{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T14:32:56Z","timestamp":1790087576173,"version":"4.0.1"},"reference-count":50,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2022,9,20]],"date-time":"2022-09-20T00:00:00Z","timestamp":1663632000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100006108","name":"National Center for Advancing Translational Sciences","doi-asserted-by":"publisher","award":["TL1TR002647-01"],"award-info":[{"award-number":["TL1TR002647-01"]}],"id":[{"id":"10.13039\/100006108","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000025","name":"National Institute of Mental Health","doi-asserted-by":"publisher","award":["R01MH074457-11S1"],"award-info":[{"award-number":["R01MH074457-11S1"]}],"id":[{"id":"10.13039\/100000025","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Aging Neurosci."],"abstract":"<jats:sec><jats:title>Introduction<\/jats:title><jats:p>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 (<jats:italic>n<\/jats:italic> = 776) subdivided by age and sex and employing brain regions of interest defined previously as the \u201cNeural Signature of MetS\u201d (NS-MetS).<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>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\u201325 years), young adult (26\u201345 years), and middle-aged adult (46\u201365 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.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>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.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>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\u2014namely diabetes and obesity\u2014should consider the NS-MetS and the differential effects of age and sex.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fnagi.2022.999288","type":"journal-article","created":{"date-parts":[[2022,9,20]],"date-time":"2022-09-20T09:50:33Z","timestamp":1663667433000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":12,"title":["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"],"prefix":"10.3389","volume":"14","author":[{"given":"Eithan","family":"Kotkowski","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Larry R.","family":"Price","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ralph A.","family":"DeFronzo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Crystal G.","family":"Franklin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maximino","family":"Salazar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Amy S.","family":"Garrett","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mary","family":"Woolsey","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John","family":"Blangero","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ravindranath","family":"Duggirala","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David C.","family":"Glahn","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peter T.","family":"Fox","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2022,9,20]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"1973","DOI":"10.1001\/jama.2015.4260","article-title":"Prevalence of the metabolic syndrome in the United States, 2003-2012.","volume":"313","author":"Aguilar","year":"2015","journal-title":"JAMA"},{"key":"B2","doi-asserted-by":"publisher","first-page":"269","DOI":"10.1111\/obr.12629","article-title":"Obesity as a risk factor for Alzheimer\u2019s disease: Weighing the evidence.","volume":"19","author":"Alford","year":"2018","journal-title":"Obes. Rev."},{"key":"B3","author":"Andersson","year":"2007","journal-title":"Non-linear registration, aka Spatial normalization. FMRIB technical report TR07JA2."},{"key":"B4","doi-asserted-by":"publisher","first-page":"2986","DOI":"10.2337\/db06-0376","article-title":"Attenuation of insulin-evoked responses in brain networks controlling appetite and reward in insulin resistance: The cerebral basis for impaired control of food intake in metabolic syndrome?","volume":"55","author":"Anthony","year":"2006","journal-title":"Diabetes"},{"key":"B5","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1007\/s12311-012-0360-z","article-title":"Effects of leptin deficiency and replacement on cerebellar response to food-related cues.","volume":"12","author":"Berman","year":"2012","journal-title":"Cerebellum"},{"key":"B6","doi-asserted-by":"publisher","first-page":"660","DOI":"10.1038\/nrn4019","article-title":"Hippocampal insulin resistance and cognitive dysfunction.","volume":"16","author":"Biessels","year":"2015","journal-title":"Nat. Rev. Neurosci."