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      A Systematic Meta-Analysis of Genetic Association Studies for Diabetic Retinopathy

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          Abstract

          OBJECTIVE

          Diabetic retinopathy is a sight-threatening microvascular complication of diabetes with a complex multifactorial pathogenesis. A systematic meta-analysis was undertaken to collectively assess genetic studies and determine which previously investigated polymorphisms are associated with diabetic retinopathy.

          RESEARCH DESIGN AND METHODS

          All studies investigating the association of genetic variants with the development of diabetic retinopathy were identified in PubMed and ISI Web of Knowledge. Crude odds ratios (ORs) and 95% CIs were calculated for single nucleotide polymorphisms and microsatellite markers previously investigated in at least two published studies.

          RESULTS

          Twenty genes and 34 variants have previously been studied in multiple cohorts. The aldose reductase ( AKR1B1) gene was found to have the largest number of polymorphisms significantly associated with diabetic retinopathy. The z−2 micro satellite was found to confer risk (OR 2.33 [95% CI 1.49–3.64], P = 2 × 10 −4) in type 1 and type 2 diabetes and z+2 to confer protection (0.58 [0.36–0.93], P = 0.02) against diabetic retinopathy in type 2 diabetes regardless of ethnicity. The T allele of the AKR1B1 promoter rs759853 variant is also significantly protective against diabetic retinopathy in type 1 diabetes (0.5 [0.35–0.71], P = 1.00 × 10 −4), regardless of ethnicity. These associations were also found in the white population alone ( P < 0.05). Polymorphisms in NOS3, VEGF, ITGA2, and ICAM1 are also associated with diabetic retinopathy after meta-analysis.

          CONCLUSIONS

          Variations within the AKR1B1 gene are highly significantly associated with diabetic retinopathy development irrespective of ethnicity. Identification of genetic risk factors in diabetic retinopathy will assist in further understanding of this complex and debilitating diabetes complication.

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          Global data on visual impairment in the year 2002.

          Serge Resnikoff, Donatella Pascolini, Daniel Etya'ale … (2004)
          This paper presents estimates of the prevalence of visual impairment and its causes in 2002, based on the best available evidence derived from recent studies. Estimates were determined from data on low vision and blindness as defined in the International statistical classification of diseases, injuries and causes of death, 10th revision. The number of people with visual impairment worldwide in 2002 was in excess of 161 million, of whom about 37 million were blind. The burden of visual impairment is not distributed uniformly throughout the world: the least developed regions carry the largest share. Visual impairment is also unequally distributed across age groups, being largely confined to adults 50 years of age and older. A distribution imbalance is also found with regard to gender throughout the world: females have a significantly higher risk of having visual impairment than males. Notwithstanding the progress in surgical intervention that has been made in many countries over the last few decades, cataract remains the leading cause of visual impairment in all regions of the world, except in the most developed countries. Other major causes of visual impairment are, in order of importance, glaucoma, age-related macular degeneration, diabetic retinopathy and trachoma.
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            A genome-wide association study identifies novel risk loci for type 2 diabetes.

            Robert Sladek, Ghislain Rocheleau, Johan Rung … (2007)
            Type 2 diabetes mellitus results from the interaction of environmental factors with a combination of genetic variants, most of which were hitherto unknown. A systematic search for these variants was recently made possible by the development of high-density arrays that permit the genotyping of hundreds of thousands of polymorphisms. We tested 392,935 single-nucleotide polymorphisms in a French case-control cohort. Markers with the most significant difference in genotype frequencies between cases of type 2 diabetes and controls were fast-tracked for testing in a second cohort. This identified four loci containing variants that confer type 2 diabetes risk, in addition to confirming the known association with the TCF7L2 gene. These loci include a non-synonymous polymorphism in the zinc transporter SLC30A8, which is expressed exclusively in insulin-producing beta-cells, and two linkage disequilibrium blocks that contain genes potentially involved in beta-cell development or function (IDE-KIF11-HHEX and EXT2-ALX4). These associations explain a substantial portion of disease risk and constitute proof of principle for the genome-wide approach to the elucidation of complex genetic traits.
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              Systematic meta-analyses of Alzheimer disease genetic association studies: the AlzGene database.

              Lars Bertram, Matthew B. McQueen, Kristina Mullin … (2007)
              The past decade has witnessed hundreds of reports declaring or refuting genetic association with putative Alzheimer disease susceptibility genes. This wealth of information has become increasingly difficult to follow, much less interpret. We have created a publicly available, continuously updated database that comprehensively catalogs all genetic association studies in the field of Alzheimer disease (http://www.alzgene.org). We performed systematic meta-analyses for each polymorphism with available genotype data in at least three case-control samples. In addition to identifying the epsilon4 allele of APOE and related effects, we pinpointed over a dozen potential Alzheimer disease susceptibility genes (ACE, CHRNB2, CST3, ESR1, GAPDHS, IDE, MTHFR, NCSTN, PRNP, PSEN1, TF, TFAM and TNF) with statistically significant allelic summary odds ratios (ranging from 1.11-1.38 for risk alleles and 0.92-0.67 for protective alleles). Our database provides a powerful tool for deciphering the genetics of Alzheimer disease, and it serves as a potential model for tracking the most viable gene candidates in other genetically complex diseases.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Diabetes
                Journal ID (hwp): diabetes
                Journal ID (pmc): diabetes
                Journal ID (publisher-id): Diabetes
                Title: Diabetes
                Publisher: American Diabetes Association
                ISSN (Print): 0012-1797
                ISSN (Electronic): 1939-327X
                Publication date (Print): September 2009
                Publication date (Electronic): 8 July 2009
                Volume: 58
                Issue: 9
                Pages: 2137-2147
                Affiliations
                [1] 1Department of Ophthalmology, Flinders Medical Centre and Flinders University, Bedford Park, SA, Australia;
                [2] 2Centre for Eye Research Australia, Melbourne University, Melbourne, Victoria, Australia.
                Author notes
                Corresponding author: Jamie Craig, jamie.craig@ 123456flinders.edu.au .
                Article
                Publisher ID: 0059
                DOI: 10.2337/db09-0059
                PMC ID: 2731535
                PubMed ID: 19587357
                SO-VID: 7ad3c5e1-43dc-434b-a354-c155985ea264
                Copyright © © 2009 by the American Diabetes Association.
                License:

                Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered. See http://creativecommons.org/licenses/by-nc-nd/3.0/ for details.

                History
                Date received : 14 January 2009
                Date accepted : 27 May 2009
                Categories
                Subject: Original Article
                Subject: Genetics

                ScienceOpen disciplines: Endocrinology & Diabetes
                Data availability:
                ScienceOpen disciplines: Endocrinology & Diabetes

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