{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,4]],"date-time":"2026-11-04T01:19:55Z","timestamp":1793755195823,"version":"4.6.1"},"reference-count":74,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,3,2]],"date-time":"2026-03-02T00:00:00Z","timestamp":1772409600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T00:00:00Z","timestamp":1774483200000},"content-version":"vor","delay-in-days":24,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62571096"],"award-info":[{"award-number":["62571096"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100012542","name":"Sichuan Provincial Department of Science and Technology | Sichuan Province Science and Technology Support Program","doi-asserted-by":"publisher","award":["2025ZNSFSC0453"],"award-info":[{"award-number":["2025ZNSFSC0453"]}],"id":[{"id":"10.13039\/100012542","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Sichuan Province Innovative Talent Funding Project for Postdoctoral Fellows"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Transl Psychiatry"],"DOI":"10.1038\/s41398-026-03902-0","type":"journal-article","created":{"date-parts":[[2026,3,2]],"date-time":"2026-03-02T05:15:17Z","timestamp":1772428517000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Mapping heterogeneous brain structural subtypes in alzheimer\u2019s disease and mild cognitive impairment using normative models"],"prefix":"10.1038","volume":"16","author":[{"given":"Xiaotong","family":"Wei","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tingting","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ronglong","family":"Xiong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiuzhu","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junjun","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhenlan","family":"Jin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2471-0181","authenticated-orcid":false,"given":"Ling","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,3,2]]},"reference":[{"key":"3902_CR1","doi-asserted-by":"publisher","first-page":"1577","DOI":"10.1016\/S0140-6736(20)32205-4","volume":"397","author":"P Scheltens","year":"2021","unstructured":"Scheltens P, De Strooper B, Kivipelto M, Holstege H, Ch\u00e9telat G, Teunissen CE, et al. Alzheimer\u2019s disease. Lancet (London, England). 2021;397:1577\u201390.","journal-title":"Lancet (London, England)"},{"key":"3902_CR2","doi-asserted-by":"publisher","first-page":"1262","DOI":"10.1016\/S0140-6736(06)68542-5","volume":"367","author":"S Gauthier","year":"2006","unstructured":"Gauthier S, Reisberg B, Zaudig M, Petersen RC, Ritchie K, Broich K, et al. Mild cognitive impairment. Lancet (London, England). 2006;367:1262\u201370.","journal-title":"Lancet (London, England)"},{"key":"3902_CR3","doi-asserted-by":"publisher","first-page":"1201","DOI":"10.1212\/01.wnl.0000238517.59286.c5","volume":"67","author":"PJ Visser","year":"2006","unstructured":"Visser PJ, Kester A, Jolles J, Verhey F. Ten-year risk of dementia in subjects with mild cognitive impairment. Neurology. 2006;67:1201\u20137.","journal-title":"Neurology"},{"key":"3902_CR4","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1017\/S1092852900016151","volume":"13","author":"RC Petersen","year":"2008","unstructured":"Petersen RC, Negash S. Mild cognitive impairment: an overview. CNS Spectr. 2008;13:45\u201353.","journal-title":"CNS Spectr"},{"key":"3902_CR5","doi-asserted-by":"publisher","first-page":"1591","DOI":"10.1212\/WNL.0b013e31826e26b7","volume":"79","author":"TD Koepsell","year":"2012","unstructured":"Koepsell TD, Monsell SE. Reversion from mild cognitive impairment to normal or near-normal cognition: risk factors and prognosis. Neurology. 2012;79:1591\u20138.","journal-title":"Neurology"},{"key":"3902_CR6","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/alzrt155","volume":"5","author":"B Lam","year":"2013","unstructured":"Lam B, Masellis M, Freedman M, Stuss DT, Black SE. Clinical, imaging, and pathological heterogeneity of the Alzheimer\u2019s disease syndrome. Alzheimer\u2019s research & therapy. 2013;5:1.","journal-title":"Alzheimer\u2019s research & therapy"},{"key":"3902_CR7","first-page":"735","volume":"140","author":"A Dong","year":"2017","unstructured":"Dong A, Toledo JB, Honnorat N, Doshi J, Varol E, Sotiras A, et al. Heterogeneity of neuroanatomical patterns in prodromal Alzheimer\u2019s disease: links to cognition, progression and biomarkers. Brain : a journal of neurology. 