements of Cortisol Awakening Response and Diurnal Slope-Area Under the Curve (AUC), Latent Trait Cortisol can be determined using established statistical modeling to reveal an individual’s trait, or stable cortisol level.

The most empirical saliva sampling indices in Salivary Bioscience by far are the Cortisol Awakening Response (CAR), Diurnal Slope and Area Under the Curve with respect to Ground (AUCg) – all of which require saliva samples to be taken over multiple days and at precise time-points. While saliva sampling indices enable estimation of the trait-like component of variance in biological measures, sources of variability (i.e., measurement error) often compromise the effectiveness of these index-based conclusions. Researchers are constantly struggling with variability due to conflicting evidence to support that saliva sampling is continuously performed in compliance with these study requirements for high-quality data. The majority of this variability is due to sample timing and poor participant compliance where subjects are collecting samples early, late, or not at all. This inconsistent sampling often leads to additional challenges when analyzing salivary cortisol data, but does a better method exist?

Typically, to account for this variability in salivary cortisol indices, researchers use statistical techniques that average samples across datasets. However, this method requires significant statistical power in terms of participants and samples collected to minimize the effects of bias. Based on these challenges, advanced statistical methods, such as Latent Trait Cortisol (LTC), have been developed to account for the shared communalities among multiple saliva samples. A number of studies have explored the LTC model in detail. For example, Doane, et al. (2015), researched the reliability, validity, and stability of LTC levels over several months and reported that “variation in single cortisol measures that were attributable to the corresponding LTC ranged from 20% to 65%.” Doane also showed that “LTC was distinct from the CAR, differentially predicted components of the diurnal profile across the day, and was highly stable across assessment waves (months).”

However, LTC isn’t just statistics, it is also a methodology that can reduce the number of sample collections required for each participant (minimum of 3 samples, Giesbrecht, et al. 2015), diminish participant burden, and increase stability estimates. The result is a latent variable factor that is essentially “free” of state characteristics and measurement error, which increases accuracy beyond that of simply averaging values across samples. This latent variable represents an individual’s trait, or stable, cortisol level.

The main advantage of LTC modeling is that it separates cortisol measurement error into a separate component instead of combining and averaging trait variability with the state variability of cortisol and measurement error. Moreover, even collecting just two cortisol samples per day in multiple waves minimizes cortisol variance and provides a more accurate picture of an individual’s cortisol levels than a single timepoint sample (e.g., Hair cortisol). In addition, single-point measurements deny researchers of any potential for highlighting expected intra-individual cortisol relationships that can’t be examined or identified using single timepoint measures. For example, the LTC modeling approach was implemented in a study by Chen et al, (2017) using the first 2 samples of each day over 3 days. Based on this analysis, LTC modeling enabled researchers to conclude “that serotonergic genetic variation may influence the impact of early adversity on individual differences in HPA-axis regulation.”

Illustrated in Figure 1 (below) is a way to think about how using a latent modeling statistical approach allows you to find all of the shared information among three samples, or the stable, trait cortisol level. This information is all gathered “behind the scenes” within the statistical program and can be used in this way for any analyses. It’s important to note that the most basic requirements to calculate LTC is a minimum of 3 samples per participant with 30 participants. However, the more participants you have in your study the more robust your results. In addition, it is possible to extricate a LTC score for each person to use in statistical analyses, an approach that is ideal when you have a smaller number of participants.

Overall, researchers continue to advance our understanding of health and human development by incorporating LTC modeling in their salivary cortisol indices. While variability inevitably still exists, understanding and incorporating advanced statistical models can support your key salivary bioscience discovery. If you’re considering LTC modeling in your study, but need more information, feel free to contact the team at Salimetrics and we can help you drive research forward.


In a seminal study published in Cell Metabolism in the fall of 2019, Berger et al., concluded that “a bone-derived signal is necessary to develop an acute stress response (ASR).” Surprisingly, a quick literature review reveals that Osteocalcin is rarely even mentioned in the history of research on stress in humans. This begs the question: Is it possible that this overlooked skeletal hormone could inform our understanding of human stress reactivity and regulation?

A substantial amount of scientific literature describes Osteocalcin as a hormone derived from bone, and the mechanisms that link its levels directly to the activity of the parasympathetic branch of the autonomic nervous system (ANS), as well as aspects of metabolism, exercise capacity, brain development, aging, and male fertility. In the past few weeks, Salimetrics released a validated Salivary Osteocalcin Assay and preliminary observations suggest a modest-to-strong serum-saliva association. These conceptual and methodological advances have the potential to break new ground, and in the interest of enabling our understanding to continue to advance to new limits, Salimetrics is allowing access to our early stage methods such that the Salivary Bioscience scientific community can leverage this know-how.

Below, we briefly review some key Osteocalcin findings and its correlates and concomitants as entry points for interested readers. For a more detailed overview, we suggest reading Moser and van der Eerdan (2018) Osteocalcin—A Versatile Bone-Derived Hormone, published in Frontiers in Endocrinology.


Contemporary theorists propose that a surge in osteocalcin levels is necessary to initiate the stress-response in the detailed study, Mediation of the Acute Stress Response by the Skeleton (Berger et al., 2019). A key assumption is that the skeleton evolved as a protective system in order to prepare boney vertebrates from danger. After sensing fear, it is hypothesized that bone rapidly (within minutes) releases massive amounts of osteocalcin which directly effects the parasympathetic brake on the ANS as a critical precursor to prepare for the fight or flight response. In multiple case controlled experimental studies, Berger’s team exposed mice and rats to various stressors followed by testing circulating bioactive osteocalcin in serum. They also exposed humans to the TSST and subsequently tested serum osteocalcin levels as well. The findings are remarkably consistent across studies– under stress-induced conditions, the bioactive osteocalcin levels rapidly increased. Further experiments in this same study followed the osteocalcin release pathway and timing necessary to mount the Acute Stress Response (ASR).


Further exploration of the Osteocalcin knock-out mice by Oury F., et al., discovered evidence that osteocalcin crosses the blood-brain barrier and binds to cerebral neurons. Subsequent experiments explored Osteocalcin’s effects on depression, anxiety, learning, and memory, suggesting additional biological functions beyond bone and metabolic functions. Evidence promoting increased depression, anxiety, decreased learning, and memory capacity was revealed between Osteocalcin deficient mice and their wild-type counterparts. Administration of Osteocalcin by intracerebro-ventricular (ICV) infusions remediated the learning and memory deficit – possibly by preventing neuronal apoptosis in the hippocampus. Further, fetal brain development was impaired in osteocalcin deficient mice resulting in mild to severe cognitive impairment. In humans, research by Puig J., et al., also showed deleterious cognitive performance indicators correlated with lower osteocalcin levels in obese subjects. This research may also carry significance in cognitive decline due to aging, since osteocalcin synthesis and/or activation also decreases with age. One such study by Khrimian L., et al., indicated that exogenous osteocalcin can improve hippocampal-dependent memory in mice and identify molecular tools to harness this pathway for therapeutic purposes.


Osteocalcin regulates glucose metabolism, and several studies have linked Osteocalcin regulation to effects on insulin sensitivity and obesity. The first evidence of this relationship was generated using Osteocalcin deficient mice, which developed an atypical storage of visceral fat (Ducy, et al). Later, experiments by Lee NK., et al., revealed further evidence that bone may actively promote regulation of energy homeostasis. It was noted in this study that Osteocalcin knock-out mice were glucose intolerant and maintained decreased insulin secretion, insulin resistance, and β-cell proliferation while exhibiting increased adiposity and serum triglyceride levels. Fulzele K., et al., also reported that mice lacking insulin receptor signaling in osteoblasts show increased adiposity and hyperglycemia in addition to severe glucose intolerance and insulin resistance. Based on this evidence, Ferron M., et al., performed a study supplying daily intermittent injections of osteocalcin to mice consuming a high-fat-diet, which partially restored insulin sensitivity and glucose tolerance, as well as displaying additional functional benefits. Results suggest a strong improvement in glucose regulation and increased type 2 diabetes resistance. Huang L., et al., also mirrored these findings in Osteocalcin treated rats while Fernandez-Real JM., et al., reproduced similar associations in humans performing resistance training.


With strong links to glucose metabolism, researchers have naturally been drawn to Osteocalcin’s role in Sports Performance with interesting results. Specifically, researchers investigated the adaption of Osteocalcin levels to provide optimal performance in humans and rodents. Research by Lin X., et al., and Mera P., et al., shows that undercarboxylated osteocalcin improved muscle glucose uptake in rodent models. In humans, research by Levinger I., et al., Kim YS., and Ahn N., et al., identified that undercarboxylated osteocalcin also supports musculoskeletal interactions, specifically noting that increases in osteocalcin levels improved performance, fitness, and even CRP levels. Many studies also found improved insulin sensitivity were highly correlated with increased in osteocalcin levels.


Is it possible that the inclusion of salivary osteocalcin in your studies of human health and development would advance your research program? Based on our review of the current literature, we believe it’s very likely. However, much more research needs to be done to make this a certainty. Salimetrics capability of measuring osteocalcin using a minimally invasive specimen opens this window of research opportunity wide. We encourage those interested to review these exciting findings, revisit the core scientific assumptions, consider the utility of this interesting bone derived hormone in their research, and connect with our scientific team for the latest updates and findings related to the integration of salivary osteocalcin in studies of human development, stress, health, performance, and well-being.



With the release of the Expanded Salimetrics Cytokine Panel, now is a great opportunity to further explore cytokine biology and review the recent surge of interest in cytokines for salivary bioscience research.

In 2016, Salimetrics SalivaLab validated and released the Core 4 Salivary Cytokine Panel, which included IL-1 Beta, IL-6, IL-8, and TNF-alpha. The initial response from the research community has been overwhelming in its desire to integrate salivary cytokines into multi-disciplinary research. To further facilitate this need and continue the scientific momentum, Salimetrics recently released an Expanded Salivary Cytokine Panel that now includes 5 additional salivary cytokines (IFN-γ, IL-2, IL-10, IL-12p70, and IL-13) which can optionally be measured along with the Core 4. The addition of these new salivary cytokines to the SalivaLab test menu further enables researchers to expand into a new era of discovery. In this bulletin, we want to share with you some of the exciting research being done with cytokines and outline how cytokine biology plays an important role in certain diseases and viral infections.


