Citations

AbstractBackgroundReproductive factors have been shown to be differentially associated with risk of estrogen receptor (ER)-positive and ER-negative breast cancer. However, their associations with intrinsic-like subtypes are less clear.MethodsAnalyses included up to 23 353 cases and 71 072 controls pooled from 31 population-based case-control or cohort studies in the Breast Cancer Association Consortium across 16 countries on 4 continents. Polytomous logistic regression was used to estimate the association between reproductive factors and risk of breast cancer by intrinsic-like subtypes (luminal A-like, luminal B-like, luminal B-HER2–like, HER2-enriched–like, and triple-negative breast cancer) and by invasiveness. All statistical tests were 2-sided.ResultsCompared with nulliparous women, parous women had a lower risk of luminal A-like, luminal B-like, luminal B-HER2–like, and HER2-enriched–like disease. This association was apparent only after approximately 10 years since last birth and became stronger with increasing time (odds ratio [OR] = 0.59, 95% confidence interval [CI] = 0.49 to 0.71; and OR = 0.36, 95% CI = 0.28 to 0.46 for multiparous women with luminal A-like tumors 20 to less than 25 years after last birth and 45 to less than 50 years after last birth, respectively). In contrast, parous women had a higher risk of triple-negative breast cancer right after their last birth (for multiparous women: OR = 3.12, 95% CI = 2.02 to 4.83) that was attenuated with time but persisted for decades (OR = 1.03, 95% CI = 0.79 to 1.34, for multiparous women 25 to less than 30 years after last birth). Older age at first birth (Pheterogeneity < .001 for triple-negative compared with luminal A-like breast cancer) and breastfeeding (Pheterogeneity < .001 for triple-negative compared with luminal A-like breast cancer) were associated with lower risk of triple-negative breast cancer but not with other disease subtypes. Younger age at menarche was associated with higher risk of all subtypes; older age at menopause was associated with higher risk of luminal A-like but not triple-negative breast cancer. Associations for in situ tumors were similar to luminal A-like.ConclusionsThis large and comprehensive study demonstrates a distinct reproductive risk factor profile for triple-negative breast cancer compared with other subtypes, with implications for the understanding of disease etiology and risk prediction.

Abstract Background The use of menopausal hormone therapy (MHT) may interact with genetic variants to influence colorectal cancer (CRC) risk. Methods We conducted a genome-wide, gene-environment interaction between single nucleotide polymorphisms and the use of any MHT, estrogen only, and combined estrogen-progestogen therapy with CRC risk, among 28 486 postmenopausal women (11 519 CRC patients and 16 967 participants without CRC) from 38 studies, using logistic regression, 2-step method, and 2– or 3–degree-of-freedom joint test. A set-based score test was applied for rare genetic variants. Results The use of any MHT, estrogen only and estrogen-progestogen were associated with a reduced CRC risk (odds ratio [OR] = 0.71, 95% confidence interval [CI] = 0.64 to 0.78; OR = 0.65, 95% CI = 0.53 to 0.79; and OR = 0.73, 95% CI = 0.59 to 0.90, respectively). The 2-step method identified a statistically significant interaction between a GRIN2B variant rs117868593 and MHT use, whereby MHT-associated CRC risk was statistically significantly reduced in women with the GG genotype (OR = 0.68, 95% CI = 0.64 to 0.72) but not within strata of GC or CC genotypes. A statistically significant interaction between a DCBLD1 intronic variant at 6q22.1 (rs10782186) and MHT use was identified by the 2–degree-of-freedom joint test. The MHT-associated CRC risk was reduced with increasing number of rs10782186-C alleles, showing odds ratios of 0.78 (95% CI = 0.70 to 0.87) for TT, 0.68 (95% CI = 0.63 to 0.73) for TC, and 0.66 (95% CI = 0.60 to 0.74) for CC genotypes. In addition, 5 genes in rare variant analysis showed suggestive interactions with MHT (2-sided P < 1.2 × 10−4). Conclusion Genetic variants that modify the association between MHT and CRC risk were identified, offering new insights into pathways of CRC carcinogenesis and potential mechanisms involved.

