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Background polygenic risk modulates the association between glaucoma and cardiopulmonary diseases and measures: an analysis from the UK Biobank
  1. Ajay Kolli1,2,
  2. Sayuri Sekimitsu3,
  3. Jiali Wang4,
  4. Ayellet Segre4,5,6,
  5. David Friedman4,
  6. Tobias Elze5,
  7. Louis R Pasquale7,
  8. Janey Wiggs4,6,
  9. Nazlee Zebardast4
  1. 1Ophthalmology and Visual Science, University of Michigan, Ann Arbor, Michigan, USA
  2. 2Harvard University T H Chan School of Public Health, Boston, Massachusetts, USA
  3. 3Tufts University School of Medicine, Boston, Massachusetts, USA
  4. 4Department of Ophthalmology, Harvard Medical School, Boston, Massachusetts, USA
  5. 5Schepens Eye Research Institute, Harvard Medical School, Boston, Massachusetts, USA
  6. 6Ocular Genomics Institute, Harvard Medical School, Boston, Massachusetts, USA
  7. 7Department of Ophthalmology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
  1. Correspondence to Professor Nazlee Zebardast, Department of Ophthalmology, Harvard Medical School, Boston, USA; nazlee_Zebardast{at}meei.harvard.edu

Abstract

Aims To assess whether associations of cardiopulmonary conditions and markers with glaucoma differ by background genetic risk for primary open angle glaucoma (POAG).

Methods We constructed a POAG polygenic risk score (PRS) using genome-wide association study summary statistics from a large cross-ancestry meta-analysis. History of glaucoma (including self-report and codes for POAG, ‘other glaucoma’ or unspecified glaucoma), history of common cardiopulmonary conditions and cardiopulmonary measures were assessed in the UK Biobank. Stratifying by PRS decile 1 (lowest risk) versus decile 10 (highest risk), separate multivariable models were estimated to assess the associations of cardiopulmonary diseases or factors with glaucoma, adjusting for age, sex, smoking and medication use. A Bonferroni correction was used to adjust p values for multiple comparisons.

Results Individuals in POAG PRS decile 1 (417 cases, 44 458 controls; mean age 56.8 years) and decile 10 (2135 cases, 42 413 controls; mean age 56.7 years) were included. Within decile 1, glaucoma cases had significantly higher glycated haemoglobin (38.5 vs 35.9 mmol/mol) and higher prevalence of diabetes (17.5% vs 6.5%), dyslipidaemia (31.2% vs 18.3%) and chronic kidney disease (CKD) (6.7% vs 2.0%) than controls (adjusted p<0.0013 for each). Within decile 10, glaucoma was associated with higher prevalence of dyslipidaemia (27.7% vs 17.3%, p=6.9E-05). The magnitude of association between glaucoma and diabetes, CKD and glycated haemoglobin differed between deciles 1 and 10 (contrast test p value for difference <0.05).

Conclusion The relations between systemic conditions and glaucoma vary by underlying genetic predisposition to POAG, with larger associations among those who developed glaucoma despite low genetic risk.

  • Glaucoma
  • Genetics
  • Epidemiology

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Data may be obtained from a third party and are not publicly available.

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Data availability statement

Data may be obtained from a third party and are not publicly available.

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Footnotes

  • JW and NZ are joint senior authors.

  • Twitter @OphthalmolAjay

  • JW and NZ contributed equally.

  • Presented at Presented by Ajay Kolli at the 9th World Glaucoma E-Congress, June 2021.

  • Contributors AK contributed to the design, analysis, interpretation and drafting of the work. SS and JWa contributed to the design, analysis and critical revision of the work. AS, DF, TE and LRP contributed to the design, interpretation and critical revision of the work. JWi and NZ contributed to the conception, acquisition, interpretation and critical revision of the work. All authors gave final approval of the work, are accountable for the parts of the work they contributed to and have confidence in the integrity of the contributions of their coauthors. NZ is responsible for the overall content as the guarantor.

  • Funding This work was supported by MEE Institutional Startup Fund and NIH K23 Career Development Award (K23EY032634) (NZ), NIH R01 EY032559 (JWi, LRP) and NIH R01 EY015473 (LRP). LRP is also supported by an unrestricted Challenge Grant from Research to Prevent Blindness (NYC) and The Glaucoma Foundation (LRP).

  • Disclaimer The funding organisation had no role in the design or conduct of this research.

  • Competing interests LRP is a consultant to Twenty Twenty, Skye Bioscience and Eyenovia. These consultancies do not relate to the topic of this manuscript. No conflicting relationship exists for the other authors.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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