Cytokines are small proteins, essential in cell signaling and responding to sites of inflammation and infection. Cytokines help regulate immune responses that are associated with various diseases and infections. The benefit of measuring cytokine levels in saliva through noninvasive methods allows researchers to analyze important factors that contribute to the immune response of inflammation and feeling “ill”. Research now shows evidence that the impact of stress also causes the release of pro-inflammatory cytokines, and researchers are now determining the effects of these changes on behavior and overall health. Over time, chronic stress can disrupt the balance of cytokine levels in circulation, which may alter the body’s ability to fight infections or control disease symptoms and progression. Researchers in dentistry have long been studying the impact of salivary cytokines in response to oral health, which also leads to systemic effects if disease progression is not addressed over time. Additional research in asthma, oral cancer, immune health, and oral lichen planus have also benefited from the investigation of salivary cytokines.


Measuring cytokines and chemokines in oral fluid offers a non-invasive assessment of biological markers associated with acute and chronic stress. A recent review by Slavish et al., summarizes several research efforts that have turned to measuring inflammatory cytokines in saliva for acute stress and the impact on brain, behavior and immunity (1). In a more recent study, levels of IL-1 β, IL-18 and IL-6 have been associated with an emotional difference during stress in young men (2). Within the panel of cytokines offered by the Salimetrics testing facility, IL-1 β is one central regulator of the acute stress response and elevated levels of this cytokine, have been linked to various psychosocial and physiologic impacts of stress (3-7). The link between cytokines and behavior has been directly established in the central nervous system, where signaling directly leads to behavior associated with being ill, including fatigue, loss of appetite, irritability and poor cognitive function (8). Various inflammatory cytokine levels have been associated with early life adversity, markers of toxic stress (9) and immune function (10).


Several cytokines are thought to orchestrate and perpetuate the chronic airway inflammation observed in asthma and COPD. These are mostly in the type 2 immune response class (11). The critical roles of these cytokines in driving immune pathology in asthma and COPD is emphasized by active drug programs targeting them for current and future treatments of these diseases (12, 13). Since oral and lung fluids are somewhat contiguous, markers in saliva directly reflect levels in the inflamed airway. In fact, saliva samples have been used to monitor cytokine levels of interest in children and adults with airway inflammation (14). This is a developing area of research attractive to child asthma or adult COPD researchers that are interested in more frequent, at home sampling to better understand these diseases. For the interested reader please see (11, 15, 16).


Often, each of these diseases have profound symptomology that enables visual diagnosis of disease and progression (e.g., in pocket depth for gingivitis) and progressive disease is common without treatment. However, there is interest in the dental research community to study key salivary cytokines in at-risk pre-symptomatic individuals as a means to study mechanisms of disease onset that may enable earlier preventative treatments in the clinic. Periodontal disease and gingivitis involve chronic inflammation fueled by pro-inflammatory cytokines, connective tissue breakdown and bone erosion (17). Many of these cytokines are part of our Core 4 panel and are in the inflammatory cytokine category. However, several may be of interest to researchers to better understand early events that lead to oral immune pathology.


Many large-scale efforts to identify biomarkers of oral cancers and precancerous lesions have involved extensive expression profiling and proteomics in saliva. The efficacy of salivary biomarkers has been assessed as diagnostic tools in the diagnosis or screening for oral squamous cell carcinoma (OSCC), (19). One promising chemokine that was identified and later confirmed in several follow up studies is IL-8. Other cytokines offered in our menu that have been associated with various oral malignancies include IL-β, IL-6 and TNF-α (20-23). Oral cancer researchers can use saliva to measure markers whose relevance is to identify pathology at the source of the marker i.e., in the oral cavity. Local confounding factors that must be controlled for when measuring the inflammatory cytokines would be local inflammation and/or periodontal disease.


Oral lichen planus (OLP) is a chronic inflammatory disease (24) of unknown cause, where elevated cytokines, including IL-6, IL-8, IL-17, IFN-γ, and TNF-α have been observed when compared to healthy individuals (25). Many studies have established interesting relationships with the levels of these salivary cytokines and the development and progression of OLP which raises the possibility that salivary cytokine measures may be valuable predictive markers for OLP (25).


From the beginning, Salimetrics has been partnering with researchers to harness emerging knowledge and develop tools that make salivary cytokine research easy. Today, a multitude of fields are benefiting from Salivary Cytokine Research, and Salimetrics is here to help facilitate that research with the methods needed to continue to advance the cutting edge. While studying cytokines in saliva can help researchers analyze stress, asthma, chronic obstructive pulmonary disease, periodontal disease, oral viral infections, HSV, and more, it’s important to understand basic cytokine biology, so that trusted, validated methods for salivary bioscience testing are used. Through a high-quality lab, such as the Salimetrics SalivaLab, you can trust that the data you receive meets the standards required for maintaining rigor and reproducibility in Salivary Bioscience.


  1. Slavish DC, Graham-Engeland JE, Smyth JM, Engeland CG. Salivary markers of inflammation in response to acute stress. Brain, behavior, and immunity. 2015;44:253-69.
  2. La Fratta I, Tatangelo R, Campagna G, Rizzuto A, Franceschelli S, Ferrone A, et al. The plasmatic and salivary levels of IL-1beta, IL-18 and IL-6 are associated to emotional difference during stress in young male. Sci Rep. 2018;8(1):3031.
  3. Goshen I, Yirmiya R. Interleukin-1 (IL-1): a central regulator of stress responses. Front Neuroendocrinol. 2009;30(1):30-45.
  4. Szabo YZ, Fernandez-Botran R, Newton TL. Cumulative trauma, emotion reactivity and salivary cytokine levels following acute stress in healthy women. Anxiety Stress Coping. 2019;32(1):82-94.
  5. Szabo YZ, Newton TL, Miller JJ, Lyle KB, Fernandez-Botran R. Acute stress induces increases in salivary IL-10 levels. Stress. 2016;19(5):499-505.
  6. Muller N, Krause D, Barth R, Myint AM, Weidinger E, Stettinger W, et al. Childhood Adversity and Current Stress are related to Pro- and Anti-inflammatory Cytokines in Major Depression. J Affect Disord. 2019;253:270-6.
  7. Riis JL, Out D, Dorn LD, Beal SJ, Denson LA, Pabst S, et al. Salivary cytokines in healthy adolescent girls: Intercorrelations, stability, and associations with serum cytokines, age, and pubertal stage. Developmental psychobiology. 2014;56(4):797-811.
  8. Dantzer R, O’Connor JC, Freund GG, Johnson RW, Kelley KW. From inflammation to sickness and depression: when the immune system subjugates the brain. Nature reviews Neuroscience. 2008;9(1):46-56.
  9. Johnson SB, Riley AW, Granger DA, Riis J. The science of early life toxic stress for pediatric practice and advocacy. Pediatrics. 2013;131(2):319-27.
  10. Riis JL, Granger DA, DiPietro JA, Bandeen-Roche K, Johnson SB. Salivary cytokines as a minimally-invasive measure of immune functioning in young children: Correlates of individual differences and sensitivity to laboratory stress. Developmental psychobiology. 2015;57(2):153-67.
  11. Barnes PJ. Targeting cytokines to treat asthma and chronic obstructive pulmonary disease. Nat Rev Immunol. 2018;18(7):454-66.
  12. Tait Wojno ED, Hunter CA, Stumhofer JS. The Immunobiology of the Interleukin-12 Family: Room for Discovery. Immunity. 2019;50(4):851-70.
  13. Teng MW, Bowman EP, McElwee JJ, Smyth MJ, Casanova JL, Cooper AM, et al. IL-12 and IL-23 cytokines: from discovery to targeted therapies for immune-mediated inflammatory diseases. Nat Med. 2015;21(7):719-29.
  14. Papadopoulos NG, Agache I, Bavbek S, Bilo BM, Braido F, Cardona V, et al. Research needs in allergy: an EAACI position paper, in collaboration with EFA. Clin Transl Allergy. 2012;2(1):21.
  15. Bradding P, Roberts JA, Britten KM, Montefort S, Djukanovic R, Mueller R, et al. Interleukin-4, -5, and -6 and tumor necrosis factor-alpha in normal and asthmatic airways: evidence for the human mast cell as a source of these cytokines. Am J Respir Cell Mol Biol. 1994;10(5):471-80.
  16. Garth J, Barnes JW, Krick S. Targeting Cytokines as Evolving Treatment Strategies in Chronic Inflammatory Airway Diseases. International journal of molecular sciences. 2018;19(11).
  17. Ghallab NA. Diagnostic potential and future directions of biomarkers in gingival crevicular fluid and saliva of periodontal diseases: Review of the current evidence. Archives of oral biology. 2018;87:115-24.
  18. Silva N, Abusleme L, Bravo D, Dutzan N, Garcia-Sesnich J, Vernal R, et al. Host response mechanisms in periodontal diseases. J Appl Oral Sci. 2015;23(3):329-55.
  19. Gaba FI, Sheth CC, Veses V. Salivary biomarkers and their efficacies as diagnostic tools for Oral Squamous Cell Carcinoma: Systematic review and meta-analysis. J Oral Pathol Med. 2018.
  20. Sahibzada HA, Khurshid Z, Khan RS, Naseem M, Siddique KM, Mali M, et al. Salivary IL-8, IL-6 and TNF-alpha as Potential Diagnostic Biomarkers for Oral Cancer. Diagnostics (Basel). 2017;7(2).
  21. Prasad G, McCullough M. Chemokines and cytokines as salivary biomarkers for the early diagnosis of oral cancer. Int J Dent. 2013;2013:813756.
  22. Saxena S, Sankhla B, Sundaragiri KS, Bhargava A. A Review of Salivary Biomarker: A Tool for Early Oral Cancer Diagnosis. Adv Biomed Res. 2017;6:90.
  23. Khurshid Z, Zafar MS, Khan RS, Najeeb S, Slowey PD, Rehman IU. Role of Salivary Biomarkers in Oral Cancer Detection. Adv Clin Chem. 2018;86:23-70.
  24. Schlosser BJ. Lichen planus and lichenoid reactions of the oral mucosa. Dermatol Ther. 2010;23(3):251-67.
  25. Humberto JSM, Pavanin JV, Rocha M, Motta ACF. Cytokines, cortisol, and nitric oxide as salivary biomarkers in oral lichen planus: a systematic review. Braz Oral Res. 2018;32:e82.

*Note: Salimetrics provides this information for research use only (RUO). Information is not provided to promote off-label use of medical devices. Please consult the full-text article.


Better Methods is a new, multi-part series highlighting ‘best practice’ methods in salivary bioscience that can have a positive impact on the quality and reproducibility of salivary bioscience research.


It’s common for researchers to design their saliva sample collection plan based on what they can afford to test in their study budget. The number of samples collected, and the volume collected from each participant are typically dependent on study design and the analytes being considered for measurement. For most researchers, every sample that is collected is used for analyte measurements, leading the researcher to believe this practice is the best practice; however, this is not the case. Once collected, all samples need not be tested right away, and researchers can benefit from having additional samples available. Collecting more samples is an often overlooked, easy and affordable way for researchers to increase the quality of their research study without substantially impacting their budget.


