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Meta-Analysis of Genome-Wide Association Studies and Network Analysis-Based Integration with Gene Expression Data Identify New Suggestive Loci and Unravel a Wnt-Centric Network Associated with Dupuytren’s Disease

Author

Listed:
  • Kerstin Becker
  • Sabine Siegert
  • Mohammad Reza Toliat
  • Juanjiangmeng Du
  • Ramona Casper
  • Guido H Dolmans
  • Paul M Werker
  • Sigrid Tinschert
  • Andre Franke
  • Christian Gieger
  • Konstantin Strauch
  • Michael Nothnagel
  • Peter Nürnberg
  • Hans Christian Hennies
  • German Dupuytren Study Group

Abstract

Dupuytren´s disease, a fibromatosis of the connective tissue in the palm, is a common complex disease with a strong genetic component. Up to date nine genetic loci have been found to be associated with the disease. Six of these loci contain genes that code for Wnt signalling proteins. In spite of this striking first insight into the genetic factors in Dupuytren´s disease, much of the inherited risk in Dupuytren´s disease still needs to be discovered. The already identified loci jointly explain ~1% of the heritability in this disease. To further elucidate the genetic basis of Dupuytren´s disease, we performed a genome-wide meta-analysis combining three genome-wide association study (GWAS) data sets, comprising 1,580 cases and 4,480 controls. We corroborated all nine previously identified loci, six of these with genome-wide significance (p-value

Suggested Citation

  • Kerstin Becker & Sabine Siegert & Mohammad Reza Toliat & Juanjiangmeng Du & Ramona Casper & Guido H Dolmans & Paul M Werker & Sigrid Tinschert & Andre Franke & Christian Gieger & Konstantin Strauch & , 2016. "Meta-Analysis of Genome-Wide Association Studies and Network Analysis-Based Integration with Gene Expression Data Identify New Suggestive Loci and Unravel a Wnt-Centric Network Associated with Dupuytr," PLOS ONE, Public Library of Science, vol. 11(7), pages 1-18, July.
    • Handle: RePEc:plo:pone00:0158101
    DOI: 10.1371/journal.pone.0158101
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    References listed on IDEAS

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    1. Bryan N Howie & Peter Donnelly & Jonathan Marchini, 2009. "A Flexible and Accurate Genotype Imputation Method for the Next Generation of Genome-Wide Association Studies," PLOS Genetics, Public Library of Science, vol. 5(6), pages 1-15, June.
    2. Olivier Delaneau & Jonathan Marchini, 2014. "Integrating sequence and array data to create an improved 1000 Genomes Project haplotype reference panel," Nature Communications, Nature, vol. 5(1), pages 1-9, September.
    3. Soumya Raychaudhuri & Robert M Plenge & Elizabeth J Rossin & Aylwin C Y Ng & International Schizophrenia Consortium & Shaun M Purcell & Pamela Sklar & Edward M Scolnick & Ramnik J Xavier & David Altsh, 2009. "Identifying Relationships among Genomic Disease Regions: Predicting Genes at Pathogenic SNP Associations and Rare Deletions," PLOS Genetics, Public Library of Science, vol. 5(6), pages 1-15, June.
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    Cited by:

    1. Sophie A. Riesmeijer & Zoha Kamali & Michael Ng & Dmitriy Drichel & Bram Piersma & Kerstin Becker & Thomas B. Layton & Jagdeep Nanchahal & Michael Nothnagel & Ahmad Vaez & Hans Christian Hennies & Pau, 2024. "A genome-wide association meta-analysis implicates Hedgehog and Notch signaling in Dupuytren’s disease," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    2. Cherif Ben Hamda & Raphael Sangeda & Liberata Mwita & Ayton Meintjes & Siana Nkya & Sumir Panji & Nicola Mulder & Lamia Guizani-Tabbane & Alia Benkahla & Julie Makani & Kais Ghedira & H3ABioNet Consor, 2018. "A common molecular signature of patients with sickle cell disease revealed by microarray meta-analysis and a genome-wide association study," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-21, July.

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