{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T10:56:30Z","timestamp":1774436190590,"version":"3.50.1"},"reference-count":32,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2024,6,5]],"date-time":"2024-06-05T00:00:00Z","timestamp":1717545600000},"content-version":"vor","delay-in-days":13,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100007625","name":"Cure Alzheimer's Fund","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100007625","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["1R01 AI 154470-01"],"award-info":[{"award-number":["1R01 AI 154470-01"]}],"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":["2U01 HG 008685"],"award-info":[{"award-number":["2U01 HG 008685"]}],"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":["R21 HD 095228 008976"],"award-info":[{"award-number":["R21 HD 095228 008976"]}],"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 HL 089856"],"award-info":[{"award-number":["U01 HL 089856"]}],"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 HL 089897"],"award-info":[{"award-number":["U01 HL 089897"]}],"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":["P01 HL 120839"],"award-info":[{"award-number":["P01 HL 120839"]}],"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":["P01 HL 132825"],"award-info":[{"award-number":["P01 HL 132825"]}],"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":["2U01 HG 008685"],"award-info":[{"award-number":["2U01 HG 008685"]}],"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":["R21 HD 095228"],"award-info":[{"award-number":["R21 HD 095228"]}],"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":["P01HL132825"],"award-info":[{"award-number":["P01HL132825"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["2033046"],"award-info":[{"award-number":["2033046"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["1745302"],"award-info":[{"award-number":["1745302"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"name":"NIH Center","award":["P30-ES002109"],"award-info":[{"award-number":["P30-ES002109"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,5,23]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>In precision medicine, both predicting the disease susceptibility of an individual and forecasting its disease-free survival are areas of key research. Besides the classical epidemiological predictor variables, data from multiple (omic) platforms are increasingly available. To integrate this wealth of information, we propose new methodology to combine both cooperative learning, a recent approach to leverage the predictive power of several datasets, and polygenic hazard score models. Polygenic hazard score models provide a practitioner with a more differentiated view of the predicted disease-free survival than the one given by merely a point estimate, for instance computed with a polygenic risk score. Our aim is to leverage the advantages of cooperative learning for the computation of polygenic hazard score models via Cox\u2019s proportional hazard model, thereby improving the prediction of the disease-free survival. In our experimental study, we apply our methodology to forecast the disease-free survival for Alzheimer\u2019s disease (AD) using three layers of data. One layer contains epidemiological variables such as sex, APOE (apolipoprotein E, a genetic risk factor for AD) status and 10 leading principal components. Another layer contains selected genomic loci, and the last layer contains methylation data for selected CpG sites. We demonstrate that the survival curves computed via cooperative learning yield an AUC of around $0.7$, above the state-of-the-art performance of its competitors. Importantly, the proposed methodology returns (1) a linear score that can be easily interpreted (in contrast to machine learning approaches), and (2) a weighting of the predictive power of the involved data layers, allowing for an assessment of the importance of each omic (or other) platform. Similarly to polygenic hazard score models, our methodology also allows one to compute individual survival curves for each patient.<\/jats:p>","DOI":"10.1093\/bib\/bbae267","type":"journal-article","created":{"date-parts":[[2024,6,5]],"date-time":"2024-06-05T17:22:20Z","timestamp":1717608140000},"source":"Crossref","is-referenced-by-count":4,"title":["Prediction of disease-free survival for precision medicine using cooperative learning on multi-omic data"],"prefix":"10.1093","volume":"25","author":[{"given":"Georg","family":"Hahn","sequence":"first","affiliation":[{"name":"Department of Biostatistics, Harvard T.H. Chan School of Public Health , 677 Huntington Ave, 02115, Boston, MA , USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dmitry","family":"Prokopenko","sequence":"additional","affiliation":[{"name":"Department of Neurology, Genetics and Aging Research Unit, McCance Center for Brain Health, Massachusetts General Hospital , 55 Fruit Street, 02114, Boston, MA , USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Julian","family":"Hecker","sequence":"additional","affiliation":[{"name":"Channing Divsion of Network Medicine, Brigham and Women\u2019s Hospital and Harvard Medical School , 75 Francis Street, 02115, Boston, MA , USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sharon M","family":"Lutz","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, Harvard T.H. Chan School of Public Health , 677 Huntington Ave, 02115, Boston, MA , USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kristina","family":"Mullin","sequence":"additional","affiliation":[{"name":"Department of Neurology, Genetics