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Demonstrating paths for unlocking the value of cloud genomics through cross cohort analysis

Abstract:
Recently, large scale genomic projects such as All of Us and the UK Biobank have introduced a new research paradigm where data are stored centrally in cloud-based Trusted Research Environments (TREs). To characterize the advantages and drawbacks of different TRE attributes in facilitating cross-cohort analysis, we conduct a Genome-Wide Association Study of standard lipid measures using two approaches: meta-analysis and pooled analysis. Comparison of full summary data from both approaches with an external study shows strong correlation of known loci with lipid levels (R2 ~ 83–97%). Importantly, 90 variants meet the significance threshold only in the meta-analysis and 64 variants are significant only in pooled analysis, with approximately 20% of variants in each of those groups being most prevalent in non-European, non-Asian ancestry individuals. These findings have important implications, as technical and policy choices lead to cross-cohort analyses generating similar, but not identical results, particularly for non-European ancestral populations.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1038/s41467-023-41185-x

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Role:
Author
ORCID:
0000-0002-9421-8048
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Role:
Author
ORCID:
0000-0002-2751-9254
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Role:
Author
ORCID:
0000-0002-2382-1376


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Funder identifier:
https://ror.org/00baak391
Grant:
U01 HG011719


Publisher:
Springer Nature
Journal:
Nature Communications More from this journal
Volume:
14
Issue:
1
Article number:
5419
Place of publication:
England
Publication date:
2023-09-05
Acceptance date:
2023-08-24
DOI:
EISSN:
2041-1723
Pmid:
37669985


Language:
English
Keywords:
Pubs id:
1524987
Local pid:
pubs:1524987
Deposit date:
2025-02-03
ARK identifier:

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