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 Table of Contents  
Year : 2016  |  Volume : 28  |  Issue : 1  |  Page : 14-19

Genetics in diabetic retinopathy - A brief review

Department of Ophthalmology, Amrita Institute of Medical Sciences, Kochi, Kerala, India

Date of Web Publication11-Nov-2016

Correspondence Address:
Gopal S Pillai
Department of Ophthalmology, Amrita Institute of Medical Sciences, Ponekkara, Kochi - 682 026, Kerala
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/0976-6677.193880

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Genetic factors are assumed to contribute to determining an individual's risk for the development of DR and for progression to proliferative diabetic retinopathy (PDR). This article aims to review the developments concerned with the genetics of DR.

Keywords: Diabetic retinopathy; genetics; genome; linkage.

How to cite this article:
Pillai GS, Varky R. Genetics in diabetic retinopathy - A brief review. Kerala J Ophthalmol 2016;28:14-9

How to cite this URL:
Pillai GS, Varky R. Genetics in diabetic retinopathy - A brief review. Kerala J Ophthalmol [serial online] 2016 [cited 2020 May 28];28:14-9. Available from: http://www.kjophthal.com/text.asp?2016/28/1/14/193880

  Introduction Top

Diabetic retinopathy (DR) is a retinal vascular complication of diabetes mellitus, which has affected the world in pandemic proportions. Untreated patients develop vision loss due to macular edema. As the duration of diabetes increases with each passing year, we see an escalation in the number of patients with DR. Increasing number of diabetics have made India the world capital of diabetes and DR. Though environment and dietary habits play a role in the development of diabetes, genetic factors may also predispose these people to the risk of diabetes. Among these diabetics as well, there is definitely a need to find out the population at risk for DR using genetic markers.

The identification of genetic variations underlying DR will help in the early recognition of presymptomatic diabetic individuals who are prone to develop retinopathy, and also to monitor progression in patients who are at risk of rapid progression. This can aid clinical management in terms of frequent examinations of high-risk patients with longer follow-ups of low-risk patients. An efficient allotment of health care resources can be executed. A specific management of disease based upon the patients' genetic and environmental profile maybe decided upon than a generalized manner of treatment. Counselling of these presymptomatic genetically predisposed individuals to adopt preventive and control measures would help delay onset of disease, thus, helping to prevent blindness in the long run.

It has often been postulated that genetic factors are contributory in determining an individual's risk for the development of DR and for progression to proliferative diabetic retinopathy (PDR) as well. In this article, we aim to review the developments concerned with the genetics of DR.

  Basis of Diabetic Retinopathy Genetic Studies Top

The ADVANCE trial showed that intensive glucose control to reduce glycosylated hemoglobin to 6.5% and lower had no effect whatsoever on the 5-year incidence of DR and lowering of blood pressure to near normal levels did not help achieve a further reduction in the progression of DR.[1] Further, some research suggests that some patients with poor control of glycemic levels or blood pressure do not develop DR.[2] This in turn raises the question whether glycemic and systemic control alone will decide the occurrence and progression of DR or whether genetic factors also play a factor in susceptibility to developing DR. Heritability has been estimated to be a contributing factor in as high as 27% in DR and 52% in PDR.[3],[4] Similarly, in the Diabetes Control and Complication Trial (DCCT) cohort, when a relative had retinopathy, the odds ratio for severe retinopathy was 3.1.[5]

Continuing in support of a genetic hypothesis of DR, several studies have found a discrepancy in the rate of prevalence of DR amidst the populations itself. Studies showed greater prevalence of retinopathy among certain ethnic groups than others. An example is the Veterans Affairs Diabetes Trial that showed prevalence of moderate-to-severe DR to be higher in Hispanics and African–Americans than nonHispanic whites in USA.[6]

In The Diabetes Control and Complications Trial, the strongest environmental factors (duration of DM and glycosylated hemoglobin) explained only 11% of the variation in retinopathy risk. Similarly, in the WESDR, a combination of glycosylated hemoglobin, blood pressure, and total cholesterol explained only a 10% of the variation in retinopathy risk, suggesting that the remaining 90% is explained by other risk factors.[7]

Population studies indicated that classical retinopathy signs, such as microaneurysms, were detectable in 7–13% of patients who did not have diabetes mellitus and in patients with glycosylated hemoglobin level below 5% as well.[8] This cannot be explained on the basis of the disease, but is possible in asymptomatic carriers of the gene.

