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Identifying interpretable gene-biomarker associations with functionally informed kernel-based tests in 190,000 exomes

  • Here we present an exome-wide rare genetic variant association study for 30 blood biomarkers in 191,971 individuals in the UK Biobank. We compare gene- based association tests for separate functional variant categories to increase interpretability and identify 193 significant gene-biomarker associations. Genes associated with biomarkers were ~ 4.5-fold enriched for conferring Mendelian disorders. In addition to performing weighted gene-based variant collapsing tests, we design and apply variant-category-specific kernel-based tests that integrate quantitative functional variant effect predictions for mis- sense variants, splicing and the binding of RNA-binding proteins. For these tests, we present a computationally efficient combination of the likelihood- ratio and score tests that found 36% more associations than the score test alone while also controlling the type-1 error. Kernel-based tests identified 13% more associations than their gene-based collapsing counterparts and had advantages in the presence of gain of function missenseHere we present an exome-wide rare genetic variant association study for 30 blood biomarkers in 191,971 individuals in the UK Biobank. We compare gene- based association tests for separate functional variant categories to increase interpretability and identify 193 significant gene-biomarker associations. Genes associated with biomarkers were ~ 4.5-fold enriched for conferring Mendelian disorders. In addition to performing weighted gene-based variant collapsing tests, we design and apply variant-category-specific kernel-based tests that integrate quantitative functional variant effect predictions for mis- sense variants, splicing and the binding of RNA-binding proteins. For these tests, we present a computationally efficient combination of the likelihood- ratio and score tests that found 36% more associations than the score test alone while also controlling the type-1 error. Kernel-based tests identified 13% more associations than their gene-based collapsing counterparts and had advantages in the presence of gain of function missense variants. We introduce local collapsing by amino acid position for missense variants and use it to interpret associations and identify potential novel gain of function variants in PIEZO1. Our results show the benefits of investigating different functional mechanisms when performing rare-variant association tests, and demonstrate pervasive rare-variant contribution to biomarker variability.zeige mehrzeige weniger

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Metadaten
Verfasserangaben:Remo MontiORCiD, Pia Rautenstrauch, Mahsa Ghanbari, Alva Rani James, Matthias KirchlerORCiD, Uwe Ohler, Stefan KonigorskiORCiDGND, Christoph LippertORCiD
URN:urn:nbn:de:kobv:517-opus4-586078
DOI:https://doi.org/10.25932/publishup-58607
Titel des übergeordneten Werks (Deutsch):Zweitveröffentlichungen der Universität Potsdam : Reihe der Digital Engineering Fakultät
Schriftenreihe (Bandnummer):Zweitveröffentlichungen der Universität Potsdam : Reihe der Digital Engineering Fakultät (16)
Publikationstyp:Postprint
Sprache:Englisch
Datum der Erstveröffentlichung:10.11.2022
Erscheinungsjahr:2022
Veröffentlichende Institution:Universität Potsdam
Datum der Freischaltung:31.03.2023
Ausgabe:16
Seitenanzahl:16
Quelle:Nature communications 13 (2022), 5332 DOI: 10.1038/s41467-022-32864-2
Organisationseinheiten:Digital Engineering Fakultät / Hasso-Plattner-Institut für Digital Engineering GmbH
DDC-Klassifikation:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Peer Review:Referiert
Publikationsweg:Open Access / Green Open-Access
Lizenz (Deutsch):License LogoCC-BY - Namensnennung 4.0 International
Externe Anmerkung:Bibliographieeintrag der Originalveröffentlichung
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