Polygenic risk score (PRS) models effectively predict breast cancer (BC) risk in European-ancestry women but have limited accuracy for African-ancestry women, particularly for aggressive subtypes. We developed PRS models for overall BC, estrogen receptor (ER)-positive, ER-negative and triple-negative BC (TNBC) in African-ancestry women using data from the African Ancestry Breast Cancer Genetics consortium (17,391 cases and 18,800 controls). We applied several PRS methods and integrated information across ancestries and BC subtypes. The best models for overall, ER-positive, ER-negative and TNBC showed an area under the receiving operating curve of 0.612, 0.621, 0.611 and 0.639, respectively, and maintained predictive accuracy in external validation studies with area under the receiving operating curves of 0.612, 0.640, 0.605 and 0.652. We further introduce a parsimonious 162-variant PRS for TNBC with comparable accuracy (0.626). These findings demonstrate markedly improved PRS accuracy for BC risk prediction in African-ancestry women. Using these PRS models for screening will help promote more equitable cancer prevention efforts.

Genome-wide association studies (GWAS) have identified over 200 genetic risk loci for breast cancer, yet the target genes in these loci remain largely unknown. To address this knowledge gap, we conducted a series of multi-ancestry transcriptome-wide association studies (TWAS) to discover potential breast cancer susceptibility genes. We developed and validated ancestry-specific genetic models to predict levels of gene expression, alternative splicing, and 3' UTR alternative polyadenylation, using genomic and transcriptomic data from normal breast tissue samples of 652 females of African, Asian, or European ancestry. These models were then applied to GWAS data of 178,534 breast cancer cases and 248,300 controls from these ancestry groups for association analyses. We identified 290 genes associated with breast cancer risk, including 103 previously unreported in TWAS and 46 located at least 500Kb away from any previously identified risk variants. Among them, 39 genes exhibited distinct associations with breast cancer risk by estrogen receptor status. The identified genes were enriched in pathways related to homologous recombination, apoptosis, p53, PI3K/AKT/mTOR, estrogen, and IL-2/STAT5 signaling. Single-cell RNA sequencing and in vitro experiment data provided additional functional evidence for 169 genes. Our study uncovered large numbers of candidate breast cancer susceptibility genes and contributed valuable insights into the genetics and biology of this common cancer.

BACKGROUND:Among premenopausal women, higher body mass index (BMI) is associated with lower breast cancer risk, although the underlying mechanisms are unclear. Investigating adiposity distribution may help clarify impacts on breast cancer risk. This study was initiated to investigate associations of central and peripheral adiposity with premenopausal breast cancer risk overall and by other risk factors and breast cancer characteristics. METHODS:We used individual-level data from 14 prospective cohort studies to estimate hazard ratios (HRs) for premenopausal breast cancer using Cox proportional hazards regression. Analyses included 440,179 women followed for a median of 7.5 years (interquartile range: 4.0-11.3) between 1976 and 2017, with 6,779 incident premenopausal breast cancers. RESULTS:All central adiposity measures were inversely associated with breast cancer risk overall when not controlling for BMI (e.g. for waist circumference, HR per 10 cm increase: 0.92, 95% confidence interval (CI): 0.90-0.94) whereas in models adjusting for BMI, these measures were no longer associated with risk (e.g. for waist circumference: HR 0.99, 95% CI: 0.95-1.03). This finding was consistent across age categories, with some evidence that BMI-adjusted associations differed by breast cancer subtype. Inverse associations for in situ breast cancer were observed with waist-to-height and waist-to-hip ratios and a positive association was observed for oestrogen-receptor-positive breast cancer with hip circumference (HR per 10 cm increase: 1.08, 95% CI: 1.10-1.14). For luminal B, HER2-positive breast cancer, we observed an inverse association with hip circumference (HR per 10 cm: 0.84, 95% CI: 0.71-0.98), but positive associations with waist circumference (HR per 10 cm: 1.18, 95% CI: 1.03-1.36), waist-to-hip ratio (HR per 0.1 units: 1.29, 95% CI: 1.15-1.45) and waist-to height ratio (HR per 0.1 units: 1.46, 95% CI: 1.17-1.84). CONCLUSIONS:Our analyses did not support an association between central adiposity and overall premenopausal breast cancer risk after adjustment for BMI. However, our findings suggest associations might differ by breast cancer hormone receptor and intrinsic subtypes.

