{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T02:40:59Z","timestamp":1781577659822,"version":"3.54.5"},"reference-count":43,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2021,5,14]],"date-time":"2021-05-14T00:00:00Z","timestamp":1620950400000},"content-version":"am","delay-in-days":133,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"},{"start":{"date-parts":[[2021,5,14]],"date-time":"2021-05-14T00:00:00Z","timestamp":1620950400000},"content-version":"vor","delay-in-days":133,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["U01 AG024904"],"award-info":[{"award-number":["U01 AG024904"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000005","name":"U.S. Department of Defense","doi-asserted-by":"publisher","award":["W81XWH\u201012\u20102\u20100012"],"award-info":[{"award-number":["W81XWH\u201012\u20102\u20100012"]}],"id":[{"id":"10.13039\/100000005","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000049","name":"National Institute on Aging","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000049","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000070","name":"National Institute of Biomedical Imaging and Bioengineering","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000070","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["alz-journals.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Alz &amp; Dem Diag Ass &amp; Dis Mo"],"published-print":{"date-parts":[[2021,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Genome\u2010wide association studies (GWAS) for late onset Alzheimer's disease (AD) may miss genetic variants relevant for delineating disease stages when using clinically defined case\/control as a phenotype due to its loose definition and heterogeneity.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We use a transfer learning technique to train three\u2010dimensional convolutional neural network (CNN) models based on structural magnetic resonance imaging (MRI) from the screening stage in the Alzheimer's Disease Neuroimaging Initiative consortium to derive image features that reflect AD progression.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      CNN\u2010derived image phenotypes are significantly associated with fasting metabolites related to early lipid metabolic changes as well as insulin resistance and with genetic variants mapped to candidate genes enriched for amyloid beta degradation, tau phosphorylation, calcium ion binding\u2010dependent synaptic loss,\n                      <jats:italic>APP<\/jats:italic>\n                      \u2010regulated inflammation response, and insulin resistance.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>This is the first attempt to show that non\u2010invasive MRI biomarkers are linked to AD progression characteristics, reinforcing their use in early AD diagnosis and monitoring.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/dad2.12140","type":"journal-article","created":{"date-parts":[[2021,5,14]],"date-time":"2021-05-14T04:15:40Z","timestamp":1620965740000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["Transfer learning\u2010trained convolutional neural networks identify novel MRI biomarkers of Alzheimer's disease progression"],"prefix":"10.1002","volume":"13","author":[{"given":"Yi","family":"Li","sequence":"first","affiliation":[{"name":"The Jackson Laboratory  Farmington Connecticut USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Annat","family":"Haber","sequence":"additional","affiliation":[{"name":"The Jackson Laboratory  Farmington Connecticut USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christoph","family":"Preuss","sequence":"additional","affiliation":[{"name":"The Jackson Laboratory  Bar Harbor Maine USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cai","family":"John","sequence":"additional","affiliation":[{"name":"The Jackson Laboratory  Farmington Connecticut USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Asli","family":"Uyar","sequence":"additional","affiliation":[{"name":"The Jackson Laboratory  Farmington Connecticut USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongtian Stanley","family":"Yang","sequence":"additional","affiliation":[{"name":"The Jackson Laboratory  Bar Harbor Maine USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Benjamin A.","family":"Logsdon","sequence":"additional","affiliation":[{"name":"Sage Bionetworks  Seattle Washington USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vivek","family":"Philip","sequence":"additional","affiliation":[{"name":"The Jackson Laboratory  Bar Harbor Maine USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"R. Krishna Murthy","family":"Karuturi","sequence":"additional","affiliation":[{"name":"The Jackson Laboratory  Farmington Connecticut USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gregory W.","family":"Carter","sequence":"additional","affiliation":[{"name":"The Jackson Laboratory  Farmington Connecticut USA"},{"name":"The Jackson Laboratory  Bar Harbor Maine USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"name":"The Alzheimer's Disease Neuroimaging Initiative","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2021,5,14]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jalz.2018.02.018"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41588-018-0311-9"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41588-019-0358-2"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.1038\/ng.2802"},{"key":"e_1_2_10_6_1","first-page":"301","article-title":"The personalized Alzheimer's disease cortical thickness index predicts likely pathology and clinical progression in mild cognitive impairment","volume":"10","author":"Racine AM","year":"2018","journal-title":"Assess Dis Monit"},{"key":"e_1_2_10_7_1","first-page":"15","article-title":"Disparate Voxel Based Morphometry (VBM) results between SPM and FSL softwares in ALS patients with frontotemporal dementia: which VBM results to consider?","author":"Rajagopalan V","year":"2015","journal-title":"BMC