| Title: | Genotype-by-environment interactions in chronic back pain |
| Journal: | The Spine Journal |
| Published: | 18 Apr 2023 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/37080360/ |
| DOI: | https://doi.org/10.1016/j.spinee.2023.04.009 |
Publication 7869
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
BACKGROUND CONTEXT: Chronic back pain (CBP) is a common debilitating condition with substantial societal impact. While understanding genotype-by-environment (GxE) interactions may be crucial to achieving the goals of personalized medicine, there are few large-scale studies investigating this topic for CBP. None of them systematically explore multiple CBP risk factors. PURPOSE: To estimate the extent to which genetic effects on CBP are modified by known demographic and clinical risk factors. RESEARCH DESIGN: Case-control study, genome-wide GxE interaction study. PATIENT SAMPLE: Data on up to 331,610 unrelated participants (57,881 CBP cases and 273,729 controls) from the UK Biobank cohort were used. UK Biobank is a prospective cohort with collected deep genetic and phenotypic data on approximately 500,000 individuals across the UK. OUTCOME MEASURES: Self-reported chronic back pain. METHODS: We applied a whole-genome approach to estimate the proportion of phenotypic variance explained by interactions between genotype and 12 known risk factors. We also analyzed if effects of common single-nucleotide polymorphisms on CBP are changed in presence of known risk factors. RESULTS: The results indicate a modest, if any, modification of genetic effects by examined risk factors in CBP. Our estimates suggest that detecting such weak effects would require a sample size of millions of individuals. CONCLUSIONS: The GxE interactions with examined common risk factors for CBP are either weak or absent. Interactions of such magnitude are unlikely to have the potential to inform and influence treatment strategies. Risk estimation models may use common genetic variation and the considered risk factors as independent predictors, without accounting for GxE.6 Authors
- Ivan A Kuznetsov
- Yakov A Tsepilov
- Maxim B Freidin
- Frances M K Williams
- Pradeep Suri
- Yurii S Aulchenko
1 Application
| Application ID | Title |
|---|---|
| 41601 | Non-additive effects in control of complex human traits |
Enabling scientific discoveries that improve human health