Mason J Lower, Mia K DeCataldo, Thomas E Kraynak, Peter J Gianaros
{"title":"Circulating Antioxidant Nutrients and Brain Age in Midlife Adults.","authors":"Mason J Lower, Mia K DeCataldo, Thomas E Kraynak, Peter J Gianaros","doi":"10.1097/PSY.0000000000001399","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>Due to population aging, the increasing prevalence of Alzheimer's disease (AD) and related dementias are major public health concerns. Dietary consumption of antioxidant nutrients, in particular the carotenoid β-carotene, has been associated with less age-related neurocognitive decline. What is unclear, however, is the extent to which antioxidant nutrients may exert neuroprotective effects through their influence on established indicators of age-related changes in brain tissue. This study thus tested associations of circulating β-carotene and other nutrients with a structural neuroimaging indicator of brain age derived from cross-validated machine learning models trained to predict chronological age from brain tissue morphology in independent cohorts.</p><p><strong>Methods: </strong>Midlife adults (N = 132, aged 30.4 to 50.8 y, 59 female at birth) underwent a structural magnetic resonance imaging (MRI) protocol and fasting phlebotomy to assess plasma concentrations of β-carotene, retinol, γ-tocopherol, α-tocopherol, and β-cryptoxanthin.</p><p><strong>Results: </strong>In regression analyses adjusting for chronological age, sex at birth, smoking status, MRI image quality, season of testing, annual income, and education, greater circulating levels of β-carotene were associated with a lower (ie, younger) predicted brain age ( β = -0.23, 95% CI = -0.40 to -0.07, p = .006). Other nutrients were not statistically associated with brain age, and results persisted after additional covariate control for body mass index, cortical volume, and cortical thickness.</p><p><strong>Conclusions: </strong>These cross-sectional findings are consistent with the possibility that dietary intake of β-carotene may be associated with slower biological aging at the level of the brain, as reflected by a neuroimaging indicator of brain age.</p>","PeriodicalId":520402,"journal":{"name":"Biopsychosocial science and medicine","volume":" ","pages":"362-371"},"PeriodicalIF":0.0000,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12225730/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biopsychosocial science and medicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1097/PSY.0000000000001399","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/5/9 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Objective: Due to population aging, the increasing prevalence of Alzheimer's disease (AD) and related dementias are major public health concerns. Dietary consumption of antioxidant nutrients, in particular the carotenoid β-carotene, has been associated with less age-related neurocognitive decline. What is unclear, however, is the extent to which antioxidant nutrients may exert neuroprotective effects through their influence on established indicators of age-related changes in brain tissue. This study thus tested associations of circulating β-carotene and other nutrients with a structural neuroimaging indicator of brain age derived from cross-validated machine learning models trained to predict chronological age from brain tissue morphology in independent cohorts.
Methods: Midlife adults (N = 132, aged 30.4 to 50.8 y, 59 female at birth) underwent a structural magnetic resonance imaging (MRI) protocol and fasting phlebotomy to assess plasma concentrations of β-carotene, retinol, γ-tocopherol, α-tocopherol, and β-cryptoxanthin.
Results: In regression analyses adjusting for chronological age, sex at birth, smoking status, MRI image quality, season of testing, annual income, and education, greater circulating levels of β-carotene were associated with a lower (ie, younger) predicted brain age ( β = -0.23, 95% CI = -0.40 to -0.07, p = .006). Other nutrients were not statistically associated with brain age, and results persisted after additional covariate control for body mass index, cortical volume, and cortical thickness.
Conclusions: These cross-sectional findings are consistent with the possibility that dietary intake of β-carotene may be associated with slower biological aging at the level of the brain, as reflected by a neuroimaging indicator of brain age.