Genome-wide meta-analysis for severe diabetic retinopathy

Development of electronic health record based algorithms to identify individuals with diabetic retinopathy

OBJECTIVES

To develop, validate, and implement algorithms to identify diabetic retinopathy (DR) cases and controls from electronic health care records (EHRs).

MATERIALS AND METHODS

We developed and validated electronic health record (EHR)-based algorithms to identify DR cases and individuals with type I or II diabetes without DR (controls) in 3 independent EHR systems: Vanderbilt University Medical Center Synthetic Derivative (VUMC), the VA Northeast Ohio Healthcare System (VANEOHS), and Massachusetts General Brigham (MGB). Cases were required to meet 1 of the following 3 criteria: (1) 2 or more dates with any DR ICD-9/10 code documented in the EHR, (2) at least one affirmative health-factor or EPIC code for DR along with an ICD9/10 code for DR on a different day, or (3) at least one ICD-9/10 code for any DR occurring within 24 hours of an ophthalmology examination. Criteria for controls included affirmative evidence for diabetes as well as an ophthalmology examination.

RESULTS

The algorithms, developed and evaluated in VUMC through manual chart review, resulted in a positive predictive value (PPV) of 0.93 for cases and negative predictive value (NPV) of 0.91 for controls. Implementation of algorithms yielded similar metrics in VANEOHS (PPV = 0.94; NPV = 0.86) and lower in MGB (PPV = 0.84; NPV = 0.76). In comparison, the algorithm for DR implemented in Phenome-wide association study (PheWAS) in VUMC yielded similar PPV (0.92) but substantially reduced NPV (0.48). Implementation of the algorithms to the Million Veteran Program identified over 62 000 DR cases with genetic data including 14 549 African Americans and 6209 Hispanics with DR.

CONCLUSIONS/DISCUSSION

We demonstrate the robustness of the algorithms at 3 separate healthcare centers, with a minimum PPV of 0.84 and substantially improved NPV than existing automated methods. We strongly encourage independent validation and incorporation of features unique to each EHR to enhance algorithm performance for DR cases and controls.

Single-cell RNA sequencing in exploring the pathogenesis of diabetic retinopathy

Diabetic retinopathy (DR) is a leading cause of irreversible blindness in the working-age populations. Despite decades of research on the pathogenesis of DR for clinical care, a comprehensive understanding of the condition is still lacking due to the intricate cellular diversity and molecular heterogeneity involved. Single-cell RNA sequencing (scRNA-seq) has made the high-throughput molecular profiling of cells across modalities possible which has provided valuable insights into complex biological systems. In this review, we summarise the application of scRNA-seq in investigating the pathogenesis of DR, focusing on four aspects. These include the identification of differentially expressed genes, characterisation of key cell subpopulations and reconstruction of developmental 'trajectories' to unveil their state transition, exploration of complex cell‒cell communication in DR and integration of scRNA-seq with genome-wide association studies to identify cell types that are most closely related to DR risk genetic loci. Finally, we discuss the future challenges and expectations associated with studying DR using scRNA-seq. We anticipate that scRNA-seq will facilitate the discovery of mechanisms and new treatment targets in the clinical care landscape for patients with DR. KEY POINTS: Progress in scRNA-seq for diabetic retinopathy (DR) research includes studies on DR patients, non-human primates, and the prevalent mouse models. scRNA-seq facilitates the identification of differentially expressed genes, pivotal cell subpopulations, and complex cell-cell interactions in DR at single-cell level. Future scRNA-seq applications in DR should target specific patient subsets and integrate with single-cell and spatial multi-omics approaches.

Development of Portable Electronic Health Record Based Algorithms to Identify Individuals with Diabetic Retinopathy

Objectives

To develop, validate and implement algorithms to identify diabetic retinopathy (DR) cases and controls from electronic health care records (EHR)s. Methods : We developed and validated EHR-based algorithms to identify DR cases and individuals with type I or II diabetes without DR (controls) in three independent EHR systems: Vanderbilt University Medical Center Synthetic Derivative (VUMC), the VA Northeast Ohio Healthcare System (VANEOHS), and Massachusetts General Brigham (MGB). Cases were required to meet one of three criteria: 1) two or more dates with any DR ICD-9/10 code documented in the EHR, or 2) at least one affirmative health-factor or EPIC code for DR along with an ICD9/10 code for DR on a different day, or 3) at least one ICD-9/10 code for any DR occurring within 24 hours of an ophthalmology exam. Criteria for controls included affirmative evidence for diabetes as well as an ophthalmology exam.

Results

The algorithms, developed and evaluated in VUMC through manual chart review, resulted in a positive predictive value (PPV) of 0.93 for cases and negative predictive value (NPV) of 0.97 for controls. Implementation of algorithms yielded similar metrics in VANEOHS (PPV=0.94; NPV=0.86) and lower in MGB (PPV=0.84; NPV=0.76). In comparison, use of DR definition as implemented in Phenome-wide association study (PheWAS) in VUMC, yielded similar PPV (0.92) but substantially reduced NPV (0.48). Implementation of the algorithms to the Million Veteran Program identified over 62,000 DR cases with genetic data including 14,549 African Americans and 6,209 Hispanics with DR.

Conclusions/Discussion

We demonstrate the robustness of the algorithms at three separate health-care centers, with a minimum PPV of 0.84 and substantially improved NPV than existing high-throughput methods. We strongly encourage independent validation and incorporation of features unique to each EHR to enhance algorithm performance for DR cases and controls.

The Role of Genetic Polymorphisms in Diabetic Retinopathy: Narrative Review

Diabetic retinopathy (DR) is renowned as a leading cause of visual loss in working-age populations with its etiopathology influenced by the disturbance of biochemical metabolic pathways and genetic factors, including gene polymorphism. Metabolic pathways considered to have an impact on the development of the disease, as well as genes and polymorphisms that can affect the gene expression, modify the quantity and quality of the encoded product (protein), and significantly alter the metabolic pathway and its control, and thus cause changes in the functioning of metabolic pathways. In this article, the screening of chromosomes and the most important genes involved in the etiology of diabetic retinopathy is presented. The common databases with manuscripts published from January 2000 to June 2023 have been taken into consideration and chosen. This article indicates the role of specific genes in the development of diabetic retinopathy, as well as polymorphic changes within the indicated genes that may have an impact on exacerbating the symptoms of the disease. The collected data will allow for a broader look at the disease and help to select candidate genes that can become markers of the disease.

To RNA-binding and beyond: Emerging facets of the role of Rbfox proteins in development and disease

The RNA-binding Fox-1 homologue (Rbfox) proteins represent an ancient family of splicing factors, conserved through evolution. All members share an RNA recognition motif (RRM), and a particular affinity for the GCAUG signature in target RNA molecules. The role of Rbfox, as a splice factor, deciding the tissue-specific inclusion/exclusion of an exon, depending on its binding position on the flanking introns, is well known. Rbfox often acts in concert with other splicing factors, and forms splicing regulatory networks. Apart from this canonical role, recent studies show that Rbfox can also function as a transcription co-factor, and affects mRNA stability and translation. The repertoire of Rbfox targets is vast, including genes involved in the development of tissue lineages, such as neurogenesis, myogenesis, and erythropoeiesis, and molecular processes, including cytoskeletal dynamics, and calcium handling. A second layer of complexity is added by the fact that Rbfox expression itself is regulated by multiple mechanisms, and, in vertebrates, exhibits tissue-specific expression. The optimum dosage of Rbfox is critical, and its misexpression is etiological to various disease conditions. In this review, we discuss the contextual roles played by Rbfox as a tissue-specific regulator for the expression of many important genes with diverse functions, through the lens of the emerging data which highlights its involvement in many human diseases. Furthermore, we explore the mechanistic details provided by studies in model organisms, with emphasis on the work with Drosophila. This article is categorized under: RNA Processing > Splicing Mechanisms RNA Interactions with Proteins and Other Molecules > Protein-RNA Interactions: Functional Implications RNA Turnover and Surveillance > Regulation of RNA Stability RNA Processing > Splicing Regulation/Alternative Splicing.

