{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,4]],"date-time":"2026-04-04T17:41:51Z","timestamp":1775324511903,"version":"3.50.1"},"reference-count":44,"publisher":"Oxford University Press (OUP)","issue":"14","license":[{"start":{"date-parts":[[2019,7,8]],"date-time":"2019-07-08T00:00:00Z","timestamp":1562544000000},"content-version":"vor","delay-in-days":7,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61602384"],"award-info":[{"award-number":["61602384"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61333017"],"award-info":[{"award-number":["61333017"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Natural Science Basic Research Plan in Shaanxi Province of China","award":["2017JQ6001"],"award-info":[{"award-number":["2017JQ6001"]}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["2017M613202"],"award-info":[{"award-number":["2017M613202"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Science and Technology Foundation for Selected Overseas Chinese Scholar","award":["2017022"],"award-info":[{"award-number":["2017022"]}]},{"name":"Postdoctoral Science Foundation of Shaanxi","award":["2017BSHEDZZ81"],"award-info":[{"award-number":["2017BSHEDZZ81"]}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01 EB022574"],"award-info":[{"award-number":["R01 EB022574"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01 LM011360"],"award-info":[{"award-number":["R01 LM011360"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"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\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["P30 AG10133"],"award-info":[{"award-number":["P30 AG10133"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01 AG19771"],"award-info":[{"award-number":["R01 AG19771"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["IIS 1837964"],"award-info":[{"award-number":["IIS 1837964"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,7,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>Identifying the genetic basis of the brain structure, function and disorder by using the imaging quantitative traits (QTs) as endophenotypes is an important task in brain science. Brain QTs often change over time while the disorder progresses and thus understanding how the genetic factors play roles on the progressive brain QT changes is of great importance and meaning. Most existing imaging genetics methods only analyze the baseline neuroimaging data, and thus those longitudinal imaging data across multiple time points containing important disease progression information are omitted.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>We propose a novel temporal imaging genetic model which performs the multi-task sparse canonical correlation analysis (T-MTSCCA). Our model uses longitudinal neuroimaging data to uncover that how single nucleotide polymorphisms (SNPs) play roles on affecting brain QTs over the time. Incorporating the relationship of the longitudinal imaging data and that within SNPs, T-MTSCCA could identify a trajectory of progressive imaging genetic patterns over the time. We propose an efficient algorithm to solve the problem and show its convergence. We evaluate T-MTSCCA on 408 subjects from the Alzheimer\u2019s Disease Neuroimaging Initiative database with longitudinal magnetic resonance imaging data and genetic data available. The experimental results show that T-MTSCCA performs either better than or equally to the state-of-the-art methods. In particular, T-MTSCCA could identify higher canonical correlation coefficients and capture clearer canonical weight patterns. This suggests that T-MTSCCA identifies time-consistent and time-dependent SNPs and imaging QTs, which further help understand the genetic basis of the brain QT changes over the time during the disease progression.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>The software and simulation data are publicly available at https:\/\/github.com\/dulei323\/TMTSCCA.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Supplementary information<\/jats:title>\n                  <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btz320","type":"journal-article","created":{"date-parts":[[2019,5,9]],"date-time":"2019-05-09T19:21:53Z","timestamp":1557429713000},"page":"i474-i483","source":"Crossref","is-referenced-by-count":55,"title":["Identifying progressive imaging genetic patterns via multi-task sparse canonical correlation analysis: a longitudinal study of the ADNI cohort"],"prefix":"10.1093","volume":"35","author":[{"given":"Lei","family":"Du","sequence":"first","affiliation":[{"name":"School of Automation, Northwestern Polytechnical University, Xi\u2019an, China"}]},{"given":"Kefei","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA"}]},{"given":"Lei","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Xi\u2019an University of Technology, Xi\u2019an, China"}]},{"given":"Xiaohui","family":"Yao","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA"}]},{"given":"Shannon L","family":"Risacher","sequence":"additional","affiliation":[{"name":"Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA"}]},{"given":"Lei","family":"Guo","sequence":"additional","affiliation":[{"name":"School of Automation, Northwestern Polytechnical University, Xi\u2019an, China"}]},{"given":"Andrew J","family":"Saykin","sequence":"additional","affiliation":[{"name":"Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA"}]},{"given":"Li","family":"Shen","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA"}]},{"name":"Alzheimer\u2019s Disease Neuroimaging Initiative","sequence":"additional","affiliation":[]}],"member":"286","published-online":{"date-parts":[[2019,7,5]]},"reference":[{"key":"2023062712371767100_btz320-B1","article-title":"Multi-task feature learning","volume":"7341","author":"Argyriou","year":"2006","journal-title":"Adv. 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