{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T10:40:06Z","timestamp":1742985606981,"version":"3.40.3"},"reference-count":68,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,3,24]],"date-time":"2025-03-24T00:00:00Z","timestamp":1742774400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,3,24]],"date-time":"2025-03-24T00:00:00Z","timestamp":1742774400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["U01 AG068057","RF1 AG054409","U01 AG068057"],"award-info":[{"award-number":["U01 AG068057","RF1 AG054409","U01 AG068057"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BioData Mining"],"DOI":"10.1186\/s13040-025-00432-1","type":"journal-article","created":{"date-parts":[[2025,3,24]],"date-time":"2025-03-24T08:54:41Z","timestamp":1742806481000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["High-dimensional mediation analysis reveals the mediating role of physical activity patterns in genetic pathways leading to AD-like brain atrophy"],"prefix":"10.1186","volume":"18","author":[{"given":"Hanxiang","family":"Xu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shizhuo","family":"Mu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jingxuan","family":"Bao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Christos","family":"Davatzikos","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haochang","family":"Shou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Li","family":"Shen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,3,24]]},"reference":[{"key":"432_CR1","unstructured":"Recent research into nicotinamide mononucleotide and ageing. Available from: https:\/\/www.nature.com\/articles\/d42473-022-00002-7. Cited 2024 Mar 28."},{"issue":"2","key":"432_CR2","doi-asserted-by":"publisher","first-page":"144","DOI":"10.1038\/d41587-022-00002-4","volume":"40","author":"M Eisenstein","year":"2022","unstructured":"Eisenstein M. Rejuvenation by controlled reprogramming is the latest gambit in anti-aging. Nat Biotechnol. 2022;40(2):144\u20136.","journal-title":"Nat Biotechnol"},{"issue":"1","key":"432_CR3","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1186\/s12929-019-0524-y","volume":"26","author":"MVF Silva","year":"2019","unstructured":"Silva MVF, Loures CDMG, Alves LCV, de Souza LC, Borges KBG, Carvalho MDG. Alzheimer\u2019s disease: risk factors and potentially protective measures. J Biomed Sci. 2019;26(1):33.","journal-title":"J Biomed Sci"},{"key":"432_CR4","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1186\/s12966-022-01280-6","volume":"19","author":"LL Yan","year":"2022","unstructured":"Yan LL, Li C, Zou S, Li Y, Gong E, He Z, et al. Healthy eating and all-cause mortality among Chinese aged 80 years or older. Int J Behav Nutr Phys Act. 2022;19:60.","journal-title":"Int J Behav Nutr Phys Act"},{"issue":"4","key":"432_CR5","doi-asserted-by":"publisher","first-page":"1598","DOI":"10.1002\/alz.13016","volume":"19","author":"Alzheimer\u2019s disease facts and figures","year":"2023","unstructured":"Alzheimer\u2019s disease facts and figures. Alzheimers Dement. 2023;19(4):1598\u2013695.","journal-title":"Alzheimers Dement."},{"issue":"7","key":"432_CR6","doi-asserted-by":"publisher","first-page":"623","DOI":"10.1080\/14737175.2019.1621750","volume":"19","author":"YC Kuo","year":"2019","unstructured":"Kuo YC, Rajesh R. Challenges in the treatment of Alzheimer\u2019s disease: recent progress and treatment strategies of pharmaceuticals targeting notable pathological factors. Expert Rev Neurother. 2019;19(7):623\u201352.","journal-title":"Expert Rev Neurother"},{"issue":"1","key":"432_CR7","doi-asserted-by":"publisher","first-page":"64","DOI":"10.1186\/s13024-018-0299-8","volume":"13","author":"J Cao","year":"2018","unstructured":"Cao J, Hou J, Ping J, Cai D. Advances in developing novel therapeutic strategies for Alzheimer\u2019s disease. Mol Neurodegener. 