The actual cost of collecting samples is very small compared to the other costs in a salivary bioscience research study. Typically, the effort and expense of study design, organization, recruitment of participants, coordination and sample collection logistics in the field and in the lab are the most expensive part of a study. Depending on the study design, sample analysis in a qualified saliva lab is the next significant expense. While the expenses associated with these two parts are largely dependent on the number of participants and the participant requirements in the study design; the cost of additional sample collection will mostly be the cost of additional saliva collection materials. In just about every grant, this is an insignificant cost to the study. This low cost compares to the high value these extra samples may bring to a researcher: (1) by improving participant compliance; (2) by providing the opportunity to overcome limitations in a study; and (3) by offering the researcher a best practice method to expand their findings with a new, cost effective grant. It is often efficient and effective to collect more saliva samples than needed for the primary study’s purpose.


Practice increases participant compliance. Participants are often new to saliva collection and can struggle with following unfamiliar protocols, no matter how well they have been given instructions. Combined with the anxiety associated with performing in front of a researcher or assistant, saliva collection can be challenging for some individuals. Providing practice samples can reduce participant performance anxiety and increase the level of comfort with the saliva collection devices. This helps participants generate more sample volumes, and more importantly, often makes it possible to get meaningful samples from the few participants who may struggle and otherwise not be able to provide sample volumes above the minimum volume required for analysis. The practice sample, while primarily used to improve participant compliance, may also be used as an extra sample to be tested and provide additional data at a later time.


Do not wait to find out you need more data. Extra samples provide flexibility when it comes time to do sample analysis. In many cases, collecting extra samples per participant enables researchers to go back and test these samples to examine finite individual changes and/or patterns using multilevel modeling, modeling which may provide the additional stability needed to develop a robust conclusion. This data also affords the opportunity to assess patterns across multiple days/time points which would not be possible from a smaller sample set. During final analysis, a researcher may find that certain observations need additional data to overcome limitations. Having these extra samples available to be tested can provide supplemental data which may make it possible to strengthen the researchers’ findings. Additionally, collected samples on-hand give the researcher opportunities they otherwise wouldn’t have.


Future research can leverage your current study. Since sample collection is a minor expense of the overall budget, the original samples and these extra samples can be biobanked for years. This is a great value because just as assays for new analytes in saliva have emerged in the past decade, more and more assays for analytes in saliva are being developed that will lead to new discoveries that push the cutting edge of salivary bioscience. In addition, new research findings may suggest an existing analyte’s relevance to your research questions that were previously unknown. Assays in oral fluids now include drugs of abuse, infectious disease exposure, hormones, cytokines and measures of inflammatory processes, microbiome analysis, epigenetics, metabolomics, and more. With such a wide range of analyses possible, collecting additional samples makes more sense than ever, and a good researcher can expand their findings by leveraging biobanked samples with a new, cost-effective research grant.


Researchers should consider the benefits of collecting additional samples in their own study based on their current and future research goals. Whether the benefits are intended to increase the power of their current study through participant compliance and statistical modeling, intended for future iterations of their research focus, or intended for future analysis based on cutting edge assay development, or all of the above, it’s important for researchers to be proactive. Following this saliva collection best practice by collecting one or more extra samples can provide increased potential without a major impact on the bottom line.

*Note: Salimetrics provides this information for research use only (RUO). Information is not provided to promote off-label use of medical devices. Please consult the full-text article.


Rigor and Reproducibility is a three-part series on the steps researchers can take to improve the quality of their salivary bioscience data.


In Part 1, How Good Are Your Lab Results? of our Rigor and Reproducibility series, we shared how controlling for sources of variability leads to higher data consistency, which is essential in establishing precise results and drawing reliable conclusions from generated data. Part 1 specifically examined the findings from the 2017 study: “Measurement of cortisol in saliva: a comparison of measurement error within and between international academic-research laboratories”, from Calvi et al. The study results were impressive – in high-quality labs, the average intra-assay (same lab, same plate) CV was only 6.2%; the average inter-assay (same lab, different plate) CV was only 6.36%; the difference attributed to the labs was only 7.93%; and just 1.76% of the difference could be attributed to the Salimetrics Cortisol Assay. This is a highly relevant conclusion: high-quality laboratories combined with better assays produce better results that are reliable and precise for the scientific community.

Part 1, was well received by the salivary bioscience research community (as was Part 2, How Good are Your Saliva Samples?), with the overwhelming follow up question being: “What makes a saliva lab high-quality?” This Salivary Bioscience Bulletin, which we are calling “Part 1 Supplement”, is dedicated to providing key attributes of a high-quality salivary bioscience laboratory and why they are important, so that researchers can make the best choice and have the best chance at getting consistent, high-quality salivary bioscience data.


#1   Performs routine calibration of lab equipment (Rigor)

Making sure lab equipment is calibrated is the same as making sure a car is in alignment. Over time, or as a result of being bumped or mishandled, equipment measurements can drift in one direction and lead to bias in the results generated. High-quality labs avoid this type of systematic error by having all their lab equipment in a scheduled, routine calibration program. A high-quality salivary bioscience lab will calibrate equipment such as pipettes every six months and monitor hard working equipment such as plate readers on a monthly basis. Calibration of lab equipment allows for reproducible measurements; conversely, uncalibrated equipment is one of the principle sources of lab error and almost always guarantees that the same samples tested across different labs will have a high inter-lab assay variability.

#2   Follows rigorous quality acceptance criteria for assay results (Rigor)

While assay manufacturers differ in their acceptance criteria, a good assay manufacturer will provide assays that meet rigorous quality acceptance criteria, and then provide protocols and guidance that ensures each laboratory can achieve great results. It’s a simple fact: the tighter the acceptance criteria, the less variability in results; the wider the acceptance criteria, the greater the variability in results. Salimetrics’ assays are manufactured and quality tested to rigorous acceptance criteria; any high-quality laboratory using Salimetrics’ assays should achieve the following quality acceptance criteria (don’t worry if you do not understand these terms – just ask Salimetrics for help. If the lab doesn’t understand these requirements, find another lab.):

  • The standard curve, using all standards, shall have an R2 curve fit ≥ 0.99
  • For multiple plate runs, the B/B0 standard curves shall overlay
  • The high and low control concentrations shall each be within the expected range provided with the assay batch documentation
  • For multiple plate runs from the same batch, the high and low control concentrations shall not deviate across all plates by more than 10%
  • Quality Acceptance Data shall be available to be provided with results

Acceptance criteria are like guide posts; they let you know you are going in the right direction and can trust the results. High-quality labs understand the importance of meeting all acceptance criteria; they do not follow some and overlook adherence to others in order to provide results – results that will likely contain errors. For example, a less qualified lab may check that the controls are within the expected range but may not check the R2 curve fit. Accuracy of the curve fit confirms that sample concentrations across the range of the standards are reading with precision. If a researcher is looking for pre and post intervention data, a good curve fit means the difference between the pre and post samples will be precise. Alternatively, if a less qualified lab checks that the R2 curve fit is ≥0.99, but the control values are out of range, the results will likely have a bias. In other words, while the difference between two samples is precise, the actual value of each of the samples may be too high or too low depending on the bias, and therefore not true. High-quality labs understand these requirements, consistently meet the criteria, and make their Quality Acceptance Data available so that you can trust the results.

#3   Follows a documented CV% acceptance/repeat criteria (Rigor)

High-quality labs can control for many possible sources of lab error, but saliva samples are unique in that they may be viscous and heterogenous, and, if the saliva samples are not processed by the lab correctly, duplicate measurements of the same sample can have large deviations between the two measures. Consider duplicate measurements of the same sample having a CV% of 20%; this means that the two measurements are actually 40% apart, and the mean value is 20% apart from each of the two values. More often than not, only one of these measures is incorrect, so choosing the mean value suggests that the value intrinsically has a 20% error. Further, if the average CV% of the entire data set is 20%, then any conclusions made by the researcher would be unsupported if the conclusion did not rely on a >20% difference between the means.

In addition to following good protocols, a high-quality lab will avoid sample processing and handling errors by having well-documented criteria that only permits the acceptance of the duplicate mean based on a maximum allowable percentage of coefficient of variation between duplicate values, or when the absolute difference of the duplicate values is small and does not have biological significance. When the criteria are not met on a sample, the sample is rerun or excluded from the final data analysis. In addition, for quality control, the lab should record the sample as having been repeated.

#4   Allows only laboratory personnel trained in salivary testing to run the assays (Rigor)

High-quality labs know there are subtleties to lab work that are minimized through proper training and experience. Understanding how to work with viscous samples to avoid the introduction of bubbles and tiny volume discrepancies when pipetting, how to prevent bias across the plate, and even how to read and interpret the aforementioned quality control data, can make a difference in the integrity of the results. As with many things, it is not difficult; however, it requires the rigor which comes from good training. Both inter- and intra-assay CVs are improved when adequately trained personnel run assays. A high-quality lab will incorporate exercises such as pipetting proficiency into the training of personnel, and document the results, before actual assays are run.

*Note: Operators #2, 3 and 5 should be retrained, focusing on small volume pipetting techniques.

#5   Routinely processes saliva samples and performs saliva testing (Repeatability)

Practice makes perfect. A proven lab has more expertise and experience at running assays compared to labs that run assays infrequently; that’s why all Salimetrics’ certified Center of Excellence labs must run a minimum of 5,000 salivary tests per year. It’s not that most labs are unable to get acceptable results from some of their salivary testing. It’s that most labs do not know how to get the best results from all of their saliva testing, and that’s simply because they have not tackled the full breadth of issues a proven, high-quality lab has experienced. A high-quality lab knows how to troubleshoot and determine where potential issues may lie, and how to correct to get the best results. For example, most studies have samples which vary in terms of volume, clarity and viscosity. A high-quality lab has the experience and know-how to get the best data from a low-volume, viscous sample and that means errors are minimized, or as is often the case, a high-quality lab will be able to test the sample and get results whereas the less qualified lab may not be able to test the sample, and that may lower the power of a researcher’s study.

