{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T23:45:39Z","timestamp":1783035939088,"version":"3.54.6"},"update-to":[{"DOI":"10.1371\/journal.pbio.3003498","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2025,12,2]],"date-time":"2025-12-02T00:00:00Z","timestamp":1764633600000}}],"reference-count":105,"publisher":"Public Library of Science (PLoS)","issue":"11","license":[{"start":{"date-parts":[[2025,11,21]],"date-time":"2025-11-21T00:00:00Z","timestamp":1763683200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001659","name":"Deutsche Forschungsgemeinschaft","doi-asserted-by":"publisher","award":["GE 2835\/2\u20131"],"award-info":[{"award-number":["GE 2835\/2\u20131"]}],"id":[{"id":"10.13039\/501100001659","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001659","name":"Deutsche Forschungsgemeinschaft","doi-asserted-by":"publisher","award":["GE 2835\/9-1"],"award-info":[{"award-number":["GE 2835\/9-1"]}],"id":[{"id":"10.13039\/501100001659","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001659","name":"Deutsche Forschungsgemeinschaft","doi-asserted-by":"publisher","award":["SFB 1451 \u2013 Project-ID 431549029"],"award-info":[{"award-number":["SFB 1451 \u2013 Project-ID 431549029"]}],"id":[{"id":"10.13039\/501100001659","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Ministry of Culture and Science of the State of Northrhine Westphalia","award":["PROFILNRW-2020-107-A"],"award-info":[{"award-number":["PROFILNRW-2020-107-A"]}]},{"name":"European Union\u00e2\u20ac\u2122s Horizon Europe Programme","award":["101147319"],"award-info":[{"award-number":["101147319"]}]}],"content-domain":{"domain":["www.plosbiology.org"],"crossmark-restriction":false},"short-container-title":["PLoS Biol"],"abstract":"<jats:p>\n                    The link between brain health and risk\/protective factors for non-communicable diseases (such as high blood pressure, high body mass index, diet, smoking, physical activity, etc.) is increasingly acknowledged. However, the specific effects that these factors have on brain health are still poorly understood, delaying their implementation in precision brain health. Here, we studied the multivariate relationships between risk factors for non-communicable diseases and brain structure, including cortical thickness (CT) and gray matter volume (GMV). Furthermore, we adopted a systems-level perspective to understand such relationships, by characterizing the cortical patterns (yielded in association to risk factors) with regards to brain morphological and functional features, as well as with neurotransmitter systems. Similarly, we related the pattern of risk\/protective factors dimensions with a peripheral marker of inflammation. First, we identified latent dimensions linking a broad set of risk factors for non-communicable diseases to parcel-wise CT and GMV across the whole cortex. Data was obtained from the UK Biobank (\n                    <jats:italic>n<\/jats:italic>\n                    \u2009=\u20097,370, age range\u2009=\u200946\u201381 years). We used regularized canonical correlation analysis (RCCA) embedded in a machine learning framework. This approach allows us to capture inter-individual variability in a multivariate association and to assess the generalizability of the model. The brain patterns (captured in association with risk\/protective factors) were characterized from a multi-level perspective, by performing correlations (spin tests) between them and different brain patterns of structure, function, and neurotransmitter systems. The association between the risk\/protective factors pattern and C-reactive protein (CRP, a marker of inflammation) was examined using Spearman correlation. We found two significant and partly replicable latent dimensions. One latent dimension linked cardiometabolic health to brain patterns of CT and GMV and was consistent across sexes. The other latent dimension linked physical robustness (including non-fat mass and strength) to patterns of CT and GMV, with the association to GMV being consistent across sexes and the association to CT appearing only in men. The CT and GMV patterns of both latent dimensions were associated to the binding potentials of several neurotransmitter systems. Finally, the cardiometabolic health dimension was correlated to CRP, while physical robustness was only very weakly associated to it. We observed robust, multi-level and multivariate links between both cardiometabolic health and physical robustness with respect to CT, GMV, and neurotransmitter systems. Interestingly, we found that cardiometabolic health and physical robustness are associated with not only increases in CT or GMV, but also with decreases of CT or GMV in some brain regions. Our results also suggested a role for low-grade chronic inflammation in the association between cardiometabolic health and brain structural health. These findings support the relevance of adopting a holistic perspective in health, by integrating neurocognitive and physical health. Moreover, our findings contribute to the challenge to the classical conceptualization of neuropsychiatric and physical illnesses as categorical entities. In this perspective, future studies should further examine the effects of risk\/protective factors on different brain regions in order to deepen our understanding of the clinical significance of such increased and decreased CT and GMV.