Dataset Information

Genetic Correlations Between Diabetes and Glaucoma: An Analysis of Continuous and Dichotomous Phenotypes.

ABSTRACT: PURPOSE:A genetic correlation is the proportion of phenotypic variance between traits that is shared on a genetic basis. Here we explore genetic correlations between diabetes- and glaucoma-related traits. DESIGN:Cross-sectional study. METHODS:We assembled genome-wide association study summary statistics from European-derived participants regarding diabetes-related traits like fasting blood sugar (FBS) and type 2 diabetes (T2D) and glaucoma-related traits (intraocular pressure [IOP], central corneal thickness [CCT], corneal hysteresis [CH], corneal resistance factor [CRF], cup-to-disc ratio [CDR], and primary open-angle glaucoma [POAG]). We included data from the National Eye Institute Glaucoma Human Genetics Collaboration Heritable Overall Operational Database, the UK Biobank, and the International Glaucoma Genetics Consortium. We calculated genetic correlation (rg) between traits using linkage disequilibrium score regression. We also calculated genetic correlations between IOP, CCT, and select diabetes-related traits based on individual level phenotype data in 2 Northern European population-based samples using pedigree information and Sequential Oligogenic Linkage Analysis Routines. RESULTS:Overall, there was little rg between diabetes- and glaucoma-related traits. Specifically, we found a nonsignificant negative correlation between T2D and POAG (rg = -0.14; P = .16). Using Sequential Oligogenic Linkage Analysis Routines, the genetic correlations between measured IOP, CCT, FBS, fasting insulin, and hemoglobin A1c were null. In contrast, genetic correlations between IOP and POAG (rg ? 0.45; P ? 3.0 × 10-4) and between CDR and POAG were high (rg = 0.57; P = 2.8 × 10-10). However, genetic correlations between corneal properties (CCT, CRF, and CH) and POAG were low (rg range -0.18 to 0.11) and nonsignificant (P ? .07). CONCLUSION:These analyses suggest that there is limited genetic correlation between diabetes- and glaucoma-related traits.

SUBMITTER: Laville V

PROVIDER: S-EPMC6864262 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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Genetic Correlations Between Diabetes and Glaucoma: An Analysis of Continuous and Dichotomous Phenotypes.

Laville Vincent V Kang Jae H JH Cousins Clara C CC Iglesias Adriana I AI Nagy Réka R Cooke Bailey Jessica N JN Igo Robert P RP Song Yeunjoo E YE Chasman Daniel I DI Christen William G WG Kraft Peter P Rosner Bernard A BA Hu Frank F Wilson James F JF Gharahkhani Puya P Hewitt Alex W AW Mackey David A DA Hysi Pirro G PG Hammond Christopher J CJ vanDuijn Cornelia M CM Haines Jonathan L JL Vitart Veronique V Fingert John H JH Hauser Michael A MA Aschard Hugues H Wiggs Janey L JL Khawaja Anthony P AP MacGregor Stuart S Pasquale Louis R LR

American journal of ophthalmology 20190520

<h4>Purpose</h4>A genetic correlation is the proportion of phenotypic variance between traits that is shared on a genetic basis. Here we explore genetic correlations between diabetes- and glaucoma-related traits.<h4>Design</h4>Cross-sectional study.<h4>Methods</h4>We assembled genome-wide association study summary statistics from European-derived participants regarding diabetes-related traits like fasting blood sugar (FBS) and type 2 diabetes (T2D) and glaucoma-related traits (intraocular pressu ...[more]