and Aging Research Unit, McCance Center for Brain Health, Massachusetts General Hospital , 55 Fruit Street, 02114, Boston, MA , USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Leinal","family":"Sejour","sequence":"additional","affiliation":[{"name":"Department of Pathology, Beth Israel Deaconess Medical Center , 330 Brookline Avenue, 02215, Boston, MA , USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Winston","family":"Hide","sequence":"additional","affiliation":[{"name":"Department of Pathology, Beth Israel Deaconess Medical Center , 330 Brookline Avenue, 02215, Boston, MA , USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ioannis","family":"Vlachos","sequence":"additional","affiliation":[{"name":"Department of Pathology, Beth Israel Deaconess Medical Center , 330 Brookline Avenue, 02215, Boston, MA , USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stacia","family":"DeSantis","sequence":"additional","affiliation":[{"name":"Houston Campus, The University of Texas Health Science Center , 1200 Pressler Street, 77030, Houston, TX , USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rudolph E","family":"Tanzi","sequence":"additional","affiliation":[{"name":"Department of Neurology, Genetics and Aging Research Unit, McCance Center for Brain Health, Massachusetts General Hospital , 55 Fruit Street, 02114, Boston, MA , USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Christoph","family":"Lange","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, Harvard T.H. Chan School of Public Health , 677 Huntington Ave, 02115, Boston, MA , USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2024,6,5]]},"reference":[{"key":"2024060508570929600_ref1","doi-asserted-by":"crossref","first-page":"535","DOI":"10.1038\/nrg.2016.56","article-title":"Type 2 diabetes: genetic data sharing to advance complex disease research","volume":"17","author":"Flannick","year":"2016","journal-title":"Nat Rev Genet"},{"key":"2024060508570929600_ref2","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1038\/nature14177","article-title":"Genetic studies of body mass index yield new insights for obesity biology","volume":"518","author":"Locke","year":"2015","journal-title":"Nature"},{"key":"2024060508570929600_ref3","doi-asserted-by":"crossref","first-page":"421","DOI":"10.1038\/nature13595","article-title":"Biological insights from 108 schizophrenia-associated genetic loci","volume":"511","author":"Schizophrenia Working Group of the Psychiatric Genomics Consortium","year":"2014","journal-title":"Nature"},{"key":"2024060508570929600_ref4","doi-asserted-by":"crossref","first-page":"1442","DOI":"10.1038\/nn.4399","article-title":"Gene expression elucidates functional impact of polygenic risk for schizophrenia","volume":"19","author":"Fromer","year":"2016","journal-title":"Nat Neurosci"},{"key":"2024060508570929600_ref5","doi-asserted-by":"crossref","first-page":"431","DOI":"10.1038\/s41588-019-0344-8","article-title":"Identification of common genetic risk variants for autism spectrum disorder","volume":"51","author":"Grove","year":"2019","journal-title":"Nat Genet"},{"key":"2024060508570929600_ref6","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1038\/nrg.2018.4","article-title":"Integrative omics for health and disease","volume":"19","author":"Karczewski","year":"2018","journal-title":"Nat Rev Genet"},{"key":"2024060508570929600_ref7","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1111\/j.2517-6161.1972.tb00899.x","article-title":"Regression models and life-tables (with discussion)","volume":"34","author":"Cox","year":"1972","journal-title":"J R Statist Soc B"},{"key":"2024060508570929600_ref8","doi-asserted-by":"crossref","first-page":"269","DOI":"10.1093\/biomet\/62.2.269","article-title":"Partial likelihood","volume":"62","author":"Cox","year":"1975","journal-title":"Biometrika"},{"key":"2024060508570929600_ref9","doi-asserted-by":"crossref","first-page":"e1002258","DOI":"10.1371\/journal.pmed.1002258","article-title":"Genetic assessment of age-associated Alzheimer disease risk: Development and validation of a polygenic hazard score","volume":"14","author":"Desikan","year":"2017","journal-title":"PLoS Med"},{"key":"2024060508570929600_ref10","doi-asserted-by":"crossref","DOI":"10.1101\/2024.04.18.590111","article-title":"Polygenic hazard score models for the prediction of Alzheimer\u2019s free survival using the lasso for Cox\u2019s proportional hazards model","author":"Hahn","year":"2024"},{"key":"2024060508570929600_ref11","doi-asserted-by":"crossref","first-page":"1219","DOI":"10.1038\/s41588-018-0183-z","article-title":"Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations","volume":"50","author":"Khera","year":"2018","journal-title":"Nat Genet"},{"key":"2024060508570929600_ref12","doi-asserted-by":"crossref","first-page":"3328","DOI":"10.1038\/s41467-019-11112-0","article-title":"Analysis of polygenic risk score usage and performance in diverse human populations","volume":"10","author":"Duncan","year":"2019","journal-title":"Nat Commun"},{"key":"2024060508570929600_ref13","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1038\/s41586-021-03243-6","article-title":"Improving reporting standards for polygenic scores in risk prediction studies","volume":"591","author":"Wand","year":"2021","journal-title":"Nature"},{"key":"2024060508570929600_ref14","doi-asserted-by":"crossref","first-page":"e2202113119","DOI":"10.1073\/pnas.2202113119","article-title":"Cooperative learning for multiview analysis","volume":"119","author":"Ding","year":"2022","journal-title":"Proc Natl Acad