BACKGROUND:Previous research investigating sedentary behavior and breast cancer risk has shown mixed results. We investigated the association between sedentary time and breast cancer incidence overall and by time-dependent menopausal status. METHODS:The Sister Study recruited 50,884 women aged 35 to 74 years from all 50 states and Puerto Rico who had not been diagnosed with breast cancer but had at least one affected sister. Sedentary time was collected at the first detailed follow-up from 2008 to 2012 and categorized as ≤5 hours/day (referent), 6 to 9 hours/day, and ≥10 hours/day. Breast cancer cases were reported annually. We used multivariable Cox proportional hazards regression to estimate the HR and 95% confidence intervals (CI) for the association of sedentary time with overall breast cancer incidence, with age as the primary time scale and adjusted for relevant covariates. Participants were followed through September 2021. We evaluated effect measure modification by menopausal status. RESULTS:Among the 39,111 eligible women with information on sedentary behavior and covariates, sedentary time [6-9 vs. ≤5 adjusted HR (aHR) = 1.18; 95% CI, 1.08-1.28; ≥10 vs. ≤5 aHR = 1.19; 95% CI, 1.07-1.32] was associated with higher breast cancer incidence. The association varied by menopausal status (P heterogeneity = 0.002), with sedentary time inversely associated with breast cancer among premenopausal women (≥10 vs. ≤5 aHR = 0.69; 95% CI, 0.50-0.95) and positively associated with breast cancer among postmenopausal women (6-9 vs. ≤5 aHR = 1.22; 95% CI, 1.11-1.33; ≥10 vs. ≤5 aHR = 1.28; 95% CI, 1.14-1.43). CONCLUSIONS:Increased sedentary time was associated with breast cancer incidence, but the direction of this association varied by time-dependent menopausal status. IMPACT:The impact of sedentary time on cancer risk may vary by menopausal status.

Genome‐wide association studies (GWAS) have identified more than 200 risk loci for breast cancer. However, target genes and their encoded proteins in these loci remain largely unknown. In this study, we utilized genetic prediction models for 1349 circulating proteins derived from individuals of African ( n = 1871) and European ( n = 7213) ancestry to investigate genetically predicted protein levels in association with breast cancer risk among females of African ( n = 40,138), Asian ( n = 137,677), and European ( n = 247,173) ancestry. We identified 51 blood protein biomarkers associated with breast cancer risk, overall or by subtypes, at a false discovery rate (FDR) < 0.05, including 27 proteins encoded by genes located at least 1 Mb away from any of the known risk loci identified in GWAS. Of them, 32 proteins showed significant associations with breast cancer risk at the Bonferroni‐corrected significance level ( p < 2.45 × 10 −4 ). Of the 24 proteins located at GWAS‐identified risk loci, associations for 14 proteins were significantly attenuated after adjustment for the index risk variant of each respective locus, suggesting that these proteins may be target proteins for the risk loci. Encoding gene expression levels in normal breast tissue could be genetically predicted for 23 of the 51 identified proteins, and 13 encoding genes were associated with breast cancer risk in the same direction ( p < .05). Our study identified potential protein targets of GWAS risk loci and biomarkers for breast cancer risk and provided additional insights into breast cancer genetics and etiology.