Characterization of direct and/or indirect genetic associations for multiple traits in longitudinal studies of disease progression

When quantitative longitudinal traits are risk factors for disease progression and subject to random biological variation, joint model analysis of time-to-event and longitudinal traits can effectively identify direct and/or indirect genetic association of single nucleotide polymorphisms (SNPs) with time-to-event. We present a joint model that integrates: (1) a multivariate linear mixed model describing trajectories of multiple longitudinal traits as a function of time, SNP effects, and subject-specific random effects and (2) a frailty Cox survival model that depends on SNPs, longitudinal trajectory effects, and subject-specific frailty accounting for dependence among multiple time-to-event traits. Motivated by complex genetic architecture of type 1 diabetes complications (T1DC) observed in the Diabetes Control and Complications Trial (DCCT), we implement a 2-stage approach to inference with bootstrap joint covariance estimation and develop a hypothesis testing procedure to classify direct and/or indirect SNP association with each time-to-event trait. By realistic simulation study, we show that joint modeling of 2 time-to-T1DC (retinopathy and nephropathy) and 2 longitudinal risk factors (HbA1c and systolic blood pressure) reduces estimation bias in genetic effects and improves classification accuracy of direct and/or indirect SNP associations, compared to methods that ignore within-subject risk factor variability and dependence among longitudinal and time-to-event traits. Through DCCT data analysis, we demonstrate feasibility for candidate SNP modeling and quantify effects of sample size and Winner's curse bias on classification for 2 SNPs identified as having indirect associations with time-to-T1DC traits. Joint analysis of multiple longitudinal and multiple time-to-event traits provides insight into complex traits architecture.

Revisiting Retinal Degeneration Hallmarks: Insights from Molecular Markers and Therapy Perspectives

Visual impairment and blindness are a growing public health problem as they reduce the life quality of millions of people. The management and treatment of these diseases represent scientific and therapeutic challenges because different cellular and molecular actors involved in the pathophysiology are still being identified. Visual system components, particularly retinal cells, are extremely sensitive to genetic or metabolic alterations, and immune responses activated by local insults contribute to biological events, culminating in vision loss and irreversible blindness. Several ocular diseases are linked to retinal cell loss, and some of them, such as retinitis pigmentosa, age-related macular degeneration, glaucoma, and diabetic retinopathy, are characterized by pathophysiological hallmarks that represent possibilities to study and develop novel treatments for retinal cell degeneration. Here, we present a compilation of revisited information on retinal degeneration, including pathophysiological and molecular features and biochemical hallmarks, and possible research directions for novel treatments to assist as a guide for innovative research. The knowledge expansion upon the mechanistic bases of the pathobiology of eye diseases, including information on complex interactions of genetic predisposition, chronic inflammation, and environmental and aging-related factors, will prompt the identification of new therapeutic strategies.

Progress in genetics of type 2 diabetes and diabetic complications

Type 2 diabetes results from a complex interaction between genetic and environmental factors. Precision medicine for type 2 diabetes using genetic data is expected to predict the risk of developing diabetes and complications and to predict the effects of medications and life-style intervention more accurately for individuals. Genome-wide association studies (GWAS) have been conducted in European and Asian populations and new genetic loci have been identified that modulate the risk of developing type 2 diabetes. Novel loci were discovered by GWAS in diabetic complications with increasing sample sizes. Large-scale genome-wide association analysis and polygenic risk scores using biobank information is making it possible to predict the development of type 2 diabetes. In the ADVANCE clinical trial of type 2 diabetes, a multi-polygenic risk score was useful to predict diabetic complications and their response to treatment. Proteomics and metabolomics studies have been conducted and have revealed the associations between type 2 diabetes and inflammatory signals and amino acid synthesis. Using multi-omics analysis, comprehensive molecular mechanisms have been elucidated to guide the development of targeted therapy for type 2 diabetes and diabetic complications.

Genome-Wide Associations and Confirmatory Meta-Analyses in Diabetic Retinopathy

The present study aimed to summarize and validate the genomic association signals for diabetic retinopathy (DR), proliferative DR, and diabetic macular edema/diabetic maculopathy. A systematic search of the genome-wide association study (GWAS) catalog and PubMed/MELINE databases was conducted to curate a comprehensive list of significant GWAS discoveries. The top signals were then subjected to meta-analysis using established protocols. The results indicate the need for improved consensus among DR GWASs, highlighting the importance of validation efforts. A subsequent meta-analysis confirmed the association of two SNPs, rs4462262 (ZWINT-MRPS35P3) (odds ratio = 1.38, p = 0.001) and rs7903146 (TCF7L2) (odd ratio = 1.30, p < 0.001), with DR in independent populations, strengthening the evidence of their true association. We also compiled a list of candidate SNPs for further validation. This study highlights the importance of consistent validation and replication efforts in the field of DR genetics. The two identified gene loci warrant further functional investigation to understand their role in DR pathogenesis.

Circulatory Biomarkers and Diabetic Retinopathy in Racial and Ethnic Populations

Clinical staging systems for diagnosis and treatment of diabetic retinopathy (DR) must closely relate to endpoints that are both relevant for patients and feasible for physicians to implement. Current DR staging systems for clinical eye care and research provide detailed phenotypic characterization to predict patient outcomes in diabetes but have limitations. Biochemical biomarkers provide a rich pool of potential candidates for new DR staging systems that can be readily measured in accessible fluids. Circulating biomarkers that are specific to the retina and relate to angiogenesis and inflammation have been suggested as relevant for DR. Although there is a lack of multi-ethnic studies evaluating circulatory biomarkers in DR, variability in circulatory biomarkers have been reported in people from different ethnic and racial backgrounds. Therefore, there is a need for future studies to evaluate individual or combinations of biomarkers in diverse populations with DR from different ethnic and racial backgrounds.

A Guide to Genome-Wide Association Study Design for Diabetic Retinopathy

Diabetic retinopathy (DR) is the most common microvascular complication related to diabetes. There is evidence that genetics play an important role in DR pathogenesis, but the complexity of the disease makes genetic studies a challenge. This chapter is a practical overview of the basic steps for genome-wide association studies with respect to DR and its associated traits. Also described are approaches that can be adopted in future DR studies. This is intended to serve as a guide for beginners and to provide a framework for further in-depth analysis.

DNA Methylation in Gestational Diabetes and its Predictive Value for Postpartum Glucose Disturbances

CONTEXT

DNA methylation in the diagnosis of gestational diabetes.

OBJECTIVE

To assess the value of DNA methylation in the diagnosis of gestational diabetes (GDM) and in the prediction of maternal postpartum glucose disturbances.

METHODS

Two-stage observational study performed between July 2006 and December 2010, at University Hospital. Forty-eight randomly selected pregnant women formed the discovery cohort (24 with GDM and 24 controls) and 252 pregnant women (94 with GDM and 158 controls) formed the replication cohort. GDM women were re-evaluated 4 years postpartum. The main outcome measures were GDM, type 2 diabetes or prediabetes at 4 years postpartum.

RESULTS

We identified 3 CpG sites related to LINC00917, TRAPPC9, and LEF1 that were differentially methylated in women with GDM and abnormal glucose tolerance; and sites associated with LINC00917 and TRAPPC9 were independently associated with an abnormal glucose tolerance status 4 years postpartum after controlling for clinical variables. Moreover, the site associated with LINC00917 and the combination of the 3 sites had the highest predictive values.

CONCLUSION

Our results suggest that some of these sites may be implicated in the development of GDM and postpartum abnormal glucose tolerance.

