Publications by authors named "Minouk J Schoemaker"

122 Publications

Gestational diabetes and risk of breast cancer before age 55 years.

Int J Epidemiol 2021 Aug 29. Epub 2021 Aug 29.

Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, USA.

Background: The history of gestational diabetes mellitus (GDM) has been associated with breast cancer risk in some studies, particularly in young women, but results of cohort studies are conflicting.

Methods: We pooled data from 257 290 young (age <55 years) women from five cohorts. We used multivariable Cox proportional-hazards regression to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between GDM history and risk of breast cancer, overall and by oestrogen receptor (ER) status, before age 55 years, adjusted for established breast cancer risk factors.

Results: Five percent of women reported a history of GDM and 6842 women reported an incident breast-cancer diagnosis (median follow-up = 16 years; maximum = 24 years). Compared with parous women without GDM, women with a history of GDM were not at increased risk of young-onset breast cancer overall (HR = 0.90; 95% CI: 0.78, 1.03) or by ER status (HR = 0.96; 95% CI: 0.79, 1.16 for ER-positive; HR = 1.07; 95% CI: 0.78, 1.47 for ER-negative). Compared with nulliparous women, parous women with a history of GDM had a lower risk of breast cancer overall (HR = 0.79; 95% CI: 0.68, 0.91) and of ER-positive (HR = 0.82; 95% CI: 0.66, 1.02) but not ER-negative (HR = 1.09; 95% CI: 0.76, 1.54) invasive breast cancer. These results were consistent with the HRs comparing parous women without GDM to nulliparous women.

Conclusions: Results of this analysis do not support the hypothesis that GDM is a risk factor for breast cancer in young women. Our findings suggest that the well-established protective effect of parity on risk of ER-positive breast cancer persists even for pregnancies complicated by GDM.
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http://dx.doi.org/10.1093/ije/dyab165DOI Listing
August 2021

Genetic insights into biological mechanisms governing human ovarian ageing.

Nature 2021 08 4;596(7872):393-397. Epub 2021 Aug 4.

Genome Integrity and Instability Group, Institut de Biotecnologia i Biomedicina, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain.

Reproductive longevity is essential for fertility and influences healthy ageing in women, but insights into its underlying biological mechanisms and treatments to preserve it are limited. Here we identify 290 genetic determinants of ovarian ageing, assessed using normal variation in age at natural menopause (ANM) in about 200,000 women of European ancestry. These common alleles were associated with clinical extremes of ANM; women in the top 1% of genetic susceptibility have an equivalent risk of premature ovarian insufficiency to those carrying monogenic FMR1 premutations. The identified loci implicate a broad range of DNA damage response (DDR) processes and include loss-of-function variants in key DDR-associated genes. Integration with experimental models demonstrates that these DDR processes act across the life-course to shape the ovarian reserve and its rate of depletion. Furthermore, we demonstrate that experimental manipulation of DDR pathways highlighted by human genetics increases fertility and extends reproductive life in mice. Causal inference analyses using the identified genetic variants indicate that extending reproductive life in women improves bone health and reduces risk of type 2 diabetes, but increases the risk of hormone-sensitive cancers. These findings provide insight into the mechanisms that govern ovarian ageing, when they act, and how they might be targeted by therapeutic approaches to extend fertility and prevent disease.
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http://dx.doi.org/10.1038/s41586-021-03779-7DOI Listing
August 2021

Mendelian randomisation study of smoking exposure in relation to breast cancer risk.

Br J Cancer 2021 Aug 2. Epub 2021 Aug 2.

Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, MD, USA.

Background: Despite a modest association between tobacco smoking and breast cancer risk reported by recent epidemiological studies, it is still equivocal whether smoking is causally related to breast cancer risk.

Methods: We applied Mendelian randomisation (MR) to evaluate a potential causal effect of cigarette smoking on breast cancer risk. Both individual-level data as well as summary statistics for 164 single-nucleotide polymorphisms (SNPs) reported in genome-wide association studies of lifetime smoking index (LSI) or cigarette per day (CPD) were used to obtain MR effect estimates. Data from 108,420 invasive breast cancer cases and 87,681 controls were used for the LSI analysis and for the CPD analysis conducted among ever-smokers from 26,147 cancer cases and 26,072 controls. Sensitivity analyses were conducted to address pleiotropy.