\n                  <\/jats:p>","DOI":"10.1371\/journal.pbio.3003498","type":"journal-article","created":{"date-parts":[[2025,11,21]],"date-time":"2025-11-21T18:43:33Z","timestamp":1763750613000},"page":"e3003498","update-policy":"https:\/\/doi.org\/10.1371\/journal.pbio.corrections_policy","source":"Crossref","is-referenced-by-count":3,"title":["Cardiometabolic health and physical robustness map onto distinct patterns of brain structure and neurotransmitter systems"],"prefix":"10.1371","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4806-2863","authenticated-orcid":true,"given":"Eliana","family":"Nicolaisen-Sobesky","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5238-2448","authenticated-orcid":true,"given":"Somayeh","family":"Maleki Balajoo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8752-0938","authenticated-orcid":true,"given":"Mostafa","family":"Mahdipour","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4510-4933","authenticated-orcid":true,"given":"Agoston","family":"Mihalik","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mahnaz","family":"Olfati","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7163-3110","authenticated-orcid":true,"given":"Felix","family":"Hoffstaedter","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Janaina","family":"Mour\u00e3o-Miranda","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3999-3807","authenticated-orcid":true,"given":"Masoud","family":"Tahmasian","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Simon B.","family":"Eickhoff","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7087-7882","authenticated-orcid":true,"given":"Sarah","family":"Genon","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2025,11,21]]},"reference":[{"key":"pbio.3003498.ref001","volume-title":"Noncommunicable diseases: progress monitor 2022","author":"World Health Organization","year":"2022"},{"key":"pbio.3003498.ref002","volume-title":"Noncommunicable diseases country profiles 2018","author":"World Health Organization","year":"2018"},{"issue":"5","key":"pbio.3003498.ref003","article-title":"Life\u2019s essential 8: updating and enhancing the American Heart Association\u2019s construct of cardiovascular health: a presidential advisory from the American Heart Association","volume":"146","author":"DM Lloyd-Jones","year":"2022","journal-title":"Circulation"},{"issue":"10452","key":"pbio.3003498.ref004","doi-asserted-by":"crossref","first-page":"572","DOI":"10.1016\/S0140-6736(24)01296-0","article-title":"Dementia prevention, intervention, and care: 2024 report of the Lancet Standing Commission","volume":"404","author":"G Livingston","year":"2024","journal-title":"Lancet"},{"issue":"12","key":"pbio.3003498.ref005","doi-asserted-by":"crossref","first-page":"100665","DOI":"10.1016\/j.lanhl.2024.100665","article-title":"Next generation brain health: transforming global research and public health to promote prevention of dementia and reduce its risk in young adult populations","volume":"5","author":"FR Farina","year":"2024","journal-title":"Lancet Healthy Longev"},{"issue":"12","key":"pbio.3003498.ref006","doi-asserted-by":"crossref","first-page":"1822","DOI":"10.1038\/s41591-019-0675-0","article-title":"Chronic inflammation in the etiology of disease across the life span","volume":"25","author":"D Furman","year":"2019","journal-title":"Nat Med"},{"key":"pbio.3003498.ref007","doi-asserted-by":"crossref","first-page":"643","DOI":"10.1186\/1471-2458-14-643","article-title":"Epidemiologic studies of modifiable factors associated with cognition and dementia: systematic review and meta-analysis","volume":"14","author":"MA Beydoun","year":"2014","journal-title":"BMC Public Health"},{"issue":"9","key":"pbio.3003498.ref008","doi-asserted-by":"crossref","first-page":"4839","DOI":"10.1038\/s41380-020-0774-9","article-title":"Brain structural abnormalities in obesity: relation to age, genetic risk, and common psychiatric disorders\u00a0: evidence through univariate and multivariate mega-analysis including 6420 participants from the ENIGMA MDD working group","volume":"26","author":"N Opel","year":"2021","journal-title":"Mol Psychiatry"},{"issue":"7","key":"pbio.3003498.ref009","doi-asserted-by":"crossref","first-page":"1177","DOI":"10.1038\/ijo.2016.42","article-title":"Increased body mass index is associated with specific regional alterations in brain structure","volume":"40","author":"N Medic","year":"2016","journal-title":"Int J Obes (Lond)"},{"issue":"1","key":"pbio.3003498.ref010","doi-asserted-by":"crossref","first-page":"24246","DOI":"10.1038\/s41598-021-03343-3","article-title":"Body mass index but not genetic risk is longitudinally associated with altered structural