Single-nucleotide polymorphisms (SNPs), which were associated with DM, were not associated with retinopathy in individuals without DM.[9] However, in the current scenario, consistent associations with DR across broad populations have not been established.

Numerous genes have been studied in their association with DR, particularly three specific genes (vascular endothelial growth factor gene, aldose reductase gene, and receptor for advanced glycation end-products gene) were indicated in the development and progression of DR, and specific polymorphisms of these potentially increased risk of DR development.[10]

  Common Genes Studied in Diabetic Retinopathy Top

  • Receptor for Advanced Glycation End products (RAGE)
  • Vascular Endothelial Growth Factors (VEGF)
  • Aldose Reductase (ALR)
  • Nitric Oxide Synthase (NOS) genes
  • Genes coding for Angiotensin Converting Enzyme (ACE gene)
  • Human Leucocyte Antigen (HLA) genes.[11]

  Where Is Diabetic Retinopathy Genetics Research Today? Top

At present, the focus of work is around mapping genes that are expressed in the retina. The genomic sequence data is used to identify mutations and develop strategies for the treatment and prevention of these complications.[12]

Research strategies to identify the genetics of diabetic retinopathy

  1. Candidate gene studies – genes implicated in diabetes development or pathways are examined
  2. Linkage studies – analyze shared alleles among family members with DR, assuming they predispose to more aggressive development of DR
  3. Genome-wide association studies (GWAS) – newer techniques such as massive evaluation of SNP are used as markers in large samples.[12]

The candidate gene approach has been predominantly uptaken. This requires knowledge of the pathogenic mechanisms underlying DR. Here, corresponding genes involved in these pathways/processes are treated as potential candidate genes. The frequency of a genetic variant in individuals with (cases) or without (controls) DR is henceforth compared.

Derived conclusions of candidate gene approach of studies

  1. Increased activation of aldose reductase was reported to induce metabolic and biochemical changes, leading to the development of early DR and PDR. Aldose reductase is an enzyme that catalyzes the reduction of glucose to sorbitol during glucose metabolism. It is encoded by the AKR1B1 gene.[13],[14] Hence, AKR1B1 was proposed as a highly suspect candidate for genetic association studies in DR. A recent meta-analysis by Abhary et al. examining 20 candidate genes in DR found that variants in AKR1B1 had the most significant association with DR, although a consireable amount of prior work has found inconsistent results [15]
  2. Meta-analysis identified Z − 2 microsatellite confers risk of DR [odds ratio (OR), 2.33; 95% CI, 1.49–3.64; P = 2E-04) in type 1 or type 2 DM. The trend was similar and significant in the subgroup analysis of NPDR (P = .008) and PDR (P = .002)
  3. On the other hand, the Z + 2 microsatellites conferred protection against overall DR (OR, 0.58; 95% CI, 0.36–0.93; P = .02) The association was seen in patients with type 1 DM independent of ethnicity [15]
  4. Similarly VEGF, a key player involved in angiogenesis and a potent mediator of vascular permeability, is activated by microvascular changes associated with DM due to hypoxia.[16],[17] The C allele of rs2010963 (-634C/G), although insignificantly associated with DR or PDR, confers risk for NPDR (OR, 1.61; 95% CI, 1.23–2.10; P = 5E-04) in meta-analyses.[15]

Evidence for the remaining candidate genes, save few, investigated to date is weak due to several factors, primary reason being small sample sizes. The P values obtained from these efforts were sometimes nominally significant but could not withstand corrections for multiple testing.[16],[17]

Because most studies failed to take into account the role of haplotype diversity, there were conflicting findings from multiple studies. It is useful to examine haplotype-disease associations. Although meta-analysis techniques were undertaken, the findings remained largely inconclusive. Selection of genes for association studies in DR is difficult because many obvious candidate genes are involved with regulation of the normal microvasculature in retina.

The major problem with the candidate gene approach of studies is that, although there were a number of gene proposals, only a few of them could be replicated. Another problem is it depends on a prior hypothesis that implies that a particular gene has a functional importance in the pathophysiology of DR.