STUDY QUESTION:Is being born of a young mother associated with worse gynecologic health, as indicated by a bilateral oophorectomy or hysterectomy before age 40? SUMMARY ANSWER:Daughters of mothers younger than 25 did not have reduced parity but did have a higher risk of having bilateral oophorectomy or hysterectomy before age 40, particularly if their mother was younger than 20 years at their birth. WHAT IS KNOWN ALREADY:Three recent studies have reported lower fecundability among daughters of mothers younger than 20 years; adverse socioeconomic conditions may explain part of that association. STUDY DESIGN, SIZE, DURATION:This study reports cumulative, primarily retrospective, accrual of outcomes up to age 40 among 41 450 women recruited into the US-based Sister Study between 2003 and 2009. PARTICIPANTS/MATERIALS, SETTING, METHODS:The analysis sample included women ≥41 years at the time of the latest follow-up and <66 years at recruitment. Using log-binomial regression, we estimated adjusted relative risks (RRs) of having major gynecologic surgery (bilateral oophorectomy or hysterectomy) before age 40 by age of the participant's mother (G1) when she gave birth to the participant (G2). All models were adjusted for father's age at G2's birth, daughter's self-identified race/ethnicity, and year of birth. We assessed possible effect modification by stratifying the analyses by self-reported G2's family income level during childhood (poor-low, medium-high) and G2's educational level (categorized as below bachelor's degree and bachelor's degree or higher) and, in the following step, by G2's age at first birth. MAIN RESULTS AND THE ROLE OF CHANCE:Compared with daughters born to mothers aged 30-34, daughters of mothers <20 and 20-24 years had an RR of 1.74 (95% CI 1.51, 2.00) and 1.35 (1.22, 1.50), respectively, of major gynecologic surgery before age 40. Although lower childhood income, G2 education, and giving birth before age 25 were strongly associated with outcome risk, the RRs changed little after accounting for those factors. LIMITATIONS, REASONS FOR CAUTION:This is a descriptive study of a proxy indicator of poor gynecologic health. Furthermore, all information was self-reported and, for nearly all women, recalled after the event. The measures used for socioeconomic status may have been insufficient. WIDER IMPLICATIONS OF THE FINDINGS:Daughters of younger mothers did not have reduced parity but appeared to have a higher risk of major gynecologic surgery before age 40. This study adds to prior evidence that daughters of young mothers have worse gynecologic health. STUDY FUNDING/COMPETING INTEREST(S):This research was supported in part by the Intramural Research Program of the NIH, National Institute of Environmental Health Sciences (Z01-ES044005, Z01-ES102245, and Z01-ES103086). The authors report no conflict of interest. TRIAL REGISTRATION NUMBER:N/A.

Background: Phthalate exposure during pregnancy has been associated with preterm birth, but mechanisms of action may depend on the timing of exposure. Objective: Investigate critical periods of susceptibility during pregnancy for associations between urinary phthalate metabolite concentrations and preterm birth. Methods: Individual-level data were pooled from 16 US cohorts (N = 6045, n = 539 preterm births). We examined trimester-averaged urinary phthalate metabolite concentrations. Most phthalate metabolites had 2248, 3703, and 3172 observations in the first, second, and third trimesters, respectively. Our primary analysis used logistic regression models with generalized estimating equations (GEE) under a multiple informant approach to estimate trimester-specific odds ratios (ORs) of preterm birth and significant (p < 0.20) heterogeneity in effect estimates by trimester. Adjusted models included interactions between each covariate and trimester. Results: Differences in trimester-specific associations between phthalate metabolites and preterm birth were most evident for di-2-ethylhexyl phthalate (DEHP) metabolites. For example, an interquartile range increase in mono (2-ethylhexyl) phthalate (MEHP) during the first and second trimesters was associated with ORs of 1.15 (95 % confidence interval [CI]: 0.99, 1.33) and 1.11 (95 % CI: 0.97, 1.28) for preterm birth, respectively, but this association was null in the third trimester (OR = 0.91 [95 % CI: 0.76, 1.09]) (p-heterogeneity = 0.03). Conclusion: The association of preterm birth with gestational biomarkers of DEHP exposure, but not other phthalate metabolites, differed by the timing of exposure. First and second trimester exposures demonstrated the greatest associations. Our study also highlights methodological considerations for critical periods of susceptibility analyses in pooled studies.