Neurology"},{"key":"e_1_2_10_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2010.01.042"},{"key":"e_1_2_10_9_1","first-page":"11","article-title":"Deep Learning in Alzheimer's Disease: diagnostic classification and prognostic prediction using neuroimaging data","author":"Jo T","year":"2019","journal-title":"Front Aging Neurosci"},{"key":"e_1_2_10_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neurad.2017.05.008"},{"key":"e_1_2_10_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.bbr.2018.02.017"},{"key":"e_1_2_10_12_1","doi-asserted-by":"crossref","unstructured":"LiR ZhangW SukHI et\u00a0al. Deep learning based imaging data completion for improved brain disease diagnosis.International Conference on Medical Image Computing and Computer\u2010Assisted Intervention.2014;17:305\u2010312.","DOI":"10.1007\/978-3-319-10443-0_39"},{"key":"e_1_2_10_13_1","unstructured":"Tien DuongV Hyung\u2010JeongY NguyenVQ et\u00a0al.Multimodal learning using convolution neural network and Sparse Autoencoder. in2017 IEEE International Conference on Big Data and Smart Computing (BigComp).2017."},{"key":"e_1_2_10_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2014.2372011"},{"key":"e_1_2_10_15_1","doi-asserted-by":"publisher","DOI":"10.1126\/science.1127647"},{"key":"e_1_2_10_16_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4615-5529-2_4"},{"key":"e_1_2_10_17_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4615-5529-2_2"},{"key":"e_1_2_10_18_1","doi-asserted-by":"crossref","unstructured":"HaraK KataokaH SatohY Can spatiotemporal 3D CNNs retrace the history of 2D CNNs and ImageNet? inIEEE\/CVF Conference on Computer Vision and Pattern Recognition.2018 IEEE.","DOI":"10.1109\/CVPR.2018.00685"},{"key":"e_1_2_10_19_1","doi-asserted-by":"publisher","DOI":"10.1016\/S1053-8119(04)00188-0"},{"key":"e_1_2_10_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/42.668698"},{"key":"e_1_2_10_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/3065386"},{"key":"e_1_2_10_22_1","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-49430-8_2"},{"key":"e_1_2_10_23_1","doi-asserted-by":"crossref","unstructured":"XieS GirshickR DollarP et\u00a0al.Aggregated residual transformations for deep neural networks.2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)2017.","DOI":"10.1109\/CVPR.2017.634"},{"key":"e_1_2_10_24_1","doi-asserted-by":"publisher","DOI":"10.1037\/h0071325"},{"key":"e_1_2_10_25_1","doi-asserted-by":"publisher","DOI":"10.2307\/1939574"},{"key":"e_1_2_10_26_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.2517-6161.1996.tb02080.x"},{"key":"e_1_2_10_27_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.dadm.2019.05.005"},{"key":"e_1_2_10_28_1","doi-asserted-by":"publisher","DOI":"10.1017\/S1041610209009405"},{"key":"e_1_2_10_29_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jalz.2017.01.020"},{"key":"e_1_2_10_30_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00125-013-2839-7"},{"key":"e_1_2_10_31_1","first-page":"8","article-title":"Functional mapping and annotation of genetic associations with FUMA","author":"Watanabe K","year":"2017","journal-title":"Nat Commun"},{"key":"e_1_2_10_32_1","doi-asserted-by":"publisher","DOI":"10.1001\/jamaneurol.2014.4040"},{"key":"e_1_2_10_33_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuron.2008.08.019"},{"key":"e_1_2_10_34_1","article-title":"A\u03b2\u2010dependent reduction of NCAM2\u2010mediated synaptic adhesion contributes to synapse loss in Alzheimer's disease","volume":"6","author":"Leshchyns'ka I","year":"2015","journal-title":"Nat Commun"},{"key":"e_1_2_10_35_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1471-4159.2011.07523.x"},{"key":"e_1_2_10_36_1","doi-asserted-by":"publisher","DOI":"10.1038\/tp.2015.152"},{"key":"e_1_2_10_37_1","doi-asserted-by":"publisher","DOI":"10.1038\/ng1207-1424"},{"key":"e_1_2_10_38_1","doi-asserted-by":"publisher","DOI":"10.1074\/jbc.M110.172106"},{"key":"e_1_2_10_39_1","doi-asserted-by":"publisher","DOI":"10.1126\/science.1195689"},{"key":"e_1_2_10_40_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41588-017-0022-7"},{"key":"e_1_2_10_41_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.brainresbull.2009.01.004"},{"key":"e_1_2_10_42_1","article-title":"The Alzheimer's Disease Metabolome: effects of Sex and APOE \u03b54 genotype","author":"Arnold M","year":"2019","journal-title":"bioRxiv"},{"key":"e_1_2_10_43_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11682-013-9262-z"},{"key":"e_1_2_10_44_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41588-018-0147-3"}],"container-title":["Alzheimer's &amp; Dementia: Diagnosis, Assessment &amp; Disease Monitoring"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/alz-journals.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/dad2.12140","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/alz-journals.onlinelibrary.wiley.com\/doi\/full-xml\/10.1002\/dad2.12140","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/alz-journals.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/dad2.12140","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/alz-journals.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/dad2.12140","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T05:09:21Z","timestamp":1780636161000},"score":1,"resource":{"primary":{"URL":"https:\/\/alz-journals.onlinelibrary.wiley.com\/doi\/10.1002\/dad2.12140"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,1]]},"references-count":43,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2021,1]]}},"alternative-id":["10.1002\/dad2.12140"],"URL":"https:\/\/doi.org\/10.1002\/dad2.12140","archive":["Portico"],"relation":{},"ISSN":["2352-8729","2352-8729"],"issn-type":[{"value":"2352-8729","type":"print"},{"value":"2352-8729","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,1]]},"assertion":[{"value":"2020-02-25","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2020-12-02","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2021-05-14","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e12140"}}