A functional genomics pipeline for genetic discovery in diabetic kidney disease

Diabetes is responsible for a large proportion of chronic kidney disease (CKD), end-stage kidney disease (ESKD), blindness, amputation, heart disease and stroke. Tight glycemic control in type 1 diabetes (T1D) or type 2 diabetes (T2D) can delay or arrest the progression of microvascular complications. How hyperglycemia leads to complications, and why some patients with long-standing diabetes are relatively spared, remains largely unknown, limiting the ability to target and improve preventive strategies. 

Inherited variation in DNA sequence contributes to individual risk of diabetic complications. Even with comparable glycemic control there is great heterogeneity in the frequency and severity of microvascular diabetic complications. Familial aggregation of diabetic complications confirms the influence of inherited risk factors, but until recently few specific genes or variants were known. 

In the past few years, genome-wide association studies (GWAS) have begun to identify the genetic factors that influence diabetic kidney disease (DKD). In a global collaboration under a novel tripartite funding mechanism, we founded the GEnetics of Nephropathy‚Äďan International Effort (GENIE) consortium, which found several associations with ESKD. Together with the Diabetic Nephropathy Collaborative Research Initiative (DNCRI), we have completed a much larger GWAS meta-analysis of ~20,000 samples with or without DKD in T1D. We identified 16 genome-wide significant loci, including a common missense mutation in the collagen type IV alpha 3 chain (COL4A3) gene, which encodes a key structural component of the glomerular basement membrane (GBM) implicated in heritable nephropathies. 

While these findings are encouraging, additional work is required to realize the hope placed in genetic discoveries in DKD. First, these initial results only capture a small proportion of the heritability of this phenotype, and as commonly observed with most other complex phenotypes they confer modest effects; much larger sample sizes are needed to reach the level of genetic discovery achieved for other metabolic diseases. Second, most of these genetic associations lie in non-coding regions, necessitating an assessment of regulatory mechanisms and a systematic search for the effector transcripts that mediate the genetic associations. In this quest, targeted approaches to identify low-frequency or rare variants directly altering the protein structure are needed. And third, in cases where such effector transcripts are known or highly suspected, functional validation in relevant model systems is required to prove and fully characterize the molecular mechanisms by which these genes affect DKD.

If successful, this proposal will fill current gaps in our collective genomic exploration of DKD, integrate genetic, epigenetic and expression data with other biological knowledge, and synergize ongoing efforts worldwide. Discoveries that ensue from this project will illuminate biological pathways that promote DKD pathogenesis, and will reveal potential biomarkers and targets for prevention or treatment.

Award Date
01 January 2023
Award Value
Principal Investigator
Professor Catherine Godson
Host Institution
University College Dublin
US-Ireland R&D Partnership Awards