Abstract
Runs of homozygosity (ROHs) are a class of important but poorly studied genomic variations and may be involved in individual susceptibility to diseases. To better understand ROH and its relationship with lung cancer, we performed a genome-wide ROH analysis of a subset of a previous genome-wide case-control study (1,473 cases and 1,962 controls) in a Han Chinese population. ROHs were classified into two classes, based on lengths, intermediate and long ROHs, to evaluate their association with lung cancer risk using existing genome-wide single nucleotide polymorphism (SNP) data. We found that the overall level of intermediate ROHs was significantly associated with a decreased risk of lung cancer (odds ratio = 0.63; 95% confidence interval: 0.51-0.77; P = 4.78×10−6 ), while the long ROHs seemed to be a risk factor of lung cancer. We also identified one ROH region at 14q23.1 that was consistently associated with lung cancer risk in the study. These results indicated that ROHs may be a new class of variation which may be associated with lung cancer risk, and genetic variants at 14q23.1 may be involved in the development of lung cancer.
Highlights
Lung cancer is the leading cause of cancer death worldwide; its incidence and mortality rates have been increasing rapidly in the last three decades[1]
As individuals were divided into 4 Runs of homozygosity (ROHs) levels according to the quartile of FROH in controls, logistic regression analysis showed that the high levels of moderate ROH were consistently associated with a decreased risk of lung cancer as compared to low levels while the association was not observed with the high levels of long ROH
genome-wide association studies (GWAS) has successfully established the link between single nucleotide polymorphism (SNP) and phenotypes, the identified loci can only explain a small fraction of the risk of diseases or the variance of traits
Summary
Lung cancer is the leading cause of cancer death worldwide; its incidence and mortality rates have been increasing rapidly in the last three decades[1]. For each group, overlapping pools between individuals were defined in case and control separately via a program coded by R based on the algorithm from command “-homozyg-group” implemented in PLINK v1.07, which calculated overlapping ROH number in each SNPs and considered regions with peak overlapping ROH number as pools.
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