2017;140:735\u201347.","journal-title":"Brain : a journal of neurology"},{"key":"3902_CR8","doi-asserted-by":"publisher","first-page":"436","DOI":"10.1212\/WNL.0000000000009058","volume":"94","author":"D Ferreira","year":"2020","unstructured":"Ferreira D, Nordberg A, Westman E. Biological subtypes of Alzheimer disease: A systematic review and meta-analysis. Neurology. 2020;94:436\u201348.","journal-title":"Neurology"},{"key":"3902_CR9","doi-asserted-by":"publisher","first-page":"235","DOI":"10.1136\/jnnp-2014-309582","volume":"87","author":"NM Scheltens","year":"2016","unstructured":"Scheltens NM, Galindo-Garre F, Pijnenburg YA, van der Vlies AE, Smits LL, Koene T, et al. The identification of cognitive subtypes in Alzheimer\u2019s disease dementia using latent class analysis. J Neurol Neurosurg Psychiatry. 2016;87:235\u201343.","journal-title":"J Neurol Neurosurg Psychiatry"},{"key":"3902_CR10","doi-asserted-by":"publisher","first-page":"2108","DOI":"10.1212\/WNL.0000000000003326","volume":"87","author":"EC Edmonds","year":"2016","unstructured":"Edmonds EC, Eppig J, Bondi MW, Leyden KM, Goodwin B, Delano-Wood L, et al. Heterogeneous cortical atrophy patterns in MCI not captured by conventional diagnostic criteria. Neurology. 2016;87:2108\u201316.","journal-title":"Neurology"},{"key":"3902_CR11","doi-asserted-by":"publisher","first-page":"2176","DOI":"10.1212\/WNL.0000000000004670","volume":"89","author":"SL Risacher","year":"2017","unstructured":"Risacher SL, Anderson WH, Charil A, Castelluccio PF, Shcherbinin S, Saykin AJ, et al. Alzheimer disease brain atrophy subtypes are associated with cognition and rate of decline. Neurology. 2017;89:2176\u201386.","journal-title":"Neurology"},{"key":"3902_CR12","doi-asserted-by":"publisher","first-page":"1792","DOI":"10.1007\/s11682-019-00115-6","volume":"14","author":"A Ezzati","year":"2020","unstructured":"Ezzati A, Zammit AR, Habeck C, Hall CB, Lipton RB. Detecting biological heterogeneity patterns in ADNI amnestic mild cognitive impairment based on volumetric MRI. Brain Imaging Behav. 2020;14:1792\u2013804.","journal-title":"Brain Imaging Behav"},{"key":"3902_CR13","doi-asserted-by":"publisher","first-page":"2400","DOI":"10.1093\/brain\/awae118","volume":"147","author":"H Baumeister","year":"2024","unstructured":"Baumeister H, Vogel JW, Insel PS, Kleineidam L, Wolfsgruber S, Stark M, et al. A generalizable data-driven model of atrophy heterogeneity and progression in memory clinic settings. Brain : a journal of neurology. 2024;147:2400\u201313.","journal-title":"Brain : a journal of neurology"},{"key":"3902_CR14","doi-asserted-by":"publisher","first-page":"3443","DOI":"10.1093\/brain\/awy264","volume":"141","author":"M Ten Kate","year":"2018","unstructured":"Ten Kate M, Dicks E, Visser PJ, van der Flier WM, Teunissen CE, Barkhof F, et al. Atrophy subtypes in prodromal Alzheimer\u2019s disease are associated with cognitive decline. Brain : a journal of neurology. 2018;141:3443\u201356.","journal-title":"Brain : a journal of neurology"},{"key":"3902_CR15","doi-asserted-by":"publisher","first-page":"278","DOI":"10.3390\/brainsci11020278","volume":"11","author":"B Zhang","year":"2021","unstructured":"Zhang B, Lin L, Wu S, Al-Masqari Z. Multiple subtypes of Alzheimer\u2019s disease base on brain atrophy pattern. Brain Sci. 2021;11:278.","journal-title":"Brain Sci"},{"key":"3902_CR16","doi-asserted-by":"publisher","first-page":"2946","DOI":"10.1093\/brain\/awab165","volume":"144","author":"S Verdi","year":"2021","unstructured":"Verdi S, Marquand AF, Schott JM, Cole JH. Beyond the average patient: how neuroimaging models can address heterogeneity in dementia. Brain : a journal of neurology. 2021;144:2946\u201353.","journal-title":"Brain : a journal of neurology"},{"key":"3902_CR17","doi-asserted-by":"publisher","first-page":"552","DOI":"10.1016\/j.biopsych.2015.12.023","volume":"80","author":"AF Marquand","year":"2016","unstructured":"Marquand AF, Rezek I, Buitelaar J, Beckmann CF. Understanding heterogeneity in clinical cohorts using normative models: beyond case-control studies. Biol Psychiatry. 