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Conditional and interaction gene-set analysis reveals novel functional pathways for blood pressure

Author

Listed:
  • Christiaan A. Leeuw

    (VU University Amsterdam)

  • Sven Stringer

    (VU University Amsterdam)

  • Ilona A. Dekkers

    (Leiden University Medical Center)

  • Tom Heskes

    (Radboud University Nijmegen)

  • Danielle Posthuma

    (VU University Amsterdam
    VU University Medical Center)

Abstract

Gene-set analysis provides insight into which functional and biological properties of genes are aetiologically relevant for a particular phenotype. But genes have multiple properties, and these properties are often correlated across genes. This can cause confounding in a gene-set analysis, because one property may be statistically associated even if biologically irrelevant to the phenotype, by being correlated with gene properties that are relevant. To address this issue we present a novel conditional and interaction gene-set analysis approach, which attains considerable functional refinement of its conclusions compared to traditional gene-set analysis. We applied our approach to blood pressure phenotypes in the UK Biobank data (N = 360,243), the results of which we report here. We confirm and further refine several associations with multiple processes involved in heart and blood vessel formation but also identify novel interactions, among others with cardiovascular tissues involved in regulatory pathways of blood pressure homoeostasis.

Suggested Citation

  • Christiaan A. Leeuw & Sven Stringer & Ilona A. Dekkers & Tom Heskes & Danielle Posthuma, 2018. "Conditional and interaction gene-set analysis reveals novel functional pathways for blood pressure," Nature Communications, Nature, vol. 9(1), pages 1-13, December.
    • Handle: RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-06022-6
    DOI: 10.1038/s41467-018-06022-6
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    Cited by:

    1. Milton Pividori & Sumei Lu & Binglan Li & Chun Su & Matthew E. Johnson & Wei-Qi Wei & Qiping Feng & Bahram Namjou & Krzysztof Kiryluk & Iftikhar J. Kullo & Yuan Luo & Blair D. Sullivan & Benjamin F. V, 2023. "Projecting genetic associations through gene expression patterns highlights disease etiology and drug mechanisms," Nature Communications, Nature, vol. 14(1), pages 1-18, December.
    2. Nagel, Mats, 2020. "Changing perspectives: Towards detailed phenotyping in genetics," Thesis Commons a4nz2, Center for Open Science.
    3. Maria Niarchou & Daniel E. Gustavson & J. Fah Sathirapongsasuti & Manuel Anglada-Tort & Else Eising & Eamonn Bell & Evonne McArthur & Peter Straub & J. Devin McAuley & John A. Capra & Fredrik Ullén & , 2022. "Genome-wide association study of musical beat synchronization demonstrates high polygenicity," Nature Human Behaviour, Nature, vol. 6(9), pages 1292-1309, September.

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