Results: Genetically predicted LSI was associated with increased breast cancer risk (OR 1.18 per SD, 95% CI: 1.07-1.30, P = 0.11 × 10), but there was no evidence of association for genetically predicted CPD (OR 1.02, 95% CI: 0.78-1.19, P = 0.85). The sensitivity analyses yielded similar results and showed no strong evidence of pleiotropic effect.

Conclusion: Our MR study provides supportive evidence for a potential causal association with breast cancer risk for lifetime smoking exposure but not cigarettes per day among smokers.
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http://dx.doi.org/10.1038/s41416-021-01432-8DOI Listing
August 2021

Breast cancer risk factors and circulating anti-Müllerian hormone concentration in healthy premenopausal women.

J Clin Endocrinol Metab 2021 Jun 22. Epub 2021 Jun 22.

Department of Population Health, New York University School of Medicine, New York, NY.

Context: In a previous study we reported that anti-Müllerian hormone (AMH), a marker of ovarian reserve, is positively associated with breast cancer risk, consistent with other studies.

Objective: Assess whether risk factors for breast cancer are correlates of AMH concentration.

Design: Cross-sectional.

Participants: 3831 healthy premenopausal women (aged 21-57, 87% aged 35-49).

Setting: Ten cohort studies, general population.

Results: Adjusting for age and cohort, we observed positive associations of AMH with age at menarche (p<0.0001) and parity (p=0.0008), and an inverse association with hysterectomy/partial oophorectomy (p=0.0008). Compared to women of normal weight (BMI 18.5-24.9 kg/m 2, AMH was lower (relative geometric mean difference 27%, p<0.0001) among women who were obese (BMI>30). Current oral contraceptive use and current/former smoking were associated with lower AMH concentration than never use (40% and 12% lower, respectively, p<0.0001). We observed higher AMH concentrations among women who had had a benign breast biopsy (15% higher, p=0.03), a surrogate for benign breast disease, an association that has not been reported. In analyses stratified by age (<40/≥40), associations of AMH with BMI and oral contraceptives were similar in younger and older women, while associations with the other factors (menarche, parity, hysterectomy/partial oophorectomy, smoking, and benign breast biopsy) were limited to women ≥40 (p-interaction<0.05).

Conclusion: This is the largest study of AMH and breast cancer risk factors among women from the general population (not presenting with infertility), and suggests that most of the associations are limited to women over 40, who are approaching menopause and whose AMH concentration is declining.
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http://dx.doi.org/10.1210/clinem/dgab461DOI Listing
June 2021

Functional annotation of the 2q35 breast cancer risk locus implicates a structural variant in influencing activity of a long-range enhancer element.

Am J Hum Genet 2021 07 18;108(7):1190-1203. Epub 2021 Jun 18.

Genomic Epidemiology Group, German Cancer Research Center (DKFZ), Heidelberg 69120, Germany.

A combination of genetic and functional approaches has identified three independent breast cancer risk loci at 2q35. A recent fine-scale mapping analysis to refine these associations resulted in 1 (signal 1), 5 (signal 2), and 42 (signal 3) credible causal variants at these loci. We used publicly available in silico DNase I and ChIP-seq data with in vitro reporter gene and CRISPR assays to annotate signals 2 and 3. We identified putative regulatory elements that enhanced cell-type-specific transcription from the IGFBP5 promoter at both signals (30- to 40-fold increased expression by the putative regulatory element at signal 2, 2- to 3-fold by the putative regulatory element at signal 3). We further identified one of the five credible causal variants at signal 2, a 1.4 kb deletion (esv3594306), as the likely causal variant; the deletion allele of this variant was associated with an average additional increase in IGFBP5 expression of 1.3-fold (MCF-7) and 2.2-fold (T-47D). We propose a model in which the deletion allele of esv3594306 juxtaposes two transcription factor binding regions (annotated by estrogen receptor alpha ChIP-seq peaks) to generate a single extended regulatory element. This regulatory element increases cell-type-specific expression of the tumor suppressor gene IGFBP5 and, thereby, reduces risk of estrogen receptor-positive breast cancer (odds ratio = 0.77, 95% CI 0.74-0.81, p = 3.1 × 10).
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http://dx.doi.org/10.1016/j.ajhg.2021.05.013DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8322933PMC
July 2021

Comparative performance of lung cancer risk models to define lung screening eligibility in the United Kingdom.

Br J Cancer 2021 Jun 12;124(12):2026-2034. Epub 2021 Apr 12.

International Agency for Research on Cancer, Lyon, France.