Role of Autotaxin in High Glucose-Induced Human ARPE-19 Cells

Autotaxin (ATX) is an enzymatic with lysophospholipase D (lysoPLD) activity. We investigated the role of ATX in high glucose (HG)-induced human retinal pigment epithelial (ARPE-19) cells to explore the pathogenesis of diabetic retinopathy (DR). We performed a quantitative real-time polymerase chain reaction, Western blotting, immunocytochemistry, enzyme-linked immunosorbent assay, cell permeability assay, and transepithelial electrical resistance measurement in HG-induced ARPE-19 cells and compared their results with those of normal glucose and osmotic pressure controls. ATX expression and its lysoPLD activity, barrier function, and expression of vascular endothelial growth factor receptors VEGFR-1 and VEGFR-2 were downregulated, while fibrotic responses, cytoskeletal reorganization, and transforming growth factor-β expression were upregulated, in the HG group. Our results suggest that HG induces intracellular ATX downregulation, barrier dysfunction, and fibrosis, which are involved in early DR and can be targeted for DR treatment.

Retinal Transcriptome and Cellular Landscape in Relation to the Progression of Diabetic Retinopathy

Purpose

Previous studies that identify putative genes associated with diabetic retinopathy are only focusing on specific clinical stages, thus resulting genes are not necessarily reflective of disease progression. This study identified genes associated with the severity level of diabetic retinopathy using the likelihood-ratio test (LRT) and ordinal logistic regression (OLR) model, as well as to profile immune and retinal cell landscape in progressive diabetic retinopathy using a machine learning deconvolution approach.

Methods

This study used a published transcriptomic dataset (GSE160306) from macular regions of donors with different degrees of diabetic retinopathy (10 healthy controls, 10 cases of diabetes, 9 cases of nonproliferative diabetic retinopathy, and 10 cases of proliferative diabetic retinopathy or combined with diabetic macular edema). LRT and OLR models were applied to identify severity-associated genes. In addition, CIBERSORTx was used to estimate proportional changes of immune and retinal cells in progressive diabetic retinopathy.

Results

By controlling for gender and age using LRT and OLR, 50 genes were identified to be significantly increased in expression with the severity of diabetic retinopathy. Functional enrichment analyses suggested these severity-associated genes are related to inflammation and immune responses. CCND1 and FCGR2B are further identified as key regulators to interact with many other severity-associated genes and are crucial to inflammation. Deconvolution analyses demonstrated that the proportions of memory B cells, M2 macrophages, and Müller glia were significantly increased with the progression of diabetic retinopathy.

Conclusions

These findings demonstrate that deep analyses of transcriptomic data can advance our understanding of progressive ocular diseases, such as diabetic retinopathy, by applying LRT and OLR models as well as bulk gene expression deconvolution.

Single-cell multiome of the human retina and deep learning nominate causal variants in complex eye diseases

Genome-wide association studies (GWASs) of eye disorders have identified hundreds of genetic variants associated with ocular disease. However, the vast majority of these variants are noncoding, making it challenging to interpret their function. Here we present a joint single-cell atlas of gene expression and chromatin accessibility of the adult human retina with more than 50,000 cells, which we used to analyze single-nucleotide polymorphisms (SNPs) implicated by GWASs of age-related macular degeneration, glaucoma, diabetic retinopathy, myopia, and type 2 macular telangiectasia. We integrate this atlas with a HiChIP enhancer connectome, expression quantitative trait loci (eQTL) data, and base-resolution deep learning models to predict noncoding SNPs with causal roles in eye disease, assess SNP impact on transcription factor binding, and define their known and novel target genes. Our efforts nominate pathogenic SNP-target gene interactions for multiple vision disorders and provide a potentially powerful resource for interpreting noncoding variation in the eye.

Association of MMP-2 genes variants with diabetic retinopathy in Tunisian population with type 2 diabetes

AIMS

Few studies investigated the association of genetic difference in metalloproteinase-2 (MMP-2) gene with diabetic retinopathy but with mixed outcome. To investigate the association between a set of MMP-2 genetic variants and the risk of diabetic retinopathy in an Arab Tunisian population with type 2 diabetes.

SUBJECTS AND METHODS

A retrospective case-control study comprising a total of 779 type 2 diabetes patients with or without diabetic retinopathy was conducted. Genotyping was prepared by TaqMan® SNP genotyping qRT-PCR. The variants used were rs243865 (C/T), rs243864 (T/G), rs243866 (G/T) and rs2285053 (C/T).

RESULTS

The minor allele frequency (MAF) of the rs243864 MMP-2 variant was significantly higher among diabetic retinopathy patients. Setting homozygous wild type genotype carrier as reference, the rs243864T/G allele was associated with increased risk of diabetic retinopathy under the dominant, recessive, and additive models which persisted when key covariates were controlled for, while a reduced risk of diabetic retinopathy progression was seen after adjustment between non-proliferative and proliferative diabetic patients. Furthermore, the heterozygous genotype GT of the rs243866 variant is positively associated with the risk of proliferative diabetic retinopathy in the additive model. A limited linkage disequilibrium (LD) was revealed between the four-matrix metalloproteinase-2 variants. Four-loci haplotype analysis identified, GCTC, TTTC, and GCTT haplotypes to be positively associated with the risk of diabetic retinopathy.

CONCLUSION

Our findings demonstrate that the MMP-2 variant rs243864 and 243866 are related to the susceptibility to diabetic retinopathy and the progression of the disease in an Arab Tunisian population with type 2 diabetes.

The E23K Polymorphism of KCNJ11 and Diabetic Retinopathy in Northern Iran

Background: Diabetic Retinopathy (DR) is one of the most severe micro-vascular complications of diabetes mellitus (DM), involving interactions between environmental and genetic risk factors. KCNJ11 gene has a key role in insulin secretion and is of substantial interest in various populations.

Methods: A population-based association of 524 T2DM patients was performed to delineate the genetic influence of KCNJ11 polymorphisms (rs5219, c.67A>G or E23K) on the risk of DR in an Iranian population. Genotyping was performed using TaqMan assay. Univariate and MLR analysis controlling for confounders was conducted to evaluate the association between rs5219 and DR.

Results: No significant difference was observed in either genotypes distribution (p = 0.83) or allele frequency (p = 0.66) between T2DM individuals with and without DR in any models of inheritance. Genotype-phenotype association showed that DR group carrying GA genotypes, a significantly higher mean age was observed compared with two other genotypes (p = 0.04). MLR analysis indicated that HbAlc with adjusted OR of 1.84 (95% CI, 1.46–2.33, p = 0.00) and first-degree relatives of family history with adjusted OR of 2.85 (95% CI, 1.45–5.58, p = 0.002) were significantly associated with DR, but the c.67A>G genotype is not an independent predictor of retinopathy.

Conclusion: Collectively, rs5219 was not associated with DR among Iranians with T2DM.

Gene Set Enrichment Analsyes Identify Pathways Involved in Genetic Risk for Diabetic Retinopathy

To identify functionally related genes associated with diabetic retinopathy (DR) risk using gene set enrichment analyses applied to genome-wide association study meta-analyses.

METHODS

We analyzed DR GWAS meta-analyses performed on 3246 Europeans and 2611 African Americans with type 2 diabetes. Gene sets relevant to 5 key DR pathophysiology processes were investigated: tissue injury, vascular events, metabolic events and glial dysregulation, neuronal dysfunction, and inflammation. Keywords relevant to these processes were queried in 4 pathway and ontology databases. Two GSEA methods, Meta-Analysis Gene set Enrichment of variaNT Associations (MAGENTA) and Multi-marker Analysis of GenoMic Annotation (MAGMA), were used. Gene sets were defined to be enriched for gene associations with DR if the P value corrected for multiple testing (Pcorr) was <.05.