},{"key":"B7","doi-asserted-by":"publisher","first-page":"183","DOI":"10.1146\/annurev-nutr-071816-064855","article-title":"Brain on fire: Incentive salience, hedonic hot spots, dopamine, obesity, and other hunger games.","volume":"37","author":"Cameron","year":"2017","journal-title":"Annu. Rev. Nutr."},{"key":"B8","doi-asserted-by":"publisher","first-page":"2489","DOI":"10.2337\/dc10-0851","article-title":"Metabolic syndrome, brain magnetic resonance imaging, and cognition.","volume":"33","author":"Cavalieri","year":"2010","journal-title":"Diabetes Care"},{"key":"B9","doi-asserted-by":"publisher","first-page":"538","DOI":"10.1016\/j.physbeh.2010.01.008","article-title":"Sex-based differences in the behavioral and neuronal responses to food.","volume":"99","author":"Cornier","year":"2010","journal-title":"Physiol. Behav."},{"key":"B10","doi-asserted-by":"publisher","first-page":"2382","DOI":"10.1093\/brain\/awu132","article-title":"The hubs of the human connectome are generally implicated in the anatomy of brain disorders.","volume":"137","author":"Crossley","year":"2014","journal-title":"Brain"},{"key":"B11","doi-asserted-by":"publisher","first-page":"136","DOI":"10.1159\/000353953","article-title":"Identification of pleiotropic genetic effects on obesity and brain anatomy.","volume":"75","author":"Curran","year":"2013","journal-title":"Hum. Hered."},{"key":"B12","doi-asserted-by":"publisher","first-page":"2375","DOI":"10.1093\/brain\/awm184","article-title":"Anatomically related grey and white matter abnormalities in adolescent-onset schizophrenia.","volume":"130","author":"Douaud","year":"2007","journal-title":"Brain"},{"key":"B13","first-page":"1","article-title":"Prevalence of metabolic syndrome among adults 20 years of age and over, by sex, age, race and ethnicity, and body mass index: United States, 2003\u20132006.","volume":"13","author":"Ervin","year":"2009","journal-title":"Natl. Health Stat. Rep."},{"key":"B14","doi-asserted-by":"publisher","first-page":"774","DOI":"10.1016\/j.neuroimage.2012.01.021","article-title":"FreeSurfer.","volume":"62","author":"Fischl","year":"2012","journal-title":"Neuroimage"},{"key":"B15","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1016\/S2213-8587(14)70148-2","article-title":"Glucose regulation, cognition, and brain MRI in type 2 diabetes: A systematic review.","volume":"3","author":"Geijselaers","year":"2014","journal-title":"Lancet Diabetes Endocrinol."},{"key":"B16","doi-asserted-by":"publisher","first-page":"1775","DOI":"10.1111\/dom.14391","article-title":"Sex differences in risk factors for cognitive decline and dementia, including death as a competing risk, in individuals with diabetes: Results from the ADVANCE trial.","volume":"23","author":"Gong","year":"2021","journal-title":"Diabetes Obes. Metab."},{"key":"B17","doi-asserted-by":"publisher","first-page":"68","DOI":"10.1093\/arclin\/acu066","article-title":"Neurocognitive function among middle-aged and older hispanic\/latinos: Results from the hispanic community health study\/study of latinos.","volume":"30","author":"Gonzalez","year":"2015","journal-title":"Arch. Clin. Neuropsychol."},{"key":"B18","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1006\/nimg.2001.0786","article-title":"Voxel-based morphometric study.","volume":"14","author":"Good","year":"2001","journal-title":"Neuroimage"},{"key":"B19","doi-asserted-by":"publisher","first-page":"285","DOI":"10.1161\/CIRCULATIONAHA.105.169405","article-title":"Diagnosis and management of the metabolic syndrome: An American heart association\/national heart, lung, and blood institute scientific statement: Executive summary.","volume":"112","author":"Grundy","year":"2005","journal-title":"Circulation"},{"key":"B20","doi-asserted-by":"publisher","first-page":"e141260","DOI":"10.1371\/journal.pone.0141260","article-title":"The relationship between native American ancestry, body mass index and diabetes risk among Mexican-Americans.","volume":"10","author":"Hu","year":"2015","journal-title":"PLoS One"},{"key":"B21","doi-asserted-by":"publisher","first-page":"149","DOI":"10.1016\/j.neuroimage.2015.07.086","article-title":"Association between waist circumference and gray matter volume in 2344 individuals from two adult community-based samples.","volume":"122","author":"Janowitz","year":"2015","journal-title":"Neuroimage"},{"key":"B22","doi-asserted-by":"publisher","first-page":"2232","DOI":"10.2337\/db14-0568","article-title":"Insulin action in brain regulates systemic metabolism and brain function.","volume":"63","author":"Kleinridders","year":"2014","journal-title":"Diabetes"},{"key":"B23","doi-asserted-by":"publisher","first-page":"957","DOI":"10.1002\/hbm.20235","article-title":"Retrospective motion correction protocol for high-resolution anatomical MRI.","volume":"27","author":"Kochunov","year":"2006","journal-title":"Hum. Brain Mapp."