brain parameters","volume":"11","author":"A T\u00fcngler","year":"2021","journal-title":"Sci Rep"},{"key":"pbio.3003498.ref011","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1016\/j.neurobiolaging.2016.07.010","article-title":"Obesity associated with increased brain age from midlife","volume":"47","author":"L Ronan","year":"2016","journal-title":"Neurobiol Aging"},{"issue":"1","key":"pbio.3003498.ref012","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1017\/S1041610214001744","article-title":"Association between body mass index and cortical thickness: among elderly cognitively normal men and women","volume":"27","author":"H Kim","year":"2015","journal-title":"Int Psychogeriatr"},{"issue":"1","key":"pbio.3003498.ref013","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1038\/s41398-021-01414-7","article-title":"Population-based body-brain mapping links brain morphology with anthropometrics and body composition","volume":"11","author":"TP Gurholt","year":"2021","journal-title":"Transl Psychiatry"},{"issue":"8","key":"pbio.3003498.ref014","doi-asserted-by":"crossref","DOI":"10.1212\/WNL.0000000000007966","article-title":"Measures of obesity are associated with MRI markers of brain aging: The Northern Manhattan Study","volume":"93","author":"MR Caunca","year":"2019","journal-title":"Neurology"},{"issue":"2","key":"pbio.3003498.ref015","doi-asserted-by":"crossref","first-page":"360","DOI":"10.1177\/0271678X17729111","article-title":"Gray matter structural networks are associated with cardiovascular risk factors in healthy older adults","volume":"38","author":"S Kharabian Masouleh","year":"2018","journal-title":"J Cereb Blood Flow Metab"},{"key":"pbio.3003498.ref016","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1016\/j.pscychresns.2006.01.009","article-title":"Effects of cerebrovascular risk factors on gray matter volume in adults aged 60-64 years: a voxel-based morphometric study","volume":"147","author":"X Chen","year":"2006","journal-title":"Psychiatry Res"},{"issue":"2","key":"pbio.3003498.ref017","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1007\/s40473-016-0077-2","article-title":"Aerobic exercise in people with schizophrenia: neural and neurocognitive benefits","volume":"3","author":"J Vakhrusheva","year":"2016","journal-title":"Curr Behav Neurosci Rep"},{"issue":"20","key":"pbio.3003498.ref018","doi-asserted-by":"crossref","first-page":"1744","DOI":"10.1212\/WNL.0000000000002121","article-title":"Mediterranean diet and brain structure in a multiethnic elderly cohort","volume":"85","author":"Y Gu","year":"2015","journal-title":"Neurology"},{"key":"pbio.3003498.ref019","doi-asserted-by":"crossref","first-page":"633619","DOI":"10.3389\/fneur.2021.633619","article-title":"The impact of common epidemiological factors on gray and white matter volumes in magnetic resonance imaging\u2014is prevention of brain degeneration possible?","volume":"12","author":"J Jack\u00f3w-Nowicka","year":"2021","journal-title":"Front Neurol"},{"issue":"6","key":"pbio.3003498.ref020","doi-asserted-by":"crossref","first-page":"1456","DOI":"10.1038\/s41591-023-02365-w","article-title":"Effects of urban living environments on mental health in adults","volume":"29","author":"J Xu","year":"2023","journal-title":"Nat Med"},{"issue":"8","key":"pbio.3003498.ref021","doi-asserted-by":"crossref","first-page":"675","DOI":"10.1016\/S2215-0366(19)30132-4","article-title":"The Lancet Psychiatry Commission: a blueprint for protecting physical health in people with mental illness","volume":"6","author":"J Firth","year":"2019","journal-title":"Lancet Psychiatry"},{"issue":"11","key":"pbio.3003498.ref022","first-page":"1055","article-title":"Canonical correlation analysis and partial least squares for identifying brain-behavior associations: a tutorial and a comparative study","volume":"7","author":"A Mihalik","year":"2022","journal-title":"Biol Psychiatry Cogn Neurosci Neuroimaging"},{"issue":"4","key":"pbio.3003498.ref023","doi-asserted-by":"crossref","first-page":"368","DOI":"10.1016\/j.biopsych.2019.12.001","article-title":"Multiple holdouts with stability: improving the generalizability of machine learning analyses of brain-behavior relationships","volume":"87","author":"A Mihalik","year":"2020","journal-title":"Biol Psychiatry"},{"key":"pbio.3003498.ref024","doi-asserted-by":"crossref","first-page":"116853","DOI":"10.1016\/j.neuroimage.2020.116853","article-title":"Neuroimaging contrast across the cortical hierarchy is the feature maximally linked to behavior and demographics","volume":"215","author":"F Han","year":"2020","journal-title":"Neuroimage"},{"key":"pbio.3003498.ref025","article-title":"Lower motor performance is linked with poor sleep quality, depressive symptoms, and grey matter volume alterations","author":"V K\u00fcppers","year":"2024","journal-title":"bioRxiv"},{"key":"pbio.3003498.ref026","article-title":"Data-driven identification of a left anterior hippocampus\u2019 morphological network associated with self-regulation","author":"S Maleki