Network medicine-based epistasis detection in complex diseases: ready for quantum computing.

Autor:	Hoffmann M; Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Germany.; Institute for Advanced Study (Lichtenbergstrasse 2 a, D-85748 Garching, Germany), Technical University of Munich, Germany.; National Institute of Diabetes, Digestive, and Kidney Diseases, Bethesda, MD 20892, United States of America., Poschenrieder JM; Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Germany.; Institute for Computational Systems Biology, University of Hamburg, Germany., Incudini M; Dipartimento di Informatica, Universit'a di Verona, Strada le Grazie 15 - 34137, Verona, Italy., Baier S; Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Germany., Fitz A; Department of Health Technology, Section for Bioinformatics, Technical University of Denmark, DTU, 2800 Kgs. Lyngby, Denmark.; Copenhagen Prospective Studies on Asthma in Childhood (COPSAC), Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark., Maier A; Institute for Computational Systems Biology, University of Hamburg, Germany., Hartung M; Institute for Computational Systems Biology, University of Hamburg, Germany., Hoffmann C; Institute for Computational Systems Biology, University of Hamburg, Germany., Trummer N; Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Germany., Adamowicz K; Institute for Computational Systems Biology, University of Hamburg, Germany., Picciani M; Computational Mass Spectrometry, Technical University of Munich, Freising, Germany., Scheibling E; Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Germany., Harl MV; Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Germany., Lesch I; Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Germany., Frey H; Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Germany., Kayser S; Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Germany., Wissenberg P; Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Germany., Schwartz L; Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Germany., Hafner L; Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Germany.; Institute for Advanced Study (Lichtenbergstrasse 2 a, D-85748 Garching, Germany), Technical University of Munich, Germany., Acharya A; Division Data Science in Biomedicine, Peter L. Reichertz Institute for Medical Informatics, Technische Universität Braunschweig and Hannover Medical School, Rebenring 56, 38106 Braunschweig, Germany.; Braunschweig Integrated Centre of Systems Biology (BRICS), Technische Universität Braunschweig, Rebenring 56, 38106 Braunschweig, Braunschweig, Germany., Hackl L; Institute for Computational Systems Biology, University of Hamburg, Germany., Grabert G; Division Data Science in Biomedicine, Peter L. Reichertz Institute for Medical Informatics, Technische Universität Braunschweig and Hannover Medical School, Rebenring 56, 38106 Braunschweig, Germany.; Braunschweig Integrated Centre of Systems Biology (BRICS), Technische Universität Braunschweig, Rebenring 56, 38106 Braunschweig, Braunschweig, Germany., Lee SG; National Institute of Diabetes, Digestive, and Kidney Diseases, Bethesda, MD 20892, United States of America.; School of Biological Sciences and Technology, Chonnam National University, Gwangju, Korea., Cho G; Department of Chemistry, Gwangju Institute of Science and Technology, Gwangju, Korea., Cloward M; Department of Biology, Brigham Young University, Provo, UT, USA., Jankowski J; National Institute of Diabetes, Digestive, and Kidney Diseases, Bethesda, MD 20892, United States of America., Lee HK; National Institute of Diabetes, Digestive, and Kidney Diseases, Bethesda, MD 20892, United States of America., Tsoy O; Institute for Computational Systems Biology, University of Hamburg, Germany., Wenke N; Institute for Computational Systems Biology, University of Hamburg, Germany., Pedersen AG; Department of Health Technology, Section for Bioinformatics, Technical University of Denmark, DTU, 2800 Kgs. Lyngby, Denmark., Bønnelykke K; Copenhagen Prospective Studies on Asthma in Childhood (COPSAC), Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark., Mandarino A; International Centre for Theory of Quantum Technologies, University of Gdańsk, 80-309 Gdańsk, Poland., Melograna F; BIO3 - Systems Genetics; GIGA-R Medical