Treffer: A multimodal vision knowledge graph of cardiovascular disease.
Title:
A multimodal vision knowledge graph of cardiovascular disease.
Authors:
Rjoob K; MRC Laboratory of Medical Sciences, Imperial College London, London, UK., McGurk KA; MRC Laboratory of Medical Sciences, Imperial College London, London, UK.; National Heart and Lung Institute, Imperial College London, London, UK., Zheng SL; MRC Laboratory of Medical Sciences, Imperial College London, London, UK.; National Heart and Lung Institute, Imperial College London, London, UK., Curran L; National Heart and Lung Institute, Imperial College London, London, UK.; Royal Brompton Hospital, London, UK., Ibrahim M; Bayer AG, Research and Development, Pharmaceuticals, Wuppertal, Germany., Zeng L; Bayer AG, Research and Development, Pharmaceuticals, Wuppertal, Germany., Kim V; Bayer AG, Research and Development, Pharmaceuticals, Wuppertal, Germany., Tahasildar S; MRC Laboratory of Medical Sciences, Imperial College London, London, UK., Kalaie S; MRC Laboratory of Medical Sciences, Imperial College London, London, UK.; Department of Computing, Department of Brain Sciences and Data Science Institute, Imperial College London, London, UK., Senevirathne DS; MRC Laboratory of Medical Sciences, Imperial College London, London, UK., Gifani P; MRC Laboratory of Medical Sciences, Imperial College London, London, UK., Losev V; MRC Laboratory of Medical Sciences, Imperial College London, London, UK., Zheng J; MRC Laboratory of Medical Sciences, Imperial College London, London, UK., Bai W; Department of Computing, Department of Brain Sciences and Data Science Institute, Imperial College London, London, UK., de Marvao A; MRC Laboratory of Medical Sciences, Imperial College London, London, UK.; British Heart Foundation Centre of Research Excellence, School of Cardiovascular and Metabolic Medicine and Sciences, King's College London, London, UK.; Department of Women and Children's Health, King's College London, London, UK., Ware JS; MRC Laboratory of Medical Sciences, Imperial College London, London, UK.; National Heart and Lung Institute, Imperial College London, London, UK.; Royal Brompton Hospital, London, UK., Bender C; Bayer AG, Research and Development, Pharmaceuticals, Wuppertal, Germany., O'Regan DP; MRC Laboratory of Medical Sciences, Imperial College London, London, UK. declan.oregan@imperial.ac.uk.
Source:
Nature cardiovascular research [Nat Cardiovasc Res] 2026 Jan; Vol. 5 (1), pp. 18-33. Date of Electronic Publication: 2025 Dec 29.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Springer Nature Country of Publication: England NLM ID: 9918284280206676 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2731-0590 (Electronic) Linking ISSN: 27310590 NLM ISO Abbreviation: Nat Cardiovasc Res Subsets: MEDLINE
Imprint Name(s):
Original Publication: [London] : Springer Nature, [2022]-
MeSH Terms:
Cardiovascular Diseases*/genetics , Cardiovascular Diseases*/drug therapy , Cardiovascular Diseases*/diagnostic imaging , Computer Graphics* , Computational Biology*/methods, Humans ; Phenotype ; Drug Repositioning ; Genetic Predisposition to Disease ; Cardiovascular Agents/therapeutic use ; Databases, Factual
