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Population genetic considerations for using biobanks as international resources in the pandemic era and beyond

Journal

BMC GENOMICS
Volume 22, Issue 1, Pages -

Publisher

BMC
DOI: 10.1186/s12864-021-07618-x

Keywords

Bioinformatics; Population structure; Population stratification bias; Genomic medicine; Biobanks

Funding

  1. MRC [MR/R025126/1]
  2. Crafoord Foundation
  3. Swedish Research Council [2020-03485, 2018-05973]
  4. Erik PhilipSorensen Foundation [G2020-011]
  5. Lund University
  6. Swedish Research Council [2020-03485] Funding Source: Swedish Research Council
  7. MRC [MR/R025126/1] Funding Source: UKRI

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The over-representation of Europeans in genomic studies restricts global understanding of disease risk and inhibits research into genomic differences between carriers and patients. To address this, more diverse samples are needed, with diversity quantified, compared and annotated for insight.
The past years have seen the rise of genomic biobanks and mega-scale meta-analysis of genomic data, which promises to reveal the genetic underpinnings of health and disease. However, the over-representation of Europeans in genomic studies not only limits the global understanding of disease risk but also inhibits viable research into the genomic differences between carriers and patients. Whilst the community has agreed that more diverse samples are required, it is not enough to blindly increase diversity; the diversity must be quantified, compared and annotated to lead to insight. Genetic annotations from separate biobanks need to be comparable and computable and to operate without access to raw data due to privacy concerns. Comparability is key both for regular research and to allow international comparison in response to pandemics. Here, we evaluate the appropriateness of the most common genomic tools used to depict population structure in a standardized and comparable manner. The end goal is to reduce the effects of confounding and learn from genuine variation in genetic effects on phenotypes across populations, which will improve the value of biobanks (locally and internationally), increase the accuracy of association analyses and inform developmental efforts.

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