Published in

American Diabetes Association, Diabetes, 2(68), p. 441-456, 2018

DOI: 10.2337/db18-0567

Links

Tools

Export citation

Search in Google Scholar

Multiethnic genome-wide association study of diabetic retinopathy using liability threshold modeling of duration of diabetes and glycemic control

Journal article published in 2019 by Chen Yi, Albert V. Smith, Ayellet V. Segrè, Gavin S. Tan, Lynn K. Stanwyck, I. Te Lee, Kaanan Shah, Kent D. Taylor, John R. Sedor, Wayne H.-H. Sheu, Atsushi Takahashi, David-Alexandre Tregouet, Rohit Varma, Iiro Toppila, Niina Sandholm and other authors.
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

Full text: Download

Green circle
Preprint: archiving allowed
Green circle
Postprint: archiving allowed
Red circle
Published version: archiving forbidden
Data provided by SHERPA/RoMEO

Abstract

To identify genetic variants associated with diabetic retinopathy (DR), we performed a large multiethnic genome-wide association study. Discovery included eight European cohorts (n = 3,246) and seven African American cohorts (n = 2,611). We meta-analyzed across cohorts using inverse-variance weighting, with and without liability threshold modeling of glycemic control and duration of diabetes. Variants with a P value <1 × 10−5 were investigated in replication cohorts that included 18,545 European, 16,453 Asian, and 2,710 Hispanic subjects. After correction for multiple testing, the C allele of rs142293996 in an intron of nuclear VCP-like (NVL) was associated with DR in European discovery cohorts (P = 2.1 × 10−9), but did not reach genome-wide significance after meta-analysis with replication cohorts. We applied the Disease Association Protein-Protein Link Evaluator (DAPPLE) to our discovery results to test for evidence of risk being spread across underlying molecular pathways. One protein–protein interaction network built from genes in regions associated with proliferative DR was found to have significant connectivity (P = 0.0009) and corroborated with gene set enrichment analyses. These findings suggest that genetic variation in NVL, as well as variation within a protein–protein interaction network that includes genes implicated in inflammation, may influence risk for DR.