2022
DOI: 10.1038/s41588-022-01058-3
|View full text |Cite
|
Sign up to set email alerts
|

Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation

Help me understand this report
View preprint versions

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
2

Citation Types

1
199
0
1

Year Published

2022
2022
2024
2024

Publication Types

Select...
5
2
2

Relationship

4
5

Authors

Journals

citations
Cited by 402 publications
(231 citation statements)
references
References 66 publications
1
199
0
1
Order By: Relevance
“…In research settings, trans-ancestry PRS are often derived from multi-ethnic meta-GWAS [7,44] or trained in each target population separately [45,46]. However, the former approach does not model population-specific allele frequency and LD patterns, which limits the performance of PRS, while the latter approach requires assigning individuals to discrete ancestral groups to optimize PRS estimation, which is challenging in clinical applications because self-reported race/ethnicity may be inconsistent with genetic ancestry.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…In research settings, trans-ancestry PRS are often derived from multi-ethnic meta-GWAS [7,44] or trained in each target population separately [45,46]. However, the former approach does not model population-specific allele frequency and LD patterns, which limits the performance of PRS, while the latter approach requires assigning individuals to discrete ancestral groups to optimize PRS estimation, which is challenging in clinical applications because self-reported race/ethnicity may be inconsistent with genetic ancestry.…”
Section: Discussionmentioning
confidence: 99%
“…Recent large-scale genome-wide association studies (GWAS) in diverse populations have identified hundreds of genetic loci associated with T2D [7][8][9]. Polygenic risk scores (PRS), which aggregate the genetic risk of individual alleles across the genome, are thus promising to predict future T2D occurrence and improve early diagnosis, intervention, and prevention of T2D [10][11][12][13][14][15].…”
Section: Introductionmentioning
confidence: 99%
“…It has been demonstrated through analysis of GWAS metadata of T2D-related traits [65,66] and human physiological studies [67] that the risk allele at this SNV increases T2D susceptibility via impaired insulin secretion. Additionally, this variant was shown colocalize with a cis-eQTL for TCF7L2 in pancreatic islets [68] and to be associated with increased TCF7L2 expression in islets and β-cells [47,69,70]. These data have established that rs7903146 increases T2D risk primarily through islet dysfunction, which is probably driven by increased TCF7L2 expression in beta cells.…”
Section: Discussionmentioning
confidence: 84%
“…Our understanding of the genetic landscape of T2D has increased substantially [2, 5, 45] and current efforts are focused on translating these genetic discoveries into disease mechanisms. Here, we characterised the role of the T2D-associated gene RREB1 in beta cell development and function.…”
Section: Discussionmentioning
confidence: 99%