Background: The National Health Service England (NHS) classifies individuals as eligible for lung cancer screening using two risk prediction models, PLCOm2012 and Liverpool Lung Project-v2 (LLPv2). However, no study has compared the performance of lung cancer risk models in the UK.

Methods: We analysed current and former smokers aged 40-80 years in the UK Biobank (N = 217,199), EPIC-UK (N = 30,813), and Generations Study (N = 25,777). We quantified model calibration (ratio of expected to observed cases, E/O) and discrimination (AUC).

Results: Risk discrimination in UK Biobank was best for the Lung Cancer Death Risk Assessment Tool (LCDRAT, AUC = 0.82, 95% CI = 0.81-0.84), followed by the LCRAT (AUC = 0.81, 95% CI = 0.79-0.82) and the Bach model (AUC = 0.80, 95% CI = 0.79-0.81). Results were similar in EPIC-UK and the Generations Study. All models overestimated risk in all cohorts, with E/O in UK Biobank ranging from 1.20 for LLPv3 (95% CI = 1.14-1.27) to 2.16 for LLPv2 (95% CI = 2.05-2.28). Overestimation increased with area-level socioeconomic status. In the combined cohorts, USPSTF 2013 criteria classified 50.7% of future cases as screening eligible. The LCDRAT and LCRAT identified 60.9%, followed by PLCOm2012 (58.3%), Bach (58.0%), LLPv3 (56.6%), and LLPv2 (53.7%).

Conclusion: In UK cohorts, the ability of risk prediction models to classify future lung cancer cases as eligible for screening was best for LCDRAT/LCRAT, very good for PLCOm2012, and lowest for LLPv2. Our results highlight the importance of validating prediction tools in specific countries.
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http://dx.doi.org/10.1038/s41416-021-01278-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8184952PMC
June 2021

Comparative validation of the BOADICEA and Tyrer-Cuzick breast cancer risk models incorporating classical risk factors and polygenic risk in a population-based prospective cohort of women of European ancestry.

Breast Cancer Res 2021 02 15;23(1):22. Epub 2021 Feb 15.

Division of Cancer Epidemiology and Genetics, National Cancer Institute of Health, 9609 Medical Center Drive 7E-342, Rockville, MD, 20850, USA.

Background: The Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) and the Tyrer-Cuzick breast cancer risk prediction models are commonly used in clinical practice and have recently been extended to include polygenic risk scores (PRS). In addition, BOADICEA has also been extended to include reproductive and lifestyle factors, which were already part of Tyrer-Cuzick model. We conducted a comparative prospective validation of these models after incorporating the recently developed 313-variant PRS.

Methods: Calibration and discrimination of 5-year absolute risk was assessed in a nested case-control sample of 1337 women of European ancestry (619 incident breast cancer cases) aged 23-75 years from the Generations Study.

Results: The extended BOADICEA model with reproductive/lifestyle factors and PRS was well calibrated across risk deciles; expected-to-observed ratio (E/O) at the highest risk decile :0.97 (95 % CI 0.51 - 1.86) for women younger than 50 years and 1.09 (0.66 - 1.80) for women 50 years or older. Adding reproductive/lifestyle factors and PRS to the BOADICEA model improved discrimination modestly in younger women (area under the curve (AUC) 69.7 % vs. 69.1%) and substantially in older women (AUC 64.6 % vs. 56.8%). The Tyrer-Cuzick model with PRS showed evidence of overestimation at the highest risk decile: E/O = 1.54(0.81 - 2.92) for younger and 1.73 (1.03 - 2.90) for older women.

Conclusion: The extended BOADICEA model identified women in a European-ancestry population at elevated breast cancer risk more accurately than the Tyrer-Cuzick model with PRS. With the increasing availability of PRS, these analyses can inform choice of risk models incorporating PRS for risk stratified breast cancer prevention among women of European ancestry.
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http://dx.doi.org/10.1186/s13058-021-01399-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7885342PMC
February 2021

CYP3A7*1C allele: linking premenopausal oestrone and progesterone levels with risk of hormone receptor-positive breast cancers.

Br J Cancer 2021 02 26;124(4):842-854. Epub 2021 Jan 26.

Molecular Epidemiology Group, C080, German Cancer Research Center (DKFZ), Heidelberg, Germany.

Background: Epidemiological studies provide strong evidence for a role of endogenous sex hormones in the aetiology of breast cancer. The aim of this analysis was to identify genetic variants that are associated with urinary sex-hormone levels and breast cancer risk.