2016;80:552\u201361.","journal-title":"Biol Psychiatry"},{"key":"3902_CR18","doi-asserted-by":"publisher","first-page":"382","DOI":"10.3109\/03014460.2012.694475","volume":"39","author":"TJ Cole","year":"2012","unstructured":"Cole TJ. The development of growth references and growth charts. Ann Hum Biol. 2012;39:382\u201394.","journal-title":"Ann Hum Biol"},{"key":"3902_CR19","doi-asserted-by":"publisher","first-page":"1146","DOI":"10.1001\/jamapsychiatry.2018.2467","volume":"75","author":"T Wolfers","year":"2018","unstructured":"Wolfers T, Doan NT, Kaufmann T, Aln\u00e6s D, Moberget T, Agartz I, et al. Mapping the heterogeneous phenotype of schizophrenia and bipolar disorder using normative models. JAMA psychiatry. 2018;75:1146\u201355.","journal-title":"JAMA psychiatry"},{"key":"3902_CR20","doi-asserted-by":"publisher","first-page":"967","DOI":"10.1016\/j.biopsych.2022.01.011","volume":"91","author":"X Shan","year":"2022","unstructured":"Shan X, Uddin LQ, Xiao J, He C, Ling Z, Li L, et al. Mapping the heterogeneous brain structural phenotype of autism spectrum disorder using the normative model. Biol Psychiatry. 2022;91:967\u201376.","journal-title":"Biol Psychiatry"},{"key":"3902_CR21","doi-asserted-by":"publisher","first-page":"936","DOI":"10.1016\/j.biopsych.2023.05.021","volume":"94","author":"X Sun","year":"2023","unstructured":"Sun X, Sun J, Lu X, Dong Q, Zhang L, Wang W, et al. Mapping neurophysiological subtypes of major depressive disorder using normative models of the functional connectome. Biol Psychiatry. 2023;94:936\u201347.","journal-title":"Biol Psychiatry"},{"key":"3902_CR22","doi-asserted-by":"publisher","first-page":"1034","DOI":"10.1016\/j.biopsych.2024.05.025","volume":"97","author":"Y Huo","year":"2024","unstructured":"Huo Y, Jing R, Li P, Chen P, Si J, Liu G, et al. Delineating the heterogeneity of Alzheimer\u2019s disease and mild cognitive impairment using normative models of dynamic brain functional networks. Biol Psychiatry. 2024;97:1034\u201344.","journal-title":"Biol Psychiatry"},{"key":"3902_CR23","doi-asserted-by":"publisher","first-page":"567","DOI":"10.1016\/j.bpsc.2018.11.013","volume":"4","author":"M Zabihi","year":"2019","unstructured":"Zabihi M, Oldehinkel M, Wolfers T, Frouin V, Goyard D, Loth E, et al. Dissecting the heterogeneous cortical anatomy of autism spectrum disorder using normative models. Biological psychiatry Cognitive neuroscience and neuroimaging. 2019;4:567\u201378.","journal-title":"Biological psychiatry Cognitive neuroscience and neuroimaging"},{"key":"3902_CR24","doi-asserted-by":"publisher","first-page":"314","DOI":"10.1017\/S0033291719000084","volume":"50","author":"T Wolfers","year":"2020","unstructured":"Wolfers T, Beckmann CF, Hoogman M, Buitelaar JK, Franke B, Marquand AF. Individual differences v. the average patient: mapping the heterogeneity in ADHD using normative models. Psychol Med. 2020;50:314\u201323.","journal-title":"Psychol Med"},{"key":"3902_CR25","doi-asserted-by":"publisher","DOI":"10.1186\/s12883-014-0204-1","volume":"14","author":"MA Shafto","year":"2014","unstructured":"Shafto MA, Tyler LK, Dixon M, Taylor JR, Rowe JB, Cusack R, et al. The cambridge centre for ageing and neuroscience (Cam-CAN) study protocol: a cross-sectional, lifespan, multidisciplinary examination of healthy cognitive ageing. BMC Neurol. 2014;14:204.","journal-title":"BMC Neurol"},{"key":"3902_CR26","doi-asserted-by":"publisher","first-page":"262","DOI":"10.1016\/j.neuroimage.2015.09.018","volume":"144","author":"JR Taylor","year":"2017","unstructured":"Taylor JR, Williams N, Cusack R, Auer T, Shafto MA, Dixon M, et al. The cambridge centre for ageing and neuroscience (Cam-CAN) data repository: structural and functional MRI, MEG, and cognitive data from a cross-sectional adult lifespan sample. Neuroimage. 2017;144:262\u20139.","journal-title":"Neuroimage"},{"key":"3902_CR27","doi-asserted-by":"publisher","unstructured":"LaMontagne PJ, Benzinger TLS, Morris JC, Keefe S, Hornbeck R, Xiong C, et al. OASIS-3: longitudinal neuroimaging, clinical, and cognitive dataset for normal aging and alzheimer disease. medRxiv. 2019 https:\/\/doi.org\/10.1101\/2019.12.13.19014902.","DOI":"10.1101\/2019.12.13.19014902"},{"key":"3902_CR28","doi-asserted-by":"publisher","first-page":"273","DOI":"10.1006\/nimg.2001.0978","volume":"15","author":"N Tzourio-Mazoyer","year":"2002","unstructured":"Tzourio-Mazoyer N, Landeau B, Papathanassiou D, Crivello F, Etard O, Delcroix N, et al. Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. Neuroimage. 2002;15:273\u201389.","journal-title":"Neuroimage"},{"key":"3902_CR29","doi-asserted-by":"publisher","first-page":"104","DOI":"10.1016\/j.neuroimage.2017.11.024","volume":"167","author":"JP Fortin","year":"2018","unstructured":"Fortin JP, Cullen N, Sheline YI, Taylor WD, Aselcioglu I, Cook PA, et al. Harmonization of cortical thickness measurements across scanners and sites. Neuroimage. 2018;167:104\u201320.","journal-title":"Neuroimage"},{"key":"3902_CR30","doi-asserted-by":"crossref","unstructured":"Carl Edward R, Christopher KIW. Model selection and adaptation of hyperparameters. Gaussian Processes for Machine Learning. MIT Press2005, pp 105-28.","DOI":"10.7551\/mitpress\/3206.003.0008"},{"key":"3902_CR31","doi-asserted-by":"publisher","first-page":"411","DOI":"10.1111\/1467-9868.00293","volume":"63","author":"R Tibshirani","year":"2002","unstructured":"Tibshirani R, Walther G, Hastie T. Estimating the number of clusters in a data set via the gap statistic. Journal of the Royal Statistical Society Series B: Statistical Methodology. 2002;63:411\u201323.","journal-title":"Journal of the Royal Statistical Society Series B: Statistical Methodology"},{"key":"3902_CR32","doi-asserted-by":"publisher","first-page":"156","DOI":"10.1002\/hbm.26108","volume":"44","author":"X Du","year":"2023","unstructured":"Du X, Wei X, Ding H, Yu Y, Xie Y, Ji Y, et al. Unraveling schizophrenia replicable functional connectivity disruption patterns across sites. Hum Brain Mapp. 2023;44:156\u201369.","journal-title":"Hum Brain Mapp"},{"key":"3902_CR33","doi-asserted-by":"publisher","DOI":"10.1192\/j.eurpsy.2023.2446","volume":"66","author":"C Chai","year":"2023","unstructured":"Chai C, Ding H, Du X, Xie Y, Man W, Zhang Y, et al. Dissociation between neuroanatomical and symptomatic subtypes in schizophrenia. European psychiatry : the journal of the Association of European Psychiatrists. 2023;66:e78.","journal-title":"European psychiatry : the journal of the Association of European Psychiatrists"},{"key":"3902_CR34","doi-asserted-by":"publisher","first-page":"eaav6221","DOI":"10.1126\/scitranslmed.aav6221","volume":"11","author":"M Ewers","year":"2019","unstructured":"Ewers M, Franzmeier N, Su\u00e1rez-Calvet M, Morenas-Rodriguez E, Caballero MAA, Kleinberger G, et al. Increased soluble TREM2 in cerebrospinal fluid is associated with reduced cognitive and clinical decline in Alzheimer\u2019s disease. Science translational medicine. 2019;11:eaav6221.","journal-title":"Science translational medicine"},{"key":"3902_CR35","doi-asserted-by":"publisher","DOI":"10.1016\/j.xcrm.2021.100467","volume":"2","author":"K Kwak","year":"2021","unstructured":"Kwak K, Giovanello KS, Bozoki A, Styner M, Dayan E. Subtyping of mild cognitive impairment using a deep learning model based on brain atrophy patterns. Cell reports Medicine. 2021;2:100467.","journal-title":"Cell reports Medicine"},{"key":"3902_CR36","doi-asserted-by":"publisher","first-page":"353","DOI":"10.1016\/j.neuroimage.2019.01.011","volume":"189","author":"A Arnatkeviciute","year":"2019","unstructured":"Arnatkeviciute A, Fulcher BD, Fornito A. A practical guide to linking brain-wide gene expression and neuroimaging data. Neuroimage. 2019;189:353\u201367.","journal-title":"Neuroimage"},{"key":"3902_CR37","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1002\/wics.51","volume":"2","author":"H Abdi","year":"2010","unstructured":"Abdi H. Partial least squares regression and projection on latent structure regression (PLS Regression). Wiley Interdisciplinary Reviews: Computational Statistics. 2010;2:97\u2013106.","journal-title":"Wiley Interdisciplinary Reviews: Computational Statistics"},{"key":"3902_CR38","first-page":"281","volume":"28","author":"F V\u00e1\u0161a","year":"2018","unstructured":"V\u00e1\u0161a F, Seidlitz J, Romero-Garcia R, Whitaker KJ, Rosenthal G, V\u00e9rtes PE, et al. Adolescent tuning of association cortex in human structural brain networks. Cerebral cortex (New York, NY : 1991). 