2018;13(1):64.","journal-title":"Mol Neurodegener"},{"key":"432_CR8","doi-asserted-by":"crossref","unstructured":"d\u2018Errico P, Meyer-Luehmann M. Mechanisms of pathogenic Tau and A\u03b2 protein spreading in Alzheimer\u2019s disease. Front Aging Neurosci. 2020;12. Available from: https:\/\/www.frontiersin.org\/articles\/10.3389\/fnagi.2020.00265. Cited 2024 Feb 21.","DOI":"10.3389\/fnagi.2020.00265"},{"issue":"2","key":"432_CR9","doi-asserted-by":"publisher","first-page":"bbad073","DOI":"10.1093\/bib\/bbad073","volume":"24","author":"J Bao","year":"2023","unstructured":"Bao J, Chang C, Zhang Q, Saykin AJ, Shen L, Long Q, et al. Integrative analysis of multi-omics and imaging data with incorporation of biological information via structural bayesian factor analysis. Brief Bioinform. 2023;24(2):bbad073.","journal-title":"Brief Bioinform"},{"issue":"6","key":"432_CR10","first-page":"1161","volume":"42","author":"YC Klimentidis","year":"2018","unstructured":"Klimentidis YC, Raichlen DA, Bea J, Garcia DO, Wineinger NE, Mandarino LJ, et al. Genome-wide association study of habitual physical activity in over 377,000 UK Biobank participants identifies multiple variants including CADM2 and APOE. Int J Obes 2005. 2018;42(6):1161\u201376.","journal-title":"Int J Obes 2005"},{"issue":"4","key":"432_CR11","doi-asserted-by":"publisher","first-page":"601","DOI":"10.14283\/jpad.2022.57","volume":"9","author":"R C\u00e1mara-Calmaestra","year":"2022","unstructured":"C\u00e1mara-Calmaestra R, Mart\u00ednez-Amat A, Aibar-Almaz\u00e1n A, Hita-Contreras F, de Miguel Hernando N, Achalandabaso-Ochoa A. Effectiveness of physical exercise on Alzheimer\u2019s disease. Syst Rev J Prev Alzheimers Dis. 2022;9(4):601\u201316.","journal-title":"Syst Rev J Prev Alzheimers Dis"},{"issue":"6","key":"432_CR12","first-page":"733","volume":"72","author":"R Stephen","year":"2017","unstructured":"Stephen R, Hongisto K, Solomon A, L\u00f6nnroos E. Physical activity and Alzheimer\u2019s disease: a systematic review. J Gerontol Biol Sci Med Sci. 2017;72(6):733\u20139.","journal-title":"J Gerontol Biol Sci Med Sci"},{"key":"432_CR13","doi-asserted-by":"publisher","first-page":"7807856","DOI":"10.1155\/2020\/7807856","volume":"2020","author":"H Nuzum","year":"2020","unstructured":"Nuzum H, Stickel A, Corona M, Zeller M, Melrose RJ, Wilkins SS. Potential benefits of physical activity in MCI and dementia. Behav Neurol. 2020;2020:7807856.","journal-title":"Behav Neurol"},{"issue":"6690","key":"432_CR14","doi-asserted-by":"publisher","first-page":"1471","DOI":"10.1126\/science.adn1011","volume":"383","author":"FRM Beinlich","year":"2024","unstructured":"Beinlich FRM, Asiminas A, Untiet V, Bojarowska Z, Pl\u00e1 V, Sigurdsson B, et al. Oxygen imaging of hypoxic pockets in the mouse cerebral cortex. Science. 2024;383(6690):1471\u20138.","journal-title":"Science"},{"issue":"1","key":"432_CR15","doi-asserted-by":"publisher","first-page":"226","DOI":"10.1186\/s12874-021-01426-3","volume":"21","author":"JJM Rijnhart","year":"2021","unstructured":"Rijnhart JJM, Lamp SJ, Valente MJ, MacKinnon DP, Twisk JWR, Heymans MW. Mediation analysis methods used in observational research: a scoping review and recommendations. BMC Med Res Methodol. 2021;21(1):226.","journal-title":"BMC Med Res Methodol"},{"issue":"1","key":"432_CR16","doi-asserted-by":"publisher","first-page":"272","DOI":"10.1007\/s11336-020-09736-z","volume":"86","author":"H Liu","year":"2021","unstructured":"Liu H, Jin IH, Zhang Z, Yuan Y. Social network mediation analysis: a Latent space approach. Psychometrika. 