Genome‐wide association study of INDELs identified four novel susceptibility loci associated with lung cancer risk
Juncheng DaiMingtao HuangChristopher I. AmosRayjean J. HungAdonina TardónAngeline S. AndrewChu ChenDavid C. ChristianiDemetrius AlbanesGad RennertJingyi FanGary E. GoodmanGeoffrey LiuJohn K. FieldKjell GrankvistLambertus A. KiemeneyLoı̈c Le MarchandMatthew B. SchabathMattias JohanssonMelinda C. AldrichMikael JohanssonNeil E. CaporasoPhilip LazarusStephan LamStig E. BojesenSusanne M. ArnoldMaria Teresa LandiAngela RischH‐Erich WichmannHeike BickeböllerPaul BrennanSanjay SheteOlle MelanderHans BrunnströmShan ZienolddinyPenella J. WollVictoria L. StevensZhibin HuHongbing Shen
14
Citation
49
Reference
10
Related Paper
Citation Trend
Abstract:
Genome‐wide association studies (GWAS) have identified 45 susceptibility loci associated with lung cancer. Only less than SNPs, small insertions and deletions (INDELs) are the second most abundant genetic polymorphisms in the human genome. INDELs are highly associated with multiple human diseases, including lung cancer. However, limited studies with large‐scale samples have been available to systematically evaluate the effects of INDELs on lung cancer risk. Here, we performed a large‐scale meta‐analysis to evaluate INDELs and their risk for lung cancer in 23,202 cases and 19,048 controls. Functional annotations were performed to further explore the potential function of lung cancer risk INDELs. Conditional analysis was used to clarify the relationship between INDELs and SNPs. Four new risk loci were identified in genome‐wide INDEL analysis (1p13.2: rs5777156, Insertion, OR = 0.92, p = 9.10 × 10 −8 ; 4q28.2: rs58404727, Deletion, OR = 1.19, p = 5.25 × 10 −7 ; 12p13.31: rs71450133, Deletion, OR = 1.09, p = 8.83 × 10 −7 ; and 14q22.3: rs34057993, Deletion, OR = 0.90, p = 7.64 × 10 −8 ). The eQTL analysis and functional annotation suggested that INDELs might affect lung cancer susceptibility by regulating the expression of target genes. After conducting conditional analysis on potential causal SNPs, the INDELs in the new loci were still nominally significant. Our findings indicate that INDELs could be potentially functional genetic variants for lung cancer risk. Further functional experiments are needed to better understand INDEL mechanisms in carcinogenesis.Keywords:
Indel
Genome-wide Association Study
Genetic Association
Genome-wide association studies (GWAS) and sequencing studies are routinely conducted for the identification of genetic variants that are associated with complex traits. Many genetic studies for association mapping include related individuals. When relatives are included in an association analysis, familial correlations must be appropriately taken into account to ensure correct type I error and to increase power. This unit provides an overview of statistical methods that are available for GWAS and sequencing association studies of complex traits in samples with related individuals.
Genome-wide Association Study
Genetic Association
Identification
Association (psychology)
Statistical power
Cite
Citations (15)
Genome-wide Association Study
Genetic Association
Genetic architecture
Identification
Candidate gene
Cite
Citations (42)
Genome-wide Association Study
Genetic Association
Complex disease
Cite
Citations (13)
Genome-wide association studies (GWAS) have become a widely used approach for genetic association studies of various human traits. A few GWAS have been conducted with the goal of identifying novel loci for pigmentation traits, melanoma, and non-melanoma skin cancer. Nevertheless, the phenotype variation explained by the genetic markers identified so far is limited. In this review, we discuss the GWAS study design and its application in pigmentation and skin cancer research. Furthermore, we summarize recent developments in post-GWAS activities such as meta-analysis, pathway analysis, and risk prediction.
Genome-wide Association Study
Genetic Association
Genetic architecture
Cite
Citations (9)
Many candidate genes for androgenetic alopecia (AGA) have been identified in studies of the Caucasians and some Asian populations.This study aimed to confirm the known susceptibility genes reported in previous studies and find additional candidate genes for high-risk individuals for AGA in Korean population.We recapitulated the previously reported SNPs and identified the novel Korean AGA risk genetic variants using a Korean hospital-based AGA case and control samples. The population was consisting of 494 individuals (275 AGA cases and 146 controls). Using the 800 K SNPs of precision medical research array (PMRA SNP microarray chip) and imputation-based SNPs, 12 previous GWAS reports for AGA and a total of 62 160 SNPs were examined in our study samples. Also, we conducted the genome-wide association study (GWAS) by the logistic regression analyses for AGA cases and controls with controlling the age as the covariates.Among the 62 160 SNPs, a total of 1143 SNPs in 76 gene regions showed weak replication tendency with the p-values <0.05 and same direction of effects. Additionally, the GWAS results showed 110 SNPs in 13 independent regions with the suggestive p-values <1.00 × 10-5 . The most significantly replicated SNP resided on chromosome 20, which were similar to other AGA replication studies including Chinese study. The GWAS identified two SNPs (rs11010734 and rs2420640) increasing the risk for AGA in our study population.Our study would be a reference of the non-European studies to better understand AGA in different populations and ancestral contexts.