Reproductive complications tend to recur. The risk of gestational diabetes is much higher in the second pregnancy if it occurred in the first. Such recurrence risks are regarded as reflecting heterogeneity among couples in their inherent risk. Pregnancy complications not only predict their own recurrence but have been shown to be associated with different later health problems like hypertension and heart disease. Epidemiologically considering reproductive history as a risk factor has been challenging, however, because women vary in their number of pregnancies and there's no obvious way to account for both prior occurrences and prior nonoccurrences. We propose a simple empirical Bayes approach, the Beta Approach for Risk Summarization (BARS). We apply BARS to retrospective data reported at enrollment in a large cohort, the Sister Study, to estimate propensity to gestational diabetes, and use that to predict subsequent occurrences of gestational diabetes based on successively updated pregnancy histories. We assess the calibration of our predictive model for gestational diabetes and demonstrate that it works well. We then apply the method to prospective data from the Sister Study, revisiting an earlier paper that linked gestational diabetes to the risk of breast cancer, but now using BARS and additional person time.

Importance:Inherited pathogenic variants (PVs) in known predisposition genes can greatly increase breast cancer risk, but the combined impact of PV status, family history, and other factors on breast cancer risk in the general US population has not been well described. Objective:To evaluate population-based breast cancer risk estimates for those with established PVs overall and stratified by first-degree family history of breast cancer and other factors. Design, Setting, and Participants:This study used pooled data from 13 US-based breast cancer case-control studies participating in the Cancer Risk Estimates Related to Susceptibility (CARRIERS) consortium. Enrollment for individual studies occurred between 1976 and 2013, and results are based on data released March 2023, with analyses conducted from June 2022 to July 2025. Exposures:PVs, breast cancer family history, self-reported race and ethnicity, and established risk factors. Main Outcomes and Measures:Breast cancer rate ratios for PVs in 7 genes were estimated from the CARRIERS consortium. PV status and incidence and mortality statistics were combined using the Individualized Coherent Absolute Risk Estimation (iCARE) model to estimate conditional cumulative breast cancer risks and 95% CIs, stratified by family history and standardized to the US population. Models that incorporated population-based data and published estimates for established epidemiologic risk factors were also evaluated. Results:A total of 67 692 women were studied, including 33 841 who were diagnosed with breast cancer. PVs in ATM, BRCA1, BRCA2, CHEK2, and PALB2 were strongly associated with breast cancer risk, with BRCA1 and PALB2 PVs showing evidence of heterogeneity by family history. In models considering PVs, family history, and established risk factors, the estimated cumulative risks of breast cancer by age 50 years ranged from 2.4% (95% CI, 2.4-2.4) in women with no PVs and no family history to 35.5% (95% CI, 21.6-55.1) in PALB2 PV carriers with a family history. Among women who have not been diagnosed with breast cancer by age 50 years, the cumulative risk of breast cancer by age 80 years ranged from 11.1% (95% CI, 11.0-11.2) in noncarriers with no family history to 70.5% (95% CI, 52.8-83.5) for PALB2 carriers with a family history. PV-specific cumulative risk estimates varied across subgroups defined by race and ethnicity and potentially modifiable epidemiologic risk factors. Conclusions and Relevance:In this study, population-based estimates of cumulative breast cancer risk for established PVs, as informed by the CARRIERS case-control sample, varied by family history and potentially modifiable risk factors. These estimates provide guidance for identifying individuals who will most benefit from enhanced screening and prevention strategies.

Blood DNA methylation (DNAm) profiles have been used to show that changes in circulating leukocyte composition occur during breast cancer development, suggesting that peripheral immune system alterations are markers of breast cancer risk. Blood DNAm profiles have recently been used to predict plasma protein concentrations (“Protein EpiScores”), but their associations with breast cancer risk have not been examined in detail. Whole blood DNAm profiles were obtained for a case-cohort sample of participants in the Sister Study and used to calculate 109 Protein EpiScores. Of the 4,479 women included, 2,151 (48