Balajoo","year":"2024","journal-title":"Res Square"},{"issue":"1","key":"pbio.3003498.ref027","doi-asserted-by":"crossref","first-page":"11536","DOI":"10.1038\/s41598-019-47277-3","article-title":"Brain-behaviour modes of covariation in healthy and clinically depressed young people","volume":"9","author":"A Mihalik","year":"2019","journal-title":"Sci Rep"},{"issue":"1","key":"pbio.3003498.ref028","doi-asserted-by":"crossref","first-page":"1297","DOI":"10.1038\/s42003-022-04244-5","article-title":"A cross-cohort replicable and heritable latent dimension linking behaviour to multi-featured brain structure","volume":"5","author":"E Nicolaisen-Sobesky","year":"2022","journal-title":"Commun Biol"},{"issue":"6","key":"pbio.3003498.ref029","doi-asserted-by":"crossref","first-page":"567","DOI":"10.1001\/jamapsychiatry.2023.0791","article-title":"Evaluation of brain-body health in individuals with common neuropsychiatric disorders","volume":"80","author":"YE Tian","year":"2023","journal-title":"JAMA Psychiatry"},{"key":"pbio.3003498.ref030","doi-asserted-by":"crossref","first-page":"202","DOI":"10.3389\/fnagi.2019.00202","article-title":"A metabolic obesity profile is associated with decreased gray matter volume in cognitively healthy older adults","volume":"11","author":"F Beyer","year":"2019","journal-title":"Front Aging Neurosci"},{"issue":"8","key":"pbio.3003498.ref031","doi-asserted-by":"crossref","DOI":"10.1212\/WNL.0000000000006947","article-title":"Association of peripheral blood pressure with gray matter volume in 19- to 40-year-old adults","volume":"92","author":"HL Schaare","year":"2019","journal-title":"Neurology"},{"issue":"7","key":"pbio.3003498.ref032","doi-asserted-by":"crossref","first-page":"3502","DOI":"10.1002\/hbm.23605","article-title":"Higher body mass index is associated with reduced posterior default mode connectivity in older adults","volume":"38","author":"F Beyer","year":"2017","journal-title":"Hum Brain Mapp"},{"issue":"9","key":"pbio.3003498.ref033","doi-asserted-by":"crossref","first-page":"540","DOI":"10.1038\/nrendo.2014.91","article-title":"Hormonal and neural mechanisms of food reward, eating behaviour and obesity","volume":"10","author":"S Murray","year":"2014","journal-title":"Nat Rev Endocrinol"},{"issue":"11","key":"pbio.3003498.ref034","doi-asserted-by":"crossref","first-page":"1569","DOI":"10.1038\/s41593-022-01186-3","article-title":"Mapping neurotransmitter systems to the structural and functional organization of the human neocortex","volume":"25","author":"JY Hansen","year":"2022","journal-title":"Nat Neurosci"},{"issue":"11","key":"pbio.3003498.ref035","doi-asserted-by":"crossref","first-page":"1472","DOI":"10.1038\/s41592-022-01625-w","article-title":"neuromaps: structural and functional interpretation of brain maps","volume":"19","author":"RD Markello","year":"2022","journal-title":"Nat Methods"},{"key":"pbio.3003498.ref036","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1016\/j.neuroimage.2017.12.027","article-title":"Systemic inflammation as a predictor of brain aging: contributions of physical activity, metabolic risk, and genetic risk","volume":"172","author":"F Corlier","year":"2018","journal-title":"Neuroimage"},{"key":"pbio.3003498.ref037","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/j.bbi.2015.03.015","article-title":"Brain morphology links systemic inflammation to cognitive function in midlife adults","volume":"48","author":"AL Marsland","year":"2015","journal-title":"Brain Behav Immun"},{"key":"pbio.3003498.ref038","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1016\/j.bbi.2014.04.001","article-title":"Obesity and neuroinflammation: a pathway to cognitive impairment","volume":"42","author":"AA Miller","year":"2014","journal-title":"Brain Behav Immun"},{"issue":"6","key":"pbio.3003498.ref039","doi-asserted-by":"crossref","first-page":"581","DOI":"10.1136\/jnnp-2023-332661","article-title":"Cardiometabolic risk factors and neurodegeneration: a review of the mechanisms underlying diabetes, obesity and hypertension in Alzheimer\u2019s disease","volume":"95","author":"V Patel","year":"2024","journal-title":"J Neurol Neurosurg Psychiatry"},{"key":"pbio.3003498.ref040","doi-asserted-by":"crossref","first-page":"637","DOI":"10.1016\/j.bbi.2024.04.033","article-title":"Obesity and the cerebral cortex: underlying neurobiology in mice and humans","volume":"119","author":"Y Patel","year":"2024","journal-title":"Brain Behav Immun"},{"issue":"5","key":"pbio.3003498.ref041","doi-asserted-by":"crossref","first-page":"307","DOI":"10.1038\/s41583-022-00584-7","article-title":"Linking interindividual variability in brain structure to behaviour","volume":"23","author":"S Genon","year":"2022","journal-title":"Nat Rev Neurosci"},{"issue":"11","key":"pbio.3003498.ref042","doi-asserted-by":"crossref","first-page":"1523","DOI":"10.1038\/nn.4393","article-title":"Multimodal population brain imaging in the UK Biobank prospective epidemiological study","volume":"19","author":"KL Miller","year":"2016","journal-title":"Nat