Sci U S A"},{"key":"2024060508570929600_ref15","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1038\/nrg3868","article-title":"Methods of integrating data to uncover genotype-phenotype interactions","volume":"16","author":"Ritchie","year":"2015","journal-title":"Nat Rev Genet"},{"key":"2024060508570929600_ref16","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1111\/j.2517-6161.1996.tb02080.x","article-title":"Regression shrinkage and selection via the lasso","volume":"58","author":"Tibshirani","year":"1996","journal-title":"J Roy Stat Soc B Met"},{"key":"2024060508570929600_ref17","doi-asserted-by":"crossref","first-page":"412","DOI":"10.1038\/s41588-022-01024-z","article-title":"New insights into the genetic etiology of Alzheimer\u2019s disease and related dementias","volume":"54","author":"Bellenguez","year":"2022","journal-title":"Nat Genet"},{"key":"2024060508570929600_ref18","doi-asserted-by":"crossref","first-page":"3517","DOI":"10.1038\/s41467-021-23243-4","article-title":"A meta-analysis of epigenome-wide association studies in Alzheimer\u2019s disease highlights novel differentially methylated loci across cortex","volume":"12","author":"Smith","year":"2021","journal-title":"Nat Commun"},{"key":"2024060508570929600_ref19","doi-asserted-by":"crossref","first-page":"691","DOI":"10.1093\/biomet\/asm037","article-title":"Adaptive Lasso for Cox\u2019s proportional hazards model","volume":"94","author":"Zhang","year":"2007","journal-title":"Biometrika"},{"key":"2024060508570929600_ref20","article-title":"survival: Survival Analysis. R-package version 3.4\u20130","author":"Therneau","year":"2022"},{"key":"2024060508570929600_ref21","article-title":"Partners Biobank","author":"Partners HealthCare Biobank","year":"2023"},{"key":"2024060508570929600_ref22","doi-asserted-by":"crossref","first-page":"643","DOI":"10.1093\/jamia\/ocab264","article-title":"The Mass General Brigham Biobank Portal: an i2b2-based data repository linking disparate and high-dimensional patient data to support multimodal analytics","volume":"29","author":"Castro","year":"2022","journal-title":"J Am Med Inform Assoc"},{"key":"2024060508570929600_ref23","article-title":"Comprehensive characterization, annotation and innovative use of Infinium DNA methylation BeadChip probes","volume":"45","author":"Zhou","year":"2017","journal-title":"Nucleic Acids Res"},{"key":"2024060508570929600_ref24","article-title":"ewastools: a quality control toolset for the Illumina Infinium DNA methylation platforms","author":"Just","year":"2022"},{"key":"2024060508570929600_ref25","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1186\/s13148-018-0504-1","article-title":"Identifying mislabeled and contaminated DNA methylation microarray data: an extended quality control toolset with examples from GEO","volume":"10","author":"Heiss","year":"2018","journal-title":"Clin Epigenetics"},{"key":"2024060508570929600_ref26","first-page":"1","article-title":"scikit-survival: A Library for Time-to-Event Analysis Built on Top of scikit-learn","volume":"21","author":"P\u00f6lsterl","year":"2020","journal-title":"J Mach Learn Res"},{"key":"2024060508570929600_ref27","author":"P\u00f6lsterl","year":"2023"},{"key":"2024060508570929600_ref28","doi-asserted-by":"crossref","first-page":"255","DOI":"10.2307\/2532051","article-title":"A concordance correlation coefficient to evaluate reproducibility","volume":"45","author":"Lin","year":"1989","journal-title":"Biometrics"},{"key":"2024060508570929600_ref29","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1175\/1520-0493(1950)078<0001:VOFEIT>2.0.CO;2","article-title":"Verification of forecasts expressed in terms of probability","volume":"78","author":"Brier","year":"1950","journal-title":"Mon Weather Rev"},{"key":"2024060508570929600_ref30","doi-asserted-by":"crossref","first-page":"2529","DOI":"10.1002\/(SICI)1097-0258(19990915\/30)18:17\/18<2529::AID-SIM274>3.0.CO;2-5","article-title":"Assessment and comparison of prognostic classification schemes for survival data","volume":"18","author":"Graf","year":"1999","journal-title":"Stat Med"},{"key":"2024060508570929600_ref31","doi-asserted-by":"crossref","DOI":"10.1007\/978-0-387-84858-7","volume-title":"The Elements of Statistical Learning: Data Mining, Inference, and Prediction (Second Edition)","author":"Hastie","year":"2009"},{"key":"2024060508570929600_ref32","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1007\/BF01441146","article-title":"A method for quantifying differentiation between populations at multi-allelic loci and its implications for investigating identity and paternity","volume":"96","author":"Balding","year":"1995","journal-title":"Genetica"}],"container-title":["Briefings in Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bib\/article-pdf\/25\/4\/bbae267\/58101626\/bbae267.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bib\/article-pdf\/25\/4\/bbae267\/58101626\/bbae267.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,5]],"date-time":"2024-06-05T17:22:45Z","timestamp":1717608165000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bib\/article\/doi\/10.1093\/bib\/bbae267\/7687754"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5,23]]},"references-count":32,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2024,5,23]]}},"URL":"https:\/\/doi.org\/10.1093\/bib\/bbae267","relation":{},"ISSN":["1467-5463","1477-4054"],"issn-type":[{"value":"1467-5463","type":"print"},{"value":"1477-4054","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2024,7]]},"published":{"date-parts":[[2024,5,23]]},"article-number":"bbae267"}}