RESULTS

Five gene sets were significantly enriched for numerous modest genetic associations with DR in one method (MAGENTA or MAGMA) and also at least nominally significant (uncorrected P < .05) in the other method. These pathways were regulation of the lipid catabolic process (2-fold enrichment, Pcorr = .014); nitric oxide biosynthesis (1.92-fold enrichment, Pcorr = .022); lipid digestion, mobilization, and transport (1.6-fold enrichment, P = .032); apoptosis (1.53-fold enrichment, P = .041); and retinal ganglion cell degeneration (2-fold enrichment, Pcorr = .049). The interferon gamma (IFNG) gene, previously implicated in DR by protein-protein interactions in our GWAS, was among the top ranked genes in the nitric oxide pathway (best variant P = .0001).

CONCLUSIONS

These GSEA indicate that variants in genes involved in oxidative stress, lipid transport and catabolism, and cell degeneration are enriched for genes associated with DR risk. NOTE: Publication of this article is sponsored by the American Ophthalmological Society.

Treatment of Macular Edema in Vascular Retinal Diseases: A 2021 Update

Macular edema (ME) is associated with various conditions; however, the main causes of ME are retinal vein occlusion (RVO) and diabetes. Laser photocoagulation, formerly the gold standard for the treatment of ME, has been replaced by anti-vascular endothelial growth factor (anti-VEGF) intravitreal injections. Despite its efficiency, this treatment requires frequent injections to preserve the outcomes of anti-VEGF therapy, and as many patients do not sufficiently respond to the treatment, ME is typically a chronic condition that can lead to permanent visual impairment. Generalized recommendations for the treatment of ME are lacking, which highlights the importance of reviewing treatment approaches, including recent anti-VEGFs, intravitreal steroid implants, and subthreshold micropulse lasers. We reviewed relevant studies, emphasizing the articles published between 2019 and 2021 and using the following keywords: macular edema, diabetic macular edema, retinal vein occlusion, laser photocoagulation, anti-VEGF, and intravitreal injections. Our results revealed that a combination of different treatment methods may be beneficial in resistant cases. Additionally, artificial intelligence (AI) is likely to help select the best treatment option for patients in the near future.

Association of four gene polymorphisms in Chinese Guangxi population with diabetic retinopathy in type 2 diabetic patients

Background

Diabetic retinopathy (DR) is one of the most common chronic microvascular complications of diabetes. Many studies have suggested that genetic factors are important in the context of DR. This study evaluated the associations of GWAS (Genome-wide association study) -identified DR-associated SNPs in a Chinese population in Guangxi Province with type 2 diabetes mellitus (T2DM).

Methods

A total of 386 hospitalized T2DM patients without proliferative diabetic retinopathy (PDR) and 316 hospitalized T2DM patients with PDR were included in this case–control study. Four tag SNPs, including rs1800896 in the IL-10 gene, rs2010963 in the VEGFA gene, rs2070600 in the RAGE gene and rs2910164 in the miR-146a gene, were examined using KASP (kompetitive allele specific PCR) genotyping assays.

Results

There were no significant differences in the genotype or allele frequencies of the miR-146a polymorphism (rs2910164) between subjects with PDR and those without DR. The TC genotype of rs1800896 was determined to be associated with an increased risk of PDR (the odds ratio (OR) was 2.366, with a 95% confidence interval (CI) ranging from 1.144 to 4.894). The CG genotypes of rs2010963 was associated with an decreased risk of PDR (the OR was 0.588, with a 95% CI ranging from 0.366 to 0.946). Regarding rs2070600, 2 genotypes (TT and CT) were associated with a decreased risk of PDR (the OR of the TT genotype was 0.180, with a 95% CI ranging from 0.037 to 0.872, and the OR of the CT genotype was 0.448, with a 95% CI ranging from 0.266 to 0.753).

Conclusions

The rs1800896 polymorphisms in the IL-10 gene, rs2010963 in the VEGFA gene and rs2070600 in the RAGE gene are associated with the risk of PDR in the Han Chinese population of Guangxi Province. Our findings provide suggestive evidence that these polymorphisms may be involved in the pathogenesis of PDR and should be investigated further.

Human Leukocyte Antigens class II (HLA II) gene profile from an admixed population of patients with type 1 diabetes with severe diabetic retinopathy: a nested case-control study in Brazil

BACKGROUND

Although the well-established role of the HLA genes on the predisposition of type 1 diabetes (T1D), its contribution to the development and progression of diabetic retinopathy is still unclear, especially in admixed populations. We aimed to study the relationship between HLA alleles and severe diabetic retinopathy in a highly admixed population of T1D patients.

METHODS

This was a nested case-control study based on a cross-sectional, nationwide survey conducted in Brazil. We included 117 patients with severe diabetic retinopathy and 117 random controls composed of T1D patients without retinopathy, matched for diabetes duration. HLA-class II genes (HLA-DRB1, -DQA1, and -DQB1) were genotyped using the SSO and NGS methods.

RESULTS

Haplotypes HLA-DRB1*04:05 ~ DQA1*03:01 g ~ DQB1*03:02 (OR 1.75, CI 0.97-3.16, p value 0.058) and HLA-DRB1*13:02 ~ DQA1*01:02 ~ DQB1*06:04 (OR 5.18, CI 1.12-23.09, p value 0.019) were more prevalent on the severe DR group but they did not present statistically difference after Bonferroni correction. The most frequent haplotype on both groups was HLA-DRB1*03:01 ~ DQA1*05:01 g ~ DQB1*02:01 (29.6% on severe DR and 33.33% on the control group).

CONCLUSIONS

Our study showed no influence of HLA genes on the development of DR. Further longitudinal data is needed to better understand the role of genetic factors on this multifactorial significant microvascular complication.

Genetics of Diabetic Retinopathy, a Leading Cause of Irreversible Blindness in the Industrialized World

Diabetic retinopathy (DR) is a chronic complication of diabetes and a leading cause of blindness in the industrialized world. Traditional risk factors, such as glycemic control and duration of diabetes, are unable to explain why some individuals remain protected while others progress to a more severe form of the disease. Differences are also observed in DR heritability as well as the response to anti-vascular endothelial growth factor (VEGF) treatment. This review discusses various aspects of genetics in DR to shed light on DR pathogenesis and treatment. First, we discuss the global burden of DR followed by a discussion on disease pathogenesis as well as the role genetics plays in the prevalence and progression of DR. Subsequently, we provide a review of studies related to DR’s genetic contribution, such as candidate gene studies, linkage studies, and genome-wide association studies (GWAS) as well as other clinical and meta-analysis studies that have identified putative candidate genes. With the advent of newer cutting-edge technologies, identifying the genetic components in DR has played an important role in understanding DR incidence, progression, and response to treatment, thereby developing newer therapeutic targets and therapies.

Onecut Regulates Core Components of the Molecular Machinery for Neurotransmission in Photoreceptor Differentiation

Photoreceptor cells (PRC) are neurons highly specialized for sensing light stimuli and have considerably diversified during evolution. The genetic mechanisms that underlie photoreceptor differentiation and accompanied the progressive increase in complexity and diversification of this sensory cell type are a matter of great interest in the field. A role of the homeodomain transcription factor Onecut (Oc) in photoreceptor cell formation is proposed throughout multicellular organisms. However, knowledge of the identity of the Oc downstream-acting factors that mediate specific tasks in the differentiation of the PRC remains limited. Here, we used transgenic perturbation of the Ciona robusta Oc protein to show its requirement for ciliary PRC differentiation. Then, transcriptome profiling between the trans-activation and trans-repression Oc phenotypes identified differentially expressed genes that are enriched in exocytosis, calcium homeostasis, and neurotransmission. Finally, comparison of RNA-Seq datasets in Ciona and mouse identifies a set of Oc downstream genes conserved between tunicates and vertebrates. The transcription factor Oc emerges as a key regulator of neurotransmission in retinal cell types.

Possible Modifying Effect of Hemoglobin A1c on Genetic Susceptibility to Severe Diabetic Retinopathy in Patients With Type 2 Diabetes

Purpose

Glycemic control has been recognized as an important modifiable risk factor for diabetic retinopathy (DR). Whether hemoglobin A1c (HbA1c), as an indicator of glycemic control, could modify the genetic susceptibility to severe DR remains to be investigated. This study aimed to investigate whether HbA1c could modulate the genetic susceptibility to severe DR in Chinese patients with type 2 diabetes.