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Nat Genet. 2024 Dec;56(12):2646-2658. (PMID: 39572783)
J Am Coll Cardiol. 2020 Dec 22;76(25):2982-3021. (PMID: 33309175)
Sci Data. 2023 Feb 2;10(1):67. (PMID: 36732524)
Heart Rhythm. 2023 Feb;20(2):315-317. (PMID: 36270578)
Cardiovasc Diabetol. 2017 Dec 19;16(1):159. (PMID: 29258504)
Nat Methods. 2013 Dec;10(12):1209-10. (PMID: 24122041)
Nucleic Acids Res. 2020 Jan 8;48(D1):D498-D503. (PMID: 31691815)
J Am Coll Cardiol. 2017 Jul 11;70(2):212-229. (PMID: 28683969)
Artif Intell Med. 2020 Mar;103:101817. (PMID: 32143785)
J Transl Med. 2024 Aug 5;22(1):726. (PMID: 39103897)
J Am Med Inform Assoc. 2015 Jan;22(1):179-91. (PMID: 25053577)
J Cardiovasc Magn Reson. 2018 Sep 14;20(1):65. (PMID: 30217194)
Nucleic Acids Res. 2019 Jan 8;47(D1):D559-D563. (PMID: 30357367)
Nat Genet. 2016 Mar;48(3):245-52. (PMID: 26854917)
Am J Hum Genet. 2017 Jul 6;101(1):5-22. (PMID: 28686856)
Nucleic Acids Res. 2020 Jan 8;48(D1):D704-D715. (PMID: 31701156)
Int J Med Sci. 2021 Jan 14;18(5):1216-1224. (PMID: 33526983)
BMC Bioinformatics. 2023 Aug 29;24(1):324. (PMID: 37644440)
Bioinformatics. 2010 Sep 1;26(17):2136-44. (PMID: 20591905)
Diabetol Metab Syndr. 2025 Apr 29;17(1):145. (PMID: 40301928)
Future Cardiol. 2024;20(13):671-683. (PMID: 39387403)
Curr Alzheimer Res. 2018;15(13):1231-1243. (PMID: 30129411)
J Biomed Semantics. 2023 Aug 14;14(1):11. (PMID: 37580835)
Alzheimers Dement (N Y). 2017 Jun 08;3(3):393-401. (PMID: 29067345)
Sci Rep. 2015 Jul 14;5:11427. (PMID: 26169582)
J Mol Cell Cardiol. 2019 May;130:36-48. (PMID: 30880250)
Ned Tijdschr Geneeskd. 2008 Mar 1;152(9):518-9. (PMID: 18389888)
Nucleic Acids Res. 2016 Jan 4;44(D1):D1075-9. (PMID: 26481350)
Nucleic Acids Res. 2021 Jan 8;49(D1):D1144-D1151. (PMID: 33237278)
Nucleic Acids Res. 2006 Jan 1;34(Database issue):D108-10. (PMID: 16381825)
JACC Heart Fail. 2019 Feb;7(2):121-128. (PMID: 30704603)
Nucleic Acids Res. 2021 Jan 8;49(D1):D1138-D1143. (PMID: 33068428)
Nat Commun. 2022 Dec 14;13(1):7753. (PMID: 36517512)
Nat Commun. 2020 May 26;11(1):2624. (PMID: 32457287)
IEEE Trans Neural Netw Learn Syst. 2022 Feb;33(2):494-514. (PMID: 33900922)
Artif Intell Rev. 2023 Apr 3;:1-32. (PMID: 37362886)
Ann Rheum Dis. 2021 Nov;80(11):1385-1392. (PMID: 34049859)
Nucleic Acids Res. 2021 Jan 8;49(D1):D325-D334. (PMID: 33290552)
Nucleic Acids Res. 2017 Jan 4;45(D1):D865-D876. (PMID: 27899602)
Genome Biol. 2012 Jan 31;13(1):R5. (PMID: 22293552)
Drugs Context. 2018 Nov 14;7:212557. (PMID: 30459819)
Nat Med. 2020 Oct;26(10):1654-1662. (PMID: 32839619)
Sci Data. 2024 Apr 11;11(1):363. (PMID: 38605048)
Nature. 2018 Oct;562(7726):203-209. (PMID: 30305743)
Am J Epidemiol. 2017 Nov 1;186(9):1026-1034. (PMID: 28641372)
Nucleic Acids Res. 2021 Jan 8;49(D1):D605-D612. (PMID: 33237311)
Brief Bioinform. 2024 Mar 27;25(3):. (PMID: 38627939)
KDD. 2016 Aug;2016:855-864. (PMID: 27853626)
Clin Pharmacol Ther. 2008 Sep;84(3):362-9. (PMID: 18500243)
J Cardiovasc Magn Reson. 2016 Feb 01;18:8. (PMID: 26830817)
