Analysis of heritability and genetic architecture of Pancreatic Cancer: A PanC4 Study
A partir de données d'études d'association sur le génome entier portant sur 3 363 témoins et 3 568 personnes atteintes d'un cancer du pancréas, cette étude analyse l'effet de variants génétiques sur la possibilité de transmission héréditaire de la maladie
Background : Pancreatic cancer is the fourth-leading cause of cancer death in both men and women in the United States. Identified common susceptibility loci account for a small fraction of estimated heritability. We sought to estimate overall heritability of pancreatic cancer and partition the heritability by variant frequencies and functional annotations.
Methods : Analysis using the genome-based restricted maximum likelihood method (GREML) was conducted on Pancreatic Cancer Case-Control Consortium (PanC4) genome-wide association study data on 3,568 pancreatic cancer cases and 3,363 controls of European Ancestry.
Results : Applying LD- and MAF-stratified GREML (GREML-LDMS) to imputated GWAS data, we estimated the overall heritability of pancreatic cancer to be 21.2% (s.e. = 4.8%). Across the functional groups (intronic, intergenic, coding and regulatory variants), intronic variants account for most of the estimated heritability (12.4%). Previously identified GWAS loci explained 4.1% of the total phenotypic variation of pancreatic cancer. Mutations in hereditary pancreatic cancer susceptibility genes are present in 4-10% of pancreatic cancer patients, yet our GREML-LDMS results suggested these regions explain only 0.4% of total phenotypic variance for pancreatic cancer.
Conclusions : While higher than previous studies, our estimated 21.2% overall heritability may still be downwardly biased due to the inherent limitation that heritablity due to individually rare variants in a gene with a substantive ovarll impact on disease are not captured in these commonly used methods
Impact : Our estimate of pancreatic cancer heritability estimates indicate both rare and common variants contribute to missing heritability, while suggesing caution when using this approach to quantify the impact of rare variants.
Cancer Epidemiology Biomarkers & Prevention , résumé, 2018