Methods

A total of 3,093 Chinese individuals with type 2 diabetes were included in the cross-sectional case-control study: 1,051 with sight-threatening DR (STDR) and 2,042 without STDR. Sixty-nine top-ranked single nucleotide polymorphisms (SNPs) identified from previous genome-wide association studies were examined for their associations with STDR and proliferative DR as a subgroup analysis. SNPs showing suggestive associations with DR were examined in the stratified analysis by dichotomized HbA1c (<7% vs. ≥7%). An interaction analysis was performed by including an interaction term of SNP × HbA1c in the regression model.

Results

Four SNPs showed suggestive associations with STDR. In the stratified analysis, patients with adequate glycemic control (HbA1c <7%) had a 42% lower risk of STDR for carrying each additional protective C allele of COL5A1 rs59126004 (P = 1.76 × 10⁻⁴; odds ratio, 0.58; 95% confidence interval, 0.44–0.77). rs59126004 demonstrated a significant interaction with dichotomized HbA1c on the risk of STDR (P_interaction = 1.733 × 10⁻³). In the subgroup analysis for proliferative DR, the protective effect of rs59126004 was even more pronouncedly demonstrated (P = 8.35 × 10⁻⁵; odds ratio, 0.37; 95% confidence interval, 0.22–0.60) and it showed similar interactions with dichotomized HbA1c (P_interaction = 1.729 × 10⁻³).

Conclusions

Our data provided evidence for possible interactions between HbA1c and COL5A1 rs59126004 on the risk of severe DR. These findings may provide new insight into the pathophysiologic mechanism of DR.

DNA Methylation Associated With Diabetic Kidney Disease in Blood-Derived DNA

A subset of individuals with type 1 diabetes will develop diabetic kidney disease (DKD). DKD is heritable and large-scale genome-wide association studies have begun to identify genetic factors that influence DKD. Complementary to genetic factors, we know that a person’s epigenetic profile is also altered with DKD. This study reports analysis of DNA methylation, a major epigenetic feature, evaluating methylome-wide loci for association with DKD. Unique features (n = 485,577; 482,421 CpG probes) were evaluated in blood-derived DNA from carefully phenotyped White European individuals diagnosed with type 1 diabetes with (cases) or without (controls) DKD (n = 677 samples). Explicitly, 150 cases were compared to 100 controls using the 450K array, with subsequent analysis using data previously generated for a further 96 cases and 96 controls on the 27K array, and de novo methylation data generated for replication in 139 cases and 96 controls. Following stringent quality control, raw data were quantile normalized and beta values calculated to reflect the methylation status at each site. The difference in methylation status was evaluated between cases and controls; resultant P-values for array-based data were adjusted for multiple testing. Genes with significantly increased (hypermethylated) and/or decreased (hypomethylated) levels of DNA methylation were considered for biological relevance by functional enrichment analysis using KEGG pathways. Twenty-two loci demonstrated statistically significant fold changes associated with DKD and additional support for these associated loci was sought using independent samples derived from patients recruited with similar inclusion criteria. Markers associated with CCNL1 and ZNF187 genes are supported as differentially regulated loci (P < 10^–8), with evidence also presented for AFF3, which has been identified from a meta-analysis and subsequent replication of genome-wide association studies. Further supporting evidence for differential gene expression in CCNL1 and ZNF187 is presented from kidney biopsy and blood-derived RNA in people with and without kidney disease from NephroSeq. Evidence confirming that methylation sites influence the development of DKD may aid risk prediction tools and stimulate research to identify epigenomic therapies which might be clinically useful for this disease.

Integration of genomics and transcriptomics predicts diabetic retinopathy susceptibility genes

We determined differential gene expression in response to high glucose in lymphoblastoid cell lines derived from matched individuals with type 1 diabetes with and without retinopathy. Those genes exhibiting the largest difference in glucose response were assessed for association with diabetic retinopathy in a genome-wide association study meta-analysis. Expression quantitative trait loci (eQTLs) of the glucose response genes were tested for association with diabetic retinopathy. We detected an enrichment of the eQTLs from the glucose response genes among small association p-values and identified folliculin (FLCN) as a susceptibility gene for diabetic retinopathy. Expression of FLCN in response to glucose was greater in individuals with diabetic retinopathy. Independent cohorts of individuals with diabetes revealed an association of FLCN eQTLs with diabetic retinopathy. Mendelian randomization confirmed a direct positive effect of increased FLCN expression on retinopathy. Integrating genetic association with gene expression implicated FLCN as a disease gene for diabetic retinopathy.

One of the side effects of diabetes is loss of vision from diabetic retinopathy, which is caused by injury to the light sensing tissue in the eye, the retina. Almost all individuals with diabetes develop diabetic retinopathy to some extent, and it is the leading cause of irreversible vision loss in working-age adults in the United States. How long a person has been living with diabetes, the extent of increased blood sugars and genetics all contribute to the risk and severity of diabetic retinopathy. Unfortunately, virtually no genes associated with diabetic retinopathy have yet been identified.

When a gene is activated, it produces messenger molecules known as mRNA that are used by cells as instructions to produce proteins. The analysis of mRNA molecules, as well as genes themselves, can reveal the role of certain genes in disease. The studies of all genes and their associated mRNAs are respectively called genomics and transcriptomics. Genomics reveals what genes are present, while transcriptomics shows how active genes are in different cells.

Skol et al. developed methods to study genomics and transcriptomics together to help discover genes that cause diabetic retinopathy. Genes involved in how cells respond to high blood sugar were first identified using cells grown in the lab. By comparing the activity of these genes in people with and without retinopathy the study identified genes associated with an increased risk of retinopathy in diabetes. In people with retinopathy, the activity of the folliculin gene (FLCN) increased more in response to high blood sugar. This was further verified with independent groups of people and using computer models to estimate the effect of different versions of the folliculin gene.

The methods used here could be applied to understand complex genetics in other diseases. The results provide new understanding of the effects of diabetes. They may also help in the development of new treatments for diabetic retinopathy, which are likely to improve on the current approach of using laser surgery or injections into the eye.

Cell Atlas of The Human Fovea and Peripheral Retina

Most irreversible blindness results from retinal disease. To advance our understanding of the etiology of blinding diseases, we used single-cell RNA-sequencing (scRNA-seq) to analyze the transcriptomes of ~85,000 cells from the fovea and peripheral retina of seven adult human donors. Utilizing computational methods, we identified 58 cell types within 6 classes: photoreceptor, horizontal, bipolar, amacrine, retinal ganglion and non-neuronal cells. Nearly all types are shared between the two retinal regions, but there are notable differences in gene expression and proportions between foveal and peripheral cohorts of shared types. We then used the human retinal atlas to map expression of 636 genes implicated as causes of or risk factors for blinding diseases. Many are expressed in striking cell class-, type-, or region-specific patterns. Finally, we compared gene expression signatures of cell types between human and the cynomolgus macaque monkey, Macaca fascicularis. We show that over 90% of human types correspond transcriptomically to those previously identified in macaque, and that expression of disease-related genes is largely conserved between the two species. These results validate the use of the macaque for modeling blinding disease, and provide a foundation for investigating molecular mechanisms underlying visual processing.

Aldose reductase (AC)n gene polymorphism in Iranian patients with type 2 diabetic microangiopathy; a case-control study

Aim

(AC)n promoter region of the aldose reductase (ALR) genes polymorphism has been associated with diabetic microvascular complications (MVCs). The aim of this study was to find the relationship between dinucleotide repeat (AC)n polymorphisms of the ALR gene and the occurrence of MVCs, such as diabetic retinopathy, neuropathy, and nephropathy in Iranian type 2 diabetic (T2D) patients.