2021;86(1):272\u201398.","journal-title":"Psychometrika"},{"issue":"6","key":"432_CR17","doi-asserted-by":"publisher","first-page":"643","DOI":"10.1080\/10376178.2015.1041999","volume":"52","author":"J Liu","year":"2016","unstructured":"Liu J, Ulrich C. Mediation analysis in nursing research: a methodological review. Contemp Nurse. 2016;52(6):643\u201356.","journal-title":"Contemp Nurse"},{"issue":"8","key":"432_CR18","doi-asserted-by":"publisher","first-page":"2441","DOI":"10.1007\/s10461-021-03207-x","volume":"25","author":"HL Smyth","year":"2021","unstructured":"Smyth HL, Pitpitan EV, MacKinnon DP, Booth RE. Assessing potential outcomes mediation in HIV interventions. AIDS Behav. 2021;25(8):2441\u201354.","journal-title":"AIDS Behav"},{"issue":"1","key":"432_CR19","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1186\/s12888-019-2016-8","volume":"19","author":"A Klumparendt","year":"2019","unstructured":"Klumparendt A, Nelson J, Barenbr\u00fcgge J, Ehring T. Associations between childhood maltreatment and adult depression: a mediation analysis. BMC Psychiatry. 2019;19(1):36.","journal-title":"BMC Psychiatry"},{"key":"432_CR20","first-page":"344","volume":"2024","author":"S Mu","year":"2024","unstructured":"Mu S, Bao J, Xu H, Shivakumar M, Yang S, Ning X, Kim D, Davatzikos C, Shou H, Shen L. Multivariate mediation analysis with voxel-based morphometry revealed the neurodegeneration pathways from genetic variants to Alzheimer\u2019s disease. AMIA Inform Summit. 2024;2024:344\u201353.","journal-title":"AMIA Inform Summit"},{"key":"432_CR21","unstructured":"Employing Informatics strategies in Alzheimer\u2019s disease research: a review from genetics, multiomics, and biomarkers to clinical outcomes | Annual reviews. Available from: https:\/\/www.annualreviews.org\/content\/journals\/10.1146\/annurev-biodatasci-102423-121021. Cited 2024 Aug 29."},{"key":"432_CR22","doi-asserted-by":"crossref","unstructured":"Estimation and inference for the indirect effect in high-dimensional linear mediation models | Biometrika | Oxford Academic. Available from: https:\/\/academic.oup.com\/biomet\/article\/107\/3\/573\/5829472. Cited 2024 Feb 21.","DOI":"10.1093\/biomet\/asaa016"},{"key":"432_CR23","doi-asserted-by":"publisher","first-page":"1195","DOI":"10.3389\/fgene.2019.01195","volume":"10","author":"Y Gao","year":"2019","unstructured":"Gao Y, Yang H, Fang R, Zhang Y, Goode EL, Cui Y. Testing mediation effects in high-dimensional epigenetic studies. Front Genet. 2019;10:1195.","journal-title":"Front Genet"},{"issue":"3","key":"432_CR24","doi-asserted-by":"publisher","first-page":"700","DOI":"10.1111\/biom.13189","volume":"76","author":"Y Song","year":"2020","unstructured":"Song Y, Zhou X, Zhang M, Zhao W, Liu Y, Kardia SLR, et al. Bayesian shrinkage estimation of high dimensional causal mediation effects in omics studies. Biometrics. 2020;76(3):700\u201310.","journal-title":"Biometrics"},{"issue":"2","key":"432_CR25","first-page":"121","volume":"19","author":"OY Ch\u00e9n","year":"2018","unstructured":"Ch\u00e9n OY, Crainiceanu C, Ogburn EL, Caffo BS, Wager TD, Lindquist MA. High-dimensional multivariate mediation with application to neuroimaging data. Biostat Oxf Engl. 2018;19(2):121\u201336.","journal-title":"Biostat Oxf Engl"},{"issue":"3","key":"432_CR26","doi-asserted-by":"publisher","first-page":"143","DOI":"10.2165\/00007256-200232030-00001","volume":"32","author":"V Seefeldt","year":"2002","unstructured":"Seefeldt V, Malina RM, Clark MA. Factors affecting levels of physical activity in adults. Sports Med. 2002;32(3):143\u201368.","journal-title":"Sports Med"},{"key":"432_CR27","doi-asserted-by":"crossref","unstructured":"Chen F, Hu W, Cai J, Chen S, Liu W. Instrumental variable-based high-dimensional mediation analysis with unmeasured confounders for survival data in the observational epigenetic study. Front Genet. 