Neurosci"},{"issue":"3","key":"pbio.3003498.ref043","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pmed.1001779","article-title":"UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age","volume":"12","author":"C Sudlow","year":"2015","journal-title":"PLoS Med"},{"key":"pbio.3003498.ref044","doi-asserted-by":"crossref","first-page":"400","DOI":"10.1016\/j.neuroimage.2017.10.034","article-title":"Image processing and Quality Control for the first 10,000 brain imaging datasets from UK Biobank","volume":"166","author":"F Alfaro-Almagro","year":"2018","journal-title":"Neuroimage"},{"issue":"1","key":"pbio.3003498.ref045","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.neuroimage.2010.06.010","article-title":"Automatic parcellation of human cortical gyri and sulci using standard anatomical nomenclature","volume":"53","author":"C Destrieux","year":"2010","journal-title":"Neuroimage"},{"issue":"1","key":"pbio.3003498.ref046","doi-asserted-by":"crossref","DOI":"10.1186\/s40537-025-01193-8","article-title":"Overview of leakage scenarios in supervised machine learning","volume":"12","author":"L Sasse","year":"2025","journal-title":"J Big Data"},{"key":"pbio.3003498.ref047","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1093\/biomet\/28.3-4.321","article-title":"Relations between two sets of variates","volume":"28","author":"H Hotelling","year":"1936","journal-title":"Biometrika"},{"key":"pbio.3003498.ref048","article-title":"On stability of canonical correlation analysis and partial least squares with application to brain-behavior associations","author":"M Helmer","year":"2023","journal-title":"BioRxiv"},{"issue":"2","key":"pbio.3003498.ref049","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1016\/0304-4076(76)90010-5","article-title":"Canonical ridge and econometrics of joint production","volume":"4","author":"HD Vinod","year":"1976","journal-title":"J Econometr"},{"issue":"12","key":"pbio.3003498.ref050","doi-asserted-by":"crossref","first-page":"2639","DOI":"10.1162\/0899766042321814","article-title":"Canonical correlation analysis: an overview with application to learning methods","volume":"16","author":"DR Hardoon","year":"2004","journal-title":"Neural Comput"},{"issue":"9","key":"pbio.3003498.ref051","doi-asserted-by":"crossref","first-page":"100804","DOI":"10.1016\/j.patter.2023.100804","article-title":"Leakage and the reproducibility crisis in machine-learning-based science","volume":"4","author":"S Kapoor","year":"2023","journal-title":"Patterns (N Y)"},{"key":"pbio.3003498.ref052","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1016\/j.jneumeth.2016.06.011","article-title":"A multiple hold-out framework for sparse partial least squares","volume":"271","author":"Alzheimer\u2019s Disease Initiative","year":"2016","journal-title":"J Neurosci Methods"},{"key":"pbio.3003498.ref053","doi-asserted-by":"crossref","first-page":"540","DOI":"10.1016\/j.neuroimage.2018.05.070","article-title":"On testing for spatial correspondence between maps of human brain structure and function","volume":"178","author":"AF Alexander-Bloch","year":"2018","journal-title":"Neuroimage"},{"issue":"1","key":"pbio.3003498.ref054","first-page":"120","article-title":"A high-resolution in vivo atlas of the human brain\u2019s serotonin system","volume":"37","author":"V Beliveau","year":"2017","journal-title":"J Neurosci"},{"issue":"1","key":"pbio.3003498.ref055","doi-asserted-by":"crossref","first-page":"447","DOI":"10.1016\/j.neuroimage.2012.07.001","article-title":"Normative database of the serotonergic system in healthy subjects using multi-tracer PET","volume":"63","author":"M Savli","year":"2012","journal-title":"NeuroImage"},{"issue":"1","key":"pbio.3003498.ref056","doi-asserted-by":"crossref","first-page":"4074","DOI":"10.1038\/s41598-018-22444-0","article-title":"Cerebral blood flow predicts differential neurotransmitter activity","volume":"8","author":"J Dukart","year":"2018","journal-title":"Sci Rep"},{"issue":"1","key":"pbio.3003498.ref057","doi-asserted-by":"crossref","first-page":"372","DOI":"10.1038\/s42003-022-03268-1","article-title":"Cellular and molecular signatures of in vivo imaging measures of GABAergic neurotransmission in the human brain","volume":"5","author":"PB Lukow","year":"2022","journal-title":"Commun Biol"},{"key":"pbio.3003498.ref058","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/j.sleep.2018.12.020","article-title":"Brain cholinergic alterations in idiopathic REM sleep behaviour disorder: a PET imaging study with 18F-FEOBV","volume":"58","author":"M-A Bedard","year":"2019","journal-title":"Sleep Med"},{"issue":"7615","key":"pbio.3003498.ref059","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1038\/nature18933","article-title":"A multi-modal parcellation of human cerebral cortex","volume":"536","author":"MF Glasser","year":"2016","journal-title":"Nature"},{"issue":"44","key":"pbio.3003498.ref060","doi-asserted-by":"crossref","first-page":"12574","DOI":"10.1073\/pnas.1608282113","article-title":"Situating the default-mode network along a principal gradient