Methods: We carried out a genome-wide association study of urinary oestrone-3-glucuronide and pregnanediol-3-glucuronide levels in 560 premenopausal women, with additional analysis of progesterone levels in 298 premenopausal women. To test for the association with breast cancer risk, we carried out follow-up genotyping in 90,916 cases and 89,893 controls from the Breast Cancer Association Consortium. All women were of European ancestry.

Results: For pregnanediol-3-glucuronide, there were no genome-wide significant associations; for oestrone-3-glucuronide, we identified a single peak mapping to the CYP3A locus, annotated by rs45446698. The minor rs45446698-C allele was associated with lower oestrone-3-glucuronide (-49.2%, 95% CI -56.1% to -41.1%, P = 3.1 × 10); in follow-up analyses, rs45446698-C was also associated with lower progesterone (-26.7%, 95% CI -39.4% to -11.6%, P = 0.001) and reduced risk of oestrogen and progesterone receptor-positive breast cancer (OR = 0.86, 95% CI 0.82-0.91, P = 6.9 × 10).

Conclusions: The CYP3A7*1C allele is associated with reduced risk of hormone receptor-positive breast cancer possibly mediated via an effect on the metabolism of endogenous sex hormones in premenopausal women.
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http://dx.doi.org/10.1038/s41416-020-01185-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7884683PMC
February 2021

Genome-wide association study meta-analysis identifies three novel loci for circulating anti-Müllerian hormone levels in women.

medRxiv 2020 Nov 3. Epub 2020 Nov 3.

Anti-Müllerian hormone (AMH) is expressed by antral stage ovarian follicles in women. Consequently, circulating AMH levels are detectable until menopause. Variation in age-specific AMH levels has been associated with breast cancer and polycystic ovary syndrome (PCOS), amongst other diseases. Identification of genetic variants underlying variation in AMH levels could provide clues about the physiological mechanisms that explain these AMH-disease associations. To date, only one variant in has been identified to be associated with circulating AMH levels in women. We aimed to identify additional variants for AMH through a GWAS meta-analysis including data from 7049 premenopausal women of European ancestry, which more than doubles the sample size of the largest previous GWAS. We identified four loci associated with AMH levels at p < 5×10 : the previously reported locus and three novel signals in or near , and . The strongest signal was a missense variant in the gene (rs10417628). Most prioritized genes at the other three identified loci were involved in cell cycle regulation. Genetic correlation analyses indicated a strong positive correlation among SNPs for AMH levels and for age at menopause (r = 0.82, FDR=0.003). Exploratory Mendelian randomization analyses did not support a causal effect of AMH on breast cancer or PCOS risk, but should be interpreted with caution as they may be underpowered and the validity of genetic instruments could not be extensively explored. In conclusion, we identified a variant in the gene and three other loci that may affect circulating AMH levels in women.
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http://dx.doi.org/10.1101/2020.10.29.20221390DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7654897PMC
November 2020

DNA methylation of the long intergenic noncoding RNA 299 gene in triple-negative breast cancer: results from a prospective study.

Sci Rep 2020 07 16;10(1):11762. Epub 2020 Jul 16.

Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany.

Triple-negative breast cancer (TNBC) is an aggressive breast cancer subtype associated with a high rate of recurrence and poor prognosis. Recently we identified a hypermethylation in the long noncoding RNA 299 (LINC00299) gene in blood-derived DNA from TNBC patients compared with healthy controls implying that LINC00299 hypermethylation may serve as a circulating biomarker for TNBC. In the present study, we investigated whether LINC00299 methylation is associated with TNBC in a prospective nested breast cancer case-control study within the Generations Study. Methylation at cg06588802 in LINC00299 was measured in 154 TNBC cases and 159 breast cancer-free matched controls using MethyLight droplet digital PCR. To assess the association between methylation level and TNBC risk, logistic regression was used to calculate odd ratios and 95% confidence intervals, adjusted for smoking status. We found no evidence for association between methylation levels and TNBC overall (P = 0.062). Subgroup analysis according to age at diagnosis and age at blood draw revealed increased methylation levels in TNBC cases compared with controls in the young age groups [age 26-52 (P = 0.0025) and age 22-46 (P = 0.001), respectively]. Our results suggest a potential association of LINC00299 hypermethylation with TNBC in young women.
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http://dx.doi.org/10.1038/s41598-020-68506-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7367270PMC
July 2020

Genome-wide association study identifies 32 novel breast cancer susceptibility loci from overall and subtype-specific analyses.