This has led to hypothesis-free approaches by linkage studies and by GWASs where no initial biochemical or pathophysiologic induction is proposed. Results are driven by chromosomal location.[18]

Few positive findings revealed relatively weak genetic associations with DR and modest associations with lack of retinopathy or severe retinopathy. In addition, there was an inability to replicate findings of either positive or negative associations (i.e., association or lack thereof) in multiple population groups.[19],[20]

The effect sizes of these genetic factors are likely to be modest although major genes have been postulated to exist. Hence, the studies were usually based on small patient samples. Consequently, individual studies yielded inconsistent and conflicting findings. To circumvent the issue, meta-analyses was undertaken to pinpoint few genes for which there might be cumulative evidence for an association with DR.[12]

There was also a variation of case definition, standardization of grading of severity of retinopathy, duration of disease, and accurate recording of other associated risk factors.[21]

Derived conclusions from linkage studies

Linkage studies identify the chromosomal regions which has the potential to harbour major genes for DR. It is based on the co-segregation of genetic markers with DR susceptibility loci within family. If linkage is present, the marker is inherited together with the causal variant. If not, the marker is inherited independently. Closer the physical distance of the marker to DR susceptibility loci, the stronger the evidence is for linkage.[18]

Three main linkage studies were performed on regions of chromosomes 1, 3, and 12 implicated for DR in populations of Pima Indians and Mexican Americans. However, except 1p36, none of these reached genome-wide statistical linkage significance.[22],[23],[24]

What linkage studies showed was that there was a tentative linkage between a region relatively close to the angiotensin II receptor gene (AGTR1), located on chromosome 3q2125, and both nephropathy and retinopathy (Pima Indians with type 2 diabetes and severe DR).[25]

A modest level of familial aggregation and evidence for linkage to chromosome 1p36 was found. The genes located in this region were: Peptidyl arginine deiminases (PAD I) 1, 2, 3, 4 and 6, CASP-9, CLCN-Ka, and CLCN-Kb. None of these genes were previously associated with DR.[13] Genetic linkage appeared to exist for both advanced stages as well as earlier manifestations of DR. However, identities of major susceptibility genes in these linkage regions remain elusive.

The challenges associated were in type 2 diabetes mellitus, parents of the patients were often deceased, leaving only one generation of family members to study. Only rough estimates of genomic region of interest were obtained because mapping resolution is generally low and it tests millions of base pairs. Extensive efforts are further needed to pinpoint specific causal variants.

Second, linkage studies often benefit from large families. Third, the penetrance of individual variants may only be of small magnitude so most studies would be underpowered to detect genomic locations via co-segregation.[18]

The weakness of these studies was that only 4% of the cohort had moderate nonPDR or any severe degree of retinopathy. This implied observations were limited to the early stages of retinopathy so they may not have described genetic factors associated with the more severe disease.[12]

Derived results from genome-wide association studies

With GWASs, millions of SNPs can be tested against traits such as DR. Data from publicly available databases, such as the HapMap and the 1000 Genome Project, have been instrumental for the studies. Using data publicly available from the HapMap database, a set of SNPs can be selected that most efficiently capture the 10 million or so common polymorphisms in the human genome.[18]

Technology based on microarrays is used and several hundred thousand selected SNPs can be typed in a single assay.

It is based on the genome-wide characterization of linkage disequilibrium, the phenomenon by which adjacent polymorphisms are correlated with each other because of their co-segregation from one generation to the next. The causal variants that are in high linkage disequilibrium with these signals are likely common alleles and are widely distributed in the human population, each contributing a small effect on disease risk.[26]

GWASs have been thought to be the most successful approach in the genetics of common diseases to date. Its use in the study of DR is recent. It has its limitations as risk alleles have low penetrance and many individuals harbour the risk alleles, however, the majority tend to remain disease-free.

GWAS will not be expected to unmask the identity of the major susceptibility genes. It will account for a very limited proportion of the familial clustering.[27] Clinically, the genetic information gleaned from GWAS will have limited utility as potential disease classifiers.[28] The novelty is the prospect of identifying novel genes which can provide fresh insight into the pathogenic pathways responsible for DR. The elucidation of these pathways can lead to new molecular targets for pharmacological intervention.

