{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,7]],"date-time":"2026-08-07T16:13:50Z","timestamp":1786119230572,"version":"build-2736575974"},"reference-count":52,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T00:00:00Z","timestamp":1782345600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T00:00:00Z","timestamp":1782345600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100000925","name":"National Health and Medical Research Council","doi-asserted-by":"publisher","award":["1031119"],"award-info":[{"award-number":["1031119"]}],"id":[{"id":"10.13039\/501100000925","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000925","name":"National Health and Medical Research Council","doi-asserted-by":"publisher","award":["1049911"],"award-info":[{"award-number":["1049911"]}],"id":[{"id":"10.13039\/501100000925","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000925","name":"National Health and Medical Research Council","doi-asserted-by":"publisher","award":["APP10499110"],"award-info":[{"award-number":["APP10499110"]}],"id":[{"id":"10.13039\/501100000925","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Bipolar Disorders"],"published-print":{"date-parts":[[2026,8]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>There is broad agreement that the onset of bipolar disorders (BD) can be predicted by using combined estimates of familial, genetic and clinical risk. However, there is a lack of consensus about the operationalisation of different risk attributes (e.g., symptoms vs. sub\u2010threshold syndromes; disorder\u2010specific polygenic risk scores [PRS] vs. multiple\u2010disorder PRS dimensions) and their utility for predicting bipolar type 1 (BD\u2010I) and 2 (BD\u2010II). Likewise, analyses often fail to consider the optimal model for predicting outcomes where true cases will be in the minority.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methodology<\/jats:title>\n                    <jats:p>Proof of concept study employing an ensemble machine learning approach (Boosting) to develop models for classifying BD cases vs. non\u2010cases using different combinations of risk attributes extracted from a database from a prospective longitudinal follow\u2010up of twin and non\u2010twin siblings in the peak age range for onset of major mental disorders.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Of 1473 participants (mean age 26.3; female\u2009=\u2009866), 104 developed BD\u2010I (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u200930) or BD\u2010II (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u200974). The best performing Boosting classification had an overall area under the receiver operating curve (AUROC) of 85.1% (95% Confidence Intervals: 80%, 88%); correctly identifying 86.7% BD cases. Variables with greatest relative influence were, in rank order: depressive symptoms, psychotic symptoms, a BD\u2010Schizophrenia PRS dimension, hypomanic symptoms, and family history of BD. The model accurately classified 89% of manic cases but only 68% of hypomanic cases.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Improving the accurate prediction of BD onset would benefit from greater consensus regarding the operationalisation of known risk attributes and selection of analytic models that consider sample imbalances.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/bdi.70140","type":"journal-article","created":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T06:50:55Z","timestamp":1782456655000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Can We Improve the Prediction of Early Onset Mania and Hypomania in the Community?"],"prefix":"10.1111","volume":"28","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7203-8601","authenticated-orcid":false,"given":"Jan","family":"Scott","sequence":"first","affiliation":[{"name":"Brain and Mind Centre The University of Sydney  Sydney Australia"},{"name":"Institute of Neuroscience Newcastle University  Newcastle UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jacob J.","family":"Crouse","sequence":"additional","affiliation":[{"name":"Brain and Mind Centre The University of Sydney  Sydney Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sarah E.","family":"Medland","sequence":"additional","affiliation":[{"name":"Brain and Mental Health Program QIMR Berghofer Institute of Medical Research  Brisbane Australia"},{"name":"Institute of Molecular Bioscience The University of Queensland  Brisbane Australia"},{"name":"School of Psychology The University of Queensland  Brisbane Queensland Australia"},{"name":"School of Psychology and Counselling Queensland University of Technology  Brisbane Queensland Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Brittany L.","family":"Mitchell","sequence":"additional","affiliation":[{"name":"Brain and Mental Health Program QIMR Berghofer Institute of Medical Research  Brisbane Australia"},{"name":"Institute of Molecular Bioscience The University of Queensland  Brisbane Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nathan A.","family":"Gillespie","sequence":"additional","affiliation":[{"name":"Virginia Institute for Psychiatric and Behavioral Genetics Virginia Commonwealth University  Richmond Virginia USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nicholas G.","family":"Martin","sequence":"additional","affiliation":[{"name":"Brain and Mental Health Program QIMR Berghofer Institute of Medical Research  Brisbane Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ian 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