2023;14. Available from: https:\/\/www.frontiersin.org\/journals\/genetics\/articles\/10.3389\/fgene.2023.1092489\/full. Cited 2024 Mar 7.","DOI":"10.3389\/fgene.2023.1092489"},{"key":"432_CR28","first-page":"422","volume":"2020","author":"E Yingxuan","year":"2021","unstructured":"Yingxuan E, Yao X, Liu K, Risacher SL, Saykin AJ, Long Q, et al. Polygenic mediation analysis of Alzheimer\u2019s disease implicated intermediate amyloid imaging phenotypes. AMIA Annu Symp Proc. 2021;2020:422\u201331.","journal-title":"AMIA Annu Symp Proc."},{"issue":"2","key":"432_CR29","doi-asserted-by":"publisher","first-page":"669","DOI":"10.3233\/JAD-230577","volume":"96","author":"J Jiang","year":"2023","unstructured":"Jiang J, Hong Y, Li W, Wang A, Jiang S, Jiang T, et al. Chain mediation analysis of the effects of nutrition and cognition on the association of apolipoprotein E \u025b4 with neuropsychiatric symptoms in Alzheimer\u2019s disease. J Alzheimers Dis JAD. 2023;96(2):669\u201381.","journal-title":"J Alzheimers Dis JAD"},{"key":"432_CR30","first-page":"2667","volume":"2022","author":"D Pala","year":"2022","unstructured":"Pala D, Lee B, Ning X, Kim D, Shen L. Mediation analysis and mixed-effects models for the identification of stage-specific imaging genetics patterns in Alzheimer\u2019s disease. Proc IEEE Int Conf Bioinforma Biomed. 2022;2022:2667\u201373.","journal-title":"Proc IEEE Int Conf Bioinforma Biomed"},{"issue":"1","key":"432_CR31","doi-asserted-by":"publisher","first-page":"88","DOI":"10.1186\/s12889-020-10100-0","volume":"21","author":"AV Romeo","year":"2021","unstructured":"Romeo AV, Edney SM, Plotnikoff RC, Olds T, Vandelanotte C, Ryan J, et al. Examining social-cognitive theory constructs as mediators of behaviour change in the active team smartphone physical activity program: a mediation analysis. BMC Public Health. 2021;21(1):88.","journal-title":"BMC Public Health"},{"key":"432_CR32","doi-asserted-by":"crossref","unstructured":"Chen T, Mandal A, Zhu H, Liu R. Imaging genetic based mediation analysis for human cognition. Front Neurosci. 2022;16. Available from: https:\/\/www.frontiersin.org\/journals\/neuroscience\/articles\/10.3389\/fnins.2022.824069\/full. Cited 2024 Mar 7.","DOI":"10.3389\/fnins.2022.824069"},{"issue":"7726","key":"432_CR33","doi-asserted-by":"publisher","first-page":"203","DOI":"10.1038\/s41586-018-0579-z","volume":"562","author":"C Bycroft","year":"2018","unstructured":"Bycroft C, Freeman C, Petkova D, Band G, Elliott LT, Sharp K, et al. The UK Biobank resource with deep phenotyping and genomic data. Nature. 2018;562(7726):203\u20139.","journal-title":"Nature"},{"issue":"2","key":"432_CR34","doi-asserted-by":"publisher","first-page":"262","DOI":"10.1007\/s12561-018-09229-9","volume":"11","author":"A Leroux","year":"2019","unstructured":"Leroux A, Di J, Smirnova E, Mcguffey EJ, Cao Q, Bayatmokhtari E, et al. Organizing and analyzing the activity data in NHANES. Stat Biosci. 2019;11(2):262\u201387.","journal-title":"Stat Biosci"},{"issue":"8","key":"432_CR35","doi-asserted-by":"publisher","first-page":"1486","DOI":"10.1093\/gerona\/glaa250","volume":"76","author":"A Leroux","year":"2020","unstructured":"Leroux A, Xu S, Kundu P, Muschelli J, Smirnova E, Chatterjee N, et al. Quantifying the predictive performance of objectively measured physical activity on mortality in the UK Biobank. J Gerontol Biol Sci Med Sci. 2020;76(8):1486\u201394.","journal-title":"J Gerontol Biol Sci Med Sci"},{"issue":"1","key":"432_CR36","doi-asserted-by":"publisher","first-page":"409","DOI":"10.1007\/s11222-014-9485-x","volume":"26","author":"L Xiao","year":"2016","unstructured":"Xiao L, Zipunnikov V, Ruppert D, Crainiceanu C. Fast covariance estimation for high-dimensional functional data. Stat Comput. 