Abstract Background: Currently known associations between common genetic variants and colorectal cancer explain less than half of its heritability of 25%. As alcohol consumption has a J-shape association with colorectal cancer risk, nondrinking and heavy drinking are both risk factors for colorectal cancer. Methods: Individual-level data was pooled from the Colon Cancer Family Registry, Colorectal Transdisciplinary Study, and Genetics and Epidemiology of Colorectal Cancer Consortium to compare nondrinkers (≤1 g/day) and heavy drinkers (>28 g/day) with light-to-moderate drinkers (1–28 g/day) in GxE analyses. To improve power, we implemented joint 2df and 3df tests and a novel two-step method that modifies the weighted hypothesis testing framework. We prioritized putative causal variants by predicting allelic effects using support vector machine models. Results: For nondrinking as compared with light-to-moderate drinking, the hybrid two-step approach identified 13 significant SNPs with pairwise r2 > 0.9 in the 10q24.2/COX15 region. When stratified by alcohol intake, the A allele of lead SNP rs2300985 has a dose–response increase in risk of colorectal cancer as compared with the G allele in light-to-moderate drinkers [OR for GA genotype = 1.11; 95% confidence interval (CI), 1.06–1.17; OR for AA genotype = 1.22; 95% CI, 1.14–1.31], but not in nondrinkers or heavy drinkers. Among the correlated candidate SNPs in the 10q24.2/COX15 region, rs1318920 was predicted to disrupt an HNF4 transcription factor binding motif. Conclusions: Our study suggests that the association with colorectal cancer in 10q24.2/COX15 observed in genome-wide association study is strongest in nondrinkers. We also identified rs1318920 as the putative causal regulatory variant for the region. Impact: The study identifies multifaceted evidence of a possible functional effect for rs1318920.

Genome-wide association studies (GWAS) have identified more than 200 susceptibility loci for breast cancer, but these variants explain less than a fifth of the disease risk. Although gene–environment interactions have been proposed to account for some of the remaining heritability, few studies have empirically assessed this. We obtained genotype and risk factor data from 46,060 cases and 47,929 controls of European ancestry from population-based studies within the Breast Cancer Association Consortium (BCAC). We built gene expression prediction models for 4,864 genes with a significant (P < 0.01) heritable component using the transcriptome and genotype data from the Genotype-Tissue Expression (GTEx) project. We leveraged predicted gene expression information to investigate the interactions between gene-centric genetic variation and 14 established risk factors in association with breast cancer risk, using a mixed-effects score test. After adjusting for number of tests using Bonferroni correction, no interaction remained statistically significant. The strongest interaction observed was between the predicted expression of the C13orf45 gene and age at first full-term pregnancy (PGXE = 4.44 × 10−6). In this transcriptome-informed genome-wide gene–environment interaction study of breast cancer, we found no strong support for the role of gene expression in modifying the associations between established risk factors and breast cancer risk. Our study suggests a limited role of gene–environment interactions in breast cancer risk.

Abstract Differences by sex in lung cancer incidence and mortality have been reported which cannot be fully explained by sex differences in smoking behavior, implying existence of genetic and molecular basis for sex disparity in lung cancer development. However, the information about sex dimorphism in lung cancer risk is quite limited despite the great success in lung cancer association studies. By adopting a stringent two-stage analysis strategy, we performed a genome-wide gene–sex interaction analysis using genotypes from a lung cancer cohort including ~ 47 000 individuals with European ancestry. Three low-frequency variants (minor allele frequency < 0.05), rs17662871 [odds ratio (OR) = 0.71, P = 4.29×10−8); rs79942605 (OR = 2.17, P = 2.81×10−8) and rs208908 (OR = 0.70, P = 4.54×10−8) were identified with different risk effect of lung cancer between men and women. Further expression quantitative trait loci and functional annotation analysis suggested rs208908 affects lung cancer risk through differential regulation of Coxsackie virus and adenovirus receptor gene expression in lung tissues between men and women. Our study is one of the first studies to provide novel insights about the genetic and molecular basis for sex disparity in lung cancer development.

AbstractBackgroundThe incidence of colorectal cancer (CRC) among individuals aged younger than 50 years has been increasing. As screening guidelines lower the recommended age of screening initiation, concerns including the burden on screening capacity and costs have been recognized, suggesting that an individualized approach may be warranted. We developed risk prediction models for early-onset CRC that incorporate an environmental risk score (ERS), including 16 lifestyle and environmental factors, and a polygenic risk score (PRS) of 141 variants.MethodsRelying on risk score weights for ERS and PRS derived from studies of CRC at all ages, we evaluated risks for early-onset CRC in 3486 cases and 3890 controls aged younger than 50 years. Relative and absolute risks for early-onset CRC were assessed according to values of the ERS and PRS. The discriminatory performance of these scores was estimated using the covariate-adjusted area under the receiver operating characteristic curve.ResultsIncreasing values of ERS and PRS were associated with increasing relative risks for early-onset CRC (odds ratio per SD of ERS = 1.14, 95% confidence interval [CI] = 1.08 to 1.20; odds ratio per SD of PRS = 1.59, 95% CI = 1.51 to 1.68), both contributing to case-control discrimination (area under the curve = 0.631, 95% CI = 0.615 to 0.647). Based on absolute risks, we can expect 26 excess cases per 10 000 men and 21 per 10 000 women among those scoring at the 90th percentile for both risk scores.ConclusionsPersonal risk scores have the potential to identify individuals at differential relative and absolute risk for early-onset CRC. Improved discrimination may aid in targeted CRC screening of younger, high-risk individuals, potentially improving outcomes.