#6   Participates in a proficiency testing program and sample exchanges (Repeatability)

Participating in a proficiency testing program is like getting a graded report card for the lab. It’s conducted after the lab meets all of the basic requirements for rigor, including training, and thereafter at minimum on an annual basis. For diagnostic labs, it is a regulatory requirement that they demonstrate proficiency in sample handling and processing by providing sample measurements on unknown, “controlled” samples. Once values are reported, the lab gets a proficiency report for each of the analytes tested and is deemed proficient to provide testing services if their results are within the expected range for the “controlled” sample. While this might not seem relevant to research, it is! A key finding of the Calvi study was that a researcher can trust that the difference in results between high-quality labs running the same assays will be small and the results repeatable. Participation in a proficiency testing program is preferred, but it is also possible to demonstrate proficiency through sample exchanges with another high-quality lab. In this instance, aliquots of samples are sent to an independent, qualified lab that is able to run the samples on the same kit/methodology. The results are demonstrated in the same way they would be demonstrated in a proficiency testing program.

#7   Uses and recommends validated saliva collection methods (Repeatability)

High-quality labs know that how a sample is collected and handled prior to testing can significantly impact the measurements obtained from that sample. They understand that data from poorly handled samples will likely harm the data set when developing scientific associations and conclusions. For example, not correcting for flow rate when measuring an analyte that is impacted by flow, using an incorrect method to stimulate flow, using samples subjected to multiple freeze-thaws, or using an unvalidated swab for the collection of saliva without fully understanding the bias/interference created by the swab material (See Part 2, How Good are Your Saliva Samples?) are all errors that may affect scientific conclusions. Conversely, following validated methods reduces variability: from collection; from transport; from storage; from freezing; from the bench – all of which increase the repeatability of the results. A high-quality lab knows what the validated saliva collection methods are, and like Salimetrics, they know how to make the best saliva collection recommendation for a study. These labs keep up with evolving best practices and are a great resource for newer researchers.


The high-quality Salimetrics SalivaLab has been an integral part of Salimetrics since the company was founded and has tested millions of saliva samples. While testing with the Salimetrics SalivaLab is always a great option for a researcher, we do recognize that at times researchers may need to select a different lab. To help make the selection of a high-quality lab better for researchers, Salimetrics developed its Center of Excellence (COE) Program which identifies and certifies high-quality saliva labs. Inclusion in the COE program is optional, and by no means does the lack of inclusion in the COE program signify that the non-participating lab is unable to achieve high-quality results. However, a researcher can be assured that in addition to the Salimetrics SalivaLab, all labs in the Salimetrics COE program meet the attributes of a high-quality lab. For researchers who intend to run assays in their own lab, following the key attributes we present here will provide the best chance of assuring that their data will be precise.

We conclude with a simple statement: salivary bioscience research is stronger when it is dedicated to the methods that bring rigor and reproducibility.

*Note: Salimetrics provides this information for research use only (RUO). Information is not provided to promote off-label use of medical devices. Please consult the full-text article.


Rigor and Reproducibility is a three-part series on the steps researchers can take to improve the quality of their salivary bioscience data.


As researchers, we understand the necessity of minimizing variability from external sources that can negatively impact data interpretation. Variability can arise from many factors, such as differences between samples, participant noncompliance, specimen handling, differences between assay kits, and/or differences between laboratories. Controlling for sources of variability leads to higher data consistency, which is essential in establishing precise results and drawing reliable conclusions from generated data. Part 1 of this 3-part series on rigor and reproducibility in salivary bioscience will take an in-depth look at improving the quality of your salivary bioscience research based on the findings from a 2017 study: “Measurement of cortisol in saliva: a comparison of measurement error within and between international academic-research laboratories,” from Calvi et al.

While it can be difficult to control sample-specific physiological variability and participant noncompliance, researchers can easily control which assays and laboratory are utilized to generate data for their studies. Dr. Calvi’s team highlighted how researchers can obtain better results by studying the effect of quality laboratories on measurement precision when using the Salimetrics Salivary Cortisol Assay kit. The study design involved sending aliquots of 100 individual samples to nine different qualified labs, and comparing the results generated from these samples by each lab. The results were impressive; in these high-quality labs, the average intra-assay (same lab, same plate) CV was only 6.2%, and the average inter-assay (same lab, different plate) CV was only 6.36%. Furthermore, when the results of the labs were compared with each other, over 90% of the variation was attributed to differences in the samples, only 7.93% was attributed to the differences in the labs, and just 1.76% could be attributed to the Salimetrics’ cortisol assay. Keep in mind that in research, normal acceptance values for inter- and intra-assay CVs are typically less than 15% and 10%, respectively, and both the inter- and intra-assay variation observed in the study were substantially better. The researchers concluded that qualified laboratories contributed to a very small portion of measurement variation. This conclusion is highly relevant – better laboratories combined with better assays will produce better results that are reliable and precise for the scientific community.


Researchers have the power to reduce variability in the salivary bioscience testing phase of their study. The first step is selecting an established, high-quality assay that is routinely published with the lowest CVs, such as the Salimetrics’ salivary cortisol assay. Next, the researcher should examine and choose an established, high-quality laboratory experienced for the assay being used before they send their samples. Salimetrics provides extensive laboratory quality control which commonly produces CVs of less than 3% for analytes such as salivary cortisol.

The research shows that if these two factors are handled correctly, the remaining source of variation, the samples, can be properly addressed to achieve better results. Often, sample variation is the product of poor participant compliance, use of non-validated collection methods or poor sample handling. Salimetrics provides researchers extensive resources and collection methods for identifying and limiting variability in samples. Part 2 of this 3-part series on rigor and reproducibility in salivary bioscience will take an in-depth look at improving the quality of samples and limiting sample variation.


To reduce overall variation in research studies, Calvi et al. determined that it is essential to choose a laboratory which meets the current standards for an experienced, qualified laboratory and a high-quality assay, such as the Salimetrics salivary cortisol assay. By choosing to do so, researchers can easily remove a substantial degree of variability from their research. It can be that simple.


Calvi, J. L., et al. (2017). Measurement of cortisol in saliva: a comparison of measurement error within and between international academic-research laboratories. BMC Research Notes. 10:479.

*Note: Salimetrics provides this information for research use only (RUO). Information is not provided to promote off-label use of medical devices. Please consult the full-text article.


Rigor and Reproducibility is a three-part series on the steps researchers can take to improve the quality of their salivary bioscience data.

Much is being written by the salivary bioscience community on maintaining reproducibility, trueness, and accuracy when selecting assays and labs to perform testing of salivary analytes. This focus is well deserved; Salimetrics assays are designed specifically for human saliva and have the highest level of reproducibility, precision, and accuracy within the salivary bioscience field.

However, there’s another aspect of salivary bioscience that gets much less attention, but has the capacity to introduce a high level of error and generate inaccurate results. A simple, incorrect assumption in the collection method, device or technique can introduce significant variability into your salivary bioscience study – at times, even more than the assay itself.

A simple, incorrect assumption in the collection method, device or technique can introduce significant variability into your salivary bioscience study

The best option for improving the integrity of a saliva specimen is to collect using passive drool. Passive drool is the gold standard, and the method for collecting the best passive drool sample is now standardized (see How to Collect the Best Saliva Samples). Passive drool does not interfere with the salivary analytes being measured, and it permits an expanded range of tests to be performed. Conversely, swab collection methods are restrictive to what analytes can be accurately measured in saliva, and some widely used swab collection methods introduce variability and negatively affect results. Clearly, however, there are participants including infants and small children where it is not possible to collect using the passive drool method. For these participants, it is essential to select a swab collection method, device and technique that closely matches passive drool and minimizes collection method error.

Collection method error was recently highlighted in a review by Gröschl, “Saliva: a reliable sample matrix in bioanalytics”. The Gröschl review identifies two common swab collection methods used in research and states that these methods are identical. However, data shows that this statement is not correct, and the potential implications to a study can be substantial based on which swab is used for collection. A second paper by Büttler, “Testosterone, Androstenedione, Cortisol and Cortisone Levels in Human Unstimulated, Stimulated and Parotid Saliva”, also highlights collection method error. The Büttler paper focuses specifically on the strength and weakness of different collection methods compared to the gold standard of collection methods: unstimulated passive drool. Both papers do well to raise the awareness of collection method error as a source of variability in research.

Unfortunately, researchers often choose a specific collection device based on previous collaborations and published studies. Similarly, they may use a meta-analysis which generalized conclusions without relaying the limitations from the original findings. This may cause researchers to overlook important details that can have a big impact on their study. As a researcher, it is necessary to have an understanding that different collection methods, as well as improvements in collection methods and protocols, will directly impact your results. “Better collection” isn’t just a statement; it’s also backed by science.

In current research there are two common swab methods for collecting saliva samples; the Salivette® from Sarstedt and the SalivaBio Oral Swab from Salimetrics. The Salivette®, which debuted around 1987, was the staple method for early swab collection techniques. With its simple cotton swab, the Salivette® still maintains its presence as a legacy swab collection device and is useful in a few select fields of study. However, in the early 2000s, based on concerns from the research community related to poor recovery, random concentration spikes, chemical odors, non-hygienic storage, randomized quality control, and lot-to-lot variability, Salimetrics developed a more reliable material.

In 2006, Salimetrics introduced the SalivaBio Oral Swab (SOS), an inert, non-cotton polymer swab that maintained sample integrity for multiple salivary analytes. The main benefit to salivary bioscience is that a synthetic swab is not prone to fluctuating measurements like an organic material, such as cotton. When measuring analytes in saliva (EIA/LIA/LC-MS/MS), numerous studies and Salimetrics’ internal data concluded that cotton can introduce errors and interference into salivary analyte measurements, depending on the analyte being measured.

To be clear, the Salivette® is NOT the SalivaBio Oral Swab…

To be clear, the Salivette® is NOT the SalivaBio Oral Swab; the material composition, manufacturing, and packaging are different. Salimetrics also performs additional QC testing to verify recovery and conformity across multiple lots to maintain minimal lot-to-lot variability. These are important differences, and Salimetrics has employed rigorous validation criteria to ensure the SalivaBio Oral Swab avoids bias in salivary analyte results. Other swabs introduce bias. Evidence of this bias is demonstrated in Figure 1 below. Presented is a correlation of different Salivettes® and the SalivaBio Oral Swab to passive drool, determined using samples from different individuals, and assayed for salivary cortisol using Salimetrics assay kits. Interestingly, the data in the graph below supports the often cited Shirtcliff paper (Shirtcliff et al., 2001) comparing the cotton Salivette® to passive drool. The conclusion from this figure is significant; cotton is not the gold standard. Passive drool is the gold standard and the correlation of the SalivaBio swab to passive drool is an astounding r=0.98 (p=<0.005). If researchers want to use a swab collection method that matches the gold standard and does not impact their data, then the SalivaBio swab is the only choice. There is no other swab method that is identical. Likewise, the Büttler paper also confirms that salivary cortisol should not be collected with cotton, and more so, cotton should not be used for any of the analytes they tested in their study.

