Genome-wide meta-analysis and omics integration identifies novel genes associated with diabetic kidney disease.

Content Provider	Europe PMC
Author	Sandholm, Niina Cole, Joanne B. Nair, Viji Sheng, Xin Liu, Hongbo Ahlqvist, Emma van Zuydam, Natalie Dahlström, Emma H. Fermin, Damian Smyth, Laura J. Salem, Rany M. Forsblom, Carol Valo, Erkka Harjutsalo, Valma Brennan, Eoin P. McKay, Gareth J. Andrews, Darrell Doyle, Ross Looker, Helen C. Nelson, Robert G. Palmer, Colin McKnight, Amy Jayne Godson, Catherine Maxwell, Alexander P. Groop, Leif McCarthy, Mark I. Kretzler, Matthias Susztak, Katalin Hirschhorn, Joel N. Florez, Jose C. Groop, Per-Henrik
Abstract	Aims/hypothesisDiabetic kidney disease (DKD) is the leading cause of kidney failure and has a substantial genetic component. Our aim was to identify novel genetic factors and genes contributing to DKD by performing meta-analysis of previous genome-wide association studies (GWAS) on DKD and by integrating the results with renal transcriptomics datasets.MethodsWe performed GWAS meta-analyses using ten phenotypic definitions of DKD, including nearly 27,000 individuals with diabetes. Meta-analysis results were integrated with estimated quantitative trait locus data from human glomerular (N=119) and tubular (N=121) samples to perform transcriptome-wide association study. We also performed gene aggregate tests to jointly test all available common genetic markers within a gene, and combined the results with various kidney omics datasets.ResultsThe meta-analysis identified a novel intronic variant (rs72831309) in the TENM2 gene associated with a lower risk of the combined chronic kidney disease (eGFR<60 ml/min per 1.73 m2) and DKD (microalbuminuria or worse) phenotype (p=9.8×10−9; although not withstanding correction for multiple testing, p>9.3×10−9). Gene-level analysis identified ten genes associated with DKD (COL20A1, DCLK1, EIF4E, PTPRN–RESP18, GPR158, INIP–SNX30, LSM14A and MFF; p<2.7×10−6). Integration of GWAS with human glomerular and tubular expression data demonstrated higher tubular AKIRIN2 gene expression in individuals with vs without DKD (p=1.1×10−6). The lead SNPs within six loci significantly altered DNA methylation of a nearby CpG site in kidneys (p<1.5×10−11). Expression of lead genes in kidney tubules or glomeruli correlated with relevant pathological phenotypes (e.g. TENM2 expression correlated positively with eGFR [p=1.6×10−8] and negatively with tubulointerstitial fibrosis [p=2.0×10−9], tubular DCLK1 expression correlated positively with fibrosis [p=7.4×10−16], and SNX30 expression correlated positively with eGFR [p=5.8×10−14] and negatively with fibrosis [p<2.0×10−16]).Conclusions/interpretationAltogether, the results point to novel genes contributing to the pathogenesis of DKD.Data availabilityThe GWAS meta-analysis results can be accessed via the type 1 and type 2 diabetes (T1D and T2D, respectively) and Common Metabolic Diseases (CMD) Knowledge Portals, and downloaded on their respective download pages (https://t1d.hugeamp.org/downloads.html; https://t2d.hugeamp.org/downloads.html; https://hugeamp.org/downloads.html).Graphical abstractSupplementary InformationThe online version contains peer-reviewed but unedited supplementary material available at 10.1007/s00125-022-05735-0.
ISSN	0012186X
Journal	Diabetologia
Volume Number	65
PubMed Central reference number	PMC9345823
Issue Number	9
PubMed reference number	35763030
e-ISSN	14320428
DOI	10.1007/s00125-022-05735-0
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2022-06-28
Publisher Place	Berlin/Heidelberg
Access Restriction	Open
Rights License	Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. © The Author(s) 2022
Subject Keyword	Diabetes complications Diabetic kidney disease Genetics Genome-wide association study; Meta-analysis; Transcriptomics
Content Type	Text
Resource Type	Article
Subject	Endocrinology, Diabetes and Metabolism Internal Medicine