Quantifying the heritability of glioma using genome-wide complex trait analysis View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2015-12

AUTHORS

Ben Kinnersley, Jonathan S. Mitchell, Konstantinos Gousias, Johannes Schramm, Ahmed Idbaih, Marianne Labussière, Yannick Marie, Amithys Rahimian, H.-Erich Wichmann, Stefan Schreiber, Khe Hoang-Xuan, Jean-Yves Delattre, Markus M. Nöthen, Karima Mokhtari, Mark Lathrop, Melissa Bondy, Matthias Simon, Marc Sanson, Richard S. Houlston

ABSTRACT

Genome-wide association studies (GWAS) have successfully identified a number of common single-nucleotide polymorphisms (SNPs) influencing glioma risk. While these SNPs only explain a small proportion of the genetic risk it is unclear how much is left to be detected by other, yet to be identified, common SNPs. Therefore, we applied Genome-Wide Complex Trait Analysis (GCTA) to three GWAS datasets totalling 3,373 cases and 4,571 controls and performed a meta-analysis to estimate the heritability of glioma. Our results identify heritability estimates of 25% (95% CI: 20-31%, P = 1.15 × 10(-17)) for all forms of glioma - 26% (95% CI: 17-35%, P = 1.05 × 10(-8)) for glioblastoma multiforme (GBM) and 25% (95% CI: 17-32%, P = 1.26 × 10(-10)) for non-GBM tumors. This is a substantial increase from the genetic variance identified by the currently identified GWAS risk loci (~6% of common heritability), indicating that most of the heritable risk attributable to common genetic variants remains to be identified. More... »

PAGES

17267

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/srep17267

DOI

http://dx.doi.org/10.1038/srep17267

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1029280811

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/26625949


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