Genetic risk converges on regulatory networks mediating early type 2 diabetes.
Document Type
Article
Publication Date
12-1-2023
Original Citation
Walker J,
Saunders D,
Rai V,
Chen H,
Orchard P,
Dai C,
Pettway Y,
Hopkirk A,
Reihsmann C,
Tao Y,
Fan S,
Shrestha S,
Varshney A,
Petty L,
Wright J,
Ventresca C,
Agarwala S,
Aramandla R,
Poffenberger G,
Jenkins R,
Mei S,
Hart N,
Phillips S,
Kang H,
Greiner D,
Shultz LD,
Bottino R,
Liu J,
Below J,
,
Parker S,
Powers A,
Brissova M.
Genetic risk converges on regulatory networks mediating early type 2 diabetes. Nature. 2023;624(7992):621-9.
Keywords
JMG, Humans, Case-Control Studies, Cell Separation, Chromatin, Diabetes Mellitus, Type 2, Gene Expression Profiling, Gene Regulatory Networks, Genetic Predisposition to Disease, Genome-Wide Association Study, Insulin Secretion, Islets of Langerhans, Reproducibility of Results
JAX Source
Nature. 2023;624(7992):621-9.
ISSN
1476-4687
PMID
38049589
DOI
https://doi.org/10.1038/s41586-023-06693-2
Abstract
Type 2 diabetes mellitus (T2D), a major cause of worldwide morbidity and mortality, is characterized by dysfunction of insulin-producing pancreatic islet β cells1,2. T2D genome-wide association studies (GWAS) have identified hundreds of signals in non-coding and β cell regulatory genomic regions, but deciphering their biological mechanisms remains challenging3–5. Here, to identify early disease-driving events, we performed traditional and multiplexed pancreatic tissue imaging, sorted-islet cell transcriptomics and islet functional analysis of early-stage T2D and control donors. By integrating diverse modalities, we show that early-stage T2D is characterized by
β cell-intrinsic defects that can be proportioned into gene regulatory modules with enrichment in signals of genetic risk. After identifying the β cell hub gene and transcription factor RFX6 within one such module, we demonstrated multiple layers of genetic risk that converge on an RFX6-mediated network to reduce insulin secretion by β cells. RFX6 perturbation in primary human islet cells alters β cell chromatin architecture at regions enriched for T2D GWAS signals, and population-scale genetic analyses causally link genetically predicted reduced RFX6 expression with increased T2D risk. Understanding the molecular mechanisms of complex, systemic diseases necessitates integration of signals from multiple molecules, cells, organs and individuals, and thus we anticipate that this approach will be a useful template to identify and validate key regulatory networks and master hub genes for other diseases or traits using GWAS data.