| Title: | Identifying modifiable factors and their joint effect on brain health: an exposome-wide association study |
| Journal: | GeroScience |
| Published: | 1 Jun 2024 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/38822946/ |
| DOI: | https://doi.org/10.1007/s11357-024-01224-x |
Publication 11935
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Abstract
Considerable uncertainty remains regarding the associations of multiple factors with brain health. We aimed to conduct an exposome-wide association study on neurodegenerative disease and neuropsychiatry disorders using data of participants from the UK Biobank. Multivariable Cox regression models with the least absolute shrinkage and selection operator technique as well as principal component analyses were used to evaluate the exposures in relation to common disorders of central nervous system (CNS). Restricted cubic splines were conducted to explore potential nonlinear correlations. Then, weighted standardized scores were generated based on the coefficients to calculate the joint effects of risk factors. We also estimated the potential impact of eliminating the unfavorable profiles of risk domains on CNS disorders using population attributable fraction (PAF). Finally, sensitivity analyses were performed to reduce the risk of reverse causality. The current study discovered the significantly associated exposures fell into six primary exposome categories. The joint effects of identified risk factors demonstrated higher risks for common disorders of CNS (HR = 1.278 ~ 3.743, p < 2e-16). The PAF varied by exposome categories, with lifestyle and medical history contributing to majority of disease cases. In total, we estimated that up to 3.7 ~ 64.1% of disease cases could be prevented.This study yielded modifiable variables of different categories and assessed their joint effects on common disorders of CNS. Targeting the identified exposures might help formulate effective strategies for maintaining brain health.</p>
13 Authors
- Liang-Yu Huang
- Yi-Jun Ge
- Yan Fu
- Yong-Li Zhao
- Ya-Nan Ou
- Yi Zhang
- Ling-Zhi Ma
- Shi-Dong Chen
- Ze-Xin Guo
- Jian-Feng Feng
- Wei Cheng
- Lan Tan
- Jin-Tai Yu
1 Application
| Application ID | Title |
|---|---|
| 19542 | Identifying multi-level biomarkers and disease mechanisms for major mental disorders |
Enabling scientific discoveries that improve human health