Assessing efficiency of fine-mapping obesity-associated variants through leveraging ancestry architecture and functional annotation using PAGE and UKBB cohorts. Anwar, M. Y., Graff, M., Highland, H. M, Smit, R., Wang, Z., Buchanan, V. L, Young, K. L, Kenny, E. E, Fernandez-Rhodes, L., Liu, S., Assimes, T., Garcia, D. O, Daeeun, K., Gignoux, C. R, Justice, A. E, Haiman, C. A, Buyske, S., Peters, U., Loos, R. J F, Kooperberg, C., & North, K. E Human Genetics, September, 2023.
Assessing efficiency of fine-mapping obesity-associated variants through leveraging ancestry architecture and functional annotation using PAGE and UKBB cohorts [link]Paper  abstract   bibtex   6 downloads  
Inadequate representation of non-European ancestry populations in genome-wide association studies (GWAS) has limited opportunities to isolate functional variants. Fine-mapping in multi-ancestry populations should improve the efficiency of prioritizing variants for functional interrogation. To evaluate this hypothesis, we leveraged ancestry architecture to perform comparative GWAS and fine-mapping of obesity-related phenotypes in European ancestry populations from the UK Biobank (UKBB) and multi-ancestry samples from the Population Architecture for Genetic Epidemiology (PAGE) consortium with comparable sample sizes. In the investigated regions with genome-wide significant associations for obesity-related traits, fine-mapping in our ancestrally diverse sample led to 95% and 99% credible sets (CS) with fewer variants than in the European ancestry sample. Lead fine-mapped variants in PAGE regions had higher average coding scores, and higher average posterior probabilities for causality compared to UKBB. Importantly, 99% CS in PAGE loci contained strong expression quantitative trait loci (eQTLs) in adipose tissues or harbored more variants in tighter linkage disequilibrium (LD) with eQTLs. Leveraging ancestrally diverse populations with heterogeneous ancestry architectures, coupled with functional annotation, increased fine-mapping efficiency and performance, and reduced the set of candidate variants for consideration for future functional studies. Significant overlap in genetic causal variants across populations suggests generalizability of genetic mechanisms underpinning obesity-related traits across populations.
@ARTICLE{Anwar2023-zs,
  title    = "Assessing efficiency of fine-mapping obesity-associated variants
              through leveraging ancestry architecture and functional
              annotation using {PAGE} and {UKBB} cohorts",
  author   = "Anwar, Mohammad Yaser and Graff, Mariaelisa and Highland, Heather
              M and Smit, Roelof and Wang, Zhe and Buchanan, Victoria L and
              Young, Kristin L and Kenny, Eimear E and Fernandez-Rhodes,
              Lindsay and Liu, Simin and Assimes, Themistocles and Garcia,
              David O and Daeeun, Kim and Gignoux, Christopher R and Justice,
              Anne E and Haiman, Christopher A and Buyske, Steve and Peters,
              Ulrike and Loos, Ruth J F and Kooperberg, Charles and North, Kari
              E",
  abstract = "Inadequate representation of non-European ancestry populations in
              genome-wide association studies (GWAS) has limited opportunities
              to isolate functional variants. Fine-mapping in multi-ancestry
              populations should improve the efficiency of prioritizing
              variants for functional interrogation. To evaluate this
              hypothesis, we leveraged ancestry architecture to perform
              comparative GWAS and fine-mapping of obesity-related phenotypes
              in European ancestry populations from the UK Biobank (UKBB) and
              multi-ancestry samples from the Population Architecture for
              Genetic Epidemiology (PAGE) consortium with comparable sample
              sizes. In the investigated regions with genome-wide significant
              associations for obesity-related traits, fine-mapping in our
              ancestrally diverse sample led to 95\% and 99\% credible sets
              (CS) with fewer variants than in the European ancestry sample.
              Lead fine-mapped variants in PAGE regions had higher average
              coding scores, and higher average posterior probabilities for
              causality compared to UKBB. Importantly, 99\% CS in PAGE loci
              contained strong expression quantitative trait loci (eQTLs) in
              adipose tissues or harbored more variants in tighter linkage
              disequilibrium (LD) with eQTLs. Leveraging ancestrally diverse
              populations with heterogeneous ancestry architectures, coupled
              with functional annotation, increased fine-mapping efficiency and
              performance, and reduced the set of candidate variants for
              consideration for future functional studies. Significant overlap
              in genetic causal variants across populations suggests
              generalizability of genetic mechanisms underpinning
              obesity-related traits across populations.",
  journal  = "Human Genetics",
  month    =  sep,
  year     =  2023,
  language = "en",
  pmid = {37658231},
	url = {https://pubmed.ncbi.nlm.nih.gov/37658231/},
  bdsk-url-1 = {https://doi.org/10.1007/s00439-023-02593-7}
}
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