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Early stratification of individuals into subgroups based on age at onset (AAO) has the potential to inform diagnosis and early intervention. Yet, the psychosocial predictors associated with AAO are unknown.<\/jats:p><\/jats:sec><jats:sec id=\"S2056472422005361_sec_a2\"><jats:title>Aims<\/jats:title><jats:p>We aim to identify psychosocial factors associated with bipolar disorder AAO.<\/jats:p><\/jats:sec><jats:sec id=\"S2056472422005361_sec_a3\" sec-type=\"methods\"><jats:title>Method<\/jats:title><jats:p>Using data from the Bipolar Disorder Research Network UK, we employed least absolute shrinkage and selection operator regression to identify psychosocial factors associated with bipolar disorder AAO. Twenty-eight factors were entered into our model, with AAO as our outcome measure.<\/jats:p><\/jats:sec><jats:sec id=\"S2056472422005361_sec_a4\" sec-type=\"results\"><jats:title>Results<\/jats:title><jats:p>We included 1022 participants with bipolar disorder (\u03bc = 23.0, s.d. \u00b1 9.86) in our model. Six variables predicted an earlier AAO: childhood abuse (\u03b2 = \u22120.2855), regular cannabis use in the year before onset (\u03b2 = \u22120.2765), death of a close family friend or relative in the 6 months before onset (\u03b2 = \u22120.2435), family history of suicide (\u03b2 = \u22120.1385), schizotypal personality traits (\u03b2 = \u22120.1055) and irritable temperament (\u03b2 = \u22120.0685). Five predicted a later AAO: the average number of alcohol units consumed per week in the year before onset (\u03b2 = 0.1385); birth of a child in the 6 months before onset (\u03b2 = 0.2755); death of parent, partner, child or sibling in the 6 months before onset (\u03b2 = 0.3125); seeking work without success for 1 month or more in the 6 months before onset (\u03b2 = 0.3505) and a major financial crisis in the 6 months before onset (\u03b2 = 0.4575).<\/jats:p><\/jats:sec><jats:sec id=\"S2056472422005361_sec_a5\" sec-type=\"conclusions\"><jats:title>Conclusions<\/jats:title><jats:p>The identified predictor variables have the potential to help stratify high-risk individuals into likely AAO groups, to inform treatment provision and early intervention.<\/jats:p><\/jats:sec>","DOI":"10.1192\/bjo.2022.536","type":"journal-article","created":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T07:29:07Z","timestamp":1658129347000},"update-policy":"https:\/\/doi.org\/10.1017\/policypage","source":"Crossref","is-referenced-by-count":9,"title":["Psychosocial markers of age at onset in bipolar disorder: a machine learning approach"],"prefix":"10.1192","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5857-6748","authenticated-orcid":false,"given":"Sorcha","family":"Bolton","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dan W.","family":"Joyce","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4083-1143","authenticated-orcid":false,"given":"Katherine","family":"Gordon-Smith","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5122-8334","authenticated-orcid":false,"given":"Lisa","family":"Jones","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5821-5889","authenticated-orcid":false,"given":"Ian","family":"Jones","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John","family":"Geddes","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kate E. 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