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Sobrin L, Susarla G, Stanwyck L, et al. Gene Set Enrichment Analsyes Identify Pathways Involved in Genetic Risk for Diabetic Retinopathy. Am J Ophthalmol. 2021;233:111-123doi: 10.1016/j.ajo.2021.06.014.
Sobrin, L., Susarla, G., Stanwyck, L., Rouhana, J. M., Li, A., Pollack, S., Igo, R. P., Jensen, R. A., Li, X., Ng, M. C. Y., Smith, A. V., Kuo, J. Z., Taylor, K. D., Freedman, B. I., Bowden, D. W., Penman, A., Chen, C. J., Craig, J. E., Adler, S. G., Chew, E. Y., Cotch, M. F., Yaspan, B., Mitchell, P., Wang, J. J., Klein, B. E. K., Wong, T. Y., Rotter, J. I., Burdon, K. P., Iyengar, S. K., & Segrè, A. V. (2022). Gene Set Enrichment Analsyes Identify Pathways Involved in Genetic Risk for Diabetic Retinopathy. American journal of ophthalmology, 233111-123. https://doi.org/10.1016/j.ajo.2021.06.014
Sobrin, Lucia, et al. "Gene Set Enrichment Analsyes Identify Pathways Involved in Genetic Risk for Diabetic Retinopathy." American journal of ophthalmology vol. 233 (2022): 111-123. doi: https://doi.org/10.1016/j.ajo.2021.06.014
Sobrin L, Susarla G, Stanwyck L, Rouhana JM, Li A, Pollack S, Igo RP, Jensen RA, Li X, Ng MCY, Smith AV, Kuo JZ, Taylor KD, Freedman BI, Bowden DW, Penman A, Chen CJ, Craig JE, Adler SG, Chew EY, Cotch MF, Yaspan B, Mitchell P, Wang JJ, Klein BEK, Wong TY, Rotter JI, Burdon KP, Iyengar SK, Segrè AV. Gene Set Enrichment Analsyes Identify Pathways Involved in Genetic Risk for Diabetic Retinopathy. Am J Ophthalmol. 2022 Jan;233:111-123. doi: 10.1016/j.ajo.2021.06.014. Epub 2021 Jun 21. PMID: 34166655; PMCID: PMC8678352.
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Am J Ophthalmol. 2022 Jan;233:111-123. doi: 10.1016/j.ajo.2021.06.014. Epub 2021 Jun 21.

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

American journal of ophthalmology

Lucia Sobrin, Gayatri Susarla, Lynn Stanwyck, John M Rouhana, Ashley Li, Samuela Pollack, Robert P Igo, Richard A Jensen, Xiaohui Li, Maggie C Y Ng, Albert V Smith, Jane Z Kuo, Kent D Taylor, Barry I Freedman, Donald W Bowden, Alan Penman, Ching J Chen, Jamie E Craig, Sharon G Adler, Emily Y Chew, Mary Frances Cotch, Brian Yaspan, Paul Mitchell, Jie Jin Wang, Barbara E K Klein, Tien Y Wong, Jerome I Rotter, Kathyrn P Burdon, Sudha K Iyengar, Ayellet V Segrè

Affiliations

  1. From the Department of Ophthalmology, Harvard Medical School, Massachusetts Eye and Ear Infirmary. Electronic address: [email protected].
  2. From the Department of Ophthalmology, Harvard Medical School, Massachusetts Eye and Ear Infirmary.
  3. Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
  4. Department of Population and Quantitative Health Sciences, Case Western University, Cleveland, Ohio.
  5. Cardiovascular Health Research Unit, Department of Medicine, Epidemiology and Health Services, University of Washington, Seattle, Washington.
  6. Institute for Translational Genomics and Population Sciences, Department of Pediatrics, the Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, California.
  7. Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine; Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA; Vanderbilt Genetics Institute and Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
  8. Department of Medicine, University of Iceland, Reykjavík, Iceland.
  9. Medical Affairs, Ophthalmology, Sun Pharmaceutical Industries, Inc, Princeton, New Jersey.
  10. Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine; Department of Internal Medicine, Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, North Carolina.
  11. Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine; Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA.
  12. Department of Preventive Medicine, John D. Bower School of Population Health (A.P.), Department of Ophthalmology.
  13. University of Mississippi Medical Center, Jackson, Mississippi, USA, FHMRI Eye & Vision, Flinders University, Bedford Park, SA, Australia.
  14. Department of Nephrology and Hypertension, Los Angeles Biomedical Research Institute at Harbor-University of California, Torrance, California.
  15. Division of Epidemiology and Clinical Applications, National Eye Institute, National Institutes of Health, Bethesda, Maryland.
  16. Genentech Inc, South San Francisco, California, USA.
  17. Department of Ophthalmology, Centre for Vision Research, Westmead Institute for Medical Research, University of Sydney, Sydney, Australia.
  18. Department of Ophthalmology, Centre for Vision Research, Westmead Institute for Medical Research, University of Sydney, Sydney, Australia; Center of Clinician-Scientist Development, Duke-NUS Medical School, Singapore.
  19. Department of Ophthalmology and Visual Sciences, University of Wisconsin-Madison, Madison, Wisconsin, USA.
  20. Center of Clinician-Scientist Development, Duke-NUS Medical School, Singapore; Singapore Eye Research Institute, Singapore National Eye Centre, Singapore.
  21. Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia.
  22. Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts; Department of Population and Quantitative Health Sciences, Case Western University, Cleveland, Ohio.
  23. From the Department of Ophthalmology, Harvard Medical School, Massachusetts Eye and Ear Infirmary; Broad Institute of Harvard and MIT, Cambridge, Massachusetts.

PMID: 34166655 PMCID: PMC8678352 DOI: 10.1016/j.ajo.2021.06.014

Abstract

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.

Copyright © 2021 Elsevier Inc. All rights reserved.

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