Abstract Background Observational studies have shown higher folate consumption to be associated with lower risk of colorectal cancer (CRC). Understanding whether and how genetic risk factors interact with folate could further elucidate the underlying mechanism. Aggregating functionally relevant genetic variants in set-based variant testing has higher power to detect gene-environment (GxE) interactions and may provide information on the underlying biological pathway. Objective We investigated interactions between folate consumption and predicted gene expression on colorectal cancer risk across the genome. Methods We used variant weights from the PrediXcan models of colon tissue-specific gene expression as a priori variant information for a set-based GxE approach. We harmonized total folate intake (mcg/day) based on dietary intake and supplemental use across cohort and case-control studies and calculated sex and study specific quantiles. Analyses were performed using a mixed effects score tests for interactions between folate and genetically predicted expression of 4,839 genes with available genetically predicted expression. We meta-analyzed results across 23 studies for a total of 13,498 cases with colorectal tumors and 13,918 controls of European ancestry. Results We found suggestive evidence of interaction with folate intake for genes including glutathione S-Transferase Alpha 1 (GSTA1; p=4.3E-4), Tonsuko Like, DNA Repair Protein (TONSL; p=4.3E-4), and Aspartylglucosaminidase (AGA: p=4.5E-4). Glutathione is an antioxidant, preventing cellular damage and is a downstream metabolite of homocysteine and metabolized by GSTA1. TONSL is part of a complex that functions in the recovery of double strand breaks and AGA plays a role in lysosomal breakdown of glycoprotein. Conclusion We identified three genes involved in preventing or repairing DNA damage that may interact with folate consumption to alter CRC risk.

Salicylic acid (SA) has observationally been shown to decrease colorectal cancer (CRC) risk. Aspirin (acetylsalicylic acid, that rapidly deacetylates to SA) is an effective primary and secondary chemopreventive agent. Through a Mendelian randomization (MR) approach, we aimed to address whether levels of SA affected CRC risk, stratifying by aspirin use. A two-sample MR analysis was performed using GWAS summary statistics of SA (INTERVAL and EPIC-Norfolk, N = 14,149) and CRC (CCFR, CORECT, GECCO and UK Biobank, 55,168 cases and 65,160 controls). The DACHS study (4410 cases and 3441 controls) was used for replication and stratification of aspirin-use. SNPs proxying SA were selected via three methods: (1) functional SNPs that influence the activity of aspirin-metabolising enzymes; (2) pathway SNPs present in enzymes’ coding regions; and (3) genome-wide significant SNPs. We found no association between functional SNPs and SA levels. The pathway and genome-wide SNPs showed no association between SA and CRC risk (OR: 1.03, 95% CI: 0.84–1.27 and OR: 1.08, 95% CI: 0.86–1.34, respectively). Results remained unchanged upon aspirin use stratification. We found little evidence to suggest that an SD increase in genetically predicted SA protects against CRC risk in the general population and upon stratification by aspirin use.

Abstract There is growing evidence showing that sex disparity in lung cancer risk cannot be fully explained by sex differences in smoking behavior, implying existence of genetic and molecular basis for sex disparity in lung cancer development. However, the information about sex dimorphism in lung cancer risk is quite limited despite the great success in lung cancer association studies. By adopting a stringent two-stage analysis strategy, we performed a genome-wide gene-sex interaction analysis using genotype from a lung cancer cohort including ~ 47,000 individuals with European ancestry. Three low-frequency variants (minor allele frequency < 0.05), rs17662871 (OR=0.71, p=4.29x10-8); rs79942605 (OR=2.17, p=2.81x10-8); and rs208908 (OR=0.70, p=4.54x10-8), were identified with different risk effect of lung cancer between men and women. Further eQTL and functional annotation analysis suggested rs208908 affect lung cancer risk through differential regulation of CXADR (Coxsackie Virus And Adenovirus Receptor) gene expression in lung tissues between men and women. Our study is one of the first studies to provide novel insights about the genetic and molecular basis for sex disparity in lung cancer development.

Abstract BackgroundCopy number variants (CNVs) are pervasive in the human genome but potential disease associations with rare CNVs have not been comprehensively assessed in large datasets. We analysed rare CNVs in genes and non-coding regions for 86,788 breast cancer cases and 76,122 controls of European ancestry with genome-wide array data.ResultsGene burden tests detected the strongest association for deletions in BRCA1 (P= 3.7E-18). Nine other genes were associated with a p-value < 0.01 including known susceptibility genes CHEK2 (P= 0.0008), ATM (P= 0.002) and BRCA2 (P= 0.008). Outside the known genes we detected associations with p-values < 0.001 for either overall or subtype-specific breast cancer at nine deletion regions and four duplication regions. Three of the deletion regions were in established common susceptibility loci.ConclusionsThis is the first genome-wide analysis of rare CNVs in a large breast cancer case-control dataset. We detected associations with exonic deletions in established breast cancer susceptibility genes. We also detected suggestive associations with non-coding CNVs in known and novel loci with large effects sizes. Larger sample sizes will be required to reach robust levels of statistical significance.