Methods

This prospective case-control study was performed on T2D patients who were categorized into two groups based on the presence or absence of diabetic microangiopathy. All patients were provided informed consent. After extracting genomic DNA, the (AC)n of the ALR gene was determined using Polymerase chain reaction (PCR).

Results

Thirteen alleles of the (AC)n gene polymorphism were detected including Z + 16, Z + 14, Z + 8, Z + 6, Z + 4, Z + 2, Z, Z - 2, Z - 4, Z - 6, Z - 8, Z - 10, and Z - 12. The frequency of the Z - 4 allele was significantly higher in patients with retinopathy, nephropathy, and autonomic neuropathy compared with those with long-term uncomplicated diabetes (P < 0.001, P < 0.001, P = 0.031, respectively). After controlling for baseline risk factors, we found that the carrier of the Z - 4 allele of ALR (AC)n polymorphism had a higher risk of diabetic retinopathy and diabetic nephropathy (P < 0.001). The homozygosity for the Z - 4 allele was found to be associated with diabetic microangiopathy.

Conclusion

Our results showed that ALR (AC)n gene polymorphism in Iranian patients with type 2 diabetes independently, predispose retinal, renal and neural microvascular to diabetic complications.

Genotypes and Phenotypes: A Search for Influential Genes in Diabetic Retinopathy

Although gene–environment interactions are known to play an important role in the inheritance of complex traits, it is still unknown how a genotype and the environmental factors result in an observable phenotype. Understanding this complex interaction in the pathogenesis of diabetic retinopathy (DR) remains a big challenge as DR appears to be a disease with heterogenous phenotypes with multifactorial influence. In this review, we examine the natural history and risk factors related to DR, emphasizing distinct clinical phenotypes and their natural course in retinopathy. Although there is strong evidence that duration of diabetes and metabolic factors play a key role in the pathogenesis of DR, accumulating new clinical studies reveal that this disease can develop independently of duration of diabetes and metabolic dysfunction. More recently, studies have emphasized the role of genetic factors in DR. However, linkage analyses, candidate gene studies, and genome-wide association studies (GWAS) have not produced any statistically significant results. Our recently initiated genomics study, the Diabetic Retinopathy Genomics (DRGen) Study, aims to examine the contribution of rare and common variants in the development DR, and how they can contribute to clinical phenotype, rate of progression, and response to available therapies. Our preliminary findings reveal a novel set of genetic variants associated with proangiogenic and inflammatory pathways that may contribute to DR pathogenesis. Further investigation of these variants is necessary and may lead to development of novel biomarkers and new therapeutic targets in DR.

Integration of eQTL and a Single-Cell Atlas in the Human Eye Identifies Causal Genes for Age-Related Macular Degeneration

Age-related macular degeneration (AMD) is a leading cause of vision loss. To better understand disease pathogenesis and identify causal genes in GWAS loci for AMD risk, we present a comprehensive database of human retina and retinal pigment epithelium (RPE). Our database comprises macular and non-macular RNA sequencing (RNA-seq) profiles from 129 donors, a genome-wide expression quantitative trait loci (eQTL) dataset that includes macula-specific retina and RPE/choroid, and single-nucleus RNA-seq (NucSeq) from human retina and RPE with subtype resolution from more than 100,000 cells. Using NucSeq, we find enriched expression of AMD candidate genes in RPE cells. We identify 15 putative causal genes for AMD on the basis of co-localization of genetic association signals for AMD risk and eye eQTL, including the genes TSPAN10 and TRPM1. These results demonstrate the value of our human eye database for elucidating genetic pathways and potential therapeutic targets for ocular diseases.

Do Genomic Factors Play a Role in Diabetic Retinopathy?

Although there is strong clinical evidence that the control of blood glucose, blood pressure, and lipid level can prevent and slow down the progression of diabetic retinopathy (DR) as shown by landmark clinical trials, it has been shown that these factors only account for 10% of the risk for developing this disease. This suggests that other factors, such as genetics, may play a role in the development and progression of DR. Clinical evidence shows that some diabetics, despite the long duration of their diabetes (25 years or more) do not show any sign of DR or show minimal non-proliferative diabetic retinopathy (NPDR). Similarly, not all diabetics develop proliferative diabetic retinopathy (PDR). So far, linkage analysis, candidate gene studies, and genome-wide association studies (GWAS) have not produced any statistically significant results. We recently initiated a genomics study, the Diabetic Retinopathy Genetics (DRGen) Study, to examine the contribution of rare and common variants in the development of different phenotypes of DR, as well as their responsiveness to anti-VEGF treatment in diabetic macular edema (DME). Our preliminary findings reveal a novel set of genetic variants involved in the angiogenesis and inflammatory pathways that contribute to DR progression or protection. Further investigation of variants can help to develop novel biomarkers and lead to new therapeutic targets in DR.

Identifying Genetic Risk Factors for Diabetic Macular Edema and the Response to Treatment

Diabetic retinopathy (DR) is the most common microvascular complication of diabetes mellitus (DM). DR is complex and the term encompasses several clinical subtypes of diabetic eye disease, including diabetic macular edema (DME), the most frequent cause of central vision loss in DR patients. Both genetic and environmental factors contribute to the pathophysiology of DR and its subtypes. While numerous studies have identified several susceptibility genes for DR, few have investigated the impact of genetics on DME susceptibility. This review will focus on the current literature surrounding genetic risk factors associated with DME. We will also highlight the small number of studies investigating the genetics of response to antivascular endothelial growth factor (anti-VEGF) injection, which is used to treat DME.

Meta-analysis of the association between aldose reductase gene (CA)n microsatellite variants and risk of diabetic retinopathy

Diabetic retinopathy (DR) is one of the most severe microvascular complications of diabetes mellitus (DM). The (CA)n microsatellite variation of the aldose reductase (ALR) gene has been indicated to be associated with DR in previous studies; however, the results were inconclusive. To provide a more precise evaluation of the association between the (CA)n variations of ALR and the risk for DR, a meta-analysis was performed in the present study. Relevant articles were retrieved from the PubMed, Embase, Chinese National Knowledge Infrastructure and Cochrane Library databases. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) were used to evaluate the strength of the associations. The present meta-analysis included 17 studies comprising 1,575 DM patients with retinopathy and 1,741 DM patients without retinopathy. The results indicated that the Z-2 allele was a risk factor for DR in Asian (OR=1.82, 95% CI: 1.16-2.86, P=0.009) and Caucasian (OR=2.08, 95% CI: 1.14-3.79, P=0.02) populations, as well as in type 1 diabetes (T1D; OR=3.42, 95% CI: 1.46-8.04, P=0.005) and type 2 diabetes (T2D; OR=1.66, 95% CI: 1.05-2.63, P=0.03). Furthermore, the Z+2 allele was determined to be a protective factor for DR in Caucasian individuals (OR=0.50, 95% CI: 0.34-0.73, P=0.0004) and those with T1D (OR=0.39, 95% CI: 0.27-0.57, P<0.00001). Z+4 was also identified to be a protective factor, reducing the risk of DR in patients with T1D (OR=0.74, 95% CI: 0.57-0.96, P=0.02). Z-4 was revealed to be a risk factor for DR in Asian populations (OR=1.57, 95% CI: 1.22-2.03, P=0.0005) and in individuals with T1D (OR=1.62, 95% CI: 1.27-2.08, P=0.0001). However, no association was detected between the Z, Z+6 and Z-6 alleles and the risk of DR (P>0.05). In conclusion, the present results revealed the following: Z+2 may serve as a protective factor for DR in Caucasian individuals and those with T1D; Z+4 may be a protective factor for DR in patients with T2D; Z-2 may represent a risk factor for DR in all subgroups analyzed; and Z-4 may be a risk factor for DR in Asian populations and patients with T2D.

