Do Genetic Variants Modify the Effect of Smoking on Risk of Preeclampsia in Pregnancy?

Under embargo until: 2022-11-28Objective Maternal smoking is associated with as much as a 50% reduced risk of preeclampsia, despite increasing risk of other poor pregnancy outcomes that often co-occur with preeclampsia, such as preterm birth and fetal growth restriction. Researchers have long sought to understand whether this perplexing association is biologically based, or a result of noncausal mechanisms. We examined whether smoking-response genes modify the smoking-preeclampsia association to investigate potential biological explanations. Study Design We conducted a nested case–control study within the Norwegian Mother, Father and Child Birth Cohort (1999–2008) of 2,596 mother–child dyads. We used family-based log-linear Poisson regression to examine modification of the maternal smoking-preeclampsia relationship by maternal and fetal single nucleotide polymorphisms involved in cellular processes related to components of cigarette smoke (n = 1,915 with minor allele frequency ≥10%). We further investigated the influence of smoking cessation during pregnancy. Results Three polymorphisms showed overall (p < 0.001) multiplicative interaction between smoking and maternal genotype. For rs3765692 (TP73) and rs10770343 (PIK3C2G), protection associated with smoking was reduced with two maternal copies of the risk allele and was stronger in continuers than quitters (interaction p = 0.02 for both loci, based on testing 3-level smoking by 3-level genotype). For rs2278361 (APAF1) the inverse smoking-preeclampsia association was eliminated by the presence of a single risk allele, and again the trend was stronger in continuers than in quitters (interaction p = 0.01). Conclusion Evidence for gene–smoking interaction was limited, but differences by smoking cessation warrant further investigation. We demonstrate the potential utility of expanded dyad methods and gene–environment interaction analyses for outcomes with complex relationships between maternal and fetal genotypes and exposures.acceptedVersio

Determinants of host susceptibility to murine respiratory syncytial virus (RSV) disease identify a role for the innate immunity scavenger receptor MARCO gene in human infants

AbstractBackgroundRespiratory syncytial virus (RSV) is the global leading cause of lower respiratory tract infection in infants. Nearly 30% of all infected infants develop severe disease including bronchiolitis, but susceptibility mechanisms remain unclear.MethodsWe infected a panel of 30 inbred strains of mice with RSV and measured changes in lung disease parameters 1 and 5days post-infection and they were used in genome-wide association (GWA) studies to identify quantitative trait loci (QTL) and susceptibility gene candidates.FindingsGWA identified QTLs for RSV disease phenotypes, and the innate immunity scavenger receptor Marco was a candidate susceptibility gene; targeted deletion of Marco worsened murine RSV disease. We characterized a human MARCO promoter SNP that caused loss of gene expression, increased in vitro cellular response to RSV infection, and associated with increased risk of disease severity in two independent populations of children infected with RSV.InterpretationTranslational integration of a genetic animal model and in vitro human studies identified a role for MARCO in human RSV disease severity. Because no RSV vaccines are approved for clinical use, genetic studies have implications for diagnosing individuals who are at risk for severe RSV disease, and disease prevention strategies (e.g. RSV antibodies)

Association between low levels of 1,25-dihydroxyvitamin D and breast cancer risk

OBJECTIVE: To determine if blood levels of 25-hydroxyvitamin D (25-D) or its active metabolite, 1,25-dihydroxyvitamin D (1,25-D), are lower in women at the time of first diagnosis of breast cancer than in comparable women without breast cancer. DESIGN: This was a clinic-based case-control study with controls frequency-matched to cases on race, age, clinic and month of blood drawing. SETTING: University-based breast referral clinics. SUBJECTS: One hundred and fifty-six women with histologically documented adenocarcinoma of the breast and 184 breast clinic controls. RESULTS: There were significant mean differences in 1,25-D levels (pmol ml(-1)) between breast cancer cases and controls; white cases had lower 1,25-D levels than white controls (mean difference +/-SE: -11.08+/-0.76), and black cases had higher 1.25-D levels than black controls (mean difference +/-SE: 4.54+/-2.14), although the number of black women in the study was small. After adjustment for age, assay batch, month of blood draw, clinic and sample storage time, the odds ratio (95% confidence interval, CI) for lowest relative to highest quartile was 5.2 (95% CI 2.1, 12.8) for white cases and controls. The association in white women was stronger in women above the median age of 54 than in younger women, 4.7 (95% CI 2.1, 10.2) vs. 1.5 (95% CI 0.7, 3.0). There were no case-control differences in 25-D levels in either group. CONCLUSIONS: These data are consistent with a protective effect of 1,25-D for breast cancer in white women

A likelihood ratio approach for utilizing case-control data in the clinical classification of rare sequence variants:Application to BRCA1 and BRCA2

A large number of variants identified through clinical genetic testing in disease susceptibility genes are of uncertain significance (VUS). Following the recommendations of the American College of Medical Genetics and Genomics (ACMG) and Association for Molecular Pathology (AMP), the frequency in case-control datasets (PS4 criterion) can inform their interpretation. We present a novel case-control likelihood ratio-based method that incorporates gene-specific age-related penetrance. We demonstrate the utility of this method in the analysis of simulated and real datasets. In the analysis of simulated data, the likelihood ratio method was more powerful compared to other methods. Likelihood ratios were calculated for a case-control dataset of BRCA1 and BRCA2 variants from the Breast Cancer Association Consortium (BCAC) and compared with logistic regression results. A larger number of variants reached evidence in favor of pathogenicity, and a substantial number of variants had evidence against pathogenicity findings that would not have been reached using other case-control analysis methods. Our novel method provides greater power to classify rare variants compared with classical case-control methods. As an initiative from the ENIGMA Analytical Working Group, we provide user-friendly scripts and preformatted Excel calculators for implementation of the method for rare variants in BRCA1, BRCA2, and other high-risk genes with known penetrance.</p

Combined Associations of a Polygenic Risk Score and Classical Risk Factors With Breast Cancer Risk.

