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Blogger's Note: not terribly useful without open access
Abstract
Background: Studies of
related individuals have consistently demonstrated notable familial
aggregation of cancer. We aim to estimate
the heritability and genetic correlation
attributable to the additive effects of common single-nucleotide
polymorphisms (SNPs)
for cancer at 13 anatomical sites.
Methods: Between 2007
and 2014, the US National Cancer Institute has generated data from
genome-wide association studies (GWAS) for
49 492 cancer case patients and 34 131 control
patients. We apply novel mixed model methodology (GCTA) to this GWAS
data to
estimate the heritability of individual cancers,
as well as the proportion of heritability attributable to cigarette
smoking
in smoking-related cancers, and the genetic
correlation between pairs of cancers.
Results: GWAS heritability was statistically significant at nearly all sites, with the estimates of array-based heritability, hl
2, on the liability threshold (LT)
scale ranging from 0.05 to 0.38. Estimating the combined heritability of
multiple smoking
characteristics, we calculate that at least 24%
(95% confidence interval [CI] = 14% to 37%) and 7% (95% CI = 4% to 11%)
of
the heritability for lung and bladder cancer,
respectively, can be attributed to genetic determinants of smoking. Most
pairs
of cancers studied did not show evidence of
strong genetic correlation. We found only four pairs of cancers with
marginally
statistically significant correlations,
specifically kidney and testes (ρ = 0.73, SE = 0.28), diffuse large
B-cell lymphoma
(DLBCL) and pediatric osteosarcoma (ρ = 0.53, SE
= 0.21), DLBCL and chronic lymphocytic leukemia (CLL) (ρ = 0.51, SE
=0.18),
and bladder and lung (ρ = 0.35, SE = 0.14).
Correlation analysis also indicates that the genetic architecture of
lung cancer
differs between a smoking population of European
ancestry and a nonsmoking Asian population, allowing for the possibility
that the genetic etiology for the same disease can vary by population and environmental exposures.
Conclusion: Our results provide important insights into the genetic architecture of cancers and suggest new avenues for investigation.
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