If researchers want to use a swab collection method that matches the gold standard and does not impact data, then the SalivaBio swab is the only choice

Beyond a comparison of correlations for the different collection methods, it is also important to evaluate specificity of the collection methods. This is where the analysis in the Büttler paper that salivary cortisol is “unaffected” when collected with the Salivette® Cortisol is incomplete. While the total mean concentration of each result may be unaffected, the individual samples vary. Figure 2 below represents specificity in relation to measurements from samples obtained by passive drool. The band represents the acceptable range, established by applying a 20% acceptance criterion as a standard. From this data, it can be easily seen that 100% (10 out of 10) of the individual samples collected with the SalivaBio Oral Swab met the acceptance criteria; 40% (4 out of 10) of the individual samples collected with the Salivette® Cortisol met the acceptance criteria; and 40% (4 out of 10) of the individual samples collected with the Cotton Salivette® met the acceptance criteria. This experiment shows that only the SalivaBio Oral Swabs met the acceptance criteria for specificity with salivary cortisol measurements.

Fig. 2
Note: The SalivaBio Oral Swab was also tested using pooled saliva samples on IBL Cortisol Assay Kits. Results showed 97% and 98% match to passive drool for morning and afternoon samples respectively.

…40% (4 out of 10) of the individual samples collected with the Salivette® met the acceptance criteria

Not surprisingly, the same lack of specificity using Salivettes® is present in the data provided by Büttler. Figure 3 below shows that of the eighteen samples in the figure, at least five (28%) of the individual samples did not meet the 20% acceptance criteria. It is unfortunate Büttler did not include the SalivaBio swabs in this study, however their independent data reinforces our conclusion that only the SalivaBio Oral Swabs provide reproducible specificity compared to the gold standard of passive drool

Fig. 3. (Büttler et al., 2018).

Some researchers also assume that since the Salivette® Cortisol is made from a synthetic polymer, it is also approved for the analysis of multiple salivary analytes. However, Salimetrics’ attempts to validate the Salivette® Cortisol using EIAs for analytes other than cortisol show even higher randomized error. This is an unnecessary additional risk to salivary analysis data. Below is a graph from the validation experiment using the Salivette® Cortisol for salivary testosterone analysis. Büttler et al., also confirmed this finding independently.

Finally, it would be a mistake to ignore the value of SalivaBio swabs’ individual, medical grade packaging and its family of swabs adopted for different age groups. It was quickly noted in field research that participants preferred using a swab that was provided in a sealed package. This, in turn, resulted in better participant compliance for saliva collection time points, leading to stronger participant data. Researchers invest a substantial amount of resources in their study and failing to achieve participant compliance is a mistake. SalivaBio swabs are designed to help researchers achieve greater than 99% compliance. Also, many studies include dyads with infants and children, and using different methods that introduce variation can also affect results. Good research considers participant compliance in study design and researchers who choose the right collection device can maximize their final data set with the best possible data.

To summarize, Salimetrics recommends the following for saliva collection:

Whenever possible, collect passive drool; it’s the gold standard.

When a swab method is required..

  • Use a swab method that closely matches passive drool such as the SalivaBio swabs from Salimetrics.
  • Use a swab method that does not change the concentration values.
  • Use a swab method only for the analytes that have been properly validated.
  • Use a swab method that increases participant compliance.


  1. Gröschl, M., (2017). Saliva: a reliable sample matrix in bioanalytics. Bioanalysis. 9(8):655-668.
  2. Büttler, R.M., et al. (2018). Testosterone, androstenedione, cortisol and cortisone levels in human unstimulated, stimulated and parotid saliva. Steroids. 138:26-34.
  3. Shirtcliff E,A., et al. (2001). Use of salivary biomarkers in biobehavioral research: cotton-based sample collection methods can interfere with salivary immunoassay results. Psychoneuroendocrinology. 26(2):165-73.

*Note: Salimetrics provides this information for research use only (RUO). Information is not provided to promote off-label use of medical devices. Please consult the full-text article.


A better assay makes great research possible, and great research can change the way people think. The new salivary oxytocin assay from Salimetrics SalivaLab is one of those assays and great oxytocin research is now possible.

“Today, we offer the research community an opportunity to standardize salivary oxytocin testing and make comparisons across future studies possible. With this new development, we can help researchers build a better understanding of the biological impact of salivary oxytocin with a better assay,” says Steve Granger Ph.D., Salimetrics CSO. “Better yet, researchers are no longer required to provide large sample volumes, sample concentration by lyophilization or solid phase extraction (SPE), which enables the measurement of oxytocin to be integrated into behavioral studies much more efficiently and effectively.”

For years, the methodological issues plaguing the salivary bioscience community regarding reliable and reproducible salivary oxytocin measures have stunted the growth and acceptance of this analyte’s integration in salivary bioscience research. However, the ability to non-invasively and reliably measure oxytocin in human specimens is vital to further knowledge surrounding its biological impact on social behavior, pair-bonding, caregiving, and relationships in multiple scientific fields.

Salimetrics has long been pursuing a relationship with salivary oxytocin since the company’s inception in 1998. However, in 2005, Horvat-Gordon et al., determined that salivary oxytocin was not a valid biomarker when measured in human saliva using currently available immunoassays. Since then, multiple approaches and methodologies have been published, but offered only a glimpse inside the complex nature of oxytocin as a salivary biomarker. This inconsistent application of protocols and processes not only added variability to the measurements researchers relied on, but also to the field in its entirety. Ultimately, this non-systematic approach led to further controversy and confusion within the salivary bioscience community. Now, over 10 years later, after a substantial commitment to research and development, the technological barrier to creating a reliable salivary oxytocin assay has finally been crossed. Thanks to increased analytical sophistication, Salimetrics aims to help researchers clarify the underlying impact of oxytocin by systematically applying a better assay to future salivary oxytocin research.

Salimetrics’ key differentiation in developing a breakthrough assay relies on a highly sensitive chemiluminescence platform with unmatched signal to noise ratios. Salimetrics further backed this assay with years of development and pilot testing. With these extensive research and development efforts, as well as support from leading researchers in the field, Salimetrics is confident in providing a new wave of researchers the right protocol for salivary oxytocin testing. For the first time, salivary oxytocin testing service from the Salimetrics SalivaLab will provide new bearings that enable salivary oxytocin research in a way that will make a difference.

We hope you are as excited about this opportunity as we are and will share this information with those who may benefit. Thank you for your continued support of the salivary bioscience community. To learn more about how salivary oxytocin can be added to your study and enable future oxytocin research, feel free to Contact Us

*Note: Salimetrics provides this information for research use only (RUO). Information is not provided to promote off-label use of medical devices. Please consult the full-text article.



Leading salivary bioscience researchers continue to map the biological landscape by including cutting-edge, multisystem measurements in their research. A single saliva sample can provide robust data for multiple analytes, when handled


Understanding how to properly incorporate multi-analyte measures ensures that researchers produce high-level research with scientifically credible results – But how do you maintain sample integrity across your multi-analyte study? This edition of the Salivary Bioscience Bulletin explores frequent scientific and practical questions, such as: How many samples do I need to collect? What should the proper collection method be? How do I properly store my saliva samples? What is the proper sequence of assays when running large sample volumes for multiple analytes?

Salimetrics has both invested in and collaborated with the research community to develop best practice collection methods, protocols, and products that make accurate multi-analyte measurements possible. Salimetrics experts maintain the latest information and are readily available to help researchers incorporate multiple analytes into research. Below is a quick overview to help make incorporating multiple analyte measurements into your study easy.


Collection Method:

  • If you want to maximize your data and increase compliance, utilize sample collection methods that improve participant compliance by reducing participant burden. Also, consider the total number of samples and sample volume being requested within a specified timeframe from each participant.
  • Passive drool is the recommended collection method, as it is approved for all salivary analytes. However, SalivaBio Swabs are also approved for many analytes and Oral Swabs are preferred if including DNA analysis. Remember that it is possible to analyze multiple analytes, and include DNA analysis for genetic markers, from the same sample.

Volume Required:

  • Increasing volume requirements can impact participant compliance. Choose a collection method that makes collecting appropriate volumes easy and, if swab-based, maximize volume recovery.
  • To determine total volume, simply add the recommended sample volume of all analytes together and then add an extra 300 µl to account for any sample handling loss and possible repeat analysis.
  • Some Salimetrics’ SalivaLab test-panels, require as little as 100 µl sample per panel.

Sample Storage & Handling:

  • Before freezing, know if the analytes you are measuring are stable or sensitive to repeated freeze-thaws. To minimize freeze/thaw cycles, we recommend testing multiple analytes on the same day, but with fewer samples to decrease burden on the assay technician. Alternatively, you can aliquot collected saliva into smaller volumes before freezing, with the awareness that concentrations between aliquots can differ slightly when handling fresh saliva.
Robust (Multiple (up to 3) freeze-thaw cycles permitted)Freeze-Thaw Sensitive (Single freeze-thaw cycle permitted)
CortisolEstrogens (E3,E2,E1)
MelatoninProgesterone, 17OH-Progesterone
CotinineCytokines (IL-1B, IL-6, TNF Alpha)
NeopterinC-Reactive Protein
Total ProteinOxytocin
  • Freeze all samples immediately or as soon as possible after sample collection at or below 20 °C (the temperature of a normal household freezer).

Sample Testing:

  • For large sample volumes, we recommend prioritizing assay order by testing unstable analytes first and applying this schedule consistently across all samples. If several sensitive analytes are being tested, we would recommend aliquoting samples either prior to the first freeze-thaw, or aliquoting the supernatant into smaller test volumes after the first freeze-thaw.
  • Be sure to choose an experienced testing lab capable of running multiple assays in the same day and maintaining sample integrity throughout the testing phase of your study.


Recent research provides a clearer link between stress and its impact on health. Whether that stress is acute or chronic, it can affect the levels of cortisol produced by the human body, which is measurable with a range of sampling regimens and sample types.

Today, the most commonly used sample specimen in cortisol based stress research is saliva. It has been extensively integrated within the scientific field to assess the levels of ‘free’ steroid and sex hormones, and correlation of these hormones with circulating levels in serum has been well established in the literature. With thousands of scientific publications in peer reviewed literature supporting and validating its use, saliva has held up to scientific rigor and provided both credible and useful information on disease states and overall health.