We evaluated the joint associations between a new 313-variant PRS (PRS313) and questionnaire-based breast cancer risk factors for women of European ancestry, using 72 284 cases and 80 354 controls from the Breast Cancer Association Consortium. Interactions were evaluated using standard logistic regression and a newly developed case-only method for breast cancer risk overall and by estrogen receptor status. After accounting for multiple testing, we did not find evidence that per-standard deviation PRS313 odds ratio differed across strata defined by individual risk factors. Goodness-of-fit tests did not reject the assumption of a multiplicative model between PRS313 and each risk factor. Variation in projected absolute lifetime risk of breast cancer associated with classical risk factors was greater for women with higher genetic risk (PRS313 and family history) and, on average, 17.5% higher in the highest vs lowest deciles of genetic risk. These findings have implications for risk prevention for women at increased risk of breast cancer

Shared heritability and functional enrichment across six solid cancers

Correction: Nature Communications 10 (2019): art. 4386 DOI: 10.1038/s41467-019-12095-8Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (r(g) = 0.57, p = 4.6 x 10(-8)), breast and ovarian cancer (r(g) = 0.24, p = 7 x 10(-5)), breast and lung cancer (r(g) = 0.18, p = 1.5 x 10(-6)) and breast and colorectal cancer (r(g) = 0.15, p = 1.1 x 10(-4)). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis.Peer reviewe

Common variants in breast cancer risk loci predispose to distinct tumor subtypes.

BACKGROUND: Genome-wide association studies (GWAS) have identified multiple common breast cancer susceptibility variants. Many of these variants have differential associations by estrogen receptor (ER) status, but how these variants relate with other tumor features and intrinsic molecular subtypes is unclear. METHODS: Among 106,571 invasive breast cancer cases and 95,762 controls of European ancestry with data on 173 breast cancer variants identified in previous GWAS, we used novel two-stage polytomous logistic regression models to evaluate variants in relation to multiple tumor features (ER, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and grade) adjusting for each other, and to intrinsic-like subtypes. RESULTS: Eighty-five of 173 variants were associated with at least one tumor feature (false discovery rate < 5%), most commonly ER and grade, followed by PR and HER2. Models for intrinsic-like subtypes found nearly all of these variants (83 of 85) associated at p < 0.05 with risk for at least one luminal-like subtype, and approximately half (41 of 85) of the variants were associated with risk of at least one non-luminal subtype, including 32 variants associated with triple-negative (TN) disease. Ten variants were associated with risk of all subtypes in different magnitude. Five variants were associated with risk of luminal A-like and TN subtypes in opposite directions. CONCLUSION: This report demonstrates a high level of complexity in the etiology heterogeneity of breast cancer susceptibility variants and can inform investigations of subtype-specific risk prediction

Identification of 12 new susceptibility loci for different histotypes of epithelial ovarian cancer.

To identify common alleles associated with different histotypes of epithelial ovarian cancer (EOC), we pooled data from multiple genome-wide genotyping projects totaling 25,509 EOC cases and 40,941 controls. We identified nine new susceptibility loci for different EOC histotypes: six for serous EOC histotypes (3q28, 4q32.3, 8q21.11, 10q24.33, 18q11.2 and 22q12.1), two for mucinous EOC (3q22.3 and 9q31.1) and one for endometrioid EOC (5q12.3). We then performed meta-analysis on the results for high-grade serous ovarian cancer with the results from analysis of 31,448 BRCA1 and BRCA2 mutation carriers, including 3,887 mutation carriers with EOC. This identified three additional susceptibility loci at 2q13, 8q24.1 and 12q24.31. Integrated analyses of genes and regulatory biofeatures at each locus predicted candidate susceptibility genes, including OBFC1, a new candidate susceptibility gene for low-grade and borderline serous EOC

Transcriptome-wide association study of breast cancer risk by estrogen-receptor status

Previous transcriptome-wide association studies (TWAS) have identified breast cancer risk genes by integrating data from expression quantitative loci and genome-wide association studies (GWAS), but analyses of breast cancer subtype-specific associations have been limited. In this study, we conducted a TWAS using gene expression data from GTEx and summary statistics from the hitherto largest GWAS meta-analysis conducted for breast cancer overall, and by estrogen receptor subtypes (ER+ and ER-). We further compared associations with ER+ and ER- subtypes, using a case-only TWAS approach. We also conducted multigene conditional analyses in regions with multiple TWAS associations. Two genes, STXBP4 and HIST2H2BA, were specifically associated with ER+ but not with ER- breast cancer. We further identified 30 TWAS-significant genes associated with overall breast cancer risk, including four that were not identified in previous studies. Conditional analyses identified single independent breast-cancer gene in three of six regions harboring multiple TWAS-significant genes. Our study provides new information on breast cancer genetics and biology, particularly about genomic differences between ER+ and ER- breast cancer.Peer reviewe