{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T11:52:57Z","timestamp":1774007577302,"version":"3.50.1"},"reference-count":32,"publisher":"Oxford University Press (OUP)","issue":"3","license":[{"start":{"date-parts":[[2026,2,16]],"date-time":"2026-02-16T00:00:00Z","timestamp":1771200000000},"content-version":"vor","delay-in-days":1,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100005725","name":"CHDI Foundation","doi-asserted-by":"publisher","award":["A-10104"],"award-info":[{"award-number":["A-10104"]}],"id":[{"id":"10.13039\/100005725","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,2,28]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>There are many diseases with established genetic factors, such as Huntington\u2019s disease (HD), that are characterized by variable rates of progression. However, beyond the contribution of the known genetic factors - in this case the Huntingtin (HTT) gene - the impact of the full human genome on the natural progression of such diseases throughout a patient\u2019s life remains largely unknown. The increased availability of genome wide association (GWA) data in HD gene expansion carriers (HDGECs), combined with the clinical assessment scores on the same set of patients, has provided a perfect opportunity to assess the potentially broader genetic impact on the natural progression of HD.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>We present a genetics-driven, probabilistic disease progression model designed to identify and investigate the ways in which a range of genetic factors affect the natural progression of HD. When applied to a clinico-genomic HD dataset, our model identified several single nucleotide polymorphisms (SNPs) with previously unreported effects on disease progression that act at distinct stages and with varying magnitudes. This discovery may shed light on the potential mechanistic impact of previously unidentified genes on HD that may have implications for clinical management. As increasing amounts of GWA data become available more generally, we anticipate that this modeling framework will be broadly applicable to other diseases with strong genetic components.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>The source code for IHDPM is available at https:\/\/github.com\/BiomedSciAI\/IHDPM<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btag072","type":"journal-article","created":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T12:43:13Z","timestamp":1770986593000},"source":"Crossref","is-referenced-by-count":0,"title":["From genes to trajectories: mapping genetic influences on Huntington\u2019s disease progression"],"prefix":"10.1093","volume":"42","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8413-9573","authenticated-orcid":false,"given":"Sanjoy","family":"Dey","sequence":"first","affiliation":[{"name":"IBM Research , Yorktown Heights, NY 10598,","place":["United States"]}]},{"given":"Zhaonan","family":"Sun","sequence":"additional","affiliation":[{"name":"IBM Research , Yorktown Heights, NY 10598,","place":["United States"]}]},{"given":"John","family":"Warner","sequence":"additional","affiliation":[{"name":"CHDI Management, CHDI Foundation , Princeton, NJ 08540,","place":["United States"]}]},{"given":"Eileen","family":"Koski","sequence":"additional","affiliation":[{"name":"IBM Research , Yorktown Heights, NY 10598,","place":["United States"]}]},{"given":"Elif","family":"Eyigoz","sequence":"additional","affiliation":[{"name":"IBM Research , Yorktown Heights, NY 10598,","place":["United States"]}]},{"given":"Swati","family":"Sathe","sequence":"additional","affiliation":[{"name":"CHDI Management, CHDI Foundation , Princeton, NJ 08540,","place":["United States"]}]},{"given":"Cristina","family":"Sampaio","sequence":"additional","affiliation":[{"name":"CHDI Management, CHDI Foundation , Princeton, NJ 08540,","place":["United States"]}]},{"given":"Jianying","family":"Hu","sequence":"additional","affiliation":[{"name":"IBM Research , Yorktown Heights, NY 10598,","place":["United States"]}]}],"member":"286","published-online":{"date-parts":[[2026,2,15]]},"reference":[{"key":"2026032005263384100_btag072-B1","first-page":"11334","article-title":"Attentive state-space modeling of disease progression","volume":"32","author":"Alaa","year":"2019","journal-title":"Adv Neural Inf Process Syst"},{"key":"2026032005263384100_btag072-B2","doi-asserted-by":"crossref","first-page":"4168","DOI":"10.1038\/s41598-021-83585-3","article-title":"Disease progression modelling from preclinical Alzheimer\u2019s disease (ad) to ad dementia","volume":"11","author":"Cho","year":"2021","journal-title":"Sci Rep"},{"key":"2026032005263384100_btag072-B3","volume-title":"The Theory of Stochastic Processes","author":"Cox","year":"1965"},{"key":"2026032005263384100_btag072-B4","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1111\/j.2517-6161.1977.tb01600.x","article-title":"Maximum likelihood from incomplete data via the EM algorithm","volume":"39","author":"Dempster","year":"1977","journal-title":"J R Stat Soc Ser B"},{"key":"2026032005263384100_btag072-B5","first-page":"92","author":"Ghosh","year":"2017"},{"key":"2026032005263384100_btag072-B6","volume-title":"Registries for Evaluating Patient Outcomes: A User\u2019s Guide. 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