Panlong Li , Xirui Zhu , Chun Huang , Shan Tian , Yuna Li , Yuan Qiao , Min Liu , Jingjing Su , Dandan Tian
{"title":"Effects of obesity on aging brain and cognitive decline: A cohort study from the UK Biobank","authors":"Panlong Li , Xirui Zhu , Chun Huang , Shan Tian , Yuna Li , Yuan Qiao , Min Liu , Jingjing Su , Dandan Tian","doi":"10.1016/j.ibneur.2025.01.001","DOIUrl":null,"url":null,"abstract":"<div><h3>Objective</h3><div>To investigate the impact of obesity on brain structure and cognition using large neuroimaging and genetic data.</div></div><div><h3>Methods</h3><div>Associations between body mass index (BMI), gray matter volume (GMV), whiter matter hyper-intensities (WMH), and fluid intelligence score (FIS) were estimated in 30283 participants from the UK Biobank. Longitudinal data analysis was conducted. Genome-wide association studies were applied to explore the genetic loci associations among BMI, GMV, WMH, and FIS. Mendelian Randomization analyses were applied to further estimate the effects of obesity on changes in the brain and cognition.</div></div><div><h3>Results</h3><div>The observational analysis revealed that BMI was negatively associated with GMV (r = -0.15, p < 1<span><math><mo>×</mo></math></span>10<sup>−24</sup>) and positively associated with WMH (r = 0.08, p < 1<span><math><mo>×</mo></math></span>10<sup>−16</sup>). The change in BMI was negatively associated with the change in GMV (r = -0.04, p < 5<span><math><mo>×</mo></math></span>10<sup>−5</sup>). Genetic overlap was observed among BMI, GMV, and FIS at SBK1 (rs2726032), SGF29 (rs17707300), TUFM (rs3088215), AKAP6 (rs1051695), IL27 (rs4788084), and SPI1 (rs3740689 and rs935914). The MR analysis provided evidence that higher BMI was associated with lower GMV (β=-1119.12, p = 5.77 ×10<sup>−6</sup>), higher WMH (β=42.76, p = 6.37 ×10<sup>−4</sup>), and lower FIS (β=-0.081, p = 1.92 ×10<sup>−23</sup>).</div></div><div><h3>Conclusions</h3><div>The phenotypic and genetic association between obesity and aging brain and cognitive decline suggested that weight control could be a promising strategy for slowing the aging brain.</div></div>","PeriodicalId":13195,"journal":{"name":"IBRO Neuroscience Reports","volume":"18 ","pages":"Pages 148-157"},"PeriodicalIF":2.0000,"publicationDate":"2025-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11786748/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IBRO Neuroscience Reports","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2667242125000016","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Objective
To investigate the impact of obesity on brain structure and cognition using large neuroimaging and genetic data.
Methods
Associations between body mass index (BMI), gray matter volume (GMV), whiter matter hyper-intensities (WMH), and fluid intelligence score (FIS) were estimated in 30283 participants from the UK Biobank. Longitudinal data analysis was conducted. Genome-wide association studies were applied to explore the genetic loci associations among BMI, GMV, WMH, and FIS. Mendelian Randomization analyses were applied to further estimate the effects of obesity on changes in the brain and cognition.
Results
The observational analysis revealed that BMI was negatively associated with GMV (r = -0.15, p < 110−24) and positively associated with WMH (r = 0.08, p < 110−16). The change in BMI was negatively associated with the change in GMV (r = -0.04, p < 510−5). Genetic overlap was observed among BMI, GMV, and FIS at SBK1 (rs2726032), SGF29 (rs17707300), TUFM (rs3088215), AKAP6 (rs1051695), IL27 (rs4788084), and SPI1 (rs3740689 and rs935914). The MR analysis provided evidence that higher BMI was associated with lower GMV (β=-1119.12, p = 5.77 ×10−6), higher WMH (β=42.76, p = 6.37 ×10−4), and lower FIS (β=-0.081, p = 1.92 ×10−23).
Conclusions
The phenotypic and genetic association between obesity and aging brain and cognitive decline suggested that weight control could be a promising strategy for slowing the aging brain.