Summary
This Nature publication presents a comprehensive atlas of genetic scores designed to predict multiple omic traits—including circulating proteins, metabolites, and lipids—across large populations. Through phenome-wide scanning, the authors identify novel disease associations and elucidate genetic mechanisms underlying metabolic pathways and disease processes, exemplified by JAK-STAT signalling in coronary atherosclerosis. The work culminates in a publicly accessible portal (omicspred.org) to democratise access to these polygenic scores and support future multi-omic prediction research.
Regional applicability
These genetic prediction tools and disease associations may be applicable to UK clinical and epidemiological research, particularly within NHS Biobank and other population cohorts. However, the transferability of polygenic scores across ancestry groups remains a consideration for equitable implementation in diverse UK populations.
Key measures
Polygenic risk scores; multi-omic trait predictions (proteins, metabolites, lipids); phenome-wide association scan results; disease associations; pathway-level biological mechanisms
Outcomes reported
The study developed and validated an atlas of genetic scores to predict multi-omic traits (proteins, metabolites, lipids) and conducted a phenome-wide scan to identify disease associations. The research identified biological insights regarding genetic mechanisms in metabolism and canonical pathway associations with disease, including JAK-STAT signalling and coronary atherosclerosis.
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