Objectives:Juvenile idiopathic arthritis (JIA) originates from a complex interplay between genetic and environmental factors. We investigated the association between seafood intake and dietary contaminant exposure during pregnancy and JIA risk, to identify sex differences and gene-environment interactions. Methods:We used the Norwegian Mother, Father, and Child Cohort Study (MoBa), a population-based prospective pregnancy cohort (1999-2008). JIA patients were identified through the Norwegian Patient Registry, with remaining mother-child pairs serving as controls. We assessed maternal seafood intake and dietary contaminants typically found in seafood using a food frequency questionnaire completed during pregnancy, mainly comparing high (≥90th percentile, P90) vs low (<P90) intake. Multivariable logistic regression calculated adjusted odds ratios (aOR), including sex-stratification analyses. A polygenic risk score (PRS) for JIA was used in a subsample to assess gene-environment interactions. Results:We identified 217 JIA patients and 71,884 controls. High vs low maternal intake of lean/semi-oily fish was associated with JIA (aOR 1.51, 95% CI 1.02-2.22), especially among boys (aOR 2.13, 95% CI 1.21-3.75). A significant gene-environment interaction was observed between total fish intake and PRS, with high fish intake associated with JIA primarily in those with low PRS (p<0.03). We found no associations between high vs low exposure to other types of seafood or environmental contaminants and JIA. Conclusions:We found a modestly increased risk of JIA associated with high intake of lean/semi-oily fish during pregnancy, not explained by estimated exposure to dietary contaminants. Our data suggest a more pronounced association in children with a lower genetic predisposition for JIA.

IntroductionPregnancy involves a double genome, and genetic variants in the mother and her fetus can act together to influence risk for pregnancy complications, adverse pregnancy outcomes, and diseases in the offspring. Large search spaces have hindered the discovery of sets of single nucleotide polymorphisms (SNPs) that act epistatically.MethodsPreviously, we proposed a method for case-parent studies, called the Genetic Algorithm for Detecting Genetic Epistasis using Triads or Siblings (GADGETS), that can reveal autosomal epistatic SNP-sets in the child’s genome. Here we incorporate maternal SNPs, thereby extending GADGETS to nominate SNP-sets containing offspring loci only, maternal loci only, or both. We use a permutation procedure to impose a preference for epistatic over outcome-related but non-epistatic SNP sets. Our maternal-fetal extension uses case-complement-sibling pairs together with mother-father pairs, exploiting Mendelian transmission and a mating-symmetry assumption.ResultsIn simulations of 1,000 case-parents triads with 10,000 candidate SNPs, GADGETS successfully detected simulated multi-locus effects involving 3-5 SNPs but was somewhat less successful at distinguishing epistatic SNPs from sets of non-epistatic SNPs that each conferred high risk independently. Though the epistasis-mining algorithms MDR-PDT, TrioFS, and EPISFA-LD were originally designed to find epistatic offspring variants, we generalize them to include maternal SNPs and search more broadly. GADGETS outperformed those competitors and could successfully mine a much larger list of candidate SNPs. Applied to dbGaP data, GADGETS nominated several multi-SNP maternal-fetal sets as potentially-interacting risk factors for orofacial clefting.DiscussionThe extended version of GADGETS can mine for epistasis that involves maternal SNPs.

Reproductive complications tend to recur. The risk of gestational diabetes is much higher in the second pregnancy if it occurred in the first. Such recurrence risks are regarded as reflecting heterogeneity among couples in their inherent risk. Pregnancy complications not only predict their own recurrence but have been shown to be associated with different later health problems like hypertension and heart disease. Epidemiologically considering reproductive history as a risk factor has been challenging, however, because women vary in their number of pregnancies and there’s no obvious way to account for both prior occurrences and prior non-occurrences. We propose a simple empirical Bayes approach, the Beta Approach for Risk Summarization (BARS). We apply BARS to retrospective data reported at enrollment in a large cohort, the Sister Study, to estimate propensity to gestational diabetes, and use that to predict subsequent occurrences of gestational diabetes based on successively updated pregnancy histories. We assess the calibration of our predictive model for gestational diabetes and demonstrate that it works well. We then apply the method to prospective data from the Sister Study, revisiting an earlier paper that linked gestational diabetes to risk of breast cancer, but now using BARS and additional person time.