of macroscale cortical organization","volume":"113","author":"DS Margulies","year":"2016","journal-title":"Proc Natl Acad Sci U S A"},{"issue":"41","key":"pbio.3003498.ref061","doi-asserted-by":"crossref","first-page":"17757","DOI":"10.1073\/pnas.1010459107","article-title":"Regional aerobic glycolysis in the human brain","volume":"107","author":"SN Vaishnavi","year":"2010","journal-title":"Proc Natl Acad Sci U S A"},{"issue":"351","key":"pbio.3003498.ref062","article-title":"Insights into neuroepigenetics through human histone deacetylase PET imaging","volume":"8","author":"H-Y Wey","year":"2016","journal-title":"Sci Transl Med"},{"issue":"7416","key":"pbio.3003498.ref063","doi-asserted-by":"crossref","first-page":"391","DOI":"10.1038\/nature11405","article-title":"An anatomically comprehensive atlas of the adult human brain transcriptome","volume":"489","author":"MJ Hawrylycz","year":"2012","journal-title":"Nature"},{"key":"pbio.3003498.ref064","doi-asserted-by":"crossref","unstructured":"Markello RD, Arnatkeviciute A, Poline B, Fulcher BD. Standardizing workflows in imaging transcriptomics with the abagen toolbox. 2021:1\u201327.","DOI":"10.7554\/eLife.72129.sa2"},{"key":"pbio.3003498.ref065","doi-asserted-by":"crossref","first-page":"119149","DOI":"10.1016\/j.neuroimage.2022.119149","article-title":"Atlas of type 2 dopamine receptors in the human brain: age and sex dependent variability in a large PET cohort","volume":"255","author":"T Mal\u00e9n","year":"2022","journal-title":"Neuroimage"},{"issue":"7","key":"pbio.3003498.ref066","doi-asserted-by":"crossref","first-page":"1065","DOI":"10.2967\/jnumed.111.101626","article-title":"Quantification of dopamine transporter in human brain using PET with 18F-FE-PE2I","volume":"53","author":"T Sasaki","year":"2012","journal-title":"J Nucl Med"},{"issue":"1","key":"pbio.3003498.ref067","doi-asserted-by":"crossref","first-page":"196","DOI":"10.1038\/jcbfm.2009.195","article-title":"Kinetic modeling of the serotonin 5-HT(1B) receptor radioligand [(11)C]P943 in humans","volume":"30","author":"J-D Gallezot","year":"2010","journal-title":"J Cereb Blood Flow Metab"},{"issue":"3","key":"pbio.3003498.ref068","doi-asserted-by":"crossref","first-page":"1095","DOI":"10.1177\/0271678X16650697","article-title":"Determination of receptor occupancy in the presence of mass dose: [11C]GSK189254 PET imaging of histamine H3 receptor occupancy by PF-03654746","volume":"37","author":"J-D Gallezot","year":"2017","journal-title":"J Cereb Blood Flow Metab"},{"issue":"5","key":"pbio.3003498.ref069","doi-asserted-by":"crossref","first-page":"1179","DOI":"10.1007\/s00259-018-4252-4","article-title":"Sex differences in [11C]ABP688 binding: a positron emission tomography study of mGlu5 receptors","volume":"46","author":"K Smart","year":"2019","journal-title":"Eur J Nucl Med Mol Imaging"},{"issue":"3","key":"pbio.3003498.ref070","doi-asserted-by":"crossref","first-page":"586","DOI":"10.1016\/j.neuron.2012.12.028","article-title":"Individual variability in functional connectivity architecture of the human brain","volume":"77","author":"S Mueller","year":"2013","journal-title":"Neuron"},{"key":"pbio.3003498.ref071","doi-asserted-by":"crossref","unstructured":"Reardon PK, Seidlitz J, Vandekar S, Liu S, Patel R, Lalonde FM. Normative brain size variation and brain shape diversity in humans. 2018;1227:4\u20138.","DOI":"10.1126\/science.aar2578"},{"issue":"1","key":"pbio.3003498.ref072","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1007\/s00259-015-3167-6","article-title":"Characterization of age\/sex and the regional distribution of mGluR5 availability in the healthy human brain measured by high-resolution [(11)C]ABP688 PET","volume":"43","author":"JM DuBois","year":"2016","journal-title":"Eur J Nucl Med Mol Imaging"},{"key":"pbio.3003498.ref073","author":"M Galovic","year":"2021","journal-title":"In vivo NMDA receptor function in people with NMDA receptor antibody encephalitis"},{"key":"pbio.3003498.ref074","doi-asserted-by":"crossref","first-page":"118194","DOI":"10.1016\/j.neuroimage.2021.118194","article-title":"Validation of a combined image derived input function and venous sampling approach for the quantification of [18F]GE-179 PET binding in the brain","volume":"237","author":"M Galovic","year":"2021","journal-title":"Neuroimage"},{"issue":"3","key":"pbio.3003498.ref075","doi-asserted-by":"crossref","first-page":"423","DOI":"10.2967\/jnumed.113.130641","article-title":"Initial evaluation of 18F-GE-179, a putative PET Tracer for activated N-methyl D-aspartate receptors","volume":"55","author":"CJ McGinnity","year":"2014","journal-title":"J Nucl Med"},{"key":"pbio.3003498.ref076","doi-asserted-by":"crossref","first-page":"116922","DOI":"10.1016\/j.neuroimage.2020.116922","article-title":"Interindividual variability and lateralization of \u03bc-opioid receptors in the human brain","volume":"217","author":"T Kantonen","year":"2020","journal-title":"Neuroimage"},{"key":"pbio.3003498.ref077","first-page":"360","article-title":"Adult attachment system