A Case–Control Study of a Sex-Specific Association between a 15q25 Variant and Lung Cancer Risk

Wei, Chongjuan; Han, Younghun; Spitz, Margaret R.; Wu, Xifeng; Chancoco, Haidee; Akiva, Pinchas; Rechavi, Gideon; Brand, Hadar; Wun, Issac; Frazier, Marsha L.; Amos, Christopher I.

doi:10.1158/1055-9965.epi-11-0749

Cited by 12 publications

(14 citation statements)

References 44 publications

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“…This includes 138 SNPs on 5p15.33, 356 SNPs on 6p22.1-p21.31 and 266 SNPs on 15q25.1. Markers used in analyses were selected based upon: known functional effect on activity of nicotinic acetylcholine receptors, previously associated in East Asian or European populations, allele frequency > 0.01 in African populations, position across the region, predicted effect on function, r-square value with respect to other markers <0.70 as determined by SNP browser version 4.0 (28), inclusion in one of three previous studies of African-American lung cancer susceptibility (24, 25, 29), or discovery by targeted sequencing (30). …”

Section: Methodsmentioning

confidence: 99%

Fine-mapping of the 5p15.33, 6p22.1-p21.31, and 15q25.1 Regions Identifies Functional and Histology-Specific Lung Cancer Susceptibility Loci in African-Americans

Walsh

Gorlov

Hansen

et al. 2013

Cancer Epidemiology, Biomarkers &Amp; Prevention

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Background Genome-wide association studies of European and East Asian populations have identified lung cancer susceptibility loci on chromosomes 5p15.33, 6p22.1-p21.31 and 15q25.1. We investigated whether these regions contain lung cancer susceptibly loci in African-Americans refined previous association signals by utilizing the reduced linkage disequilibrium observed in African-Americans. Methods 1308 African-American cases and 1241 African-American controls from three centers were genotyped for 760 single nucleotide polymorphisms spanning three regions, and additional SNP imputation was performed. Associations between polymorphisms and lung cancer risk were estimated using logistic regression, stratified by tumor histology where appropriate. Results The strongest associations were observed on 15q25.1 in/near CHRNA5, including a missense substitution (rs16969968: OR = 1.57, 95% CI = 1.25–1.97, P = 1.1 × 10−4) and variants in the 5′-UTR. Associations on 6p22.1-p21.31 were histology-specific and included a missense variant in BAT2 associated with squamous-cell carcinoma (rs2736158: OR = 0.64, 95% CI = 0.48–0.85, P = 1.82 × 10−3). Associations on 5p15.33 were detected near TERT, the strongest of which was rs2735940 (OR = 0.82, 95% CI = 0.73–0.93, P = 1.1 × 10−3). This association was stronger among cases with adenocarcinoma (OR = 0.75, 95% CI = 0.65–0.86, P = 8.1 × 10−5). Conclusions Polymorphisms in 5p15.33, 6p22.1-p21.31 and 15q25.1 are associated with lung cancer in African-Americans. Variants on 5p15.33 are stronger risk factors for adenocarcinoma and variants on 6p21.33 associated only with squamous-cell carcinoma. Impact Results implicate the BAT2, TERT and CHRNA5 genes in the pathogenesis of specific lung cancer histologies.

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Section: Methodsmentioning

confidence: 99%

Fine-mapping of the 5p15.33, 6p22.1-p21.31, and 15q25.1 Regions Identifies Functional and Histology-Specific Lung Cancer Susceptibility Loci in African-Americans

Walsh

Gorlov

Hansen

et al. 2013

Cancer Epidemiology, Biomarkers &Amp; Prevention

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“…It has been suggested that the A allele of this SNP is a risk allele for nicotine dependency. A high linkage disequilibrium between the rs16969968 and rs3841324 polymorphisms was reported [9], as well as protective and sex-dependent effects of the S/S_G/G diplotype in terms of lung cancer [9]. A high linkage disequilibrium between the rs16969968 and rs3841324 polymorphisms was reported [9], as well as protective and sex-dependent effects of the S/S_G/G diplotype in terms of lung cancer [9].…”

Section: Introductionmentioning

confidence: 94%

“…These difficulties were not attributable to impairments on a motoric level [2]. It is highly likely that this polymorphism encompasses a binding site for the SP1 transcription factor [9]. The response speed in a spatial cuing task was improved both in humans and in monkeys after nicotine intake [4].…”