Introduction:Despite well-known harmful health effects of smoking, research supports an inverse association with some autoimmune diseases. High-titer antinuclear antibodies (ANA) are associated with autoimmune diseases, and ANA prevalence in the US increased between 1988 and 2012. Tobacco smoking decreased during those years while vaping of electronic cigarettes (e-cigarettes) increased after their introduction in 2007. Carbon monoxide (CO) may ameliorate autoimmunity, and e-cigarettes deliver much less CO than regular cigarettes. We explored interdependencies among ANA, smoking, and time. Methods:We analyzed cross-sectional data on ANA and the primary nicotine metabolite, cotinine, in 13,288 participants ≥12 years old from three time periods (1988-1991, 1999-2004, 2011-2012) of the US National Health and Nutrition Examination Survey. Smoking exposure (none, passive, active) was inferred from serum cotinine. We used logistic regression to analyze ANA prevalence, adjusted for sex, age, and race/ethnicity. Results:Over the study periods, ANA prevalence was highest (13.3-19.2%) for nonsmokers but non-trending; lower (11.1-15.5%) for "passive" smokers but steadily increasing; and even lower for active smokers but increasing from 7.4% in 1999-2004 to 13.3% in 2011-2012. The increases in ANA among passive and active smokers were mainly in adolescents (ages 12-19 years). Smokers had reduced odds of ANA in 1999-2004, with an odds ratio (OR) of 0.65 and a 95% confidence interval (CI) of 0.45-0.93, but this association was weaker in 1988-1991 (OR=0.80; 95% CI:0.52-1.22) and 2011-2012 (OR=0.82; 95% CI:0.56-1.21). Discussion:Although smoking causes harmful health effects, ANA data are consistent with smoking playing a role in decreasing autoimmunity. Recent vaping among adolescents may partially explain their large increase in ANA prevalence. The inverse ANA association with smoking strengthened between 1988-1991 and 1999-2004 but then weakened by 2011-2012. The initial strengthening was potentially because nonsmokers were exposed to progressively less CO (and/or other components of secondhand smoke), due to tightened smoking restrictions, while the potential nicotine-associated protection against ANA may have weakened after e-cigarettes became a source. Smoking should not be recommended given its negative health impacts. However, further studies could elucidate new mechanisms, perhaps involving components of tobacco smoke or vaping, possibly enabling development of novel preventative or treatment measures.

Background/Objectives: Iron is necessary for bodily function, but abnormal levels can increase the risk of chronic diseases. Studies of leukocyte telomere length suggest blood iron levels are positively associated with cellular senescence and accelerated aging. However, associations between blood iron and more robust metrics of biological aging, specifically those based on DNA methylation, have not been examined. Methods: In a random sample of women from the Sister Study (n = 1260) with measured serum iron (ferritin, iron, transferrin saturation), we used linear regression models to assess cross-sectional associations between standardized serum iron and three methylation-based biological aging metrics (GrimAgeAccel, PhenoAgeAccel, and DunedinPACE), with and without adjustment for smoking, alcohol, menopause status, education, time since menopause, exercise, and diet. Results: In adjusted models, a one standard deviation increase in serum ferritin was positively associated with higher standardized levels of DunedinPACE, GrimAgeAccel, and PhenoAgeAccel (DunedinPACE: 0.05, (0.00, 0.10); PhenoAgeAccel: 0.06 (0.00, 0.11); GrimAgeAccel: 0.06 (0.01, 0.11)). In contrast, higher serum iron and transferrin saturation were inversely associated with the biological aging metrics (serum iron, DunedinPACE: −0.02, (−0.07, 0.03); PhenoAgeAccel: −0.04 (−0.10, 0.01); GrimAgeAccel: −0.05 (−0.10, −0.01); transferrin saturation (DunedinPACE: −0.01, (−0.06, 0.05); PhenoAgeAccel: −0.01 (−0.06, 0.05); GrimAgeAccel: −0.05 (−0.10, −0.01))). Conclusions: The positive association with ferritin is consistent with the proposed role of oxidative stress in accelerated aging associated with high iron exposure. However, the observed inverse associations with serum iron and transferrin saturation are not consistent with this common explanation, and future studies are needed to examine potential explanations.

