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Review Article
Biomarkers as a predictor for diabetic retinopathy risk and management: A review
African Vision and Eye Health | Vol 77, No 1 | a430 |
DOI: https://doi.org/10.4102/aveh.v77i1.430
| © 2018 Kevin C. Phillips, Peter C. Clarke-Farr, Tandi E. Matsha, David Meyer
| This work is licensed under CC Attribution 4.0
Submitted: 16 October 2017 | Published: 30 August 2018
Submitted: 16 October 2017 | Published: 30 August 2018
About the author(s)
Kevin C. Phillips, Department of Ophthalmic Sciences, Cape Peninsula University of Technology, South AfricaPeter C. Clarke-Farr, Department of Ophthalmic Sciences, Cape Peninsula University of Technology, South Africa
Tandi E. Matsha, Department of Biomedical Sciences, Cape Peninsula University of Technology, South Africa
David Meyer, Division of Ophthalmology, University of Stellenbosch, South Africa
Abstract
Background: The systemic and ocular manifestations of diabetes are an increasing burden on both private and public healthcare systems. The ability to accurately predict patient susceptibility and prognostic implications of the disease is essential to its optimal management and planning.
Aim: The purpose of this paper was to review alternative biomarkers to those currently in use regarding the diagnosis and prognosis of diabetes and the ocular effects of the disease. Current biomarkers include Fasting Plasma Glucose (FPG), Oral Glucose Tolerance Test (OGTT) and Glycolated Haemoglobin (HbA1c).
Methods: The research strategy comprised of a comprehensive literature review of articles from Mendeley, Cochrane and Elsevier with additional input from experts in the field serving as co-authors.
Results: The review found that there are alternative biomarkers to those currently utilised. These include adiponectin, apolipoprotein B, C-reactive protein and ferritin. Fructosamine, while useful where whole blood is available, is unreliable as a diagnostic biomarker resulting in a 10% variation coefficient. Post-prandial glucose (PPG) measurement most closely predicted HbA1c.
Conclusion: With prediction of risk for diabetes in individuals, a value combination, expressed as either a numerical score or a percentage, consisting of adiponectin, apolipoprotein B, C-reactive protein and ferritin, almost doubled the relative risk of contracting the disease. Eye care practitioners need to question diabetic patients about their FPG and HbA1c levels and encourage them to have the relevant tests regularly, including PPG. The importance of biomarkers should be emphasised and used as an educational tool to facilitate better diabetes management and treatment adherence.
Aim: The purpose of this paper was to review alternative biomarkers to those currently in use regarding the diagnosis and prognosis of diabetes and the ocular effects of the disease. Current biomarkers include Fasting Plasma Glucose (FPG), Oral Glucose Tolerance Test (OGTT) and Glycolated Haemoglobin (HbA1c).
Methods: The research strategy comprised of a comprehensive literature review of articles from Mendeley, Cochrane and Elsevier with additional input from experts in the field serving as co-authors.
Results: The review found that there are alternative biomarkers to those currently utilised. These include adiponectin, apolipoprotein B, C-reactive protein and ferritin. Fructosamine, while useful where whole blood is available, is unreliable as a diagnostic biomarker resulting in a 10% variation coefficient. Post-prandial glucose (PPG) measurement most closely predicted HbA1c.
Conclusion: With prediction of risk for diabetes in individuals, a value combination, expressed as either a numerical score or a percentage, consisting of adiponectin, apolipoprotein B, C-reactive protein and ferritin, almost doubled the relative risk of contracting the disease. Eye care practitioners need to question diabetic patients about their FPG and HbA1c levels and encourage them to have the relevant tests regularly, including PPG. The importance of biomarkers should be emphasised and used as an educational tool to facilitate better diabetes management and treatment adherence.
Keywords
Diabetes; Diabetic retinopathy; HbA1; Adiponectin; Apolipoprotein; Retinopathy Screening
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