Nat Genet 2020 06 18;52(6):572-581. Epub 2020 May 18.

Molecular Medicine Unit, Fundación Pública Galega de Medicina Xenómica, Santiago de Compostela, Spain.

Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype. To identify novel loci, we performed a genome-wide association study including 133,384 breast cancer cases and 113,789 controls, plus 18,908 BRCA1 mutation carriers (9,414 with breast cancer) of European ancestry, using both standard and novel methodologies that account for underlying tumor heterogeneity by estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 status and tumor grade. We identified 32 novel susceptibility loci (P < 5.0 × 10), 15 of which showed evidence for associations with at least one tumor feature (false discovery rate < 0.05). Five loci showed associations (P < 0.05) in opposite directions between luminal and non-luminal subtypes. In silico analyses showed that these five loci contained cell-specific enhancers that differed between normal luminal and basal mammary cells. The genetic correlations between five intrinsic-like subtypes ranged from 0.35 to 0.80. The proportion of genome-wide chip heritability explained by all known susceptibility loci was 54.2% for luminal A-like disease and 37.6% for triple-negative disease. The odds ratios of polygenic risk scores, which included 330 variants, for the highest 1% of quantiles compared with middle quantiles were 5.63 and 3.02 for luminal A-like and triple-negative disease, respectively. These findings provide an improved understanding of genetic predisposition to breast cancer subtypes and will inform the development of subtype-specific polygenic risk scores.
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http://dx.doi.org/10.1038/s41588-020-0609-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7808397PMC
June 2020

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

J Natl Cancer Inst 2021 03;113(3):329-337

Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.

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.
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http://dx.doi.org/10.1093/jnci/djaa056DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7936056PMC
March 2021

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

Genet Epidemiol 2020 07 1;44(5):442-468. Epub 2020 Mar 1.

Department of Radiation Oncology, Hannover Medical School, Hannover, Germany.

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.
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http://dx.doi.org/10.1002/gepi.22288DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7987299PMC
July 2020

Correction to: Timing of pubertal stages and breast cancer risk: the Breakthrough Generations Study.

Breast Cancer Res 2020 02 11;22(1):19. Epub 2020 Feb 11.

Division of Genetics and Epidemiology, Institute of Cancer Research, Sutton, UK.

As a consequence of responding to colleagues who asked about the publication of the original article [1], the authors have determined that the data published in Table 4 of the paper are incorrect.
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http://dx.doi.org/10.1186/s13058-020-1257-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7014730PMC
February 2020

Adult weight change and premenopausal breast cancer risk: A prospective pooled analysis of data from 628,463 women.

Int J Cancer 2020 09 15;147(5):1306-1314. Epub 2020 Feb 15.

Albert Einstein College of Medicine, Bronx, NY.

Early-adulthood body size is strongly inversely associated with risk of premenopausal breast cancer. It is unclear whether subsequent changes in weight affect risk. We pooled individual-level data from 17 prospective studies to investigate the association of weight change with premenopausal breast cancer risk, considering strata of initial weight, timing of weight change, other breast cancer risk factors and breast cancer subtype. Hazard ratios (HR) and 95% confidence intervals (CI) were obtained using Cox regression. Among 628,463 women, 10,886 were diagnosed with breast cancer before menopause. Models adjusted for initial weight at ages 18-24 years and other breast cancer risk factors showed that weight gain from ages 18-24 to 35-44 or to 45-54 years was inversely associated with breast cancer overall (e.g., HR per 5 kg to ages 45-54: 0.96, 95% CI: 0.95-0.98) and with oestrogen-receptor(ER)-positive breast cancer (HR per 5 kg to ages 45-54: 0.96, 95% CI: 0.94-0.98). Weight gain from ages 25-34 was inversely associated with ER-positive breast cancer only and weight gain from ages 35-44 was not associated with risk. None of these weight gains were associated with ER-negative breast cancer. Weight loss was not consistently associated with overall or ER-specific risk after adjusting for initial weight. Weight increase from early-adulthood to ages 45-54 years is associated with a reduced premenopausal breast cancer risk independently of early-adulthood weight. Biological explanations are needed to account for these two separate factors.
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http://dx.doi.org/10.1002/ijc.32892DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7365745PMC
September 2020

Fine-mapping of 150 breast cancer risk regions identifies 191 likely target genes.

