PMID- 36255737
OWN - NLM
STAT- MEDLINE
DCOM- 20240409
LR  - 20240410
IS  - 1460-2083 (Electronic)
IS  - 0964-6906 (Print)
IS  - 0964-6906 (Linking)
VI  - 33
IP  - 8
DP  - 2024 Apr 8
TI  - Ancestry-specific high-risk gene variant profiling unmasks diabetes-associated 
      genes.
PG  - 655-666
LID - 10.1093/hmg/ddac255 [doi]
AB  - How ancestry-associated genetic variance affects disparities in the risk of 
      polygenic diseases and influences the identification of disease-associated genes 
      warrants a deeper understanding. We hypothesized that the discovery of genes 
      associated with polygenic diseases may be limited by the overreliance on 
      single-nucleotide polymorphism (SNP)-based genomic investigation, as most 
      significant variants identified in genome-wide SNP association studies map to 
      introns and intergenic regions of the genome. To overcome such potential 
      limitations, we developed a gene-constrained, function-based analytical method 
      centered on high-risk variants (hrV) that encode frameshifts, stopgains or splice 
      site disruption. We analyzed the total number of hrV per gene in populations of 
      different ancestry, representing a total of 185 934 subjects. Using this 
      analysis, we developed a quantitative index of hrV (hrVI) across 20 428 genes 
      within each population. We then applied hrVI analysis to the discovery of genes 
      associated with type 2 diabetes mellitus (T2DM), a polygenic disease with 
      ancestry-related disparity. HrVI profiling and gene-to-gene comparisons of 
      ancestry-specific hrV between the case (20 781 subjects) and control (24 440 
      subjects) populations in the T2DM national repository identified 57 genes 
      associated with T2DM, 40 of which were discoverable only by ancestry-specific 
      analysis. These results illustrate how a function-based, ancestry-specific 
      analysis of genetic variations can accelerate the identification of genes 
      associated with polygenic diseases. Besides T2DM, such analysis may facilitate 
      our understanding of the genetic basis for other polygenic diseases that are also 
      greatly influenced by environmental and behavioral factors, such as obesity, 
      hypertension and Alzheimer's disease.
CI  - Published by Oxford University Press 2022.
FAU - Zhang, Jianhua
AU  - Zhang J
AD  - Metabolic Diseases Branch, National Institute of Diabetes and Digestive and 
      Kidney Diseases, Bethesda, MD 20892, United States.
FAU - Chen, Weiping
AU  - Chen W
AD  - Genomic Core, National Institute of Diabetes and Digestive and Kidney Diseases, 
      Bethesda, MD 20892, United States.
AD  - Laboratory of Cell and Molecular Biology, National Institute of Diabetes and 
      Digestive and Kidney Diseases, Bethesda, MD 20892, United States.
FAU - Chen, Guanjie
AU  - Chen G
AUID- ORCID: 0000-0002-5745-5618
AD  - Center for Research on Genomics and Global Health, National Human Genome Research 
      Institute, Bethesda, MD 20892, United States.
FAU - Flannick, Jason
AU  - Flannick J
AD  - Metabolism Program, Broad Institute, Cambridge, MA 02142, United States.
FAU - Fikse, Emma
AU  - Fikse E
AD  - Metabolic Diseases Branch, National Institute of Diabetes and Digestive and 
      Kidney Diseases, Bethesda, MD 20892, United States.
FAU - Smerin, Glenda
AU  - Smerin G
AD  - Metabolic Diseases Branch, National Institute of Diabetes and Digestive and 
      Kidney Diseases, Bethesda, MD 20892, United States.
FAU - Degner, Katherine
AU  - Degner K
AD  - Metabolic Diseases Branch, National Institute of Diabetes and Digestive and 
      Kidney Diseases, Bethesda, MD 20892, United States.
FAU - Yang, Yanqin
AU  - Yang Y
AD  - Laboratory of Transplantation Genomics, National Heart Lung and Blood Institute; 
      National Institutes of Health, Bethesda, MD 20892, United States.
FAU - Xu, Catherine
AU  - Xu C
AD  - Genomic Core, National Institute of Diabetes and Digestive and Kidney Diseases, 
      Bethesda, MD 20892, United States.
CN  - Consortium AMP-T2D-GENES
FAU - Li, Yulong
AU  - Li Y
AD  - Milton S. Hershey Medical Center, Division of Endocrinology, Diabetes and 
      Metabolism, Penn State University, Hershey, PA 17033, United States.
FAU - Hanover, John A
AU  - Hanover JA
AD  - Laboratory of Cell and Molecular Biology, National Institute of Diabetes and 
      Digestive and Kidney Diseases, Bethesda, MD 20892, United States.
FAU - Simonds, William F
AU  - Simonds WF
AUID- ORCID: 0000-0001-7806-706X
AD  - Metabolic Diseases Branch, National Institute of Diabetes and Digestive and 
      Kidney Diseases, Bethesda, MD 20892, United States.
LA  - eng
GR  - 1ZIA HG200362/NH/NIH HHS/United States
GR  - ZIA HG200362/ImNIH/Intramural NIH HHS/United States
GR  - CT/CIT NIH HHS/United States
GR  - HG/NHGRI NIH HHS/United States
GR  - ZIA DK043304/ImNIH/Intramural NIH HHS/United States
GR  - DK/NIDDK NIH HHS/United States
PT  - Journal Article
PL  - England
TA  - Hum Mol Genet
JT  - Human molecular genetics
JID - 9208958
SB  - IM
MH  - Humans
MH  - *Diabetes Mellitus, Type 2/genetics/epidemiology
MH  - Genetic Predisposition to Disease
MH  - Genome-Wide Association Study
MH  - Obesity
MH  - Polymorphism, Single Nucleotide/genetics
PMC - PMC11000659
EDAT- 2022/10/19 06:00
MHDA- 2024/04/09 06:45
PMCR- 2023/10/18
CRDT- 2022/10/18 11:33
PHST- 2022/05/04 00:00 [received]
PHST- 2022/09/28 00:00 [revised]
PHST- 2022/10/10 00:00 [accepted]
PHST- 2024/04/09 06:45 [medline]
PHST- 2022/10/19 06:00 [pubmed]
PHST- 2022/10/18 11:33 [entrez]
PHST- 2023/10/18 00:00 [pmc-release]
AID - 6762999 [pii]
AID - ddac255 [pii]
AID - 10.1093/hmg/ddac255 [doi]
PST - ppublish
SO  - Hum Mol Genet. 2024 Apr 8;33(8):655-666. doi: 10.1093/hmg/ddac255.