INTRODUCTION: This project aimed to investigate the association between biometric components of metabolic syndrome (MetS) with gray matter volume (GMV) obtained with magnetic resonance imaging (MRI) from a large cohort of community-based adults (n = 776) subdivided by age and sex and employing brain regions of interest defined previously as the "Neural Signature of MetS" (NS-MetS). METHODS: Lipid profiles, biometrics, and regional brain GMV were obtained from the Genetics of Brain Structure (GOBS) image archive. Participants underwent T1-weighted MR imaging. MetS components (waist circumference, fasting plasma glucose, triglycerides, HDL cholesterol, and blood pressure) were defined using the National Cholesterol Education Program Adult Treatment Panel III. Subjects were grouped by age: early adult (18-25 years), young adult (26-45 years), and middle-aged adult (46-65 years). Linear regression modeling was used to investigate associations between MetS components and GMV in five brain regions comprising the NS-MetS: cerebellum, brainstem, orbitofrontal cortex, right insular/limbic cluster and caudate. RESULTS: In both men and women of each age group, waist circumference was the single component most strongly correlated with decreased GMV across all NS-MetS regions. The brain region most strongly correlated to all MetS components was the posterior cerebellum. CONCLUSION: The posterior cerebellum emerged as the region most significantly associated with MetS individual components, as the only region to show decreased GMV in young adults, and the region with the greatest variance between men and women. We propose that future studies investigating neurological effects of MetS and its comorbidities-namely diabetes and obesity-should consider the NS-MetS and the differential effects of age and sex.
Metabolic syndrome predictors of brain gray matter volume in an age-stratified community sample of 776 Mexican- American adults: Results from the genetics of brain structure image archive.
代谢综合征对 776 名墨西哥裔美国成年人按年龄分层的社区样本中脑灰质体积的预测:来自脑结构图像档案遗传学的结果
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作者:Kotkowski Eithan, Price Larry R, DeFronzo Ralph A, Franklin Crystal G, Salazar Maximino, Garrett Amy S, Woolsey Mary, Blangero John, Duggirala Ravindranath, Glahn David C, Fox Peter T
| 期刊: | Frontiers in Aging Neuroscience | 影响因子: | 4.500 |
| 时间: | 2022 | 起止号: | 2022 Sep 20; 14:999288 |
| doi: | 10.3389/fnagi.2022.999288 | 研究方向: | 代谢 |
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