Nat Genet 2020 01 7;52(1):56-73. Epub 2020 Jan 7.

Unit of Medical Genetics, Department of Medical Oncology and Hematology, Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, Milan, Italy.

Genome-wide association studies have identified breast cancer risk variants in over 150 genomic regions, but the mechanisms underlying risk remain largely unknown. These regions were explored by combining association analysis with in silico genomic feature annotations. We defined 205 independent risk-associated signals with the set of credible causal variants in each one. In parallel, we used a Bayesian approach (PAINTOR) that combines genetic association, linkage disequilibrium and enriched genomic features to determine variants with high posterior probabilities of being causal. Potentially causal variants were significantly over-represented in active gene regulatory regions and transcription factor binding sites. We applied our INQUSIT pipeline for prioritizing genes as targets of those potentially causal variants, using gene expression (expression quantitative trait loci), chromatin interaction and functional annotations. Known cancer drivers, transcription factors and genes in the developmental, apoptosis, immune system and DNA integrity checkpoint gene ontology pathways were over-represented among the highest-confidence target genes.
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http://dx.doi.org/10.1038/s41588-019-0537-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6974400PMC
January 2020

Reply to Comment on: "Night shift work and risk of breast cancer in women: the Generations Study cohort".

Br J Cancer 2019 10 5;121(8):723-724. Epub 2019 Sep 5.

Division of Genetics and Epidemiology, The Institute of Cancer Research, London, SW7 3RP, UK.

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http://dx.doi.org/10.1038/s41416-019-0568-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6889433PMC
October 2019

Two truncating variants in FANCC and breast cancer risk.

Sci Rep 2019 08 29;9(1):12524. Epub 2019 Aug 29.

Westmead Institute for Medical Research, University of Sydney, Sydney, New South Wales, Australia.

Fanconi anemia (FA) is a genetically heterogeneous disorder with 22 disease-causing genes reported to date. In some FA genes, monoallelic mutations have been found to be associated with breast cancer risk, while the risk associations of others remain unknown. The gene for FA type C, FANCC, has been proposed as a breast cancer susceptibility gene based on epidemiological and sequencing studies. We used the Oncoarray project to genotype two truncating FANCC variants (p.R185X and p.R548X) in 64,760 breast cancer cases and 49,793 controls of European descent. FANCC mutations were observed in 25 cases (14 with p.R185X, 11 with p.R548X) and 26 controls (18 with p.R185X, 8 with p.R548X). There was no evidence of an association with the risk of breast cancer, neither overall (odds ratio 0.77, 95%CI 0.44-1.33, p = 0.4) nor by histology, hormone receptor status, age or family history. We conclude that the breast cancer risk association of these two FANCC variants, if any, is much smaller than for BRCA1, BRCA2 or PALB2 mutations. If this applies to all truncating variants in FANCC it would suggest there are differences between FA genes in their roles on breast cancer risk and demonstrates the merit of large consortia for clarifying risk associations of rare variants.
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http://dx.doi.org/10.1038/s41598-019-48804-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6715680PMC
August 2019

A combination of the immunohistochemical markers CK7 and SATB2 is highly sensitive and specific for distinguishing primary ovarian mucinous tumors from colorectal and appendiceal metastases.

Mod Pathol 2019 12 25;32(12):1834-1846. Epub 2019 Jun 25.

Department of Obstetrics and Gynecology, Sahlgrenska Cancer Center, Inst Clinical Scienses, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden.