2018;28:281\u201394.","journal-title":"Cerebral cortex (New York, NY : 1991)"},{"key":"3902_CR39","doi-asserted-by":"publisher","first-page":"9105","DOI":"10.1073\/pnas.1601745113","volume":"113","author":"KJ Whitaker","year":"2016","unstructured":"Whitaker KJ, V\u00e9rtes PE, Romero-Garcia R, V\u00e1\u0161a F, Moutoussis M, Prabhu G, et al. Adolescence is associated with genomically patterned consolidation of the hubs of the human brain connectome. Proc Natl Acad Sci USA. 2016;113:9105\u201310.","journal-title":"Proc Natl Acad Sci USA"},{"key":"3902_CR40","doi-asserted-by":"publisher","first-page":"9604","DOI":"10.1073\/pnas.1820754116","volume":"116","author":"SE Morgan","year":"2019","unstructured":"Morgan SE, Seidlitz J, Whitaker KJ, Romero-Garcia R, Clifton NE, Scarpazza C, et al. Cortical patterning of abnormal morphometric similarity in psychosis is associated with brain expression of schizophrenia-related genes. Proc Natl Acad Sci USA. 2019;116:9604\u20139.","journal-title":"Proc Natl Acad Sci USA"},{"key":"3902_CR41","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-019-09234-6","volume":"10","author":"Y Zhou","year":"2019","unstructured":"Zhou Y, Zhou B, Pache L, Chang M, Khodabakhshi AH, Tanaseichuk O, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun. 2019;10:1523.","journal-title":"Nat Commun"},{"key":"3902_CR42","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.neuroimage.2015.07.075","volume":"122","author":"ET Rolls","year":"2015","unstructured":"Rolls ET, Joliot M, Tzourio-Mazoyer N. Implementation of a new parcellation of the orbitofrontal cortex in the automated anatomical labeling atlas. Neuroimage. 2015;122:1\u20135.","journal-title":"Neuroimage"},{"key":"3902_CR43","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2019.116189","volume":"206","author":"ET Rolls","year":"2020","unstructured":"Rolls ET, Huang CC, Lin CP, Feng J, Joliot M. Automated anatomical labelling atlas 3. Neuroimage. 2020;206:116189.","journal-title":"Neuroimage"},{"key":"3902_CR44","first-page":"3508","volume":"26","author":"L Fan","year":"2016","unstructured":"Fan L, Li H, Zhuo J, Zhang Y, Wang J, Chen L, et al. The human brainnetome atlas: a new brain atlas based on connectional architecture. Cerebral cortex (New York, NY : 1991). 2016;26:3508\u201326.","journal-title":"Cerebral cortex (New York, NY : 1991)"},{"key":"3902_CR45","doi-asserted-by":"publisher","first-page":"193","DOI":"10.1007\/BF01908075","volume":"2","author":"L Hubert","year":"1985","unstructured":"Hubert L, Arabie PJJC. Comparing partitions. Journal of Classification. 1985;2:193\u2013218.","journal-title":"Journal of Classification"},{"key":"3902_CR46","doi-asserted-by":"publisher","first-page":"348","DOI":"10.1002\/acn3.51273","volume":"8","author":"W Pelkmans","year":"2021","unstructured":"Pelkmans W, Legdeur N, Ten Kate M, Barkhof F, Yaqub MM, Holstege H, et al. Amyloid-\u03b2, cortical thickness, and subsequent cognitive decline in cognitively normal oldest-old. Ann Clin Transl Neurol. 2021;8:348\u201358.","journal-title":"Ann Clin Transl Neurol"},{"key":"3902_CR47","doi-asserted-by":"publisher","first-page":"129","DOI":"10.3233\/JAD-201578","volume":"82","author":"DC Woodworth","year":"2021","unstructured":"Woodworth DC, Scambray KA, Corrada MM, Kawas CH, Sajjadi SA. Neuroimaging in the oldest-old: a review of the literature. Journal of Alzheimer\u2019s disease: JAD. 2021;82:129\u201347.","journal-title":"Journal of Alzheimer\u2019s disease: JAD"},{"key":"3902_CR48","doi-asserted-by":"publisher","first-page":"4459","DOI":"10.1093\/brain\/awac238","volume":"145","author":"J Luo","year":"2022","unstructured":"Luo J, Agboola F, Grant E, Morris JC, Masters CL, Albert MS, et al. Accelerated longitudinal changes and ordering of Alzheimer disease biomarkers across the adult lifespan. Brain: a journal of neurology. 2022;145:4459\u201373.","journal-title":"Brain: a journal of neurology"},{"key":"3902_CR49","doi-asserted-by":"publisher","first-page":"843","DOI":"10.1002\/alz.12079","volume":"16","author":"R de Flores","year":"2020","unstructured":"de Flores R, Wisse LEM, Das SR, Xie L, McMillan CT, Trojanowski JQ, et al. Contribution of mixed pathology to medial temporal lobe atrophy in Alzheimer\u2019s disease. Alzheimer\u2019s & dementia : the journal of the Alzheimer\u2019s Association. 