Background: Cancer survivors are at high risk for weight gain and cardiovascular disease (CVD) after treatment. Artificial light at night (ALAN) may contribute to elevate risks by disrupting circadian rhythm, affecting hormonal regulation and metabolism. This relationship has not been evaluated in women cancer survivors. Methods: After excluding women with daytime sleep schedules and those with prevalent CVD, 2,401 women (aged 35-74 years) who reported a history of cancer other than non-melanoma skin cancer when they enrolled in the Sister Study (2003-2009) were followed through September 2021 (mean follow-up: 11.8 years). Self-reported indoor ALAN exposure during sleep was categorized as: no light (reference group), small nightlight in the room, light outside the room, and television/light on in the room. Generalized Poisson regression models with a log link and robust standard errors were used to estimate multivariable relative risks (RRs) for weight gain ≥5 kg and a BMI increase ≥10% over follow-up. Multivariable Cox proportional hazards models were used to estimate hazard ratios (HRs) for incident CVD, including myocardial infarction, angina, heart failure, heart bypass surgery, angioplasty, transient ischemic attack, or stroke. Results: At cohort entry, the median time since cancer diagnosis was 9.8 years and 28.6% of participants were obese (BMI ≥30). Any ALAN was associated with weight gain (RR 1.51, 95% CI 1.12-2.03) and BMI increase (RR 1.46, 95% CI 1.02-2.09). Sleeping with a television or light on was positively associated with weight gain (RR 1.83, 95% CI 1.27-2.65, P trend =0.0002), particularly in long-term survivors (>10 years, RR 2.99, 95% CI 1.71-5.23, P trend <0.0001), and with BMI increase (RR 1.89, 95% CI 1.21-2.94, P trend =0.003) over follow-up. These associations persisted after adjusting for sleep duration and quality, dietary patterns, and physical activity. Sleeping with a television or light on was also associated with increased CVD risk (HR 1.61, 95% CI 1.05-2.46, P trend =0.03), with a stronger association among survivors with pre-existing CVD risk factors (diabetes, hypertension, or dyslipidemia) at enrollment (HR 1.90, 95% CI 1.13-3.17, P trend =0.0008). Conclusions: ALAN may contribute to weight gain, higher BMI, and elevated CVD incidence in cancer survivors who are women. ALAN may be a modifiable risk factor for obesity and CVD in this high-risk population. Future studies should include an assessment of daytime light exposure.

PURPOSE:To determine the relationship between germline pathogenic variants (PV) in cancer predisposition genes and the risk of ductal carcinoma in situ (DCIS). EXPERIMENTAL DESIGN:Germline PV frequencies in breast cancer predisposition genes (ATM, BARD1, BRCA1, BRCA2, CDH1, CHEK2, PALB2, RAD51C, and RAD51D) were compared between DCIS cases and unaffected controls and between DCIS and invasive ductal breast cancer (IDC) cases from a clinical testing cohort (n = 9,887), a population-based cohort (n = 3,876), and the UK Biobank (n = 2,421). The risk of contralateral breast cancer (CBC) for DCIS cases with PV was estimated in the population-based cohort. RESULTS:Germline PV were observed in 6.5% and 4.6% of women with DCIS in the clinical testing and population-based cohorts, respectively. BRCA1, BRCA2, and PALB2 PV frequencies were significantly lower among women with DCIS than those with IDC (clinical cohort: 2.8% vs. 5.7%; population-based cohort: 1.7% vs. 3.7%), whereas the PV frequencies for ATM and CHEK2 were similar. ATM, BRCA1, BRCA2, CHEK2, and PALB2 PV were significantly associated with an increased risk of DCIS (OR > 2.0), but only BRCA2 PV were associated with high risk (OR > 4) in both cohorts. The cumulative incidence of CBC among carriers of PV in high-penetrance genes with DCIS was 23% over 15 years. CONCLUSIONS:The enrichment of PV in ATM, BRCA1, BRCA2, CHEK2, and PALB2 among women with DCIS suggests that multigene panel testing may be appropriate for women with DCIS. Elevated risks of CBC in carriers of PV in high-penetrance genes with DCIS confirmed the utility of testing for surgical decision-making.