2016;26(1):409\u201321.","journal-title":"Stat Comput"},{"key":"432_CR37","unstructured":"Refund.pdf. Available from: https:\/\/cran.r-project.org\/web\/packages\/refund\/refund.pdf. Cited 2024 Feb 21."},{"issue":"8","key":"432_CR38","doi-asserted-by":"publisher","first-page":"2026","DOI":"10.1093\/brain\/awp091","volume":"132","author":"C Davatzikos","year":"2009","unstructured":"Davatzikos C, Xu F, An Y, Fan Y, Resnick SM. Longitudinal progression of Alzheimer\u2019s-like patterns of atrophy in normal older adults: the SPARE-AD index. Brain. 2009;132(8):2026\u201335.","journal-title":"Brain"},{"issue":"1","key":"432_CR39","doi-asserted-by":"publisher","first-page":"89","DOI":"10.1002\/alz.12178","volume":"17","author":"M Habes","year":"2021","unstructured":"Habes M, Pomponio R, Shou H, Doshi J, Mamourian E, Erus G, et al. The brain chart of aging: machine-learning analytics reveals links between brain aging, white matter disease, amyloid burden, and cognition in the iSTAGING consortium of 10,216 harmonized MR scans. Alzheimers Dement J Alzheimers Assoc. 2021;17(1):89\u2013102.","journal-title":"Alzheimers Dement J Alzheimers Assoc"},{"issue":"5","key":"432_CR40","doi-asserted-by":"publisher","first-page":"464","DOI":"10.1001\/jamapsychiatry.2022.0020","volume":"79","author":"J Wen","year":"2022","unstructured":"Wen J, Fu CHY, Tosun D, Veturi Y, Yang Z, Abdulkadir A, et al. Characterizing heterogeneity in neuroimaging, cognition, clinical symptoms, and genetics among patients with late-life depression. JAMA Psychiatry. 2022;79(5):464\u201374.","journal-title":"JAMA Psychiatry"},{"key":"432_CR41","doi-asserted-by":"publisher","first-page":"186","DOI":"10.1016\/j.neuroimage.2015.11.073","volume":"127","author":"J Doshi","year":"2016","unstructured":"Doshi J, Erus G, Ou Y, Resnick SM, Gur RC, Gur RE, et al. MUSE: MUlti-atlas region segmentation utilizing ensembles of registration algorithms and parameters, and locally optimal atlas selection. NeuroImage. 2016;127:186\u201395.","journal-title":"NeuroImage"},{"issue":"1","key":"432_CR42","doi-asserted-by":"publisher","first-page":"411","DOI":"10.1186\/s12859-022-04966-7","volume":"23","author":"Q Yang","year":"2022","unstructured":"Yang Q, Gao S, Lin J, Lyu K, Wu Z, Chen Y, et al. A machine learning-based data mining in medical examination data: a biological features-based biological age prediction model. BMC Bioinformatics. 2022;23(1):411.","journal-title":"BMC Bioinformatics"},{"issue":"1","key":"432_CR43","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41514-021-00068-5","volume":"7","author":"N Holzscheck","year":"2021","unstructured":"Holzscheck N, Falckenhayn C, S\u00f6hle J, Kristof B, Siegner R, Werner A, et al. Modeling transcriptomic age using knowledge-primed artificial neural networks. Npj Aging Mech Dis. 2021;7(1):1\u201313.","journal-title":"Npj Aging Mech Dis"},{"issue":"8","key":"432_CR44","doi-asserted-by":"publisher","first-page":"844","DOI":"10.1001\/jamacardio.2022.1900","volume":"7","author":"MW Segar","year":"2022","unstructured":"Segar MW, Hall JL, Jhund PS, Powell-Wiley TM, Morris AA, Kao D, et al. Machine learning-based models incorporating social determinants of health vs traditional models for predicting in-hospital mortality in patients with heart failure. JAMA Cardiol. 2022;7(8):844\u201354.","journal-title":"JAMA Cardiol"},{"issue":"1","key":"432_CR45","doi-asserted-by":"publisher","first-page":"129","DOI":"10.1038\/s43587-023-00536-5","volume":"4","author":"NM Cohen","year":"2024","unstructured":"Cohen NM, Lifshitz A, Jaschek R, Rinott E, Balicer R, Shlush LI, et al. Longitudinal machine learning uncouples healthy aging factors from chronic disease risks. Nat Aging. 