Cortisol is the major circulating hormone of the hypothalamic pituitary adrenal (HPA) axis, exerting its effects through the glucocorticoid receptor expressed in almost all human cells. Secretion of cortisol and its regulation are shown in Figure 1. Outside of its upregulation in response to stress, cortisol levels follow a regular diurnal rhythm of expression in humans, and characterization of the diurnal profile of cortisol expression is a key indicator of HPA axis dysfunction (Fries et al., 2009). One of the most important measures when assessing the diurnal rhythm for cortisol is the concentration of salivary cortisol levels at awakening compared to levels 30 to 45 minutes post awakening. The surge in levels of between 50-150% of free cortisol observed at the 30 minute time point is routinely used in the scientific field to assess adrenocortical activity and the correlation of the surge in cortisol levels post awakening to chronic stress, HPA axis dysfunction, and burnout are well established (Fries et al., 2009). This vital assessment also known as the Cortisol Awakening Response or CAR is driven by ‘morning awakening’ and reveals issues beyond just measuring diurnal rhythm. The surge in cortisol is believed to be due to anticipation of the day ahead and an increased CAR is observed in individuals with perceived elevated burden e.g., unemployed individuals have higher CAR measurements when compared to employed individuals. It is also thought to be an important component of preparedness or “boosting” an individual’s performance for the day ahead (Law et al., 2015; Thorn et al., 2006).

Figure 1. Secretion and regulation of cortisol (Qi and Rodrigues, 2007). Under physiological conditions, neurons in the hypothalamus synthesize and secrete corticotropin-releasing hormone (CRH), which subsequently acts on the pituitary gland causing the release of ACTH, or adrenocorticotropic hormone. ACTH is transported to the adrenal gland where it stimulates the secretion of glucocorticoids, the main one being cortisol.

Figure 2 below is representative of a typical diurnal rhythm pattern for salivary cortisol, and reveals the dynamic nature of cortisol expression in humans. Researchers have shown that abnormal diurnal patterns of free salivary cortisol expression through the course of the day correlate with various pre-clinical or symptomatic and disease conditions including Type 2 diabetes, metabolic syndrome, clinical depression, chronic fatigue syndrome, persistent pain, and cardiovascular disease (Chrousos, 2009). The underlying etiology and subsequent prevalence of disease states emphasize the need to assess CAR regulation with the highest levels of precision and reproducibility. Inaccurate measurements of diurnal rhythms and CAR can lead to misdiagnosis and incorrect intervention regimens (Ryan et al., 2016). Delays in 5 to 15 minutes have been shown to alter CAR measurements, and can lead to an overestimation or underestimation of CAR magnitude and lead to erroneous interpretations (Stalder et al., 2016).

Figure 2. A typical diurnal rhythm using a 5 sampling regimen is shown. It is recommended to collect saliva samples at awakening, 30 minutes post awakening, prior to lunch, prior to dinner, and at bed time as depicted in the graph.


Using saliva, cortisol diurnal rhythm measurements can be performed easily with periodic, timed collections being stress-free, straightforward, non-invasive, and with higher levels of participant compliance (Ryan et al., 2016; Woods and Mentes, 2011). Saliva is considered the most biologically relevant specimen type used to assess cortisol concentrations when compared to other specimen types such as serum and urine samples, since only ‘free’ biologically relevant cortisol measures are analyzed in saliva while serum measures total cortisol, including bound cortisol, and 24 hour urine measures are unable to capture a diurnal rhythm profile. Hair cortisol can also be used to assess chronic stress by capturing extended exposure to elevated levels of cortisol (Levine et al., 2007).

Recently, a method to assess cortisol levels using 4 samples of urine dried on a filter paper strip has been advertised to provide diurnal cortisol assessment. To the best of our knowledge, there is no peer reviewed publication to date that has verified the methodology used, the level of compliance achieved with this method, or how the data obtained from dried urine compares to saliva or serum, to lend it any scientific credibility. The table below outlines the usefulness of saliva, hair, fresh urine, and blood, and their demonstrated usefulness in cortisol measurements as described in the scientific literature.

SalivaBloodFresh UrineHair
Peer reviewed studies to support testing of cortisolYesYesYesYes
Clinical applications supported by researchYesYesYesYes
Stability of analytes demonstrated in sample typeYesYesYesYes
Measures biologically relevant ‘free’ cortisolYesYesYes_
Ability to test diurnal cortisol patternYesYes__
Measurement of cortisol awakening response (CAR)YesYes__
Easy home collectionYes_Yes_
Measures total hormone load over 24 h__Yes_
Measurement of cortisol metabolites__Yes_


Both Cushing’s syndrome and Addison’s disease are at the extreme ends of the spectrum of cortisol level expression and not frequently observed. However, subclinical manifestations of HPA axis dysfunctions more commonly affect health and wellness. These dysfunctions are also determined by measuring the levels of cortisol produced and most importantly, the diurnal rhythm pattern associated with its production. A deviation from normal diurnal rhythm of expression, including the cortisol awakening response, has been associated with many diseases, both physiological and psychological, and can lead to adverse health outcomes over a prolonged period of time. A full list of disease outcomes due to HPA axis dysfunction is found in the table below (taken from (Chrousos, 2009).

Studies on conditions with altered HPA axis activity rely on determining free cortisol production over the course of a day using the most credible methods supported by scientific literature and focus on either multiple samplings of saliva or 24 hour urine collection. However, 24 hour urine measures are representative of total free cortisol production over the course of a day, and while useful in determining the allostatic load experienced by individuals, it is unable to represent the diurnal variation of cortisol expression. The only scientifically reproducible method to non-invasively and accurately determine the diurnal rhythm pattern of cortisol expression is by collecting 3-4 saliva samples through the course of the day and determining salivary free cortisol measures. Therefore, the only scientifically credible sample type currently accepted by the scientific community is saliva.

Conditions Related to HPA Axis Dysfunction

Increased activity of the HPA axis
ushing’s syndrome
Chronic stress
Melancholic depression
Anorexia nervosa
Obsessive-compulsive disorder
Panic disorder
Excessive exercise (obligate athleticism)
Chronic, active alcoholism
Alcohol and narcotic withdrawal
Diabetes mellitus
Central obesity (metabolic syndrome)
Post-traumatic stress disorder in children
Decreased activity of the HPA axis
Adrenal Insufficiency
Atypical/seasonal depression
Chronic fatigue syndrome
Premenstrual tension syndrome
Climacteric depression
Nicotine withdrawal
Following cessation of glucocorticoid therapy
Alcohol and narcotic withdrawal
Following Cushing’s syndrome cure
Following chronic stress
Postpartum period
Adult post-traumatic stress disorder
Rheumatoid arthritis
Asthma, eczema


Since cortisol plays a key role in regulating multiple systems in the body, including metabolism, stress responsiveness, immune function, wound healing, and bone formation, it is a very tightly regulated steroid. Approximately 90 to 95% of circulating cortisol in plasma is found bound to proteins that make it unavailable for biological activity (Hellhammer et al., 2009). Free cortisol is also interconverted to cortisone by 11-beta HSD enzymes, and is maintained at a ratio of 2:1 or 3:1 cortisone to cortisol (Tomlinson and Stewart, 2001).

Excess amounts of circulating free cortisol, also known as hyper-cortisolemia, lead to disease conditions such as Cushing’s syndrome. The incidence of Cushing’s syndrome, either exogenously generated due to prolonged use of glucocorticoid therapy or due to endogenous overexpression due to adrenal tumors, is very low and reported to be at approximately 0.7 to 2.4 individuals per million in the general population (Newell-Price et al., 2006). Screening for this condition is commonly performed by measuring midnight salivary cortisol levels and can also be performed by determining free cortisol levels in 24 hour urine samples. With both sample types, an excess of free cortisol levels is used as a determinant for diagnosis of the condition, and may require additional testing using serum.

It is also possible to have low levels of circulating cortisol. This condition, known as Addison’s disease, is a type of hypo-cortisolemia in which the adrenal glands produce inadequate levels of cortisol. The incidence of Addison’s disease is approximated at 40-140 individuals per million people, and is diagnosed by injecting the hormone ACTH which stimulates cortisol production, and testing for an increase in cortisol levels in serum. For this type of adrenal insufficiency, multiple studies have also shown the utility of using saliva instead of serum as a sample type with excellent correlation between the two (Raff, 2009).


  1. Chrousos, G.P (2009). Stress and disorders of the stress system. Nat Rev Endocrinol, 5, 374-381.
  2. Fries, E., Dettenborn, L., and Kirschbaum, C (2009). The cortisol awakening response (CAR): facts and future directions. Int J Psychophysiol, 72, 67-73.
  3. Hellhammer, D.H., Wust, S., and Kudielka, B.M (2009). Salivary cortisol as a biomarker in stress research. Psychoneuroendocrinology, 34, 163-171.
  4. Law, R., Evans, P., Thorn, L., Hucklebridge, F., and Clow, A (2015). The cortisol awakening response predicts same morning executive function: results from a 50-day case study. Stress, 18, 616-621.
  5. Levine, A., Zagoory-Sharon, O., Feldman, R., Lewis, J.G., and Weller, A (2007). Measuring cortisol in human psychobiological studies. Physiology & behavior, 90, 43-53.
  6. Newell-Price, J., Bertagna, X., Grossman, A.B., and Nieman, L.K (2006). Cushing’s syndrome. Lancet, 367, 1605-1617.
  7. Qi, D., and Rodrigues, B (2007). Glucocorticoids produce whole body insulin resistance with changes in cardiac metabolism. Am J Physiol Endocrinol Metab, 292, E654-667.
  8. Raff, H (2009). Utility of salivary cortisol measurements in Cushing’s syndrome and adrenal insufficiency. Journal of clinical endocrinology and metabolism, 94, 3647-3655.
  9. Ryan, R., Booth, S., Spathis, A., Mollart, S., and Clow, A (2016). Use of Salivary Diurnal Cortisol as an Outcome Measure in Randomised Controlled Trials: a Systematic Review. Ann Behav Med, 50, 210-236.
  10. Stalder, T., Kirschbaum, C., Kudielka, B.M., Adam, E.K., Pruessner, J.C., Wust, S., Dockray, S., Smyth, N., Evans, P., Hellhammer, D.H., et al (2016). Assessment of the cortisol awakening response: Expert consensus guidelines. Psychoneuroendocrinology , 63, 414-432.
  11. Thorn, L., Hucklebridge, F., Evans, P., and Clow, A (2006). Suspected non-adherence and weekend versus week day differences in the awakening cortisol response. Psychoneuroendocrinology , 31, 1009-1018.
  12. Tomlinson, J.W., and Stewart, P.M (2001). Cortisol metabolism and the role of 11beta-hydroxysteroid dehydrogenase. Best Pract Res Clin Endocrinol Metab, 15, 61-78.
  13. Woods, D.L., and Mentes, J.C (2011). Spit: saliva in nursing research, uses and methodological considerations in older adults. Biological research for nursing, 13, 320-327


For more than two decades, Salivary Bioscience has been unlocking effective interdisciplinary opportunities to engage investigators studying mental health. Salivary cortisol has been at the leading edge of this effort and now joins many other salivary analytes and genetic markers as key components in RDoC.