2020;16:843\u201352.","journal-title":"Alzheimer\u2019s & dementia : the journal of the Alzheimer\u2019s Association"},{"key":"3902_CR50","doi-asserted-by":"publisher","first-page":"263","DOI":"10.1016\/j.jalz.2011.03.005","volume":"7","author":"GM McKhann","year":"2011","unstructured":"McKhann GM, Knopman DS, Chertkow H, Hyman BT, Jack CR Jr., et al. The diagnosis of dementia due to Alzheimer\u2019s disease: recommendations from the National Institute on Aging-Alzheimer\u2019s Association workgroups on diagnostic guidelines for Alzheimer\u2019s disease. Alzheimer\u2019s & dementia : the journal of the Alzheimer\u2019s Association. 2011;7:263\u20139.","journal-title":"Alzheimer\u2019s & dementia : the journal of the Alzheimer\u2019s Association"},{"key":"3902_CR51","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1016\/j.arr.2016.01.002","volume":"30","author":"L Pini","year":"2016","unstructured":"Pini L, Pievani M, Bocchetta M, Altomare D, Bosco P, Cavedo E, et al. Brain atrophy in Alzheimer\u2019s disease and aging. Ageing Res Rev. 2016;30:25\u201348.","journal-title":"Ageing Res Rev"},{"key":"3902_CR52","doi-asserted-by":"publisher","first-page":"S299","DOI":"10.1016\/j.jalz.2013.06.007","volume":"10","author":"LL Smits","year":"2014","unstructured":"Smits LL, Tijms BM, Benedictus MR, Koedam EL, Koene T, Reuling IE, et al. Regional atrophy is associated with impairment in distinct cognitive domains in Alzheimer\u2019s disease. Alzheimer\u2019s & dementia : the journal of the Alzheimer\u2019s Association. 2014;10:S299\u2013305.","journal-title":"Alzheimer\u2019s & dementia : the journal of the Alzheimer\u2019s Association"},{"key":"3902_CR53","doi-asserted-by":"publisher","first-page":"e2442","DOI":"10.1212\/WNL.0000000000207298","volume":"100","author":"S Verdi","year":"2023","unstructured":"Verdi S, Kia SM, Yong KXX, Tosun D, Schott JM, Marquand AF, et al. Revealing individual neuroanatomical heterogeneity in alzheimer disease using neuroanatomical normative modeling. Neurology. 2023;100:e2442\u201353.","journal-title":"Neurology"},{"key":"3902_CR54","doi-asserted-by":"publisher","first-page":"6998","DOI":"10.1002\/alz.14174","volume":"20","author":"S Verdi","year":"2024","unstructured":"Verdi S, Rutherford S, Fraza C, Tosun D, Altmann A, Raket LL, et al. Personalizing progressive changes to brain structure in Alzheimer\u2019s disease using normative modeling. Alzheimer\u2019s & dementia : the journal of the Alzheimer\u2019s Association. 2024;20:6998\u20137012.","journal-title":"Alzheimer\u2019s & dementia : the journal of the Alzheimer\u2019s Association"},{"key":"3902_CR55","doi-asserted-by":"publisher","first-page":"20954","DOI":"10.1073\/pnas.0906053106","volume":"106","author":"D Holland","year":"2009","unstructured":"Holland D, Brewer JB, Hagler DJ, Fennema-Notestine C, Dale AM. Subregional neuroanatomical change as a biomarker for Alzheimer\u2019s disease. Proc Natl Acad Sci USA. 2009;106:20954\u20139.","journal-title":"Proc Natl Acad Sci USA"},{"key":"3902_CR56","doi-asserted-by":"publisher","first-page":"511","DOI":"10.1016\/j.jalz.2013.09.003","volume":"10","author":"J Nettiksimmons","year":"2014","unstructured":"Nettiksimmons J, DeCarli C, Landau S, Beckett L. Biological heterogeneity in ADNI amnestic mild cognitive impairment. Alzheimer\u2019s & dementia : the journal of the Alzheimer\u2019s Association. 2014;10:511\u201321.e511.","journal-title":"Alzheimer\u2019s & dementia : the journal of the Alzheimer\u2019s Association"},{"key":"3902_CR57","doi-asserted-by":"publisher","first-page":"2944","DOI":"10.1093\/brain\/awac484","volume":"146","author":"JK Wisch","year":"2023","unstructured":"Wisch JK, Butt OH, Gordon BA, Schindler SE, Fagan AM, Henson RL, et al. Proteomic clusters underlie heterogeneity in preclinical Alzheimer\u2019s disease progression. Brain: a journal of neurology. 2023;146:2944\u201356.","journal-title":"Brain: a journal of neurology"},{"key":"3902_CR58","doi-asserted-by":"publisher","first-page":"648","DOI":"10.1212\/WNL.0b013e318281ccd3","volume":"80","author":"KK Leung","year":"2013","unstructured":"Leung KK, Bartlett JW, Barnes J, Manning EN, Ourselin S, Fox NC. Cerebral atrophy in mild cognitive impairment and Alzheimer disease: rates and acceleration. Neurology. 2013;80:648\u201354.","journal-title":"Neurology"},{"key":"3902_CR59","doi-asserted-by":"publisher","first-page":"750154","DOI":"10.3389\/fnagi.2021.750154","volume":"13","author":"L Chauveau","year":"2021","unstructured":"Chauveau L, Kuhn E, Palix C, Felisatti F, Ourry V, de La Sayette V, et al. Medial temporal lobe subregional atrophy in aging and Alzheimer\u2019s disease: a longitudinal study. Front Aging Neurosci. 