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  • 标题:Implementation of genome-wide complex trait analysis to quantify the heritability in multiple myeloma
  • 本地全文:下载
  • 作者:Jonathan S. Mitchell ; David C. Johnson ; Kevin Litchfield
  • 期刊名称:Scientific Reports
  • 电子版ISSN:2045-2322
  • 出版年度:2015
  • 卷号:5
  • DOI:10.1038/srep12473
  • 出版社:Springer Nature
  • 摘要:A sizeable fraction of multiple myeloma (MM) is expected to be explained by heritable factors. Genome-wide association studies (GWAS) have successfully identified a number of common single-nucleotide polymorphisms (SNPs) influencing MM 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 2,282 cases and 5,197 controls individuals to estimate the heritability of MM. We estimated that the heritability explained by known common MM risk SNPs identified in GWAS was 2.9% (±2.4%), whereas the heritability explained by all common SNPs was 15.2% (±2.8%). Comparing the heritability explained by the common variants with that from family studies, a fraction of the heritability may be explained by other genetic variants, such as rare variants. In summary, our results suggest that known MM SNPs only explain a small proportion of the heritability and more common SNPs remain to be identified.
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