South Asian patient population genetics reveal strong founder effects and high rates of homozygosity - new resources for precision medicine
Wall, J.; Sathirapongsasuti, J. F.; Gupta, R.; Barik, A.; Rai, R. K.; Rasheed, A.; Radha, V.; Belsare, S.; Menon, R.; Phalke, S.; Mittal, A.; Fang, J.; Tanneeru, D.; Robinson, J.; Chaudhary, R.; Fuchsberger, C.; Forer, L.; Schoenherr, S.; Bei, Q.; Bhangale, T.; Tom, J.; Gadde, S. G. K.; V, P. B.; Naik, N. K.; Wang, M.; Kwok, P.-Y.; Khera, A. V.; Lakshmi, B. R.; Butterworth, A.; Danesh, J.; Seshagiri, S.; Kathiresan, S.; Ghosh, A.; Mohan, V.; Chowdhury, A.; Saleheen, D.; Stawiski, E.; Peterson, A. S.
Show abstract
Population-scale genetic studies can identify drug targets and allow disease risk to be predicted with resulting benefit for management of individual health risks and system-wide allocation of health care delivery resources. Although population-scale projects are underway in many parts of the world, genetic variation between population groups means that additional projects are warranted. South Asia has a population whose genetics is the least characterized of any of the worlds major populations. Here we describe GenomeAsia studies that characterize population structure in South Asia and that create tools for economical and accurate genotyping at population-scale. Prior work on population structure characterized isolated population groups, the relevance of which to large-scale studies of disease genetics is unclear. For our studies we used whole genome sequence information from 4,807 individuals recruited in the health care delivery systems of Pakistan, India and Bangladesh to ensure relevance to population-scale studies of disease genetics. We combined this with WGS data from 927 individuals from isolated South Asian population groups, and developed a custom SNP array (called SARGAM) that is optimized for future human genetic studies in South Asia. We find evidence for high rates of reproductive isolation, endogamy and consanguinity that vary across the subcontinent and that lead to levels of homozygosity that approach 100 times that seen in outbred populations. We describe founder effects that increase the power to associate functional variants with disease processes and that make South Asia a uniquely powerful place for population-scale genetic studies.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Enrichment analyses identify shared associations for 25 quantitative traits in over 600,000 individuals from seven diverse ancestries 97%
- Bayesian model comparison for rare variant association studies 97%
- Estimating heritability explained by local ancestry and evaluating stratification bias in admixture mapping from summary statistics 97%
Similar papers in this journal
- Large scale genome-wide association study in a Japanese population identified 45 novel susceptibility loci for 22 diseases 97%
- Leveraging fine-mapping and non-European training data to improve trans-ethnic polygenic risk scores 96%
- Leveraging functional genomic annotations and genome coverage to improve polygenic prediction of complex traits within and between ancestries 96%
Similar papers in this journal
- Multivariate adaptive shrinkage improves cross-population transcriptome prediction for transcriptome-wide association studies in underrepresented populations 97%
- Evaluating genetic-ancestry inference from single-cell transcriptomic datasets 96%
- Distinct positions of genetic and oral histories: Perspectives from India 96%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.