{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"bioRxiv"}],"indexed":{"date-parts":[[2026,8,19]],"date-time":"2026-08-19T14:24:02Z","timestamp":1787149442265,"version":"build-2736575974"},"posted":{"date-parts":[[2026,8,16]]},"group-title":"Neuroscience","reference-count":50,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2026,8,16]],"date-time":"2026-08-16T00:00:00Z","timestamp":1786838400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"crossref","award":["T32 GM140935"],"award-info":[{"award-number":["T32 GM140935"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100000092","name":"National Library of Medicine","doi-asserted-by":"crossref","award":["5T15LM007359"],"award-info":[{"award-number":["5T15LM007359"]}],"id":[{"id":"10.13039\/100000092","id-type":"DOI","asserted-by":"crossref"}]},{"name":"National Center for Advancing Translational Science grant","award":["UL1TR002373"],"award-info":[{"award-number":["UL1TR002373"]}]},{"name":"National Center for Advancing Translational Science grant","award":["TL1TR002375"],"award-info":[{"award-number":["TL1TR002375"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2026,8,16]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                <jats:sec>\n                  <jats:title>BACKGROUND AND PURPOSE<\/jats:title>\n                  <jats:p>Neighborhood-level socioeconomic disadvantage is associated with adverse brain morphometry, yet whether these associations differ by biological sex remain opaque. Here, we investigated sex-specific associations between the area deprivation index and brain morphometry derived from routine clinical MRI in a real-world clinical population.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>MATERIALS AND METHODS<\/jats:title>\n                  <jats:p>Intracranial volume-normalized regional brain volumes were extracted from T1-weighted MRI examinations performed in 2,863 consecutive clinical patients (median age 54 years [IQR 38\u201368]; 61.2% female) at a single academic medical center and associated community partners using an automated atlas-based segmentation pipeline. Exploratory factor analysis was applied to 131 regional brain volumes to identify latent neuroanatomical morphometric networks. Sex-stratified linear regression models examined associations between area deprivation index national percentile rank and each factor score, adjusting for age, with correction for multiple comparisons.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>RESULTS<\/jats:title>\n                  <jats:p>\n                    Factor analysis identified five neuroanatomical morphometric networks: cerebellar (ML1), frontal\/executive (ML2), subcortical-ventricular (ML3), medial temporal\/limbic (ML4), and posterior cortical\/visual (ML5). In male patients (\n                    <jats:italic>n<\/jats:italic>\n                    = 1,112), linear regressions revealed that greater neighborhood-level socioeconomic disadvantage was significantly associated with lower factor scores on the cerebellar (\u03b2 = \u22120.006, 95% CI [\u22120.009, \u22120.003],\n                    <jats:italic>P<\/jats:italic>\n                    &lt; .001), medial temporal\/limbic (\u03b2 = \u22120.004, 95% CI [\u22120.007, \u22120.001],\n                    <jats:italic>P<\/jats:italic>\n                    = .01), and frontal\/executive (\u03b2 = \u22120.004, 95% CI [\u22120.007, \u22120.0004],\n                    <jats:italic>P<\/jats:italic>\n                    = .04) networks. No significant associations were observed in female patients (all\n                    <jats:italic>P<\/jats:italic>\n                    s \u2265 .61).\n                  <\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>CONCLUSIONS<\/jats:title>\n                  <jats:p>In a real-world clinical population, neighborhood-level socioeconomic disadvantage was associated with lower regional brain volumes across cerebellar, frontal\/executive, and medial temporal\/limbic neuroanatomical morphometric networks in male but not female patients. These findings suggest that the neuroanatomical correlates of neighborhood disadvantage may be sex-specific, and that sex-stratified analyses may be necessary to fully characterize the relationship between the social exposome and brain morphometry in clinical neuroimaging research.