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Nature Research, Scientific Reports, 1(5), 2015

DOI: 10.1038/srep17267

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

Journal article published in 2015 by Ben Kinnersley ORCID, Jonathan S. Mitchell, Konstantinos Gousias, Johannes Schramm, Ahmed Idbaih, Marianne Labussière, Yannick Marie, Amithys Rahimian, H.-Erich Wichmann, H. Erich Wichmann, Stefan Schreiber, Khe Hoang-Xuan, Jean-Yves Delattre, Markus M. Noethen, Markus M. Nöthen and other authors.
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

AbstractGenome-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.