2024;4(1):129\u201344.","journal-title":"Nat Aging"},{"issue":"2","key":"432_CR46","doi-asserted-by":"publisher","first-page":"e55531","DOI":"10.1371\/journal.pone.0055531","volume":"8","author":"JB Toledo","year":"2013","unstructured":"Toledo JB, Da X, Bhatt P, Wolk DA, Arnold SE, Shaw LM, et al. Relationship between plasma analytes and SPARE-AD defined brain atrophy patterns in ADNI. PLoS One. 2013;8(2):e55531.","journal-title":"PLoS One"},{"key":"432_CR47","doi-asserted-by":"publisher","first-page":"164","DOI":"10.1016\/j.nicl.2013.11.010","volume":"4","author":"X Da","year":"2013","unstructured":"Da X, Toledo JB, Zee J, Wolk DA, Xie SX, Ou Y, et al. Integration and relative value of biomarkers for prediction of MCI to AD progression: spatial patterns of brain atrophy, cognitive scores, APOE genotype and CSF biomarkers. Neuroimage Clin. 2013;4:164\u201373.","journal-title":"Neuroimage Clin"},{"issue":"6","key":"432_CR48","doi-asserted-by":"publisher","first-page":"e2316182","DOI":"10.1001\/jamanetworkopen.2023.16182","volume":"6","author":"M Habes","year":"2023","unstructured":"Habes M, Jacobson AM, Braffett BH, Rashid T, Ryan CM, Shou H, et al. Patterns of regional brain atrophy and brain aging in middle- and older-aged adults with type 1 diabetes. JAMA Netw Open. 2023;6(6):e2316182.","journal-title":"JAMA Netw Open"},{"key":"432_CR49","doi-asserted-by":"publisher","first-page":"120346","DOI":"10.1016\/j.neuroimage.2023.120346","volume":"280","author":"J Bao","year":"2023","unstructured":"Bao J, Wen J, Wen Z, Yang S, Cui Y, Yang Z, et al. Brain-wide genome-wide colocalization study for integrating genetics, transcriptomics and brain morphometry in Alzheimer\u2019s disease. Neuroimage. 2023;280:120346.","journal-title":"Neuroimage"},{"issue":"10","key":"432_CR50","doi-asserted-by":"publisher","first-page":"1466","DOI":"10.1038\/s41588-022-01178-w","volume":"54","author":"W Zhou","year":"2022","unstructured":"Zhou W, Bi W, Zhao Z, Dey KK, Jagadeesh KA, Karczewski KJ, et al. SAIGE-GENE\u2009+\u2009improves the efficiency and accuracy of set-based rare variant association tests. Nat Genet. 2022;54(10):1466\u20139.","journal-title":"Nat Genet"},{"issue":"6","key":"432_CR51","doi-asserted-by":"publisher","first-page":"634","DOI":"10.1038\/s41588-020-0621-6","volume":"52","author":"W Zhou","year":"2020","unstructured":"Zhou W, Zhao Z, Nielsen JB, Fritsche LG, LeFaive J, Gagliano Taliun SA, et al. Scalable generalized linear mixed model for region-based association tests in large biobanks and cohorts. Nat Genet. 2020;52(6):634\u20139.","journal-title":"Nat Genet"},{"issue":"10","key":"432_CR52","doi-asserted-by":"publisher","first-page":"e0291305","DOI":"10.1371\/journal.pone.0291305","volume":"18","author":"NR Yaseen","year":"2023","unstructured":"Yaseen NR, Barnes CLK, Sun L, Takeda A, Rice JP. Genetics of vegetarianism: a genome-wide association study. PLoS One. 2023;18(10):e0291305.","journal-title":"PLoS One"},{"issue":"5","key":"432_CR53","doi-asserted-by":"publisher","first-page":"1391","DOI":"10.1111\/rssc.12518","volume":"70","author":"Y Song","year":"2021","unstructured":"Song Y, Zhou X, Kang J, Aung MT, Zhang M, Zhao W, et al. Bayesian sparse mediation analysis with targeted penalization of natural indirect effects. J R Stat Soc Ser C Appl Stat. 2021;70(5):1391\u2013412.","journal-title":"J R Stat Soc Ser C Appl Stat"},{"issue":"1","key":"432_CR54","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1214\/10-STS321","volume":"25","author":"K Imai","year":"2010","unstructured":"Imai K, Keele L, Yamamoto T. Identification, inference and sensitivity analysis for causal mediation effects. Stat Sci. 2010;25(1):51\u201371.","journal-title":"Stat Sci"},{"issue":"4","key":"432_CR55","doi-asserted-by":"publisher","first-page":"309","DOI":"10.1037\/a0020761","volume":"15","author":"K Imai","year":"2010","unstructured":"Imai K, Keele L, Tingley D. A general approach to causal mediation analysis. Psychol Methods. 