Early Detection of Diabetic Kidney Disease with Biomarkers


Over one third of diabetics will develop diabetic kidney disease (DKD) in their lifetime1. Despite the large amount of diabetics suffering from DKD, current methods for measuring and tracking kidney function may not be specific enough for diabetic systems2,3.

Part III of The Common Denominator eBook series examines the kidney complications caused by diabetes, and current research to improve the early detection of diabetic kidney disease with biomarkers.

A 3d rendered illustration of the human kidneys.

The Filtration and Urinary Systems: An Overview

The body’s filtration and urinary systems have several key functions which include cleaning and removing waste products from the blood and recycling key nutrients.  The kidneys, ureters, bladder, and urethra make up these systems.

In order to achieve homeostasis, these highly specialized organs and muscles must work together properly.

Kidney Complications Caused by Diabetes

They kidneys recycle glucose and remove insulin from the blood, which helps to maintain energy homeostasis8,9.  Kidney disease is the general term used for all of the different diseases, disorders, and damages that can occur within the kidneys5. Kidney disease that develops as a result of having diabetes is called diabetic kidney disease (DKD) or diabetic nephropathy (DN).

Having diabetes is a major risk factor for developing kidney damage2,6,7.

Research on the Early Detection of Diabetic Kidney Disease with Biomarkers

Current methods for detecting kidney damage in diabetics may not be specific enough to accurately reflect kidney health2,3.  There are several important kidney damage and disease biomarkers making appearances in diabetes research in an effort to improve the early detection of diabetic kidney disease.

Cystatin C

Cystatin C is a small cysteine proteinase produced in nearly every cell containing a nucleus in the human body. It is easily filtered out by the kidneys and levels can directly correlate with how well kidneys are filtering blood.10,11,12

Neutrophil Gelatinase-Associated Lipocalin (NGAL)

NGAL is part of the innate immune system’s bacterial defense structure. It binds to iron in the presence of invading bacteria, preventing the bacteria from utilizing the body’s iron13. NGAL is also rapidly released into urine when the kidneys are damaged14.

Kidney Injury Molecule-1 (KIM-1)

KIM-1 is a type 1 transmembrane structural glycoprotein found in kidney epithelia cells and is released during regeneration16,17. It is not detectable in healthy kidneys, making urinary KIM-1 a useful biomarker for detecting kidney damage16,16,17.

Alpha-2-Macroglobulin (A2M)

A2M is one of the largest known plasma proteins acting as a protest inhibitor18,19. Levels of A2M increase in blood if there is kidney damage20.


Fetuin-A is a glycoprotein synthesized by the liver and secreted into the blood stream. It is involved in calcium metabolism and bone formation. Levels of fetuin-A may be associated with kidney failure21.


Researchers have been working diligently to better understand how to improve the early detection of diabetic kidney disease with biomarkers. Using kidney damage and disease biomarkers to research diabetes can continue to further the understanding of both diseases while also improving the lives of thousands.

The Common Denominator is a three part eBook series reviewing diabetes, cardiovascular and kidney complications associated with diabetes, as well as important biomarkers that have become useful in researching these areas.

Part III: Detecting Kidney Damage – An Investigation into Diabetic Nephropathy reviews the kidney complications of diabetes, and how kidney damage and  disease biomarkers are emerging as useful tools in diabetes research.

Click on this preview to download our ebook, Early Detection of Diabetic Kidney Disease with Biomarkers.

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  1. Wang et al. (2013). New urinary biomarkers for diabetic kidney disease. Biomark. Res., 1, 9. doi: 10.1186/2050-7771-1-9. PMCID: PMC4177619.
  2. Molitch et al. (2004). Nephropathy in diabetes. Diabetes Care, 27, S79-S83. doi: 10.2337/diacare.27.2007.S79.
  3. Cavanaugh. (2007). Diabetes management issues for patients with chronic kidney disease. Clinical Diabetes, 25, 90-97. doi: 10.2337/diaclin.25.3.90.
  4. Lynch & Wein. (2014). The Urinary Tract and How It Works. National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). nih.gov.
  5. National Kidney and Urologic Diseases Information Clearinghouse. (2016). Kidney Disease Statistics for the United States. NKUDIC and NIDDK. nih.gov.
  6. de Boer et al. (2011). Temporal trends in the prevalence of diabetic kidney disease in the United States. JAMA, 305(24), 2532-9. PMID: 21693741.
  7. The National Diabetes Information Clearinghouse. (2008). DCCT and EDIC: The Diabetes Control and Complications Trial and Follow-up Study. U.S. Department of Health and Human Services, NIH, NIDDK. nih.gov.
  8. Wilding. (2014). The role of the kidneys in glucose homeostasis in type 2 diabetes: clinical implications and therapeutic significance through sodium glucose co-transporter 2 inhibitors. Metabolism, 63(10), 1228-37. PMID: 25104103.
  9. Duckworth et al. (1998). Insulin degradation: Progress and potential. Endocrine Reviews, 19(5), 608-624. doi: 1210/edrv.19.5.0349.
  10. Centers for Disease Control and Prevention. (2012) Percentage with CKD Stage 3 or 4 Who Were Aware of Their Disease. From NHANES Survey Chronic Kidney Disease Surveillance System—United States. CDCcdc.gov.
  11. Diazyme. (2016). Cystatin C as a GFR Marker. Diazyme. Diazyme.com.
  12. Randers et al. (1998). Serum cystatin C as a marker of the renal function. Scand J Clin Lab Invest., 58(7), 585-92. PMID: 9890342.
  13. Kranendork et al. (2014). Extracellular vesicle markers in relation to obesity and metabolic complications in patients with manifest cardiovascular disease. Cardiovascular Diabetology, 13, 37. PMID: 24498934.
  14. Skaar. (2010). The battle for iron between bacterial pathogens and their vertebrate hosts. PLoS Pathog., 6(8), e1000949. doi:10.1371/journal. ppat.1000949.
  15. Fiseh. (2015). Urinary biomarkers for early diabetic nephropathy in type 2 diabetic patients. Biomark. Res., 3, 16. PMCID: PMC4491239.
  16. Bonventre. (2009). Kidney injury molecule-1 (KIM-1): A urinary biomarker and much more. Nephrol. Dial. Transplant., 24(11), 3265-3268. doi:10.1093/ndt/gfp010.
  17. Han et al. (2002). Kidney injury molecule-1 (KIM-1): A novel biomarker for human renal proximal tubule injury. Kidney Int., 62(1), 237-44. PMID: 12081583.
  18. Ahmed & Hamed. (2015). Kidney injury molecule-1 as a predicting factor for inflamed kidney, diabetic and diabetic nephropathy Egyptian patients. Journal of Diabetes & Metabolic Disorders, 14, 6. PMCID: PMC4347934.
  19. InterPro (2016). Alpha-2-macroglobulin, N-terminal 2. European Bioinformatics Institute. Interpro entry IPR011625.
  20. Lin et al. (2012). An N-glycosylation analysis of human alpha-2-macroglobulin using an integrated approach. J. Proteomics Bioinform., 5, 127–134. PMCID: PMC3460646.
  21. Mori et al. (2011). Fetuin-A: A multifunctional protein. Recent Pat. Endocr. Metab. Immune Drug Discov., 5(2), 124-46. PMID: 22074587.


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