Example include therapies based on known pathogenic pathways, particularly intravitreal antiangiogenesis agents that act to suppress VEGF.[28]

To summarize the results of the studies, till date none of the regions reached genome-wide statistical significance and had inconsistent results. Limitations include commercial arrays for GWA scans that provide excellent coverage of common SNPs, however, limited for rare frequency variants (with a minor allele frequency below 5%).[29]

If susceptibility alleles have minor allele frequencies of less than 0.1 and their effect sizes are less than OR of 1.3, then unrealistically large sample sizes are required for statistical support for disease association.[30] Often only modest sample sizes are got by GWAS standard.

Other problems of GWAS were combining heterogeneous phenotypes (patients with PDR, NPDR, and diabetic macular edema) as cases, poor characterization of healthy individuals, (those with no DR) and poor DR standardization.[31]

The genetic effects identified by GWAS were not consistent across populations of different ancestry.[32] Therefore, genomic risk markers need a separate evaluation in different ethnic groups (as per the Candidate-gene Association Resource study). To circumvent these issues, it is a useful measure to join forces by international collaborative efforts to increase statistical power by increasing sample size. Moreover, analysis by treating the phenotype as a dichotomous trait and analysis of a related, quantitative trait is useful. Third, connection of genetic findings with more defined physiologic parameters increases understanding.[33]

  Current Scenario: 2015 Top

  • A subgroup analysis showed a genetic association between ALR C (-106) T polymorphism and the risk of DR of type 1 DM but not type 2 DM [34]
  • Genetic variation near GRB2 on chromosome 17q251 is associated with sight-threatening DR. GRB2 is upregulated during retinal stress and neovascularization
  • Several genes here are promising candidates

  • It has been strongly hypothesised that SYVN1 confers DR resistance. It may play an important role in inhibiting ER stress, chronic inflammation, and vascular overgrowth associated with DR
  • Individuals with Type 1 diabetes and PDR exhibited altered DNA methylation patterns in the blood
  • Hmg CoA reductase degradation protein 1 (SYVN1) is considered a DR protective gene via gene expression analysis studies
  • A relationship between the intergenic SNP rs476141 and the presence of severe DR was found in 2013.[34] The strongest association was at rs4865047, an intronic SNP in the gene CEP125 for severe DR. Further studies are required to confirm it [35]
  • Meta-analysis suggested that the +869T/C (L10P) polymorphism in TGFβ1 gene would be a potential protective factor for DR.[36]

  Future – biomarkers, Proteomics, and Metabolomics Top

A new approach to find genetic susceptibility genes in DR is through associations with biomarkers (also known as intermediate phenotypes), an approach analogous to that of the investigations seen in lipids with myocardial infarctions.[37]

A number of biomarkers have been a subject of investigation for association with DR.[38],[39],[40],[41],[42],[43] Proteomics is a large-scale study of structure and function of proteins. Multiple proteins, such as apolipoprotein A-I and apolipoprotein H, are more likely to contribute to retinal disease than single proteins alone.[44]

Metabolomics is a measurement of immediate cellular state within a given biological system. A recent small study, examining the metabolomics in DR of 89 Chinese patients, found disturbances in fatty acid, amino acids, and glucose alterations to vary between diabetic patients without DR, NPDR, and PDR.[45]

At this time, no definite genetic associations with DR have been consistently reported because associations with DR have not been replicated in multiple populations, and hence no gene has achieved widespread acceptance as associative with DR.

  Changes to Be Made in the Field of Research in Diabetic Retinopathy Genetics Top

  • First, establishment of a large-scale consortia based on disease phenotypes or cohort
  • Second is standardization of a DR phenotype, classified with the ETDRS severity scale
  • Third, standardization of associated phenotypes (DM duration, glycemic controls, blood pressure, lipid profiles, and medications) to minimize heterogeneity on comparison
  • Fourth, larger sample cohorts to find modest associations.
  • Fifth, standardization of study protocols among different studies to perform meta-analyses between different cohorts and ethnicities
  • Sixth, novel statistical approaches, such as combination of GWAS and genome-wide linkage studies to prioritize the genome, could be a more efficient means to identify candidate genes for DR
  • Studies of different ethnicities need to be conducted to find population-specific signals in DR
  • Lastly, novel approaches, such as biomarkers as intermediate phenotypes, proteomics, metabolomics, exome array, and next-generation sequencing, may better our understanding of DR

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

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