links with brain Mu opioid receptor availability in vivo. biological psychiatry","volume":"6","author":"O Turtonen","year":"2021","journal-title":"Cogn Neurosci Neuroimaging"},{"issue":"13","key":"pbio.3003498.ref078","doi-asserted-by":"crossref","first-page":"2539","DOI":"10.1038\/s41386-018-0199-1","article-title":"PET imaging reveals lower kappa opioid receptor availability in alcoholics but no effect of age","volume":"43","author":"A Vijay","year":"2018","journal-title":"Neuropsychopharmacology"},{"key":"pbio.3003498.ref079","doi-asserted-by":"crossref","first-page":"834","DOI":"10.1016\/j.neuroimage.2018.10.013","article-title":"Sex difference in brain CB1 receptor availability in man","volume":"184","author":"H Laurikainen","year":"2019","journal-title":"Neuroimage"},{"issue":"8","key":"pbio.3003498.ref080","doi-asserted-by":"crossref","first-page":"1313","DOI":"10.1038\/jcbfm.2015.46","article-title":"Imaging the cannabinoid CB1 receptor in humans with [11C]OMAR: assessment of kinetic analysis methods, test-retest reproducibility, and gender differences","volume":"35","author":"MD Normandin","year":"2015","journal-title":"J Cereb Blood Flow Metab"},{"key":"pbio.3003498.ref081","doi-asserted-by":"crossref","first-page":"117346","DOI":"10.1016\/j.neuroimage.2020.117346","article-title":"Cross-species functional alignment reveals evolutionary hierarchy within the connectome","volume":"223","author":"T Xu","year":"2020","journal-title":"Neuroimage"},{"issue":"18","key":"pbio.3003498.ref082","doi-asserted-by":"crossref","first-page":"2820","DOI":"10.1016\/j.neuron.2021.06.016","article-title":"Neurodevelopment of the association cortices: patterns, mechanisms, and implications for psychopathology","volume":"109","author":"VJ Sydnor","year":"2021","journal-title":"Neuron"},{"issue":"6","key":"pbio.3003498.ref083","article-title":"Cardiometabolic multimorbidity, genetic risk, and dementia: a prospective cohort study","volume":"3","author":"XY Tai","year":"2022","journal-title":"Lancet Healthy Longev"},{"key":"pbio.3003498.ref084","doi-asserted-by":"crossref","first-page":"308","DOI":"10.1016\/j.neubiorev.2020.04.001","article-title":"Cardiometabolic determinants of early and advanced brain alterations: insights from conventional and novel MRI techniques","volume":"115","author":"LWM Vergoossen","year":"2020","journal-title":"Neurosci Biobehav Rev"},{"issue":"2","key":"pbio.3003498.ref085","doi-asserted-by":"crossref","first-page":"700","DOI":"10.1002\/hbm.25680","article-title":"Cardiometabolic risk factors associated with brain age and accelerate brain ageing","volume":"43","author":"D Beck","year":"2022","journal-title":"Hum Brain Mapp"},{"issue":"6","key":"pbio.3003498.ref086","doi-asserted-by":"crossref","first-page":"776","DOI":"10.1038\/s41380-018-0058-9","article-title":"Is psychosis a multisystem disorder? A meta-review of central nervous system, immune, cardiometabolic, and endocrine alterations in first-episode psychosis and perspective on potential models","volume":"24","author":"T Pillinger","year":"2019","journal-title":"Mol Psychiatry"},{"issue":"1","key":"pbio.3003498.ref087","doi-asserted-by":"crossref","first-page":"1953","DOI":"10.1038\/s41467-023-37579-6","article-title":"Associations between mental health, blood pressure and the development of hypertension","volume":"14","author":"HL Schaare","year":"2023","journal-title":"Nat Commun"},{"issue":"3","key":"pbio.3003498.ref088","doi-asserted-by":"crossref","first-page":"180","DOI":"10.2174\/0113816128285578231218102020","article-title":"Interplay of G-proteins and serotonin in the neuroimmunoinflammatory model of chronic stress and depression: a narrative review","volume":"30","author":"E Gusev","year":"2024","journal-title":"Curr Pharm Des"},{"issue":"6","key":"pbio.3003498.ref089","doi-asserted-by":"crossref","first-page":"465","DOI":"10.1016\/S1474-4422(17)30084-4","article-title":"Neurological consequences of obesity","volume":"16","author":"PD O\u2019Brien","year":"2017","journal-title":"Lancet Neurol"},{"issue":"1","key":"pbio.3003498.ref090","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.pneurobio.2008.01.004","article-title":"Neurotransmitter, peptide and cytokine processes in relation to depressive disorder: comorbidity between depression and neurodegenerative disorders","volume":"85","author":"H Anisman","year":"2008","journal-title":"Prog Neurobiol"},{"issue":"1","key":"pbio.3003498.ref091","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1038\/s41398-024-02778-2","article-title":"Genetic evidence for causal effects of immune dysfunction in psychiatric disorders: where are we?","volume":"14","author":"O Iakunchykova","year":"2024","journal-title":"Transl Psychiatry"},{"key":"pbio.3003498.ref092","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1016\/j.pnpbp.2013.10.018","article-title":"Impact of inflammation on neurotransmitter changes in major depression: an insight into the action of antidepressants","volume":"48","author":"BE Leonard","year":"2014","journal-title":"Prog