<\/jats:p>\n                <\/jats:sec>","DOI":"10.64898\/2026.08.10.743987","type":"posted-content","created":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T04:40:38Z","timestamp":1786941638000},"source":"Crossref","is-referenced-by-count":0,"title":["Sex-Specific Regional Brain Morphometric Correlates of Neighborhood Socioeconomic Disadvantage in Clinical Neuroimaging"],"prefix":"10.64898","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4625-5642","authenticated-orcid":false,"given":"Ethan H.","family":"Willbrand","sequence":"first","affiliation":[{"name":"Medical Scientist Training Program, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States"},{"name":"Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States"},{"name":"Neuroscience Training Program, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luis A.","family":"Vazquez","sequence":"additional","affiliation":[{"name":"Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States"},{"name":"Neuroscience Training Program, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael B.","family":"Fromandi","sequence":"additional","affiliation":[{"name":"Medical Scientist Training Program, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States"},{"name":"Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States"},{"name":"Department of Biostatistics and Medical Informatics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Paloma C.","family":"Frautschi","sequence":"additional","affiliation":[{"name":"Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Troy B.","family":"Powell","sequence":"additional","affiliation":[{"name":"Medical Scientist Training Program, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John-Paul J.","family":"Yu","sequence":"additional","affiliation":[{"name":"Medical Scientist Training Program, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States"},{"name":"Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States"},{"name":"Neuroscience Training Program, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States"},{"name":"Department of Biostatistics and Medical Informatics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA"},{"name":"Department of Psychiatry, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"54368","reference":[{"key":"2026081906251107000_2026.08.10.743987v1.1","doi-asserted-by":"crossref","first-page":"116485","DOI":"10.1016\/j.envres.2023.116485","article-title":"Integrating the social environment with an equity perspective into the exposome paradigm: A new conceptual framework of the Social Exposome","volume":"233","year":"2023","journal-title":"Environ Res"},{"key":"2026081906251107000_2026.08.10.743987v1.2","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMp1802313"},{"key":"2026081906251107000_2026.08.10.743987v1.3","doi-asserted-by":"crossref","first-page":"102373","DOI":"10.1016\/j.cpcardiol.2024.102373","article-title":"Social determinants of health and its impact on cardiovascular disease in underserved populations: A critical review","volume":"49","year":"2024","journal-title":"Curr Probl Cardiol"},{"key":"2026081906251107000_2026.08.10.743987v1.4","doi-asserted-by":"publisher","DOI":"10.1080\/13607863.2019.1594169"},{"key":"2026081906251107000_2026.08.10.743987v1.5","doi-asserted-by":"crossref","first-page":"822","DOI":"10.1001\/jamapediatrics.2015.1475","article-title":"Association of child poverty, brain development, and academic achievement","volume":"169","year":"2015","journal-title":"JAMA Pediatr"},{"key":"2026081906251107000_2026.08.10.743987v1.6","doi-asserted-by":"crossref","first-page":"451","DOI":"10.1001\/jamaneurol.2019.4501","article-title":"Association of neighborhood-level disadvantage with cerebral and hippocampal volume","volume":"77","year":"2020","journal-title":"JAMA Neurol"},{"key":"2026081906251107000_2026.08.10.743987v1.7","doi-asserted-by":"crossref","first-page":"e2512289","DOI":"10.1001\/jamanetworkopen.2025.12289","article-title":"Adverse