},{"key":"B24","doi-asserted-by":"publisher","first-page":"189","DOI":"10.1016\/j.neuroimage.2015.10.050","article-title":"The common genetic influence over processing speed and white matter microstructure: Evidence from the Old Order Amish and Human Connectome Projects.","volume":"125","author":"Kochunov","year":"2016","journal-title":"Neuroimage"},{"key":"B25","doi-asserted-by":"publisher","first-page":"3575","DOI":"10.1002\/hbm.24617","article-title":"A neural signature of metabolic syndrome.","volume":"40","author":"Kotkowski","year":"2019","journal-title":"Hum. Brain Mapp."},{"key":"B26","doi-asserted-by":"publisher","first-page":"295","DOI":"10.1007\/s12311-020-01212-9","article-title":"Using the schmahmann syndrome scale to assess cognitive impairment in young adults with metabolic syndrome: A hypothesis-generating report.","volume":"20","author":"Kotkowski","year":"2020","journal-title":"Cerebellum"},{"key":"B27","doi-asserted-by":"publisher","first-page":"1737","DOI":"10.1002\/hbm.22021","article-title":"Relationships between gray matter, body mass index, and waist circumference in healthy adults.","volume":"34","author":"Kurth","year":"2013","journal-title":"Hum. Brain Mapp."},{"key":"B28","doi-asserted-by":"publisher","first-page":"819","DOI":"10.1016\/j.neubiorev.2013.03.006","article-title":"Localized grey matter atrophy in multiple sclerosis: A meta-analysis of voxel-based morphometry studies and associations with functional disability.","volume":"37","author":"Lansley","year":"2013","journal-title":"Neurosci. Biobehav. Rev."},{"key":"B29","doi-asserted-by":"publisher","first-page":"747","DOI":"10.1016\/j.clnu.2008.07.001","article-title":"Association of metabolic syndrome with cognitive function: The role of sex and age.","volume":"27","author":"Laudisio","year":"2008","journal-title":"Clin. Nutr."},{"key":"B30","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1007\/s00401-013-1190-x","article-title":"The neuropathology of obesity: Insights from human disease.","volume":"127","author":"Lee","year":"2014","journal-title":"Acta Neuropathol."},{"key":"B31","doi-asserted-by":"publisher","first-page":"e59153","DOI":"10.1371\/journal.pone.0059153","article-title":"Waist circumference independently associates with the risk of insulin resistance and type 2 diabetes in Mexican American Families.","volume":"8","author":"Mamtani","year":"2013","journal-title":"PLoS One"},{"key":"B32","doi-asserted-by":"publisher","first-page":"139","DOI":"10.1016\/j.neuroscience.2014.04.006","article-title":"Insulin resistance and gray matter volume in neurodegenerative disease.","volume":"13","author":"Morris","year":"2014","journal-title":"Neuroscience"},{"key":"B33","doi-asserted-by":"publisher","first-page":"651","DOI":"10.1007\/s11682-014-9348-2","article-title":"Meta-analyses of structural regional cerebral effects in type 1 and type 2 diabetes.","volume":"9","author":"Moulton","year":"2015","journal-title":"Brain Imaging Behav."},{"key":"B34","doi-asserted-by":"publisher","first-page":"1595","DOI":"10.2337\/diab.37.12.1595","article-title":"Banting lecture 1988: Role of insulin resistance in human disease.","volume":"37","author":"Reaven","year":"1988","journal-title":"Diabetes"},{"key":"B35","doi-asserted-by":"publisher","first-page":"136","DOI":"10.1007\/s00392-006-0351-5","article-title":"Gender differences in the metabolic syndrome and their role for cardiovascular disease.","volume":"95","author":"Regitz-Zagrosek","year":"2006","journal-title":"Clin. Res. Cardiol."},{"key":"B36","doi-asserted-by":"publisher","first-page":"137","DOI":"10.2337\/dc12-0493","article-title":"Microstructural white matter abnormalities and cognitive functioning in type 2 diabetes.","volume":"36","author":"Reijmer","year":"2012","journal-title":"Diabetes Care"},{"key":"B37","doi-asserted-by":"publisher","first-page":"1178","DOI":"10.1001\/archneur.1991.00530230086029","article-title":"An emerging concept: The cerebellar contribution to higher function.","volume":"48","author":"Schmahmann","year":"1991","journal-title":"Arch. Neurol."