Age-dependent topic modeling of comorbidities in UK Biobank identifies disease subtypes with differential genetic risk.

"all codes generated in this study are available at https://zenodo org/record/8304651 (10 5281/zenodo 8304651)."

"code availability open-source software implementing the atm method is available at https://github com/xilin-jiang/atm .; heritability and genetic correlation analysis were performed using ldsc which is available at https://github com/bulik/ldsc ."

"Competing interests G.M. is a director of and shareholder in Genomics PLC and is a partner in Peptide Groove LLP. The other authors declare no competing financial interests."

"This research has been conducted using the UK Biobank Resource (application 12788). The All of Us Research Program is supported by the National Institutes of Health, Office of the Director: Regional Medical Centers (1 OT2 OD026549, 1 OT2 OD026554, 1 OT2 OD026557, 1 OT2 OD026556, 1 OT2 OD026550, 1 OT2 OD 026552, 1 OT2 OD026553, 1 OT2 OD026548, 1 OT2 OD026551, 1 OT2 OD026555 and IAA: AOD 16037), Federally Qualified Health Centers (HHSN 263201600085U), Data and Research Center (5 U2C OD023196), Biobank (1 U24 OD023121), The Participant Center: (U24 OD023176), Participant Technology Systems Center (1 U24 OD023163), Communications and Engagement (3 OT2 OD023205 and 3 OT2 OD023206) and Community Partners (1 OT2 OD025277, 3 OT2 OD025315, 1 OT2 OD025337 and 1 OT2 OD025276). In addition, the All of Us Research Program would not be possible without the partnership of its participants. This work was funded by Wellcome (215096/Z/18/Z to X.J. and 100956/Z/13/Z to G.M.; https://wellcome.org); the Li Ka Shing Foundation (to G.M.; https://www.lksf.org); NIH (grants R01 HG006399, R01 MH101244 and R37 MH107649 to A.L.P.); the Alan Turing Institute (https://www.turing.ac.uk), Health Data Research UK (https://www.hdruk.ac.uk), the Medical Research Council UK (https://mrc.ukri.org), the Engineering and Physical Sciences Research Council (EPSRC; https://epsrc.ukri.org) through the Bayes4Health program (grant EP/R018561/1) and AI for Science and Government UK Research and Innovation (UKRI (to C.H.); https://www.turing.ac.uk/research/asg); British Heart Foundation award reference number CH/12/2/29428 (to X.J.); Munz Chair of Cardiovascular Prediction and Prevention and the NIHR Cambridge Biomedical Research Center (BRC-1215-20014; NIHR203312) and UK Economic and Social Research 878 Council (ES/T013192/1 to M.I.). This work was supported by core funding from the British Heart Foundation (RG/13/13/30194 and RG/18/13/33946), Cambridge BHF Center of Research Excellence (RE/18/1/34212) and NIHR Cambridge Biomedical Research Center (BRC-1215-20014 and NIHR203312). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. This work uses data provided by patients and collected by the NHS as part of their care and Support. Computation used the Oxford Biomedical Research Computing (BMRC) facility, a joint development between the Wellcome Center for Human Genetics and the Big Data Institute supported by Health Data Research UK and the NIHR Oxford Biomedical Research Center. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. We thank K. Dey (Sloan Kettering Institute), L. Kelly (University of Oxford) and Yunlong Jiao (University of Oxford) for the helpful discussion."