BACKGROUND:Pathogenic variants (PVs) in ATM, BRCA1, BRCA2, CHEK2, and PALB2 are associated with increased breast cancer risk. It is unknown, however, whether this risk differs by PV type or location in carriers ascertained from the general population. PATIENTS AND METHODS:To evaluate breast cancer risks associated with PV type and location in ATM, BRCA1, BRCA2, CHEK2, and PALB2, we carried out age-adjusted case-control association analysis in 32 247 women with and 32 544 age-matched women without breast cancer from the CARRIERS Consortium. PVs were grouped by type and location within genes and assessed for risks of breast cancer [odds ratios (OR), 95% confidence intervals (CI), and P values] using logistic regression. RESULTS:Compared with women carrying BRCA2 exon 11 protein truncating variants (PTVs) in the CARRIERS population-based study, women with BRCA2 ex1-10 PTVs (OR = 13.5, 95% CI 6.0-38.7, P < 0.001) and ex13-27 PTVs (OR = 9.0, 95% CI 4.9-18.5, P < 0.001) had higher breast cancer risks, lower rates of estrogen receptor (ER)-negative breast cancer (ex13-27 OR = 0.5, 95% CI 0.2-0.9, P = 0.035; ex1-10 OR = 0.5, 95% CI 0.1-1.0, P = 0.065), and earlier age at breast cancer diagnosis (ex13-27 5.5 years, P < 0.001; ex1-10 2.4 years, P = 0.169). These associations with ER-negative breast cancer and age were replicated in a high-risk clinical cohort from Ambry Genetics and the population-based UK Biobank cohort. No differences in risk by gene region were observed for PTVs in other predisposition genes. CONCLUSIONS:Population-based and clinical high-risk cohorts establish that PTVs in exon 11 of BRCA2 are associated with reduced breast cancer risk, later age at diagnosis, and greater risk of ER-negative disease. These differential risks may improve individualized risk prediction and clinical management for women carrying BRCA2 PTVs.

Supplemental Figure S2. Meta-analysis full forest plots from AABCG for rs2814778 in relation to risk of breast cancer overall, ER- and TNBC. Figure shows non-significant odds ratio (OR) estimates for breast cancer risk overall, ER- and TNBC for ACKR1/DARC variant, rs2814778 in reference to controls.

BACKGROUND:Immune response in blood varies by ancestry, linked to an African-specific variant (rs2814778) in the Duffy Antigen Receptor for Chemokines (DARC/ACKR1) gene. We examined associations between rs2814778, CD8+ T-cell density in breast tumors, and breast cancer risk in African-American/Black women. METHODS:CD8+ T-cell density in tumors from 428 Black women were examined in relation to the rs2814778 variant. In the African Ancestry Breast Cancer Genetics (AABCG) Consortium with 16,886 cases and 18,044 controls, rs2814778 was evaluated in relation to risk of overall breast cancer and to more aggressive subtypes [estrogen receptor-negative (ER-) and triple-negative breast cancer (TNBC)]. RESULTS:Women with the African-specific CC genotype had lower tumor CD8+ T-cell density (87.0 per mm2) than those with TT genotypes (146.6 per mm2; P < 0.05). Each T allele was significantly associated with an increase in T-cell density (P = 0.04). In the largest analysis, to date, there were no associations between rs2814778 and risk of overall breast cancer [OR = 0.90 (95% confidence interval (CI), 0.66-1.22)] or with ER- breast cancer [OR = 0.86 (95% CI, 0.68-1.08)] or TNBC [OR = 0.77 (95% CI, 0.56-1.05)]. CONCLUSIONS:Although breast tumors from women with the African-specific DARCC allele had lower CD8+ T-cell density levels than those with T alleles, in a large breast cancer consortium with adequate statistical power, the variant was not associated with breast cancer risk overall, nor with risk of ER- breast cancer or TNBC, as previously hypothesized. IMPACT:Although the "Duffy-null" allele has been the focus of research as a contributor to aggressive breast cancer in Black women, this study with 34,930 cases and controls found no associations with risk.