2010;15(4):309\u201334.","journal-title":"Psychol Methods"},{"key":"432_CR56","doi-asserted-by":"publisher","first-page":"129","DOI":"10.1007\/978-1-4419-1764-5_8","volume-title":"Advances in social science research using","author":"K Imai","year":"2010","unstructured":"Imai K, Keele L, Tingley D, Yamamoto T. Causal mediation analysis using R. In: Vinod HD, editor. Advances in social science research using. New York: Springer; 2010. p. 129\u201354. (Lecture Notes in Statistics)."},{"key":"432_CR57","doi-asserted-by":"publisher","first-page":"1","DOI":"10.18637\/jss.v059.i05","volume":"59","author":"D Tingley","year":"2014","unstructured":"Tingley D, Yamamoto T, Hirose K, Keele L, Imai K. Mediation: R package for causal mediation analysis. J Stat Softw. 2014;59:1\u201338.","journal-title":"J Stat Softw"},{"issue":"4","key":"432_CR58","doi-asserted-by":"publisher","first-page":"765","DOI":"10.1017\/S0003055411000414","volume":"105","author":"K Imai","year":"2011","unstructured":"Imai K, Keele L, Tingley D, Yamamoto T. Unpacking the black box of causality: learning about causal mechanisms from experimental and observational studies. Am Polit Sci Rev. 2011;105(4):765\u201389.","journal-title":"Am Polit Sci Rev"},{"issue":"8","key":"432_CR59","doi-asserted-by":"publisher","first-page":"3943","DOI":"10.1038\/s41380-019-0569-z","volume":"26","author":"B Zhao","year":"2021","unstructured":"Zhao B, Zhang J, Ibrahim JG, Luo T, Santelli RC, Li Y, et al. Large-scale GWAS reveals genetic architecture of brain white matter microstructure and genetic overlap with cognitive and mental health traits (n\u2009=\u200917,706). Mol Psychiatry. 2021;26(8):3943\u201355.","journal-title":"Mol Psychiatry"},{"issue":"5","key":"432_CR60","doi-asserted-by":"publisher","first-page":"1214","DOI":"10.1016\/j.cell.2020.08.008","volume":"182","author":"D Vuckovic","year":"2020","unstructured":"Vuckovic D, Bao EL, Akbari P, Lareau CA, Mousas A, Jiang T, et al. The polygenic and monogenic basis of blood traits and diseases. Cell. 2020;182(5):1214-1231.e11.","journal-title":"Cell"},{"issue":"4","key":"432_CR61","first-page":"e12517","volume":"15","author":"J Li","year":"2023","unstructured":"Li J, Zhang Y, Wang H, Guo Y, Shen X, Li M, et al. Exploring the links among peripheral immunity, biomarkers, cognition, and neuroimaging in Alzheimer\u2019s disease. Alzheimers Dement Diagn Assess Dis Monit. 2023;15(4):e12517.","journal-title":"Alzheimers Dement Diagn Assess Dis Monit"},{"issue":"2","key":"432_CR62","doi-asserted-by":"publisher","first-page":"184","DOI":"10.1016\/j.maturitas.2014.05.009","volume":"79","author":"S Bennett","year":"2014","unstructured":"Bennett S, Thomas AJ. Depression and dementia: cause, consequence or coincidence? Maturitas. 2014;79(2):184\u201390.","journal-title":"Maturitas"},{"issue":"3","key":"432_CR63","doi-asserted-by":"publisher","first-page":"368","DOI":"10.1016\/S0002-9149(02)03175-2","volume":"91","author":"C Pitsavos","year":"2003","unstructured":"Pitsavos C, Chrysohoou C, Panagiotakos DB, Skoumas J, Zeimbekis A, Kokkinos P, et al. Association of leisure-time physical activity on inflammation markers (C-reactive protein, white cell blood count, serum amyloid A, and fibrinogen) in healthy subjects (from the ATTICA study). Am J Cardiol. 