CACNB2 Is a Novel Susceptibility Gene for Diabetic Retinopathy in Type 1 Diabetes

Diabetic retinopathy is a common diabetes complication that threatens the eyesight and may eventually lead to acquired visual impairment or blindness. While a substantial heritability has been reported for proliferative diabetic retinopathy (PDR), only a few genetic risk factors have been identified. Using genome-wide sib pair linkage analysis including 361 individuals with type 1 diabetes, we found suggestive evidence of linkage with PDR at chromosome 10p12 overlapping the CACNB2 gene (logarithm of odds = 2.73). Evidence of association between variants in CACNB2 and PDR was also found in association analysis of 4,005 individuals with type 1 diabetes with an odds ratio of 0.83 and P value of 8.6 × 10^-4 for rs11014284. Sequencing of CACNB2 revealed two coding variants, R476C/rs202152674 and S502L/rs137886839. CACNB2 is abundantly expressed in retinal cells and encodes the β2 subunit of the L-type calcium channel. Blocking vascular endothelial growth factor (VEGF) by intravitreous anti-VEGF injections is a promising clinical therapy to treat PDR. Our data show that L-type calcium channels regulate VEGF expression and secretion from retinal pigment epithelial cells (ARPE19) and support the role of CACNB2 via regulation of VEGF in the pathogenesis of PDR. However, further genetic and functional studies are necessary to consolidate the findings.

Decreased expression of EFCC1 and its prognostic value in lung adenocarcinoma

Background

So far, there is a lack of reliable prognostic biomarkers for lung adenocarcinoma (ADC). Initially, we found that EF-hand and coiled-coil domain containing 1 (EFCC1) was a novel gene which was downregulated consistently with the progression of lung ADC in The Cancer Genome Atlas (TCGA) data through bioinformatics analysis. In this study, we aimed to evaluate the prognostic significance of EFCC1 in lung ADC in both TCGA data and clinical samples.

Methods

Firstly, the expression level and prognostic significance of EFCC1 in lung ADC were investigated in TCGA data. Then, the expression level of EFCC1 was validated by qPCR, Western blot, and immunohistochemistry (IHC) in five clinical lung ADC and matched adjacent non-tumor tissues. Finally, the association of EFCC1 expression with clinicopathological characteristics and overall survival (OS) in lung ADC patients was further evaluated in 130 clinical lung ADC samples with tissue microarray (TMA).

Results

In TCGA data, we found that decreased mRNA expression (P<0.001), elevated DNA methylation (P<0.001) of EFCC1 in lung ADC samples compared with normal lung samples, and low EFCC1 mRNA expression was associated with poor OS in lung ADC patients (HR =0.856, 95% CI: 0.754-0.970, P=0.015). In five clinical lung ADC and matched adjacent non-tumor tissues, both mRNA and protein levels of EFCC1 were lower in all lung ADC tissues than in their adjacent non-tumor counterparts. In 130 clinical lung ADC samples with TMA, EFCC1 expression was correlated with tumor-node-metastasis (TNM) stages (P=0.040) and lymph node metastasis status (P=0.001). The Kaplan-Meier survival curve revealed that low EFCC1 expression was significantly associated with poor OS in lung ADC patients (P=0.001) and multivariate Cox regression hazard model demonstrated that EFCC1 expression level was an independent prognostic factor for lung ADC patients (HR =0.557, 95% CI: 0.351-0.883, P=0.013).

Conclusions

Our findings suggested that decreased expression of EFCC1 was significantly associated with progression of lung ADC and could serve as a novel prognostic biomarker for lung ADC patients.

Vascular Inflammation Risk Factors in Retinal Disease

Inflammation of the blood vessels that serve the central nervous system has been increasingly identified as an early and possibly initiating event among neurodegenerative conditions such as Alzheimer's disease and related dementias. However, the causal relevance of vascular inflammation to major retinal degenerative diseases is unresolved. Here, we describe how genetics, aging-associated changes, and environmental factors contribute to vascular inflammation in age-related macular degeneration, diabetic retinopathy, and glaucoma. We highlight the importance of mouse models in studying the underlying mechanisms and possible treatments for these diseases. We conclude that data support vascular inflammation playing a central if not primary role in retinal degenerative diseases, and this association should be a focus of future research.

Genome-wide association study for proliferative diabetic retinopathy in Africans

Proliferative diabetic retinopathy (PDR) is a sight-threatening complication of diabetes that is associated with longer duration of diabetes and poor glycemic control under a genetic susceptibility background. Although GWAS of PDR have been conducted in Europeans and Asians, none has been done in continental Africans, a population at increased risk for PDR. Here, we report a GWAS of PDR among Africans. PDR cases (n = 64) were T2D patients with neovascularization in the retina and/or retinal detachment. Controls (n = 227) were T2D patients without listed eye complications despite high risk (T2D duration ≥10 years and fasting blood glucose >169 mg/dl). Replication was assessed in African Americans enrolled in the ARIC study. We identified 4 significant loci: WDR72, HLA-B, GAP43/RP11-326J18.1, and AL713866.1. At WDR72 the most strongly associated SNPs were rs12906891 (MAF = 0.071; p = 9.68 × 10-10; OR = 1.46, 95% CI [1.30,1.64]) and rs11070992 (MAF = 0.14; p = 4.23 × 10-8; OR = 1.28, 95%CI [1.17-1.40]). rs11070992 replicated in African Americans (p = 0.04). Variants in this gene have been associated with diabetic retinopathy, glycemic control, revascularization, and kidney disease.

Unraveling the role of genetics in the pathogenesis of diabetic retinopathy

Diabetic retinopathy (DR) is a microvascular disease of the retina and the leading cause of visual disability in diabetic patients. Genetic factors have shown to play a pivotal role in DR onset, and several candidate genes have been associated with its progression. A literature search was performed to identify the genes known to be associated with DR through linkage analysis, candidate gene association, and genome-wide association studies (GWAS). A further literature search was performed to discover their potential connection with various biological pathways. A total of 65 genes were found and several of these genes belong to major signaling pathways known to play a significant role in DR, including systemic inflammation, angiogenesis, and neurogenesis. A comprehensive analysis presented in this review will be helpful in unraveling the role of genetics in the pathogenesis of DR.

Multiethnic Genome-Wide Association Study of Diabetic Retinopathy Using Liability Threshold Modeling of Duration of Diabetes and Glycemic Control

To identify genetic variants associated with diabetic retinopathy (DR), we performed a large multiethnic genome-wide association study. Discovery included eight European cohorts (n = 3,246) and seven African American cohorts (n = 2,611). We meta-analyzed across cohorts using inverse-variance weighting, with and without liability threshold modeling of glycemic control and duration of diabetes. Variants with a P value <1 × 10-5 were investigated in replication cohorts that included 18,545 European, 16,453 Asian, and 2,710 Hispanic subjects. After correction for multiple testing, the C allele of rs142293996 in an intron of nuclear VCP-like (NVL) was associated with DR in European discovery cohorts (P = 2.1 × 10-9), but did not reach genome-wide significance after meta-analysis with replication cohorts. We applied the Disease Association Protein-Protein Link Evaluator (DAPPLE) to our discovery results to test for evidence of risk being spread across underlying molecular pathways. One protein-protein interaction network built from genes in regions associated with proliferative DR was found to have significant connectivity (P = 0.0009) and corroborated with gene set enrichment analyses. These findings suggest that genetic variation in NVL, as well as variation within a protein-protein interaction network that includes genes implicated in inflammation, may influence risk for DR.

A genome-wide association study suggests new evidence for an association of the NADPH Oxidase 4 (NOX4) gene with severe diabetic retinopathy in type 2 diabetes

Purpose

Diabetic retinopathy is the most common eye complication in patients with diabetes. The purpose of this study is to identify genetic factors contributing to severe diabetic retinopathy.