Neuropsychopharmacol Biol Psychiatry"},{"issue":"6","key":"pbio.3003498.ref093","doi-asserted-by":"crossref","first-page":"1503","DOI":"10.1007\/s11064-022-03569-1","article-title":"The potential crosstalk between the brain and visceral adipose tissue in Alzheimer\u2019s development","volume":"47","author":"TT Nguyen","year":"2022","journal-title":"Neurochem Res"},{"issue":"2","key":"pbio.3003498.ref094","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1177\/13872877251317624","article-title":"Longitudinal and concurrent C-reactive protein and diet associations with cognitive function in the population-based Troms\u00f8 study","volume":"104","author":"O Iakunchykova","year":"2025","journal-title":"J Alzheimers Dis"},{"issue":"1","key":"pbio.3003498.ref095","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1038\/s43856-024-00576-x","article-title":"Exposure to multiple ambient air pollutants changes white matter microstructure during early adolescence with sex-specific differences","volume":"4","author":"DL Cotter","year":"2024","journal-title":"Commun Med (Lond)"},{"key":"pbio.3003498.ref096","doi-asserted-by":"crossref","first-page":"375","DOI":"10.3389\/fpubh.2019.00375","article-title":"Gender difference in the effects of outdoor air pollution on cognitive function among elderly in Korea","volume":"7","author":"H Kim","year":"2019","journal-title":"Front Public Health"},{"issue":"8","key":"pbio.3003498.ref097","doi-asserted-by":"crossref","first-page":"2351","DOI":"10.3390\/jcm9082351","article-title":"Gender differences in association between air pollution and daily mortality in the capital of the green lungs of Poland-population-based study with 2,953,000 person-years of follow-up","volume":"9","author":"\u0141 Ku\u017ama","year":"2020","journal-title":"J Clin Med"},{"key":"pbio.3003498.ref098","doi-asserted-by":"crossref","first-page":"163980","DOI":"10.1016\/j.scitotenv.2023.163980","article-title":"Sex disparity in cognitive aging related to later-life exposure to ambient air pollution","volume":"886","author":"S Mo","year":"2023","journal-title":"Sci Total Environ"},{"issue":"9","key":"pbio.3003498.ref099","doi-asserted-by":"crossref","first-page":"3801","DOI":"10.3390\/ijerph10093801","article-title":"Extricating sex and gender in air pollution research: a community-based study on cardinal symptoms of exposure","volume":"10","author":"TH Oiamo","year":"2013","journal-title":"Int J Environ Res Public Health"},{"issue":"7","key":"pbio.3003498.ref100","doi-asserted-by":"crossref","DOI":"10.1111\/obr.13210","article-title":"Serotonin, food intake, and obesity","volume":"22","author":"KA van Galen","year":"2021","journal-title":"Obes Rev"},{"key":"pbio.3003498.ref101","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1016\/j.bbr.2014.08.065","article-title":"Serotonin controlling feeding and satiety","volume":"277","author":"J-P Voigt","year":"2015","journal-title":"Behav Brain Res"},{"issue":"12","key":"pbio.3003498.ref102","article-title":"Physical exercise-induced fatigue: the role of serotonergic and dopaminergic systems","volume":"50","author":"LMS Cordeiro","year":"2017","journal-title":"Braz J Med Biol Res"},{"issue":"4","key":"pbio.3003498.ref103","doi-asserted-by":"crossref","first-page":"391","DOI":"10.1017\/S1092852915000012","article-title":"Advances from neuroimaging studies in eating disorders","volume":"20","author":"GKW Frank","year":"2015","journal-title":"CNS Spectr"},{"key":"pbio.3003498.ref104","doi-asserted-by":"crossref","first-page":"101166","DOI":"10.1016\/j.lanepe.2024.101166","article-title":"Immuno-metabolic depression: from concept to implementation","volume":"48","author":"BWJH Penninx","year":"2024","journal-title":"Lancet Reg Health Eur"},{"issue":"1","key":"pbio.3003498.ref105","doi-asserted-by":"crossref","first-page":"114","DOI":"10.1007\/s11481-019-09851-4","article-title":"Where is dopamine and how do immune cells see it?: Dopamine-mediated immune cell function in health and disease","volume":"15","author":"SM Matt","year":"2020","journal-title":"J Neuroimmune Pharmacol"}],"updated-by":[{"DOI":"10.1371\/journal.pbio.3003498","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2025,12,2]],"date-time":"2025-12-02T00:00:00Z","timestamp":1764633600000}}],"container-title":["PLOS Biology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pbio.3003498","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,2]],"date-time":"2025-12-02T18:55:42Z","timestamp":1764701742000},"score":1,"resource":{"primary":{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pbio.3003498"}},"subtitle":[],"editor":[{"given":"Marcus","family":"Munaf\u00f2","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]}],"short-title":[],"issued":{"date-parts":[[2025,11,21]]},"references-count":105,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2025,11,21]]}},"URL":"https:\/\/doi.org\/10.1371\/journal.pbio.3003498","relation":{},"ISSN":["1545-7885"],"issn-type":[{"value":"1545-7885","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,11,21]]}}}