CNS neuroscience & therapeutics · 2024
Identifying modifiable factors associated with neuroimaging markers of brain health.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод пока не подготовлен
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Huang Liang-Yu, Fu Yan, Zhang Yi, Hu He-Ying, Ma Ling-Zhi, Ge Yi-Jun, Zhao Yong-Li, Zhang Ya-Ru, Chen Shi-Dong, Feng Jian-Feng, Cheng Wei, Tan Lan, Yu Jin-Tai
Аннотация
AIMS: Brain structural alterations begin long before the presentation of brain disorders; therefore, we aimed to systematically investigate a wide range of influencing factors on neuroimaging markers of brain health.
METHODS: Utilizing data from 30,651 participants from the UK Biobank, we explored associations between 218 modifiable factors and neuroimaging markers of brain health. We conducted an exposome-wide association study using the least absolute shrinkage and selection operator (LASSO) technique. Restricted cubic splines (RCS) were further employed to estimate potential nonlinear correlations. Weighted standardized scores for neuroimaging markers were computed based on the estimates for individual factors. Finally, stratum-specific analyses were performed to examine differences in factors affecting brain health at different ages.
RESULTS: The identified factors related to neuroimaging markers of brain health fell into six domains, including systematic diseases, lifestyle factors, personality traits, social support, anthropometric indicators, and biochemical markers. The explained variance percentage of neuroimaging markers by weighted standardized scores ranged from 0.5% to 7%. Notably, associations between systematic diseases and neuroimaging markers were stronger in older individuals than in younger ones.
CONCLUSION: This study identified a series of factors related to neuroimaging markers of brain health. Targeting the identified factors might help in formulating effective strategies for maintaining brain health.
METHODS: Utilizing data from 30,651 participants from the UK Biobank, we explored associations between 218 modifiable factors and neuroimaging markers of brain health. We conducted an exposome-wide association study using the least absolute shrinkage and selection operator (LASSO) technique. Restricted cubic splines (RCS) were further employed to estimate potential nonlinear correlations. Weighted standardized scores for neuroimaging markers were computed based on the estimates for individual factors. Finally, stratum-specific analyses were performed to examine differences in factors affecting brain health at different ages.
RESULTS: The identified factors related to neuroimaging markers of brain health fell into six domains, including systematic diseases, lifestyle factors, personality traits, social support, anthropometric indicators, and biochemical markers. The explained variance percentage of neuroimaging markers by weighted standardized scores ranged from 0.5% to 7%. Notably, associations between systematic diseases and neuroimaging markers were stronger in older individuals than in younger ones.
CONCLUSION: This study identified a series of factors related to neuroimaging markers of brain health. Targeting the identified factors might help in formulating effective strategies for maintaining brain health.