| Title: | Branched chain amino acids harbor distinct and often opposing effects on health and disease |
| Journal: | Communications Medicine |
| Published: | 28 Nov 2023 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/38017291/ |
| DOI: | https://doi.org/10.1038/s43856-023-00382-x |
| URL: | https://www.nature.com/articles/s43856-023-00382-x.pdf |
Publication 8240
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Abstract
BackgroundThe branched chain amino acids (BCAA) leucine, isoleucine, and valine are essential nutrients that have been associated with diabetes, cancers, and cardiovascular diseases. Observational studies suggest that BCAAs exert homogeneous phenotypic effects, but these findings are inconsistent with results from experimental human and animal studies.MethodsHypothesizing that inconsistencies between observational and experimental BCAA studies reflect bias from shared lifestyle and genetic factors in observational studies, we used data from the UK Biobank and applied multivariable Mendelian randomization causal inference methods designed to address these biases.ResultsIn n = 97,469 participants of European ancestry (mean age = 56.7 years; 54.1% female), we estimate distinct and often opposing total causal effects for each BCAA. For example, of the 117 phenotypes with evidence of a statistically significant total causal effect for at least one BCAA, almost half (44%, n = 52) are associated with only one BCAA. These 52 associations include total causal effects of valine on diabetic eye disease [odds ratio = 1.51, 95% confidence interval (CI) = 1.31, 1.76], valine on albuminuria (odds ratio = 1.14, 95% CI = 1.08, 1.20), and isoleucine on angina (odds ratio = 1.17, 95% CI = 1.31, 1.76).ConclusionsOur results suggest that the observational literature provides a flawed picture of BCAA phenotypic effects that is inconsistent with experimental studies and could mislead efforts developing novel therapeutics. More broadly, these findings motivate the development and application of causal inference approaches that enable 'omics studies conducted in observational settings to account for the biasing effects of shared genetic and lifestyle factors.</p>
13 Authors
- Christy L. Avery
- Annie Green Howard
- Harold H. Lee
- Carolina G. Downie
- Moa P. Lee
- Sarah H. Koenigsberg
- Anna F. Ballou
- Michael H. Preuss
- Laura M. Raffield
- Rina A. Yarosh
- Kari E. North
- Penny Gordon-Larsen
- Mariaelisa Graff
1 Application
| Application ID | Title |
|---|---|
| 25953 | Transcriptome-wide Association Study of Cardiometabolic Traits in the UK Biobank Cohort |
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