Abstract:
BACKGROUND:This report evaluated sex-specific differences in the association between brain aging and body mass index (BMI) in young adults using the publicly available data from the Human Connectome Project (HCP). METHODS:Participants of HCP with available structural imaging and BMI data were included [n = 1112; mean age = 28.80 (SD = 3.70); mean BMI = 26.53 (SD = 5.20); males n = 507, females n = 605]. Predicted brain age was generated using raw T1-weighted MRI scan and a Gaussian Processes regression model. The difference (Δ aging) between brain age predicted by structural imaging and chronological age was computed. A linear regression model was used with Δ aging as the dependent variable, and sex, BMI, and BMI-by-sex interaction as independent variables of interest, and race, ethnicity, income, and education as covariates. RESULTS:There was a significant BMI-by-sex interaction for Δ aging (p = 0.041). Higher BMI was associated with greater brain aging in both sexes. However, this association was substantially stronger in males (β = 0.215; SE = 0.050; p < 0.0001) than in females (β = 0.122; SE = 0.035; p = 0.0005). CONCLUSION:We found evidence suggesting that higher BMI is associated with greater brain aging in adults. Furthermore, the association between higher BMI and greater brain aging was stronger in males than in females. Future studies are needed to explore the mechanistic pathways that link higher BMI to greater brain aging and whether weight-loss interventions, such as exercise, can reverse higher BMI-associated greater brain aging.
journal_name
Psychoneuroendocrinologyjournal_title
Psychoneuroendocrinologyauthors
Chin Fatt CR,Jha MK,Minhajuddin A,Mayes T,Trivedi MHdoi
10.1016/j.psyneuen.2020.105059subject
Has Abstractpub_date
2020-11-16 00:00:00pages
105059eissn
0306-4530issn
1873-3360pii
S0306-4530(20)30482-0journal_volume
124pub_type
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