},{"key":"B38","doi-asserted-by":"publisher","first-page":"62","DOI":"10.1016\/j.neulet.2018.07.005","article-title":"The cerebellum and cognition.","volume":"688","author":"Schmahmann","year":"2018","journal-title":"Neurosci. Lett."},{"key":"B39","doi-asserted-by":"publisher","first-page":"S208","DOI":"10.1016\/j.neuroimage.2004.07.051","article-title":"Advances in functional and structural MR image analysis and implementation as FSL.","volume":"23","author":"Smith","year":"2004","journal-title":"Neuroimage"},{"key":"B40","doi-asserted-by":"publisher","first-page":"489","DOI":"10.1016\/j.neuroimage.2008.08.039","article-title":"Functional topography in the human cerebellum: A meta-analysis of neuroimaging studies.","volume":"44","author":"Stoodley","year":"2009","journal-title":"Neuroimage"},{"key":"B41","doi-asserted-by":"publisher","first-page":"8543","DOI":"10.1038\/ncomms9543","article-title":"Insulin enhances striatal dopamine release by activating cholinergic interneurons and thereby signals reward.","volume":"6","author":"Stouffer","year":"2015","journal-title":"Nat. Commun."},{"key":"B42","doi-asserted-by":"publisher","first-page":"621","DOI":"10.1007\/s11011-016-9792-3","article-title":"Alterations in white matter volume and integrity in obesity and type 2 diabetes.","volume":"31","author":"Van Bloemendaal","year":"2016","journal-title":"Metab. Brain Dis."},{"key":"B43","doi-asserted-by":"publisher","first-page":"843","DOI":"10.1212\/01.wnl.0000234037.91185.99","article-title":"Association of metabolic syndrome with Alzheimer disease.","volume":"67","author":"Vanhanen","year":"2006","journal-title":"Neurology"},{"key":"B44","doi-asserted-by":"publisher","first-page":"22","DOI":"10.1016\/j.nbd.2015.04.008","article-title":"The role of type 2 diabetes in neurodegeneration.","volume":"84","author":"Verdile","year":"2015","journal-title":"Neurobiol. Dis."},{"key":"B45","doi-asserted-by":"publisher","first-page":"1135","DOI":"10.1016\/j.neuroimage.2009.12.028","article-title":"Cortical thickness or gray matter volume? The importance of selecting the phenotype for imaging genetics studies.","volume":"15","author":"Winkler","year":"2010","journal-title":"Neuroimage"},{"key":"B46","doi-asserted-by":"publisher","first-page":"363","DOI":"10.1016\/j.biopsych.2015.11.023","article-title":"Posttraumatic stress disorder as a catalyst for the association between metabolic syndrome and reduced cortical thickness.","volume":"80","author":"Wolf","year":"2016","journal-title":"Biol. Psychiatry"},{"key":"B47","doi-asserted-by":"publisher","first-page":"1698","DOI":"10.1016\/j.jdiacomp.2017.09.001","article-title":"Brain gray matter changes in type 2 diabetes mellitus: A meta-analysis of whole-brain voxel-based morphometry study.","volume":"31","author":"Wu","year":"2017","journal-title":"J. Diabetes Complications"},{"key":"B48","doi-asserted-by":"publisher","first-page":"2060","DOI":"10.1161\/ATVBAHA.112.252759","article-title":"Impact of metabolic syndrome on cognition and brain: A selected review of the literature.","volume":"32","author":"Yates","year":"2012","journal-title":"Arterioscler. Thromb. Vasc. Biol."},{"key":"B49","doi-asserted-by":"publisher","first-page":"1216","DOI":"10.1016\/j.neuron.2012.03.004","article-title":"Predicting regional neurodegeneration from the healthy brain functional connectome.","volume":"73","author":"Zhou","year":"2012","journal-title":"Neuron"},{"key":"B50","doi-asserted-by":"publisher","first-page":"6411","DOI":"10.1038\/s41598-018-24398-9","article-title":"Allostatic load as a predictor of grey matter volume and white matter integrity in old age: The Whitehall II MRI study.","volume":"8","author":"Zsoldos","year":"2018","journal-title":"Sci. Rep."}],"container-title":["Frontiers in Aging Neuroscience"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fnagi.2022.999288\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,9,20]],"date-time":"2022-09-20T09:50:43Z","timestamp":1663667443000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fnagi.2022.999288\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9,20]]},"references-count":50,"alternative-id":["10.3389\/fnagi.2022.999288"],"URL":"https:\/\/doi.org\/10.3389\/fnagi.2022.999288","relation":{},"ISSN":["1663-4365"],"issn-type":[{"value":"1663-4365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,9,20]]},"article-number":"999288"}}