Nucleic Acids Res. 2020 Jan 8;48(D1):D845-D855. (PMID: 31680165)
Clin Transl Discov. 2024 Jul;4(3):. (PMID: 38737752)
Protein Sci. 2021 Jan;30(1):187-200. (PMID: 33070389)
Nucleic Acids Res. 2021 Jan 8;49(D1):D831-D847. (PMID: 33037820)
Nucleic Acids Res. 2018 Jan 4;46(D1):D1074-D1082. (PMID: 29126136)
J Mol Cell Cardiol. 2024 Nov;196:141-151. (PMID: 39307416)
NAR Genom Bioinform. 2024 May 14;6(2):lqae049. (PMID: 38745993)
Nat Genet. 2024 Dec;56(12):2646-2658. (PMID: 39572783)
J Am Coll Cardiol. 2020 Dec 22;76(25):2982-3021. (PMID: 33309175)
Sci Data. 2023 Feb 2;10(1):67. (PMID: 36732524)
Heart Rhythm. 2023 Feb;20(2):315-317. (PMID: 36270578)
Grant Information:
S10 OD017985 United States OD NIH HHS; UL1 TR000445 United States TR NCATS NIH HHS; CH/F/24/90015 British Heart Foundation (BHF); S10 RR025141 United States RR NCRR NIH HHS; FS/IPBSRF/22/27059 British Heart Foundation (BHF); UL1 TR002243 United States TR NCATS NIH HHS; BBC/F/21/220106 British Heart Foundation (BHF); RE/24/130023 British Heart Foundation (BHF); RG/F/24/110138 British Heart Foundation (BHF); MC_UP_1605/13 RCUK | Medical Research Council (MRC); S10 OD025092 United States OD NIH HHS; 21JTA Sir Jules Thorn Charitable Trust; UL1 RR024975 United States RR NCRR NIH HHS
Substance Nomenclature:
0 (Cardiovascular Agents)
Entry Date(s):
Date Created: 20251230 Date Completed: 20260116 Latest Revision: 20260120
Update Code:
20260120
PubMed Central ID:
PMC12811117
DOI:
10.1038/s44161-025-00757-4
PMID:
41461900
Database:
MEDLINE
Weitere Informationen
Understanding gene-disease associations is important for uncovering pathological mechanisms and identifying potential therapeutic targets. Knowledge graphs can represent and integrate data from multiple biomedical sources, but lack individual-level information on target organ structure and function. Here we develop CardioKG, a knowledge graph that integrates over 200,000 computer vision-derived cardiovascular phenotypes from biomedical images with data extracted from 18 biological databases to model over a million relationships. We used a variational graph auto-encoder to generate node embeddings from the knowledge graph to predict gene-disease associations, assess druggability and identify drug repurposing strategies. The model predicted genetic associations and therapeutic opportunities for leading causes of cardiovascular disease, which were associated with improved survival. Candidate therapies included methotrexate for heart failure and gliptins for atrial fibrillation, and the addition of imaging data enhanced pathway discovery. These capabilities support the use of biomedical imaging to enhance graph-structured models for identifying treatable disease mechanisms.
(© 2025. The Author(s).)
Competing interests: D.P.O’R. receives research support from Bayer AG and Calico Labs, and is a paid consultant to Bayer AG and Bristol Myers Squibb. J.S.W. has received research support from Bristol Myers Squibb, has acted as a paid advisor to Health Lumen, Tenaya Therapeutics, and Solid Biosciences, and is a founder with equity in Saturnus Bio. All other authors declare no competing interests.