2003;91(3):368\u201370.","journal-title":"Am J Cardiol"},{"key":"432_CR64","doi-asserted-by":"publisher","first-page":"1096798","DOI":"10.3389\/fnagi.2023.1096798","volume":"15","author":"S Konwar","year":"2023","unstructured":"Konwar S, Manca R, De Marco M, Soininen H, Venneri A. The effect of physical activity on white matter integrity in aging and prodromal to mild Alzheimer\u2019s disease with vascular comorbidity. Front Aging Neurosci. 2023;15:1096798.","journal-title":"Front Aging Neurosci"},{"key":"432_CR65","doi-asserted-by":"publisher","first-page":"116202","DOI":"10.1016\/j.socscimed.2023.116202","volume":"335","author":"S Lenzen","year":"2023","unstructured":"Lenzen S, Gannon B, Rose C, Norton EC. The relationship between physical activity, cognitive function and health care use: a mediation analysis. Soc Sci Med. 2023;335:116202.","journal-title":"Soc Sci Med"},{"issue":"19","key":"432_CR66","doi-asserted-by":"publisher","first-page":"1392","DOI":"10.1136\/bjsports-2016-097385","volume":"51","author":"D Ding","year":"2017","unstructured":"Ding D, Kolbe-Alexander T, Nguyen B, Katzmarzyk PT, Pratt M, Lawson KD. The economic burden of physical inactivity: a systematic review and critical appraisal. Br J Sports Med. 2017;51(19):1392\u2013409.","journal-title":"Br J Sports Med"},{"issue":"3","key":"432_CR67","doi-asserted-by":"publisher","first-page":"239","DOI":"10.1093\/abm\/kax043","volume":"52","author":"M K\u00e4rmeniemi","year":"2018","unstructured":"K\u00e4rmeniemi M, Lankila T, Ik\u00e4heimo T, Koivumaa-Honkanen H, Korpelainen R. The built environment as a determinant of physical activity: a systematic review of longitudinal studies and natural experiments. Ann Behav Med. 2018;52(3):239\u201351.","journal-title":"Ann Behav Med"},{"key":"432_CR68","doi-asserted-by":"crossref","unstructured":"Zotcheva E, Bratsberg B, Strand BH, Jugessur A, Engdahl BL, Bowen C, et al. Trajectories of occupational physical activity and risk of later-life mild cognitive impairment and dementia: the HUNT4 70\u2009+\u2009study. Lancet Reg Health Eur. 2023;34. Available from: https:\/\/www.thelancet.com\/journals\/lanepe\/article\/PIIS2666-7762(23)00140-0\/fulltext. Cited 2024 Mar 7.","DOI":"10.1016\/j.lanepe.2023.100721"}],"container-title":["BioData Mining"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13040-025-00432-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s13040-025-00432-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13040-025-00432-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T10:17:14Z","timestamp":1742984234000},"score":1,"resource":{"primary":{"URL":"https:\/\/biodatamining.biomedcentral.com\/articles\/10.1186\/s13040-025-00432-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,3,24]]},"references-count":68,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["432"],"URL":"https:\/\/doi.org\/10.1186\/s13040-025-00432-1","relation":{},"ISSN":["1756-0381"],"issn-type":[{"type":"electronic","value":"1756-0381"}],"subject":[],"published":{"date-parts":[[2025,3,24]]},"assertion":[{"value":"31 August 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 February 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 March 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Ethics approval is not required. The data used for the preparation of this article is from the UK Biobank (UKBB). The UKBB study has ethical approval, and the ethics committee is detailed here: .","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"All the authors have read and approved the final version of the manuscript.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"We would like to declare a competing interest, as the last author Li Shen is one of the Guest Editors of the Collection.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"24"}}