PMID: 31121135

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Project description:ImportanceMechanisms behind pigmentary glaucoma, a form of early-onset glaucoma that may potentially lead to severe visual impairment or blindness, are poorly understood.ObjectiveTo calculate the single-nucleotide polymorphism (SNP) heritability of pigmentary glaucoma and identify genetic associations with the disease.Design, setting and participantsThis genome-wide association study included affected individuals from Germany and control participants from the United Kingdom. Genome-wide information was obtained for patients with pigmentary glaucoma and control participants free of glaucoma by using the Illumina Human Omni Express Exome 8v1-2 chip and genomic imputation. The SNP heritability of pigmentary glaucoma was estimated through a restricted maximum likelihood analysis. Associations between the genetic variants and pigmentary glaucoma obtained from age, sex, and principal component-adjusted logistic regression models were compared with those of SNPs previously associated with other eye phenotypes using Pearson product-moment correlations. Data were collected from November 2008 to January 2018, and analysis was completed between April 2018 and August 2019.Main outcomes and measuresAn estimate of SNP-explained heritability for pigmentary glaucoma; correlations of effect sizes between pigmentary glaucoma and iris pigmentation and myopia; and correlations of effect sizes between pigmentary glaucoma and other eye phenotypes.ResultsA total of 227 affected individuals (mean [SD] age, 58.7 [13.3] years) and 291 control participants (mean [SD] age, 80.2 [4.9] years) were included; all were of European ancestry. The SNP heritability of pigmentary glaucoma was 0.45 (SE, 0.22; P = 6.15 × 10-10). Twelve SNPs previously reported with genome-wide significant associations with eye pigmentation were associated with pigmentary glaucoma's SNP heritability (4.9% SNP heritability; 0.022; P = 6.0 × 10-4). Pigmentary glaucoma SNP effect sizes were correlated moderately for myopia (r, 0.42 [95% CI, 0.14-0.63]; P = 4.3 × 10-3) and more strongly with those for iris pigmentation (r = -0.69 [95% CI, -0.91 to -0.20]; P = .01), although this was nonsignificant per a strict adjusted significance threshold (P < .01).Conclusions and relevanceThese findings support the conclusion that pigmentary glaucoma may have a genetic basis and be highly heritable. Variants associated with lighter eye color and myopia appear to be associated with increased risk of pigmentary glaucoma, but no shared genetic basis with primary open-angle glaucoma (or its quantitative endophenotype of cup-disc ratio) was observed.

Project description:Clinical studies have indicated a comorbidity between sepsis and kidney diseases. Individuals with specific mutations that predispose them to kidney conditions are also at an elevated risk for developing sepsis, and vice versa. This suggests a potential shared genetic etiology that has not been fully elucidated. Summary statistics data on exposure and outcomes were obtained from genome-wide association meta-analysis studies. We utilized these data to assess genetic correlations, employing a pleiotropy analysis method under the composite null hypothesis to identify pleiotropic loci. After mapping the loci to their corresponding genes, we conducted pathway analysis using Generalized Gene-Set Analysis of GWAS Data (MAGMA). Additionally, we utilized MAGMA gene-test and eQTL information (whole blood tissue) for further determination of gene involvement. Further investigation involved stratified LD score regression, using diverse immune cell data, to study the enrichment of SNP heritability in kidney-related diseases and sepsis. Furthermore, we employed Mendelian Randomization (MR) analysis to investigate the causality between kidney diseases and sepsis. In our genetic correlation analysis, we identified significant correlations among BUN, creatinine, UACR, serum urate, kidney stones, and sepsis. The PLACO analysis method identified 24 pleiotropic loci, pinpointing a total of 28 nearby genes. MAGMA gene-set enrichment analysis revealed a total of 50 pathways, and tissue-specific analysis indicated significant enrichment of five pairs of pleiotropic results in kidney tissue. MAGMA gene test and eQTL information (whole blood tissue) identified 33 and 76 pleiotropic genes, respectively. Notably, genes PPP2R3A for BUN, VAMP8 for UACR, DOCK7 for creatinine, and HIBADH for kidney stones were identified as shared risk genes by all three methods. In a series of immune cell-type-specific enrichment analyses of pleiotropy, we identified a total of 37 immune cells. However, MR analysis did not reveal any causal relationships among them. This study lays the groundwork for shared etiological factors between kidney and sepsis. The confirmed pleiotropic loci, shared pathogenic genes, and enriched pathways and immune cells have enhanced our understanding of the multifaceted relationships among these diseases. This provides insights for early disease intervention and effective treatment, paving the way for further research in this field.

Dataset Information

Genetic Correlations Between Diabetes and Glaucoma: An Analysis of Continuous and Dichotomous Phenotypes.

Publications

Genetic Correlations Between Diabetes and Glaucoma: An Analysis of Continuous and Dichotomous Phenotypes.

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