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

Abstract

Background: Diabetes is the leading cause of kidney disease, and heritability studies demonstrate a substantial, yet poorly understood, contribution of genetics to kidney complications in people with diabetes. Methods: We performed genome-wide association study (GWAS) meta-analyses using ten different phenotypic definitions of diabetic kidney disease (DKD), including nearly 27,000 individuals with diabetes, and integrated the results with various kidney omics datasets. Results: The meta-analysis identified a novel low frequency intronic variant (rs72831309) in the TENM2 gene encoding teneurin transmembrane protein 2 associated with a lower risk of the combined chronic kidney disease (CKD; eGFR<60 ml/min/1.73 m2) and DKD (microalbuminuria or worse) phenotype ("CKD-DKD", odds ratio 2.08, p=9.8×10-9). 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 data with human glomerular and tubular expression data in a transcriptome-wide association study demonstrated higher tubular AKIRIN2 gene expression in DKD versus non-DKD controls (p=1.1×10-6). The lead SNPs within the DCLK1, AKIRIN2, SNX30 and three other gene regions significantly alterated the methylation at this region in kidneys (p<2.2×10-11). Expression of target genes in kidney tubules or glomeruli correlated with relevant pathological phenotypes. For example, tubular TENM2 expression positively correlated with eGFR (p=2.3×10-9) and negatively with tubulointerstitial fibrosis (p=4.7×10-9), tubular DCLK1 expression positively correlated with fibrosis (p=1.6×10-12), and SNX30 level positively correlated with eGFR (p=7.6×10-13) and negatively with fibrosis (p<2×10-16). Conclusions: GWAS meta-analysis and integration with renal omics data points to novel genes contributing to pathogenesis of DKD.

The Microbiome, Epigenome, and Diet in Adults with Obesity during Behavioral Weight Loss

“…Expression of COL18A1 has been associated with human adipocyte differentiation and susceptibility to obesity, and preclinical work demonstrates that knockout of COL18A1 is associated with a reduction in adiposity in murine models [38,39]. A genome-wide meta-analysis linked the COL20A1 gene to diabetic kidney disease [40]. The expression of NT5E has also been associated with the consumption of a high fat diet in preclinical models and, thus, may be associated with obesity [41].…”

Identification of Multiple Hub Genes in Acute Kidney Injury after Kidney Transplantation by Bioinformatics Analysis

“…It plays a major role in adaptive and autoimmunity in the pathogenesis of nephrotic syndrome [ 20 ]. TENM2, which enables signaling receptor binding activity and cell adhesion molecule binding activity, is involved with renal fibrosis and the development of diabetic kidney disease [ 21 ]. TLR2, which plays a fundamental role in pathogen recognition and innate immunity activation, is essential to the pro-inflammatory and detrimental role in the kidney after ischemic reperfusion injury [ 22 ].…”

Diabetes and Renal Complications: An Overview on Pathophysiology, Biomarkers and Therapeutic Interventions

“…To date, over 2500 genes and 650 proteins have been linked to DKD. Notably, collagen gene COL and its fragments have consistently emerged as significant in multiple studies [145][146][147]. Recent GWAS studies revealed that approximately half of these 2519 genes were upregulated and the other half downregulated in DKD [146].…”

“…Notably, collagen gene COL and its fragments have consistently emerged as significant in multiple studies [145][146][147]. Recent GWAS studies revealed that approximately half of these 2519 genes were upregulated and the other half downregulated in DKD [146]. At the protein level, out of 678 identified proteins, 279 were upregulated while the remainder were downregulated in DKD [146].…”

“…Recent GWAS studies revealed that approximately half of these 2519 genes were upregulated and the other half downregulated in DKD [146]. At the protein level, out of 678 identified proteins, 279 were upregulated while the remainder were downregulated in DKD [146]. The integration of omics approaches shows promise in identifying new therapeutic targets and biomarkers for DKD.…”