The NIMH, Research Domain Criteria (RDoC) initiative is a research framework that enables new ways to study mental disorders. RDoC is designed to integrate many levels of relevant biologic information in order to better understand the relationships between biology and behavior in mental illness. Researchers familiar with the RDoC matrix know that the goal is to provide a resource for “systematic focus on development and the environment – as well as with their mutual interactions – and their individual and interacting relationships to specific circuits and functions.”

Salivary bioscience provides simple, non-invasive methods for designing RDoC-related profiles that build on the biological properties of saliva to power interdisciplinary research – and Salimetrics is here to help. “We are readily available to support salivary bio-behavioral research,” says Steve Granger, Ph.D., Salimetrics CSO. “As a resource, we can assist in the process of effectively integrating salivary bioscience into RDoC constructs.”

Today, Salivary Bioscience is powered by discoveries made through the National Institute of Dental and Craniofacial Research’s (NICDR) efforts to characterize the salivary proteome and NIH’s efforts to define genomic associations with various diseases. A wide variety of proteins and hormones measured in oral fluid are now regularly employed in behavioral studies. Likewise, associations of specific genomic variations (SNPs & VNTRs) have been made with behavioral tendencies, emotional resilience and responses, as well as vulnerability to disease states using DNA extracted from saliva samples.

Translating phenotypes through salivary genetic analysis can provide access to both biomarker and genetic information from the same sample, using inexpensive collection methods, and without added preservatives. “To be clear,” says Dr. Granger, “a separate saliva DNA collection device is not required. We have done extensive validation on SalivaBio swabs and devices to explore salivary DNA. By optimizing the DNA isolation protocol, we obtain high purity DNA with A260/A280 ratios consistently at or above 1.8 and the A260/A230 ratios at or above 1.5. High purity DNA results in exceedingly low non-reportable findings (0.05%). Quality results provide researchers confidence in their data and assures that they will have a complete picture for their study.”

For investigators, the expansive combination of salivary DNA analysis with salivary biomarkers and participant self-reports have facilitated multi-modal approaches to mapping fundamental bio-behavioral pathways. Building on innovative measures, Salimetrics is positioning innovative interdisciplinary, multi-modal, and multidimensional methods for the investigation of mental disorders in alignment with the RDoC initiative, framework, and matrix of constructs.

*Note: Salimetrics provides this information for research use only (RUO). Information is not provided to promote off-label use of medical devices. Please consult the full-text article.


Renewed interest by the research community has focused on the salivary testosterone/cortisol (T/C) ratio and its supporting biological mechanisms. In this issue of the Salivary Bioscience Bulletin, we explore the scientific literature and provide a summary of our findings.

Research suggests that testosterone and cortisol work together as part of a biological system influencing very basic and primary reactions to threats by balancing the hypothalamus-pituitary-adrenal (HPA) axis and the hypothalamus-pituitary-gonadal (HPG) axis responses (9). In response to a stressor, the human body increases the production of cortisol and decreases production of testosterone (12). In sports and exercise studies, salivary bioscience researchers have already concluded that the balancing of the T/C ratio not only supports a healthier lifestyle, but it can also act as a hormonal biomarker that targets overtraining and susceptibility to certain diseases and disorders (5,10).

General findings in the context of exercise and sports performance show the value of the salivary T/C ratio when observing training intensity levels and for determining potential overtraining and recovery (3, 7). This is often seen when there is evidence of a low or decreased T/C ratio (i.e., cortisol rises and testosterone decreases (2). In athletes, the T/C ratio has also been associated with skeletal muscle atrophy, as it may be reflective of the anabolism/catabolism balance of skeletal muscle as well (11).

However, the salivary T/C story doesn’t end with sports and performance. Additional research is beginning to encompass a much broader impact of the T/C ratio by expanding into the field of social biology. Findings related to social aggression and the T/C ratio have revealed a significant positive relationship between testosterone and aggression in subjects with high cortisol levels, but not in subjects with average to low cortisol levels (8). Now, research is beginning to elucidate the T/C ratio as a consistent hormonal marker for social aggression and criminal or aggressive tendencies (8,9).

While research continues to define the significant health implications of monitoring the T/C ratio by further understanding its biobehavioral influences, the team at Salimetrics stands ready to support you with convenient sample collection methods, salivary analysis and accurate results, so that you can unlock the potential of the T/C ratio in your research.


  1. Guilhem, G. et al (2015). Salivary Hormones Response to Preparation and Pre-competitive Training of World-class Level Athletes. Front Physiol, PMID, 26635619.
  2. Lippi, G. et al (2016). Analytical Evaluation of Free Testosterone and Cortisol Immunoassays in Saliva as a Reliable Alternative to Serum in Sports Medicine. J Clin Lab Anal, PMID, 26990800.
  3. Kreher, J.B. et al (2012). Overtraining Syndrome. Sports Health, 4(2), 128–138.
  4. Hug, M. et al (2003). Training modalities: over-reaching and over-training in athletes, including a study of the role of hormones. Best Pract Res Clin Endocrinol Metab, 17(2), 191-209.
  5. Filaire, E. et al (2001). Preliminary results on mood state, salivary testosterone:cortisol ratio and team performance in a professional soccer team. Eur J Appl Physiol, 86(2), 179-84.
  6. Ghiciuc, C.M. et al (2015). Imbalance in the diurnal salivary testosterone/cortisol ratio in men with severe obstructive sleep apnea: an observational study. Braz J Otorhinolaryngol, S1808-8694(15), 00241-4.
  7. Glenn, A.L. et al (2012). Increased testosterone to cortisol ratio in psychopathy. J Abnorm Psychol, 120(2), 389-399.
  8. Denson, T.F. et al (2013). Endogenous testosterone and cortisol jointly influence reactive aggression in women. Psychoneuroendocrinology, 38(3), 416-24.
  9. Terburg, D. et al (2009). The testosterone-cortisol ratio: A hormonalmarker for proneness to social aggression. Int J Law Psychiatry, 32(4), 216-23.
  10. Smith, G.D. et al (2005). Cortisol, testosterone, and coronary heart disease: prospective evidence from the Caerphilly study. Circulation, 112(3), 332-40.
  11. Grandys, M. et al (2016). The importance of the training-induced decrease in basal cortisol concentration in the improvement in muscular performance in humans. Physiol Res, 65(1), 109-20.
  12. Edwards, D.A. et al (2015). Baseline cortisol moderates testosterone reactivity to women’s intercollegiate athletic competition. Physiol Behav, 142, 48-51.


*Note: Salimetrics provides this information for research use only (RUO). Information is not provided to promote off-label use of medical devices. Please consult the full-text article.


Last year marked a milestone in Salivary Bioscience history. Salivary Cortisol has now been featured in over 25,000 scientific research publications. For this issue of the Salivary Bioscience Bulletin, we wanted to take a moment to thank the scientific community for allowing Salimetrics to be a part of this journey.

Since its release in 1998, the Salimetrics Salivary Cortisol Assay Kit has evolved from being a novel alternative to radioimmunoassay, to becoming a fundamental building block of Salivary Bioscience Research. During this evolution, the number of scientific publications involving salivary cortisol has increased over 2,000%. Salivary Cortisol is now widespread across many fields of research including:

  • Stress
  • Reproductive Health
  • Mental Health
  • Wellness & Aging
  • Smoking & Environment
  • Biological sensitivity/Susceptibility to context
  • Sports & Performance
  • Inflammation
  • Obesity & Metabolic Problems
  • Social Behavior
  • Child Development
  • Behavioral Neuroscience
  • DNA and Gene Expression
  • Sleep & Circadian Rhythm
  • Animal Welfare
  • Nutrition & Health
  • Military, Law Enforcement, & Medical Training

Salimetrics is honored to support salivary cortisol researchers around the world by consistently delivering better results.


Studies of the Oxytocin Receptor Gene (OXTR) have provided critical information about the downstream effects of oxytocin on a variety of behaviors including stress, anxiety, social memory, sexual and aggressive behavior, bonding, and maternal behavior (1). The OXTR protein is part of the G-protein coupled receptor family, and is expressed in the mammary glands, uterus, and central nervous system (2). Research studies surveying behavioral associations with multiple Single Nucleotide Polymorphisms (SNPs) in the Oxytocin Receptor Gene have found links to individual differences in emotional regulation, personality traits, and social behaviors (3-7).

Three possible genetic variants exist for the most commonly studied oxytocin receptor polymorphism rs53576: A/G, A/A or G/G. Results from one study showed that individuals homozygous for the G allele of rs53576 (G/G) exhibited higher behavioral and dispositional empathy. The same study also showed that individuals with one or two copies of the A allele possess lower levels of optimism, mastery, parenting skills, and self-esteem, when compared to those with the G/G allele (8, 9). Interestingly, Bradley et al. demonstrated rs53576 G/G allele carriers who were severely maltreated during childhood showed enhanced levels of emotional dysregulation in adulthood when compared to A/A or A/G carriers (4). Consistent with these behavioral associations for the OXTR SNP rs53576, multiple other SNPs within OXTR have also been shown to have an impact on behavioral traits in several studies (10).

High quality salivary DNA is easily available without the need for expensive specialized collection devices. With Salimetrics’ DNA extraction protocol and greater than 99% call rate or genotype assignment, you can expand your data set to draw better conclusions by simply adding DNA analysis to your study design.


  1. Lee, H.J. et al (2009). Oxytocin: the great facilitator of life.. Prog Neurobiol, 88(2), 127-51.
  2. Aspé-Sánchez, M. et al (2015). Oxytocin and Vasopressin Receptor Gene Polymorphisms: Role in Social and Psychiatric Traits. Front Neurosci, 9:510, eCollection.
  3. Ng, P.K. et al (2004). Effect of storage conditions on the extraction of PCR-quality DNA from saliva. Clinica Chimica Acta, 343(2004), 191-194.
  4. Bradley, B. et al (2011). Association between childhood maltreatment and adult emotional dysregulation in low-income, urban, African American sample: Moderation by ox. Development and Psychopathology, 23(2011), 439-452.
  5. Behnia, F. et al (2015). Fetal DNA methylation of autism spectrum disorders candidate genes: association with spontaneous preterm birth. American Journal of Obstetrics & Gynecology, 212(4), 533.e1–533.e9.
  6. Myers, A. et al (2014). Variation in the oxytocin receptor gene is associated with increased risk for anxiety, stress, and depression in individuals with a history . Journal of Psychiatric Research, 59(2014), 93-100.
  7. Davis, MC. et al (2014). Associations Between Oxytocin receptor genotypes and social cognitive performance in individuals with schizophrenia. Official Journal of the Schizophrenia Institutional Research Society, 159(2-3), 353-357.
  8. Spahire-Bernstein, S. et al (2011). Oxytocin receptor gene (OXTR) is related to psychological resources. PNAS, 108(37), 15118–15122.
  9. Rodrigues, S. et al (2009). Oxytocin receptor genetic variation relates to empathy and stress reactivity in humans. PNAS, 106(50), 21437-21441.
  10. Tost, H. et al (2010). A common allele in the oxytocin receptor gene (OXTR) impacts prosocial temperament and human hypothalamic-limbic structure and function. PNAS, 107(31), 13936-41.


