| Title: | Metabolomic and genomic prediction of common diseases in 700,217 participants in three national biobanks |
| Journal: | Nature Communications |
| Published: | 21 Nov 2024 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/39572536/ |
| DOI: | https://doi.org/10.1038/s41467-024-54357-0 |
Publication 14309
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
Identifying individuals at high risk of chronic diseases via easily measured biomarkers could enhance efforts to prevent avoidable illness and death. Using 'omic data can stratify risk for many diseases simultaneously from a single measurement that captures multiple molecular predictors of risk. Here we present nuclear magnetic resonance metabolomics in blood samples from 700,217 participants in three national biobanks. We built metabolomic scores that identify high-risk groups for diseases that cause the most morbidity in high-income countries and show consistent cross-biobank replication of the relative risk of disease for these groups. We show that these metabolomic scores are more strongly associated with disease onset than polygenic scores for most of these diseases. In a subset of 18,709 individuals with metabolomic biomarkers measured at two time points we show that people whose scores change have different risk of disease, suggesting that repeat measurements capture changes both to health status and disease risk possibly due to treatment, lifestyle changes or other factors. Lastly, we assessed the incremental predictive value of metabolomic scores over existing clinical risk scores for multiple diseases and found modest improvements in discrimination for several diseases whose clinical utility, while promising, remains to be determined.</p>
11 Keywords
- Adult
- Aged
- Biological Specimen Banks
- Biomarkers
- Female
- Genomics
- Humans
- Male
- Metabolomics
- Middle Aged
- Risk Factors
25 Authors
- Jeffrey C. Barrett
- Tõnu Esko
- Krista Fischer
- Luke Jostins-Dean
- Pekka Jousilahti
- Heli Julkunen
- Tuija Jääskeläinen
- Antti Kangas
- Nurlan Kerimov
- Sini Kerminen
- Anastassia Kolde
- Harri Koskela
- Jaanika Kronberg
- Sara N. Lundgren
- Annamari Lundqvist
- Valtteri Mäkelä
- Kristian Nybo
- Markus Perola
- Veikko Salomaa
- Kirsten Schut
- Maiju Soikkeli
- Pasi Soininen
- Mika Tiainen
- Taavi Tillmann
- Peter Würtz
1 Application
| Application ID | Title |
|---|---|
| 30418 | Biomarker profiling by NMR metabolomics for the study of chronic disease risk and underlying risk factors |
Enabling scientific discoveries that improve human health