2021;13:750154.","journal-title":"Front Aging Neurosci"},{"key":"3902_CR60","doi-asserted-by":"publisher","first-page":"141","DOI":"10.1186\/s13195-020-00712-4","volume":"12","author":"S Emrani","year":"2020","unstructured":"Emrani S, Arain HA, DeMarshall C, Nuriel T. APOE4 is associated with cognitive and pathological heterogeneity in patients with Alzheimer\u2019s disease: a systematic review. Alzheimer\u2019s research & therapy. 2020;12:141.","journal-title":"Alzheimer\u2019s research & therapy"},{"key":"3902_CR61","doi-asserted-by":"publisher","first-page":"109","DOI":"10.3233\/JAD-2012-110426","volume":"29","author":"F Cl\u00e9ment","year":"2012","unstructured":"Cl\u00e9ment F, Belleville S. Effect of disease severity on neural compensation of item and associative recognition in mild cognitive impairment. Journal of Alzheimer\u2019s disease: JAD. 2012;29:109\u201323.","journal-title":"Journal of Alzheimer\u2019s disease: JAD"},{"key":"3902_CR62","doi-asserted-by":"publisher","first-page":"447","DOI":"10.1007\/s00259-014-2919-z","volume":"42","author":"A Ashraf","year":"2015","unstructured":"Ashraf A, Fan Z, Brooks DJ, Edison P. Cortical hypermetabolism in MCI subjects: a compensatory mechanism?. Eur J Nucl Med Mol Imaging. 2015;42:447\u201358.","journal-title":"Eur J Nucl Med Mol Imaging"},{"key":"3902_CR63","volume":"9","author":"K Zhao","year":"2022","unstructured":"Zhao K, Zheng Q, Dyrba M, Rittman T, Li A, Che T, et al. Regional radiomics similarity networks reveal distinct subtypes and abnormality patterns in mild cognitive impairment. Advanced science (Weinheim, Baden-Wurttemberg, Germany). 2022;9:e2104538.","journal-title":"Advanced science (Weinheim, Baden-Wurttemberg, Germany)"},{"key":"3902_CR64","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1186\/s13195-023-01173-1","volume":"15","author":"R Mohanty","year":"2023","unstructured":"Mohanty R, Ferreira D, Nordberg A, Westman E. Associations between different tau-PET patterns and longitudinal atrophy in the Alzheimer\u2019s disease continuum: biological and methodological perspectives from disease heterogeneity. Alzheimer\u2019s research & therapy. 2023;15:37.","journal-title":"Alzheimer\u2019s research & therapy"},{"key":"3902_CR65","doi-asserted-by":"publisher","first-page":"421","DOI":"10.3390\/jpm14040421","volume":"14","author":"D Machado Reyes","year":"2024","unstructured":"Machado Reyes D, Chao H, Hahn J, Shen L, Yan P. For the Alzheimer\u2019s disease neuroimaging I. identifying progression-specific Alzheimer\u2019s subtypes using multimodal transformer. J Pers Med. 2024;14:421.","journal-title":"J Pers Med"},{"key":"3902_CR66","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-025-98338-9","volume":"15","author":"BS Rauchmann","year":"2025","unstructured":"Rauchmann BS, Ers\u00f6zl\u00fc E, Luedecke D, Franzmeier N, Perneczky R. Multimodal and longitudinal characterization of distinct tau and atrophy clusters in Alzheimer\u2019s disease spectrum. Sci Rep. 2025;15:18142.","journal-title":"Sci Rep"},{"key":"3902_CR67","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1186\/s13195-017-0283-5","volume":"9","author":"PS Aisen","year":"2017","unstructured":"Aisen PS, Cummings J, Jack CR Jr., Morris JC, Sperling R, Fr\u00f6lich L, et al. On the path to 2025: understanding the Alzheimer\u2019s disease continuum. Alzheimer\u2019s research & therapy. 2017;9:60.","journal-title":"Alzheimer\u2019s research & therapy"},{"key":"3902_CR68","volume":"2020","author":"M K\u00e4rkk\u00e4inen","year":"2020","unstructured":"K\u00e4rkk\u00e4inen M, Prakash M, Zare M, Tohka J, For The Alzheimer\u2019s Disease Neuroimaging I. Structural brain imaging phenotypes of mild cognitive impairment (MCI) and Alzheimer\u2019s disease (AD) found by hierarchical clustering. International journal of Alzheimer\u2019s disease. 2020;2020:2142854.","journal-title":"International journal of Alzheimer\u2019s disease"},{"key":"3902_CR69","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1038\/s41582-022-00749-z","volume":"19","author":"M Tzioras","year":"2023","unstructured":"Tzioras M, McGeachan RI, Durrant CS, Spires-Jones TL. Synaptic degeneration in Alzheimer disease. Nature reviews Neurology. 