Genome-wide Association Study
SNP
Genetic Association
Imputation (statistics)
Candidate gene
SNP genotyping
SNP array
Cite
Citations (6)
Abstract Genome-wide association studies (GWAS) can serve as strong evidence in correlating biological pathways with human diseases. Although ischemic stroke has been found to be associated with many biological pathways, the genetic mechanism of ischemic stroke is still unclear. Here, we performed GWAS for a major subtype of stroke—small-vessel occlusion (SVO)—to identify potential genetic factors contributing to ischemic stroke. GWAS were conducted on 342 individuals with SVO stroke and 1,731 controls from a Han Chinese population residing in Taiwan. The study was replicated in an independent Han Chinese population comprising an additional 188 SVO stroke cases and 1,265 controls. Three SNPs (rs2594966, rs2594973, rs4684776) clustered at 3p25.3 in ATG7 (encoding Autophagy Related 7), with P values between 2.52 × 10 −6 and 3.59 × 10 −6 , were identified. Imputation analysis also supported the association between ATG7 and SVO stroke. To our knowledge, this is the first GWAS to link stroke and autophagy. ATG7 , which has been implicated in autophagy, could provide novel insights into the genetic basis of ischemic stroke.
Genome-wide Association Study
Genetic Association
Stroke
Imputation (statistics)
Han Chinese
Cite
Citations (19)
Recent genome-wide association studies (GWAS) have identified a number of novel genetic associations with complex human diseases. In spite of these successes, results from GWAS generally explain only a small proportion of disease heritability, an observation termed the 'missing heritability problem'. Several sources for the missing heritability have been proposed, including the contribution of many common variants with small individual effect sizes, which cannot be reliably found using the standard GWAS approach. The goal of our study was to explore a complimentary approach, which combines GWAS results with functional data in order to identify novel genetic associations with small effect sizes. To do so, we conducted a GWAS for lymphocyte count, a physiologic quantitative trait associated with asthma, in 462 Hutterites. In parallel, we performed a genome-wide gene expression study in lymphoblastoid cell lines from 96 Hutterites. We found significant support for genetic associations using the GWAS data when we considered variants near the 193 genes whose expression levels across individuals were most correlated with lymphocyte counts. Interestingly, these variants are also enriched with signatures of an association with asthma susceptibility, an observation we were able to replicate. The associated loci include genes previously implicated in asthma susceptibility as well as novel candidate genes enriched for functions related to T cell receptor signaling and adenosine triphosphate synthesis. Our results, therefore, establish a new set of asthma susceptibility candidate genes. More generally, our observations support the notion that many loci of small effects influence variation in lymphocyte count and asthma susceptibility.
Genome-wide Association Study
Candidate gene
Genetic Association
Missing heritability problem
Cite
Citations (51)
Genome-wide Association Study
Genetic Association
SNP
Identification
SNP array
Cite
Citations (241)
Genome-wide association study (GWAS)-based pathway association analysis is a powerful approach for the genetic studies of human complex diseases. However, the genetic confounding effects of environment exposure-related genes can decrease the accuracy of GWAS-based pathway association analysis of target diseases. In this study, we developed a pathway association analysis approach, named Mendelian randomization-based pathway enrichment analysis (MRPEA), which was capable of correcting the genetic confounding effects of environmental exposures, using the GWAS summary data of environmental exposures. After analyzing the real GWAS summary data of cardiovascular disease and cigarette smoking, we observed significantly improved performance of MRPEA compared with traditional pathway association analysis (TPAA) without adjusting for environmental exposures. Further, simulation studies found that MRPEA generally outperformed TPAA under various scenarios. We hope that MRPEA could help to fill the gap of TPAA and identify novel causal pathways for complex diseases.
Genome-wide Association Study
Mendelian Randomization
Genetic Association
Pathway Analysis
Association (psychology)
Cite
Citations (4)
The application of high-throughput genotyping in humans has yielded numerous insights into the genetic basis of human phenotypes and an unprecedented amount of genetic data. Genome-wide association studies (GWAS) have increased in number in recent years, but the variants that have been found have generally explained only a tiny proportion of the estimated genetic contribution to phenotypic variation. This article summarizes the progress made in the development of gene set analysis (GSA) and network analysis for GWAS was a way to identify the underlying molecular processes of human phenotypes. It also highlights some promising findings and indicates future directions that may greatly enhance the analysis and interpretation of GWAS.
Genome-wide Association Study
Genetic Association
Cite
Citations (24)