Biomarkers for Detecting Kidney Dysfunction in Type-2 Diabetics and Diabetic Nephropathy Subjects: A Case-Control Study to Identify Potential Biomarkers of DN to Stratify Risk of Progression in T2D Patients

Carla Harkin, Diego Cobice, Simon Brockbank, Stephanie Bolton, Frances Johnston, Anna Strzelecka, Joanne Watt, Mary Jo Kurth, John Lamont, Peter Fitzgerald, Tara C. B. Moore, MW Ruddock

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Abstract

Introduction
Currently there are no biomarkers that are predictive of when patients with type-2 diabetes (T2D) will progress to more serious kidney disease i.e. diabetic nephropathy (DN). Biomarkers that could identify patients at risk of progression would allow earlier, more aggressive treatment intervention and management, reducing patient morbidity and mortality.
Materials and methods
Study participants (N=88; control n=26; T2D n=32; DN n=30) were recruited from the renal unit at Antrim Area Hospital, Antrim, UK and Whiteabbey Hospital Diabetic Clinic, Newtownabbey, UK, between 2019 and 2020. Venous blood (30 ml) and urine (10 ml) were collected together with a detailed clinical history for each study participant.
Results
In total, 13/25 (52.0%) biomarkers measured in urine and 25/34 (73.5%) biomarkers measured in serum were identified as significantly different between control, T2D and DN participants. DN patients, were older, smoked more, had higher systolic blood pressure and higher serum creatinine levels and lower eGFR function. Serum biomarkers significantly inversely correlated with eGFR.
Conclusion
This pilot-study identified several serum biomarkers that could be used to predict progression of T2D to more serious kidney disease; namely, midkine, sTNFR1 and 2, H-FABP and Cystatin C. Our results warrant confirmation in a longitudinal study using a larger patient cohort.
Original languageEnglish
Article number887237
Pages (from-to)1-11
Number of pages11
JournalFrontiers in Endocrinology
Volume13
Early online date29 Jun 2022
DOIs
Publication statusPublished online - 29 Jun 2022

Bibliographical note

Funding Information:
This study was funded by the Randox Laboratories Ltd – Ulster University Industrial Ph.D. Academy.

Publisher Copyright:
Copyright © 2022 Harkin, Cobice, Brockbank, Bolton, Johnston, Strzelecka, Watt, Kurth, Lamont, Fitzgerald, Moore and Ruddock.

Keywords

  • Algorithm
  • diabetic nephropathy
  • midkine
  • sTNFR1
  • sTNFR2
  • L-FABP,
  • H-FABP
  • Type-2 diabetes
  • chronic kidney disease
  • kidney
  • L-FABP
  • cystatin C
  • type-2 diabetes

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