Genomics, University of Liège, Liège, Belgium.; BIO3 - Systems Medicine; Department of Human Genetics, KU Leuven, Leuven, Belgium., Schulz L; Leibniz Supercomputing Centre of the Bavarian Academy of Sciences and Humanities (LRZ), Garching b. München, Germany., Climente-González H; RIKEN Center for Advanced Intelligence Project, Tokyo, Japan., Wilhelm M; Computational Mass Spectrometry, Technical University of Munich, Freising, Germany., Iapichino L; Leibniz Supercomputing Centre of the Bavarian Academy of Sciences and Humanities (LRZ), Garching b. München, Germany., Wienbrandt L; Institute of Clinical Molecular Biology, Christian Albrechts University of Kiel, Kiel, Germany., Ellinghaus D; Institute of Clinical Molecular Biology, Christian Albrechts University of Kiel, Kiel, Germany., Van Steen K; BIO3 - Systems Genetics; GIGA-R Medical Genomics, University of Liège, Liège, Belgium.; BIO3 - Systems Medicine; Department of Human Genetics, KU Leuven, Leuven, Belgium., Grossi M; European Organization for Nuclear Research (CERN), Geneva 1211, Switzerland., Furth PA; National Institute of Diabetes, Digestive, and Kidney Diseases, Bethesda, MD 20892, United States of America.; Departments of Oncology & Medicine, Georgetown University, Washington, DC, USA., Hennighausen L; Institute for Advanced Study (Lichtenbergstrasse 2 a, D-85748 Garching, Germany), Technical University of Munich, Germany.; National Institute of Diabetes, Digestive, and Kidney Diseases, Bethesda, MD 20892, United States of America., Di Pierro A; Dipartimento di Informatica, Universit'a di Verona, Strada le Grazie 15 - 34137, Verona, Italy., Baumbach J; Institute for Computational Systems Biology, University of Hamburg, Germany.; Computational BioMedicine Lab, University of Southern Denmark, Denmark., Kacprowski T; Division Data Science in Biomedicine, Peter L. Reichertz Institute for Medical Informatics, Technische Universität Braunschweig and Hannover Medical School, Rebenring 56, 38106 Braunschweig, Germany.; Braunschweig Integrated Centre of Systems Biology (BRICS), Technische Universität Braunschweig, Rebenring 56, 38106 Braunschweig, Braunschweig, Germany., List M; Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Germany., Blumenthal DB; Department Artificial Intelligence in Biomedical Engineering (AIBE), Friedrich-Alexander University Erlangen-Nürnberg (FAU), Erlangen, Germany.
Jazyk:	angličtina
Zdroj:	MedRxiv : the preprint server for health sciences [medRxiv] 2023 Nov 09. Date of Electronic Publication: 2023 Nov 09.
DOI:	10.1101/2023.11.07.23298205
Abstrakt:	Most heritable diseases are polygenic. To comprehend the underlying genetic architecture, it is crucial to discover the clinically relevant epistatic interactions (EIs) between genomic single nucleotide polymorphisms (SNPs) 1-3 . Existing statistical computational methods for EI detection are mostly limited to pairs of SNPs due to the combinatorial explosion of higher-order EIs. With NeEDL ( ne twork-based e pistasis d etection via l ocal search), we leverage network medicine to inform the selection of EIs that are an order of magnitude more statistically significant compared to existing tools and consist, on average, of five SNPs. We further show that this computationally demanding task can be substantially accelerated once quantum computing hardware becomes available. We apply NeEDL to eight different diseases and discover genes (affected by EIs of SNPs) that are partly known to affect the disease, additionally, these results are reproducible across independent cohorts. EIs for these eight diseases can be interactively explored in the Epistasis Disease Atlas (https://epistasis-disease-atlas.com). In summary, NeEDL is the first application that demonstrates the potential of seamlessly integrated quantum computing techniques to accelerate biomedical research. Our network medicine approach detects higher-order EIs with unprecedented statistical and biological evidence, yielding unique insights into polygenic diseases and providing a basis for the development of improved risk scores and combination therapies. Competing Interests: Competing interests During the course of the project, HCG became a full-time employee of Novo Nordisk Ltd.
Databáze:	MEDLINE
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