Methods

A genome‐wide association approach was applied. In the Genetics of Diabetes Audit and Research in Tayside Scotland (GoDARTS) datasets, cases of severe diabetic retinopathy were defined as type 2 diabetic patients who were ever graded as having severe background retinopathy (Level R3) or proliferative retinopathy (Level R4) in at least one eye according to the Scottish Diabetic Retinopathy Grading Scheme or who were once treated by laser photocoagulation. Controls were diabetic individuals whose longitudinal retinopathy screening records were either normal (Level R0) or only with mild background retinopathy (Level R1) in both eyes. Significant Single Nucleotide Polymorphisms (SNPs) were taken forward for meta‐analysis using multiple Caucasian cohorts.

Results

Five hundred and sixty cases of type 2 diabetes with severe diabetic retinopathy and 4,106 controls were identified in the GoDARTS cohort. We revealed that rs3913535 in the NADPH Oxidase 4 (NOX4) gene reached a p value of 4.05 × 10⁻⁹. Two nearby SNPs, rs10765219 and rs11018670 also showed promising p values (p values = 7.41 × 10⁻⁸ and 1.23 × 10⁻⁸, respectively). In the meta‐analysis using multiple Caucasian cohorts (excluding GoDARTS), rs10765219 and rs11018670 showed associations for diabetic retinopathy (p = 0.003 and 0.007, respectively), while the p value of rs3913535 was not significant (p = 0.429).

Conclusion

This genome‐wide association study of severe diabetic retinopathy suggests new evidence for the involvement of the NOX4 gene.

Genome-wide association studies for diabetic macular edema and proliferative diabetic retinopathy

Background

Diabetic macular edema (DME) and proliferative diabetic retinopathy (PDR) are sight-threatening complications of diabetes mellitus and leading causes of adult-onset blindness worldwide. Genetic risk factors for diabetic retinopathy (DR) have been described previously, but have been difficult to replicate between studies, which have often used composite phenotypes and been conducted in different populations. This study aims to identify genetic risk factors for DME and PDR as separate complications in Australians of European descent with type 2 diabetes.

Methods

Caucasian Australians with type 2 diabetes were evaluated in a genome-wide association study (GWAS) to compare 270 DME cases and 176 PDR cases with 435 non-retinopathy controls. All participants were genotyped by SNP array and after data cleaning, cases were compared to controls using logistic regression adjusting for relevant covariates.

Results

The top ranked SNP for DME was rs1990145 (p = 4.10 × 10^− 6, OR = 2.02 95%CI [1.50, 2.72]) on chromosome 2. The top-ranked SNP for PDR was rs918519 (p = 3.87 × 10^− 6, OR = 0.35 95%CI [0.22, 0.54]) on chromosome 5. A trend towards association was also detected at two SNPs reported in the only other reported GWAS of DR in Caucasians; rs12267418 near MALRD1 (p = 0.008) in the DME cohort and rs16999051 in the diabetes gene PCSK2 (p = 0.007) in the PDR cohort.

Conclusion

This study has identified loci of interest for DME and PDR, two common ocular complications of diabetes. These findings require replication in other Caucasian cohorts with type 2 diabetes and larger cohorts will be required to identify genetic loci with statistical confidence. There is considerable overlap in the patient cohorts with each retinopathy subtype, complicating the search for genes that contribute to PDR and DME biology.

Electronic supplementary material

The online version of this article (10.1186/s12881-018-0587-8) contains supplementary material, which is available to authorized users.

Genetic basis of diabetic kidney disease and other diabetic complications

Diabetic kidney disease and other long-term complications are common in diabetes, and comprise the main cause of co-morbidity and premature mortality in individuals with diabetes. While familial clustering and heritability have been reported for all diabetic complications, the genetic background and the molecular mechanisms remain poorly understood. In recent years, genome-wide association studies have identified a few susceptibility loci for the renal complications as well as for diabetic retinopathy, diabetic cardiovascular disease and mortality. As for many complex diseases, the genetic factors increase the risk of complications in concert with the environment, and certain associations seem specific for particular conditions, for example, SP3-CDCA7 associated with end-stage renal disease only in women, or MGMT and variants on chromosome 5q13 associated with cardiovascular mortality only under tight glycaemic control. The characterization of the phenotypes is one of the main challenges for genetic research on diabetic complications, in addition to an urgent need to increase the number of individuals with diabetes with high quality phenotypic data to be included in future genetic studies.

Nutrient Sensing, Signaling and Ageing: The Role of IGF-1 and mTOR in Ageing and Age-Related Disease

Nutrient signaling through insulin/IGF-1 was the first pathway demonstrated to regulate ageing and age-related disease in model organisms. Pharmacological or dietary interventions targeting nutrient signaling pathways have been shown to robustly attenuate ageing in many organisms. Caloric restriction, the most widely studied longevity promoting intervention, works through multiple nutrient signaling pathways, while inhibition of mTOR through treatment with rapamycin reproducibly delays ageing and disease through specific inhibition of the mTOR complexes. Although the benefits of reduced insulin/IGF-1 in lifespan and health are well documented in model organisms, defining the precise role of the IGF-1 in human ageing and age-related disease has proven more difficult. Association studies provide some insight but also reveal paradoxes. Low serum IGF-1 predicts longevity, but IGF-1 decreases with age and IGF-1 therapy benefits some of age-related pathologies. Circulating IGF-1 has been associated both positively and negatively with risk of age-related diseases in humans, and in some cases both activation and inhibition of IGF-1 signaling have provided benefit in animal models of the same diseases. Interventions designed modulate the nutrient sensing signaling pathways positively or negatively are already available for clinical use, highlighting the need for a clear understanding of the role of nutrient signaling in ageing and age-related disease. This chapter examines data from model organisms and human genetic association studies, with a special emphasis on IGF-1 and mTOR, and discusses potential models for resolving the paradoxes surrounding IGF-1 data.

Characterization of Large Copy Number Variation in Mexican Type 2 Diabetes subjects

The effect of Copy Number Variants (CNVs) on Type 2 Diabetes (T2D) remains little explored. The present study characterized large rare CNVs in 686 T2D and 194 non-T2D subjects of Mexican ancestry genotyped using the Affymetrix Genome-Wide Human SNP array 5.0. Rare CNVs with ≥ 100 kb length were identified using a stringent strategy based on merging CNVs calls generated using Birdsuit, iPattern and PennCNV algorithms. We applied three different strategies to evaluate the distribution of CNVs in the T2D and non-T2D samples: 1) Burden analysis, 2) Identification of CNVs in loci previously associated to T2D, and 3) Identification of CNVs observed only in the T2D group. In the CNV burden analysis, the T2D group showed a higher proportion of CNVs, and also a higher proportion of CNVs overlapping at least one gene than the non T2D group. Five of the six loci previously associated with T2D had duplications or deletions in the T2D sample, but not the non-T2D sample. A gene-set analysis including genes with CNVs observed only in the T2D group highlighted gene-sets related with sensory perception (olfactory receptors, OR) and phenylpyruvate tautomerase/dopachrome isomerase activity (MIF and DDT genes).

Progress in Defining the Genetic Basis of Diabetic Complications

PURPOSE OF REVIEW

Diabetic complications affecting the kidneys, retina, nerves, and the cardiovasculature are the major causes of morbidity and mortality in diabetes. This paper aims to review the current understanding of the genetic basis of these complications, based on recent findings especially from genome-wide association studies.

RECENT FINDINGS

Variants in or near AFF3, RGMA-MCTP2, SP3-CDCA7, GLRA3, CNKSR3, and UMOD have reached genome-wide significance (p value <5 × 10^-8) for association with diabetic kidney disease, and recently, GRB2 was reported to be associated at genome-wide significance with diabetic retinopathy. While some loci affecting cardiovascular disease in the general population have been replicated in diabetes, GLUL affects the risk of cardiovascular disease specifically in diabetic subjects. Genetic findings are emerging for diabetic complications, although the studies remain relatively small compared to those for type 1 and type 2 diabetes. In addition to pinpointing specific loci, the studies also reveal biological information on correlated traits and pathways.