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Am J Ophthalmol. 2019 May 20. pii: S0002-9394(19)30245-4. doi: 10.1016/j.ajo.2019.05.015. [Epub ahead of print]

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

Author information

1
Department of Computational Biology - USR 3756 CNRS), Institut Pasteur, Paris, France.
2
Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
3
Department of Ophthalmology, Massachusetts Eye and Ear Infirmary, Harvard Medical School, Boston, MA, USA.
4
Departments of Ophthalmology and Clinical Genetics, Erasmus Medical Center, Rotterdam, The Netherlands.
5
MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh.
6
Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, USA; Institute for Computational Biology, Case Western Reserve University School of Medicine, Cleveland, OH, USA.
7
Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, USA.
8
Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, USA.
9
Department of Epidemiology, Harvard T. H. Chan School of Public Health, Harvard Medical School, Boston, MA, USA; Department of Biostatistics, Harvard T. H. Chan School of Public Health, Harvard Medical School, Boston, MA, USA.
10
Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Department of Biostatistics, Harvard T. H. Chan School of Public Health, Harvard Medical School, Boston, MA, USA.
11
Department of Epidemiology, Harvard T. H. Chan School of Public Health, Harvard Medical School, Boston, MA, USA; Department of Nutrition, Harvard T. H. Chan School of Public Health, Harvard Medical School, Boston, MA, USA.
12
MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh; Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK.
13
Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia.154, Centre for Eye Research Australia.
14
Centre for Eye Research Australia, University of Melbourne, Royal Victorian Eye and Ear Hospital, East Melbourne, Australia; School of Medicine, Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia.
15
Lions Eye Institute, Centre for Ophthalmology and Visual Science, University of Western Australia, Perth, Western Australia, Australia.
16
Department of Twin Research and Genetic Epidemiology, King's College London, UK.
17
Departments of Ophthalmology and Clinical Genetics, Erasmus Medical Center, Rotterdam, The Netherlands; Nuffield Department of Population Health, University of Oxford, Oxford, UK.
18
Department of Ophthalmology and Visual Science, University of Iowa, Iowa City, Iowa, USA.
19
Departments of Ophthalmology and Medicine, Duke University, Durham, NC, USA.
20
Department of Computational Biology - USR 3756 CNRS), Institut Pasteur, Paris, France; Department of Epidemiology, Harvard T. H. Chan School of Public Health, Harvard Medical School, Boston, MA, USA.
21
Department of Public Health and Primary Care, Institute of Public Health, University of Cambridge School of Clinical Medicine, Cambridge, UK.
22
Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Icahn School of Medicine at Mount Sinai, Department of Ophthalmology, New York, NY, USA. Electronic address: Louis.Pasquale@mssm.edu.

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.

PMID:
31121135
DOI:
10.1016/j.ajo.2019.05.015

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