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Genetic correlations between diabetes and glaucoma: an analysis of continuous and dichotomous phenotypes

Research output: Contribution to journalArticle

UK Biobank, International Glaucoma Genetics Consortium, NEIGHBORHOOD Consortium

Original languageEnglish
Pages (from-to)245-255
Number of pages11
JournalAmerican Journal of Ophthalmology
Volume206
Early online date20 May 2019
DOIs
Publication statusPublished - 1 Oct 2019

Bibliographical note

Copyright © 2019 Elsevier Inc. All rights reserved.

King's Authors

  • UK Biobank, International Glaucoma Genetics Consortium, NEIGHBORHOOD Consortium

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-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 selected diabetes-related traits based on individual level phenotype data in two Northern European population-based samples using pedigree information and Sequential Oligogenic Linkage Analysis Routines (SOLAR).

RESULTS: Overall, there was little rg between diabetes- and glaucoma-related traits. Specifically, we found a non-significant negative correlation between T2D and POAG (rg=-0.14; p=0.16). Using SOLAR, 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≤3.0E-04) and between CDR and POAG were high (rg =0.57; p=2.8E-10). However, genetic correlations between corneal properties (CCT, CRF and CH) and POAG were low (rg range: -0.18 - 0.11) and non-significant (p≥0.07).

CONCLUSION: These analyses suggest there is limited genetic correlation between diabetes- and glaucoma-related traits.

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