Section: Introductionmentioning

confidence: 99%

“…As significant differences in CHRNA5 mRNA expression between S allele homozygotes and S allele heterozygotes of the CHRNA5 rs3841324 SNP were noted, but not between S allele heterozygotes and L allele homozygotes [8], we analyzed this polymorphism on the basis of comparisons between the homozygous S allele group and the group of L allele carriers (S/S vs. L + ). Sex will be considered a factor in the analyses [9], and the effect of the diplotypes of the polymorphisms will also be examined. Sex will be considered a factor in the analyses [9], and the effect of the diplotypes of the polymorphisms will also be examined.…”

Section: Introductionmentioning

confidence: 99%

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Sex matters! Interactions of sex and polymorphisms of a cholinergic receptor gene (CHRNA5) modulate response speed

Schneider¹,

Hüle²,

Schote

et al. 2015

NeuroReport

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Acetylcholine influences the speed of information processing. We examined the effect of the rs3841324 polymorphism (L/S) and the rs16969968 (G/A) polymorphism on response speed in the Stroop task and the Negative priming task. These polymorphisms are located in the gene that encodes the nicotinic acetylcholine receptor α5-subunit (CHRNA5). Male carriers of the rs3841324 S/S genotype and the rs16969968 G/G genotype were faster than male carriers of at least one L allele or one A allele. In contrast, female carriers of the rs3841324 S/S genotype and the rs16969968 G/G genotype were slower than female carriers of at least one L allele or one A allele. These results indicate that the minor alleles of both polymorphisms modulate response speed in a sex-dependent, diametrically opposed manner.

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“…SNP 754 in gene 21 refers to rs1051730 in CHRNA3 on chromosome 15, and SNP 747 in gene 65 refers to rs8034191 in AGPHPD1. Both SNPs have been found consistently associated with lung cancer risk and survival [2, 3, 23, 43, 44, 55, 57] and in strong LD with each other ( R 2 = 0.85). CHRNA3 encodes the α –3 subunit of the nicotinic cholinergic receptor, which mediates cholinergic activity.…”

Section: Resultsmentioning

confidence: 99%

A Bayesian approach to identify genes and gene-level SNP aggregates in a genetic analysis of cancer data

Stingo

Swartz

Vannucci

2015

Statistics and Its Interface

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Complex diseases, such as cancer, arise from complex etiologies consisting of multiple single-nucleotide polymorphisms (SNPs), each contributing a small amount to the overall risk of disease. Thus, many researchers have gone beyond single-SNPs analysis methods, focusing instead on groups of SNPs, for example by analysing haplotypes. More recently, pathway-based methods have been proposed that use prior biological knowledge on gene function to achieve a more powerful analysis of genome-wide association studies (GWAS) data. In this paper we propose a novel Bayesian modeling framework to identify molecular biomarkers for disease prediction. Our method combines pathway-based approaches with multiple SNP analyses of a specified region of interest. The model’s development is motivated by SNP data from a lung cancer study. In our approach we define gene-level scores based on SNP allele frequencies and use a linear modeling setting to study the scores association to the observed phenotype. The basic idea behind the definition of gene-level scores is to weigh the SNPs within the gene according to their rarity, based on genotype frequencies expected under the Hardy-Weinberg equilibrium law. This results in scores giving more importance to the unusually low frequencies, i.e. to SNPs that might indicate peculiar genetic differences between subjects belonging to different groups. An additional feature of our approach is that we incorporate information on SNP-to-SNP associations into the model. In particular, we use network priors that model the linkage disequilibrium between SNPs. For posterior inference, we design a stochastic search method that identifies significant biomarkers (genes and SNPs) for disease prediction. We assess performances on simulated data and compare results to existing approaches. We then show the ability of the proposed methodology to detect relevant genes and associated SNPs in a lung cancer dataset.

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A Case–Control Study of a Sex-Specific Association between a 15q25 Variant and Lung Cancer Risk

Cited by 12 publications

References 44 publications

Fine-mapping of the 5p15.33, 6p22.1-p21.31, and 15q25.1 Regions Identifies Functional and Histology-Specific Lung Cancer Susceptibility Loci in African-Americans

Fine-mapping of the 5p15.33, 6p22.1-p21.31, and 15q25.1 Regions Identifies Functional and Histology-Specific Lung Cancer Susceptibility Loci in African-Americans

Sex matters! Interactions of sex and polymorphisms of a cholinergic receptor gene (CHRNA5) modulate response speed

A Bayesian approach to identify genes and gene-level SNP aggregates in a genetic analysis of cancer data

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