Modifiable traits and genetic associations with grey matter volume in mid-to-late adulthood: a population-based study in the UK biobank.

Guoqing Pan, Yi Zhang, Ju-Jiao Kang, Yuchao Jiang, Wei Zhang, Peng Ren, Jia You, Weikang Gong, Jin-Tai Yu, Jian-Feng Feng, Xuejuan Zhang, Wei Cheng, Linbo Wang

Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China. · pubmed

Paper

Abstract

Given the growing global elderly population and the accelerating decrease in grey matter volume (GMV) with age, understanding healthy brain aging is increasingly important. This study investigates whether variations in modifiable traits can account for differences in GMV and whether these traits can inform strategies to mitigate risks of future brain disorders. We identified 66 traits significantly associated with total GMV. Further, we examined the joint contributions of different domain traits to the GMV variance, finding that blood biomarkers and physical measurements accounted for the largest proportion of GMV variance. Some traits mediated the relationship between the genetic risk for brain disorders and GMV. Moreover, the identified traits divided the population into two subgroups, with significant differences in GMV and incidences of brain disorders. Our findings underscore the importance of modifiable traits in supporting healthy brain aging and reducing the risk of brain disorders, suggesting potential targets for intervention.

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Research summary

Modifiable traits can significantly influence grey matter volume in mid-to-late adulthood. The study addresses factors that may mitigate risks of brain disorders, which is pertinent to understanding healthy aging and longevity.

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