One of the first saliva swab collection devices designed to collect saliva for the measurement of salivary cortisol was the Sarstedt Salivette®. Over time and because of its simple design, the use of the term Salivette® in the literature became synonymous with swab-based saliva collection methods. The Salivette® features a tube, a swab, an internal container to hold the swab, and a slip fit cap.


Since then, new technology and next generation protocols for saliva swab collection have been introduced that significantly improve on the performance of the Salivette® (View Timeline). These improvements have optimized the collection devices and collection techniques, and as a result, have minimized variability in results, enhanced adaptability for multiple testing applications, maximized sample volumes and recoveries, and increased the ease of use and minimized participant burden (Granger et. al, 2007).

Researchers should look beyond the Salivette® and be sure the saliva collection method they choose includes the following features:

  • Validated for accurate results
  • Suitable for possible DNA collection
  • Ease of use for participants of different ages
  • Clean, safe, and non-toxic
  • Collects sufficient sample volume for analysis
  • Minimizes risk of choking

For better results and the best practices in saliva collection, visit the Salimetrics Recommended Saliva Collection Devices and Methods page.


  1. Shirtcliff, E.A., et al (2001). Use of salivary biomarkers in biobehavioral research: cotton-based sample collection methods can interfere with salivary immunoassay results. Psychoneuroendocrinology, 26(2), 165-73.
  2. Harmon, A. G., et al (2007). Measuring salivary cortisol in studies of child development: Watch out—what goes in may not come out of saliva collection devices. Psychobiology, 49(5), 495-500.
  3. Granger, D.A., et al (2007). Integration of salivary biomarkers into developmental and behaviorally-oriented research: problems and solutions for collecting specimens. Physiology and Behavior, 92(4), 583-90.
  4. Beltzer, E., et al (2010). Salivary flow and salivary alpha-amylase: Collection technique, duration, and oral fluid type. Physiology and Behavior, 101(2), 289-96.
  5. Nemoda, Z., et al (2011). Assessing genetic polymorphisms using DNA extracted from cells present in saliva samples. BMC Medical Research Methodology, 11, 170.
  6. Wilde, C., et al (2013). Sample collection, including participant preparation and sample handling. The Immunoassay Handbook: Theory and applications of ligand binding, ELISA and related techniques, 4th Edition, 427-40.

*Note: Salimetrics provides this information for research use only (RUO). Information is not provided to promote off-label use of medical devices. Please consult the full-text article.


The latest research continues to reinforce the correlation between SNP-related associations and genetic biology, behaviors, and diseases. But did you know that you can easily and affordably incorporate accurate, high-quality DNA analysis from saliva and get results that are identical to blood samples?

By optimizing the extraction process, Salimetrics created a protocol for researchers that optimizes high quality salivary DNA, using the same inexpensive saliva collection methods researchers have relied on for years. This enables researchers to expand the scope of their studies by including specific SNPs for genomic DNA testing without the need for specialized collection devices, preservatives or complicated collection techniques. For studies focused on a targeted number of SNPs, Salimetrics’ new protocol enables researchers to incorporate the efficiency and simplicity of using the same saliva sample for genetic analysis that researchers use for other biomarkers.

Empirical evidence shows that variations in gene composition (SNPs & VNTRs) express the ability to moderate behavioral tendencies, emotional resilience and responses, as well as vulnerability to disease states. SNP genotyping creates an inter-individual biological profile that enhances the conclusions of observed abnormalities in participant groups. For example, past studies on child maltreatment have shown a correlation between children with genetic variants in OXTR (specifically AA/AG) and being more at risk for increased emotional dysregulation when compared to children with the GG variant who were at lowest risk (Bakermans-Kranenburg et al., 2008; Rodrigues et al., 2009). When genomic analysis was used, there was a definite contrast to these past studies and it was discovered that maltreated children who carry AA/AG genetic variants were not more at risk for increased emotional dysregulation but were rather resilient individuals (Bradley 2011).

Bodenmann, 2009 studied subjects with the Val/Val genotype for the polymorphism of COMT and participants responded positively to Modafinil, a drug that stimulates wakefulness by modifying dopaminergic and nor-adrenergic neurotransmission. Results of this study confirmed that participants with the COMT polymorphism were influenced by Modafinil, which allowed them to function properly after a sleepless night and how the Met/Met genotype subjects were hardly affected by the drug. The use of DNA analysis this study became the first instance where a drug intervention yielded high and stable waking functions for a genetically distinct group with sleep deprivation.

Frielingsdorf et al., 2010 observed that carriers of the BDNF Met allele were capable of extinguishing a learned fear memory and fMRI proved these individuals were slower at suppressing a learned fear response. Frielingsdorf further discusses the importance of BDNF genotyping and neuroimaging when it comes to customizing a therapeutic treatment for PTSD.

Way et al., 2008 used genotyping in a study to provide a solid case for the association between OPRM1 and both physical and social pain analysis. In this study, DNA Analysis of the OPRM1 gene was used to show that the same neural and neurochemical systems behind generating the uncomfortable feelings of physical pain are also in charge of creating feelings of “social pain” (hurt feelings that result from social rejection, separation, or loss). Through fMRI it was shown in areas of the brain that have previously been proven to associate with social and physical pain, that G allele carriers had a greater reaction to social rejection.

The SalivaLab’s DNA isolation protocol yields high purity, low salt DNA with A260/A280 ratios (indicating protein content) consistently at or above 1.8 and the A260/A230 ratios (indicative of salt and carbohydrate content) at or above 1.5. These high quality results with low sample retest rates allow for confidence in SNP calls and exceedingly low non-reportable findings (0.05%). The final result is a cost-effective service for targeted DNA genotyping, bringing ease, affordability, and painless sample collection to researchers. You already have access to the genetic material from your existing samples that you have collected for other analytes, and now with the simplicity of Salimetrics SalivaLab you have the opportunity to gain additional insight with cost-effective genetic analysis.


  1. Bakermans-Kranenburg, M., & van IJzendoorn, M (2008). Oxytocin receptor (OXTR) and serotonin transporter (5-HTT) genes associated with observed parenting. Social Cognitive and Affective Neuroscience, 3(2), 128–134.
  2. Rodrigues, S. M., Saslow, L. R., Garcia, N., John, O. P., & Keltner, D (2009). Oxytocin receptor genetic variation relates to empathy and stress reactivity in humans. Proceedings of the National Academy of Sciences of the United States of America, 106(50), 21437–21441.
  3. Bradley, B. et al (2011). Association between childhood maltreatment and adult emotional dysregulation in a low-income, urban, African American sample: Moderation by . Development and Psychopathology, 23(2011), 439-452.
  4. Bodenmann, S. et al (2009). Pharmacogenetics of Modafinil After Sleep Loss: Catechol-O-Methyltransferase Genotype Modulates Waking Functions But Not Recovery Sleep. Nature, 85(3), 296-304.
  5. Frielingsdorf, H. et al (2010). Variant brain-derived neurotrophic factor Val66Met endophenotypes: implications for posttraumatic stress disorder. Annals of the NY Academy of Sciences, 1208, 150-157.


*Note: Salimetrics provides this information for research use only (RUO). Information is not provided to promote off-label use of medical devices. Please consult the full-text article.


Riis, JL. et al., (2021) Psychoneuroendocrinology


Summary Highlight: This study highlights how advances in salivary assay precision, combined with a qualified laboratory reduces the necessity to test samples in duplicate. As best practice standards evolve, researchers can now reliably shift resources to collecting more samples and testing biological replicates in singlet, instead of expensing those resources on technical replicates for duplicate testing. By analyzing more samples, researchers can increase their statistical power by allocating better strategies and resources to obtain a higher level of rigor and reproducibility in their study data. As the most experienced Salivary Bioscience laboratory for research, the Salimetrics SalivaLab maintains some of the lowest laboratory-based measurement variability and further ensures confidence in the results of this work.

Abstract: Best practice standards for measuring analyte levels in saliva recommend that all biospecimens be tested in replicate with mean concentrations used in statistical analyses. This approach prioritizes minimizing laboratory-based measurement error but, in the process, expends considerable resources. We explore the possibility that, due to advances in salivary assay precision, the contribution of laboratory-based measurement error in salivary analyte data is very small relative to more important and meaningful variability in analyte levels across biological replicates (i.e., between different specimens). To evaluate this possibility, we examine the utility of the repeatability intra-class correlation (rICC) as an additional index of salivary analyte data precision. Using randomly selected subsamples (Ns=200 and 60) of salivary analyte data collected as part of a larger epidemiologic study, we compute the rICCs for seven commonly assayed salivary measures in biobehavioral research – cortisol, alpha-amylase, c-reactive protein, interlekin-6, uric acid, secretory immunoglobulin A, and testosterone. We assess the sensitivity of rICC estimates to assay type and the unique distributions of the underlying analyte data. We also use simulations to examine the bias, precision, and coverage probability of rICC estimates calculated for small to large sample sizes. For each analyte, the rICCs revealed that less than 5% of variation in analyte levels was attributable to laboratory-based measurement error. rICC estimates were similar across all analytes despite differences in analyte levels, average intra-assay coefficients of variation, and in the distributional properties of the data. Guidelines for calculating rICC are provided to enable investigators and laboratory staff to apply this metric and more accurately quantify, and communicate, the magnitude of laboratory-based measurement error in their data. By helping investigators scale measurement error relative to more scientifically meaningful variability between biological replicates, the application of the rICC has the potential to influence research strategies and tactics such that resources (e.g., finances, effort, number/volume of biospecimens) are allocated more efficiently and effectively.

*Note: Salimetrics provides this information for research use only (RUO). Information is not provided to promote off-label use of medical devices. Please consult the full-text article.


outstanding technical support


we offer a full product guarantee


we offer free delivery to UK universities and non profit organisations