2023;19:19\u201338.","journal-title":"Nature reviews Neurology"},{"key":"3902_CR70","doi-asserted-by":"publisher","first-page":"661","DOI":"10.1161\/STROKEAHA.122.040578","volume":"54","author":"AV Andjelkovic","year":"2023","unstructured":"Andjelkovic AV, Situ M, Citalan-Madrid AF, Stamatovic SM, Xiang J, Keep RF. Blood-brain barrier dysfunction in normal aging and neurodegeneration: mechanisms, impact, and treatments. Stroke. 2023;54:661\u201372.","journal-title":"Stroke"},{"key":"3902_CR71","doi-asserted-by":"publisher","first-page":"446","DOI":"10.1038\/s41593-025-01873-x","volume":"28","author":"S Kedia","year":"2025","unstructured":"Kedia S, Simons M. Oligodendrocytes in Alzheimer\u2019s disease pathophysiology. Nat Neurosci. 2025;28:446\u201356.","journal-title":"Nat Neurosci"},{"key":"3902_CR72","doi-asserted-by":"publisher","first-page":"759","DOI":"10.1016\/j.biopsych.2022.06.019","volume":"93","author":"P Chen","year":"2023","unstructured":"Chen P, Yao H, Tijms BM, Wang P, Wang D, Song C, et al. Four distinct subtypes of Alzheimer\u2019s disease based on resting-state connectivity biomarkers. Biol Psychiatry. 2023;93:759\u201369.","journal-title":"Biol Psychiatry"},{"key":"3902_CR73","doi-asserted-by":"publisher","DOI":"10.1016\/j.brainres.2023.148675","volume":"1823","author":"P Chen","year":"2024","unstructured":"Chen P, Zhang S, Zhao K, Kang X, Rittman T, Liu Y. Robustly uncovering the heterogeneity of neurodegenerative disease by using data-driven subtyping in neuroimaging: A review. Brain Res. 2024;1823:148675.","journal-title":"Brain Res"},{"key":"3902_CR74","doi-asserted-by":"publisher","first-page":"1022","DOI":"10.1016\/j.biopsych.2024.12.009","volume":"97","author":"K Zhao","year":"2025","unstructured":"Zhao K, Chen P, Wang D, Zhou R, Ma G, Liu Y. A multiform heterogeneity framework for Alzheimer\u2019s disease based on multimodal neuroimaging. Biol Psychiatry. 2025;97:1022\u201333.","journal-title":"Biol Psychiatry"}],"container-title":["Translational Psychiatry"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41398-026-03902-0","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41398-026-03902-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41398-026-03902-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T13:05:00Z","timestamp":1774530300000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41398-026-03902-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3,2]]},"references-count":74,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["3902"],"URL":"https:\/\/doi.org\/10.1038\/s41398-026-03902-0","relation":{},"ISSN":["2158-3188"],"issn-type":[{"value":"2158-3188","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,3,2]]},"assertion":[{"value":"7 August 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 December 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 February 2026","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 March 2026","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare no biomedical financial interests or conflicts of interest.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}},{"value":"The original studies underlying the Cam-CAN, OASIS-3, and ADNI datasets received approval from the relevant Institutional Review Boards (IRBs) or ethics committees. The Cam-CAN study was approved by the Cambridgeshire 2 Research Ethics Committee (reference: 10\/H0308\/50). All participants in the OASIS-3 study were consented into Knight ADRC-related projects following procedures approved by the IRB of Washington University School of Medicine. For ADNI, study procedures and consent forms were approved by the IRBs of all participating centers. Written informed consent was obtained from all participants or their legally authorized representatives in the original studies. All datasets used in the present study were anonymized and contained no protected health information or identifiable participant images. All procedures involving human participants were conducted in accordance with the relevant guidelines and regulations and with the Declaration of Helsinki and its later amendments or comparable ethical standards.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}}],"article-number":"168"}}