{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"medRxiv"}],"indexed":{"date-parts":[[2026,1,16]],"date-time":"2026-01-16T13:01:51Z","timestamp":1768568511997,"version":"3.49.0"},"posted":{"date-parts":[[2025,4,22]]},"group-title":"Orthopedics","reference-count":28,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2025,4,22]],"date-time":"2025-04-22T00:00:00Z","timestamp":1745280000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2025,4,22]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                <jats:sec>\n                  <jats:title>Background<\/jats:title>\n                  <jats:p>Enthesopathy and enthesitis, including rotator cuff disease and other tendon disorders, represent a heterogeneous group of musculoskeletal conditions with complex etiologies. Understanding how systemic health profiles influence their onset remains a critical challenge in musculoskeletal medicine.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Methods<\/jats:title>\n                  <jats:p>We conducted a large-scale, phenome-wide comorbidity analysis using longitudinal electronic health records (EHR) from 432,757 UK Biobank participants. Incident cases of peripheral enthesopathies were compared to controls across 434 baseline disease phenotypes. A directed ego network was constructed to link significantly associated comorbidities to the target condition using odds ratio-based associations. Unsupervised clustering via UMAP and DBSCAN identified data-driven comorbidity clusters, which were consolidated into unified endotypes-interpreted as distinct systemic profiles contributing to disease risk. Additionally, metapath-based trajectory analysis was applied to uncover temporally structured multimorbidity chains leading to disease onset.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>We identified 183 baseline conditions significantly associated with the future development of enthesopathy (FDR &lt; 0.05). Network clustering revealed eight comorbidity clusters, which were consolidated into four unified endotypes: Metabolic-Psychosomatic, Inflammatory-Multisystem, Mechanical-Injury-driven, and Aging-Intervention-related. Metapath analysis uncovered common three-step disease trajectories, such as metabolic-infectious-musculoskeletal and inflammatory skin-to-joint progressions, highlighting potential mechanistic pathways. These endotypes showed diverse clinical features but shared biological coherence, suggesting that different systemic health profiles can converge to drive tendon-related disease.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Conclusions<\/jats:title>\n                  <jats:p>This study introduces a scalable framework for identifying systemic multimorbidity patterns underlying enthesopathy and enthesitis using phenome-wide comorbidity networks. By integrating network clustering and metapath analysis, we uncover interpretable, data-driven endotypes that may inform individualized risk assessment and targeted care strategies. These findings contribute to the growing field of biobank-scale disease modeling and offer a foundation for precision approaches in musculoskeletal medicine.<\/jats:p>\n                <\/jats:sec>","DOI":"10.1101\/2025.04.21.25326169","type":"posted-content","created":{"date-parts":[[2025,4,23]],"date-time":"2025-04-23T12:34:19Z","timestamp":1745411659000},"source":"Crossref","is-referenced-by-count":1,"title":["Phenome-wide comorbidity network analysis reveals clinical risk patterns in enthesopathy and enthesitis"],"prefix":"10.64898","author":[{"given":"Yonghyun","family":"Nam","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dong-gi","family":"Lee","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jakob","family":"Woerner","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Se-Hwan","family":"Lee","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Min Ji","family":"Lee","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sung-Han","family":"Jo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jaeun","family":"Jung","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Su 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