| Title: | Demonstrating paths for unlocking the value of cloud genomics through cross cohort analysis |
| Journal: | Nature Communications |
| Published: | 5 Sep 2023 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/37669985/ |
| DOI: | https://doi.org/10.1038/s41467-023-41185-x |
| URL: | https://www.nature.com/articles/s41467-023-41185-x.pdf |
| Citations: | 4 (4 in last 2 years) as of 8 Aug 2024 |
Publication 9633
WARNING: the interactive features of this website use CSS3, which your browser does not support. To use the full features of this website, please update your browser.
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.</p>
17 Authors
- Nicole Deflaux
- Margaret Sunitha Selvaraj
- Henry Robert Condon
- Kelsey Mayo
- Sara Haidermota
- Melissa A. Basford
- Chris Lunt
- Anthony A. Philippakis
- Dan M. Roden
- Joshua C. Denny
- Anjene Musick
- Rory Collins
- Naomi Allen
- Mark Effingham
- David Glazer
- Pradeep Natarajan
- Alexander G. Bick
1 Application
| Application ID | Title |
|---|---|
| 7089 | Exome Sequencing of All Premature Coronary Artery Disease Participants in UK Biobank |
Enabling scientific discoveries that improve human health