social exposome during the life course and vascular brain injury","volume":"8","year":"2025","journal-title":"JAMA Netw Open"},{"key":"2026081906251107000_2026.08.10.743987v1.8","doi-asserted-by":"crossref","first-page":"e2416484","DOI":"10.1001\/jamanetworkopen.2024.16484","article-title":"Aspects of area deprivation index in relation to hippocampal volume among children","volume":"7","year":"2024","journal-title":"JAMA Netw Open"},{"key":"2026081906251107000_2026.08.10.743987v1.9","first-page":"139","article-title":"Geographic measures of early life-course social exposome in the evaluation of structural neuroanatomy: A scoping review","volume":"11","year":"2026","journal-title":"Biol Psychiatry Cogn Neurosci Neuroimaging"},{"key":"2026081906251107000_2026.08.10.743987v1.10","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1186\/s13293-025-00739-y","article-title":"Sex-based associations between neighborhood disadvantage and brain-gut alterations in individuals with irritable bowel syndrome","volume":"16","year":"2025","journal-title":"Biol Sex Differ"},{"key":"2026081906251107000_2026.08.10.743987v1.11","doi-asserted-by":"publisher","DOI":"10.64898\/2026.03.16.712147"},{"key":"2026081906251107000_2026.08.10.743987v1.12","doi-asserted-by":"publisher","DOI":"10.1016\/j.neubiorev.2013.12.004"},{"key":"2026081906251107000_2026.08.10.743987v1.13","doi-asserted-by":"publisher","DOI":"10.1038\/nn.4112"},{"key":"2026081906251107000_2026.08.10.743987v1.14","doi-asserted-by":"publisher","DOI":"10.1016\/j.jalz.2018.04.008"},{"key":"2026081906251107000_2026.08.10.743987v1.15","first-page":"1128177","article-title":"Editorial: Sex differences in cerebrovascular diseases","volume":"13","year":"2022","journal-title":"Front Neurol"},{"key":"2026081906251107000_2026.08.10.743987v1.16","doi-asserted-by":"publisher","DOI":"10.1038\/s41582-018-0032-9"},{"key":"2026081906251107000_2026.08.10.743987v1.17","doi-asserted-by":"publisher","DOI":"10.3389\/fneur.2019.00789"},{"key":"2026081906251107000_2026.08.10.743987v1.18","doi-asserted-by":"publisher","DOI":"10.1038\/mp.2017.62"},{"key":"2026081906251107000_2026.08.10.743987v1.19","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1038\/s43587-021-00044-4","article-title":"Disparities in the pace of biological aging among midlife adults of the same chronological age have implications for future frailty risk and policy","volume":"1","year":"2021","journal-title":"Nat Aging"},{"key":"2026081906251107000_2026.08.10.743987v1.20","doi-asserted-by":"crossref","first-page":"435","DOI":"10.1016\/j.nicl.2016.02.019","article-title":"Differential diagnosis of neurodegenerative diseases using structural MRI data","volume":"11","year":"2016","journal-title":"NeuroImage Clin"},{"key":"2026081906251107000_2026.08.10.743987v1.21","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2004.06.018"},{"key":"2026081906251107000_2026.08.10.743987v1.22","doi-asserted-by":"crossref","first-page":"11623","DOI":"10.1093\/cercor\/bhad396","article-title":"Brain asymmetry is globally different in males and females: exploring cortical volume, area, thickness, and mean curvature","volume":"33","year":"2023","journal-title":"Cereb Cortex"},{"key":"2026081906251107000_2026.08.10.743987v1.23","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1718418115"},{"key":"2026081906251107000_2026.08.10.743987v1.24","doi-asserted-by":"crossref","unstructured":"Machado AMC , Gee JC , Campos MFM . Exploratory Factor Analysis in Morphometry. In: Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI\u201999. Lecture Notes in Computer Science. Berlin, Heidelberg: Springer Berlin Heidelberg; 1999:378\u201385.","DOI":"10.1007\/10704282_41"},{"key":"2026081906251107000_2026.08.10.743987v1.25","first-page":"1","article-title":"Exploratory factor analysis with structured residuals for brain network data","volume":"5","year":"2021","journal-title":"Netw Neurosci"},{"key":"2026081906251107000_2026.08.10.743987v1.26","doi-asserted-by":"crossref","unstructured":"Li X , Pu F , Fan Y , et al. Age-related changes in brain structural covariance networks. Front Hum Neurosci 