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识别与大脑健康的神经影像学标志物相关的可改变因素。

Identifying modifiable factors associated with neuroimaging markers of brain health.

机构信息

Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China.

Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.

出版信息

CNS Neurosci Ther. 2024 Oct;30(10):e70057. doi: 10.1111/cns.70057.

Abstract

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.

摘要

目的

大脑结构的改变早在出现大脑疾病之前就已经开始了;因此,我们旨在系统地研究广泛的影响因素对大脑健康的神经影像学标志物的影响。

方法

利用英国生物库 30651 名参与者的数据,我们探讨了 218 个可改变因素与大脑健康的神经影像学标志物之间的关联。我们使用最小绝对收缩和选择算子(LASSO)技术进行了外显子组全关联研究。进一步使用限制立方样条(RCS)估计潜在的非线性相关性。根据个体因素的估计值计算神经影像学标志物的加权标准化分数。最后,进行分层特异性分析,以检查不同年龄影响大脑健康的因素的差异。

结果

与大脑健康的神经影像学标志物相关的确定因素分为六个领域,包括系统疾病、生活方式因素、人格特质、社会支持、人体测量指标和生化标志物。加权标准化分数解释的神经影像学标志物的方差百分比范围为 0.5%至 7%。值得注意的是,系统性疾病与神经影像学标志物之间的关联在老年人中比在年轻人中更强。

结论

本研究确定了一系列与大脑健康的神经影像学标志物相关的因素。针对确定的因素可能有助于制定维持大脑健康的有效策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9735/11474882/49f735b34839/CNS-30-e70057-g005.jpg

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