2013;7:98.","DOI":"10.3389\/fnhum.2013.00098"},{"key":"2026081906251107000_2026.08.10.743987v1.27","doi-asserted-by":"publisher","DOI":"10.1007\/BF02291575"},{"key":"2026081906251107000_2026.08.10.743987v1.28","doi-asserted-by":"publisher","DOI":"10.1037\/h0036316"},{"key":"2026081906251107000_2026.08.10.743987v1.29","doi-asserted-by":"publisher","DOI":"10.1037\/1082-989X.4.1.84"},{"key":"2026081906251107000_2026.08.10.743987v1.30","first-page":"1626","article-title":"Metabolic determinants of cerebellar circuit formation and maintenance","volume":"23","year":"2024","journal-title":"Cerebellum"},{"key":"2026081906251107000_2026.08.10.743987v1.31","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1010459107"},{"key":"2026081906251107000_2026.08.10.743987v1.32","doi-asserted-by":"crossref","unstructured":"Welberg L . Metabolism: Spotlight on aerobic glycolysis. Nat Rev Neurosci 2010;11:729.","DOI":"10.1038\/nrn2937"},{"key":"2026081906251107000_2026.08.10.743987v1.33","doi-asserted-by":"publisher","DOI":"10.1016\/j.neulet.2018.07.005"},{"key":"2026081906251107000_2026.08.10.743987v1.34","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2008.08.039"},{"key":"2026081906251107000_2026.08.10.743987v1.35","doi-asserted-by":"crossref","first-page":"100429","DOI":"10.1016\/j.ynstr.2022.100429","article-title":"The cerebellum and psychological trauma: A systematic review of neuroimaging studies","volume":"17","year":"2022","journal-title":"Neurobiol Stress"},{"key":"2026081906251107000_2026.08.10.743987v1.36","doi-asserted-by":"publisher","DOI":"10.1038\/npp.2015.252"},{"key":"2026081906251107000_2026.08.10.743987v1.37","doi-asserted-by":"publisher","DOI":"10.1146\/annurev.neuro.27.070203.144130"},{"key":"2026081906251107000_2026.08.10.743987v1.38","doi-asserted-by":"publisher","DOI":"10.3389\/neuro.09.068.2009"},{"key":"2026081906251107000_2026.08.10.743987v1.39","doi-asserted-by":"publisher","DOI":"10.1016\/j.biopsych.2014.04.020"},{"key":"2026081906251107000_2026.08.10.743987v1.40","unstructured":"Luria AR . Higher Cortical Functions in Man. Springer US; 1966."},{"key":"2026081906251107000_2026.08.10.743987v1.41","doi-asserted-by":"crossref","unstructured":"Stuss DT , Knight RT . Principles of Frontal Lobe Function. OUP USA; 2013.","DOI":"10.1093\/med\/9780199837755.001.0001"},{"key":"2026081906251107000_2026.08.10.743987v1.42","doi-asserted-by":"publisher","DOI":"10.1523\/JNEUROSCI.1745-22.2023"},{"key":"2026081906251107000_2026.08.10.743987v1.43","doi-asserted-by":"publisher","DOI":"10.1016\/j.cortex.2024.08.009"},{"key":"2026081906251107000_2026.08.10.743987v1.44","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0080954"},{"key":"2026081906251107000_2026.08.10.743987v1.45","doi-asserted-by":"publisher","DOI":"10.1111\/desc.12096"},{"key":"2026081906251107000_2026.08.10.743987v1.46","doi-asserted-by":"publisher","DOI":"10.1146\/annurev-med-052209-100430"},{"key":"2026081906251107000_2026.08.10.743987v1.47","doi-asserted-by":"publisher","DOI":"10.1093\/brain\/121.6.1013"},{"key":"2026081906251107000_2026.08.10.743987v1.48","doi-asserted-by":"publisher","DOI":"10.1146\/annurev-neuro-071714-033936"},{"key":"2026081906251107000_2026.08.10.743987v1.49","doi-asserted-by":"publisher","DOI":"10.1093\/cercor\/bhu214"},{"key":"2026081906251107000_2026.08.10.743987v1.50","doi-asserted-by":"crossref","first-page":"osad003","DOI":"10.1093\/exposome\/osad003","article-title":"Exposomics as a tool to investigate differences in health and disease by sex and gender","volume":"3","year":"2023","journal-title":"Exposome"}],"container-title":[],"original-title":[],"link":[{"URL":"https:\/\/syndication.highwire.org\/content\/doi\/10.64898\/2026.08.10.743987","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,19]],"date-time":"2026-08-19T13:25:21Z","timestamp":1787145921000},"score":1,"resource":{"primary":{"URL":"http:\/\/biorxiv.org\/lookup\/doi\/10.64898\/2026.08.10.743987"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8,16]]},"references-count":50,"URL":"https:\/\/doi.org\/10.64898\/2026.08.10.743987","relation":{},"subject":[],"published":{"date-parts":[[2026,8,16]]},"subtype":"preprint"}}