Primary ovarian mucinous tumors can be difficult to distinguish from metastatic gastrointestinal neoplasms by histology alone. The expected immunoprofile of a suspected metastatic lower gastrointestinal tumor is CK7/CK20/CDX2/PAX8. This study assesses the addition of a novel marker SATB2, to improve the diagnostic algorithm. A test cohort included 155 ovarian mucinous tumors (105 carcinomas and 50 borderline tumors) and 230 primary lower gastrointestinal neoplasms (123 colorectal adenocarcinomas and 107 appendiceal neoplasms). All cases were assessed for SATB2, PAX8 CK7, CK20, and CDX2 expression on tissue microarrays. Expression was scored in a 3-tier system as absent, focal (1-50% of tumor cells) and diffuse ( >50% of tumor cells) and then categorized into either absent/present or nondiffuse/diffuse. SATB2 and PAX8 expression was further evaluated in ovarian tumors from an international cohort of 2876 patients (expansion cohort, including 159 mucinous carcinomas and 46 borderline mucinous tumors). The highest accuracy of an individual marker in distinguishing lower gastrointestinal from ovarian mucinous tumors was CK7 (91.7%, nondiffuse/diffuse cut-off) followed by SATB2 (88.8%, present/absent cut-off). The most effective combination was CK7 and SATB2 with accuracy of 95.3% using the 3-tier interpretation, absent/focal/diffuse. This combination outperformed the standard clinical set of CK7, CK20 and CDX2 (87.5%). Re-evaluation of outlier cases confirmed ovarian origin for all but one case. The accuracy of SATB2 was confirmed in the expansion cohort (91.5%). SATB2 expression was also detected in 15% of ovarian endometrioid carcinoma but less than 5% of other ovarian histotypes. A simple two marker combination of CK7 and SATB2 can distinguish lower gastrointestinal from ovarian primary mucinous tumors with greater than 95% accuracy. PAX8 and CDX2 have value as second-line markers. The utility of CK20 in this setting is low and this warrants replacement of this marker with SATB2 in clinical practice.
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http://dx.doi.org/10.1038/s41379-019-0302-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8207534PMC
December 2019

Comparative Validation of Breast Cancer Risk Prediction Models and Projections for Future Risk Stratification.

J Natl Cancer Inst 2020 03;112(3):278-285

Johns Hopkins University, Baltimore, MD.

Background: External validation of risk models is critical for risk-stratified breast cancer prevention. We used the Individualized Coherent Absolute Risk Estimation (iCARE) as a flexible tool for risk model development and comparative model validation and to make projections for population risk stratification.

Methods: Performance of two recently developed models, one based on the Breast and Prostate Cancer Cohort Consortium analysis (iCARE-BPC3) and another based on a literature review (iCARE-Lit), were compared with two established models (Breast Cancer Risk Assessment Tool and International Breast Cancer Intervention Study Model) based on classical risk factors in a UK-based cohort of 64 874 white non-Hispanic women (863 patients) age 35-74 years. Risk projections in a target population of US white non-Hispanic women age 50-70 years assessed potential improvements in risk stratification by adding mammographic breast density (MD) and polygenic risk score (PRS).

Results: The best calibrated models were iCARE-Lit (expected to observed number of cases [E/O] = 0.98, 95% confidence interval [CI] = 0.87 to 1.11) for women younger than 50 years, and iCARE-BPC3 (E/O = 1.00, 95% CI = 0.93 to 1.09) for women 50 years or older. Risk projections using iCARE-BPC3 indicated classical risk factors can identify approximately 500 000 women at moderate to high risk (>3% 5-year risk) in the target population. Addition of MD and a 313-variant PRS is expected to increase this number to approximately 3.5 million women, and among them, approximately 153 000 are expected to develop invasive breast cancer within 5 years.

Conclusions: iCARE models based on classical risk factors perform similarly to or better than BCRAT or IBIS in white non-Hispanic women. Addition of MD and PRS can lead to substantial improvements in risk stratification. However, these integrated models require independent prospective validation before broad clinical applications.
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http://dx.doi.org/10.1093/jnci/djz113DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7073933PMC
March 2020

Night shift work and risk of breast cancer in women: the Generations Study cohort.

Br J Cancer 2019 07 29;121(2):172-179. Epub 2019 May 29.

Division of Genetics and Epidemiology, The Institute of Cancer Research, London, SW7 3RP, UK.

Background: It is plausible that night shift work could affect breast cancer risk, possibly by melatonin suppression or circadian clock disruption, but epidemiological evidence is inconclusive.

Methods: Using serial questionnaires from the Generations Study cohort, we estimated hazard ratios (HR) and 95% confidence intervals (95%CI) for breast cancer in relation to being a night shift worker within the last 10 years, adjusted for potential confounders.

Results: Among 102,869 women recruited in 2003-2014, median follow-up 9.5 years, 2059 developed invasive breast cancer. The HR in relation to night shift work was 1.00 (95%CI: 0.86-1.15). There was a significant trend with average hours of night work per week (P = 0.035), but no significantly raised risks for hours worked per night, nights worked per week, average hours worked per week, cumulative years of employment, cumulative hours, time since cessation, type of occupation, age starting night shift work, or age starting in relation to first pregnancy.

Conclusions: The lack of overall association, and no association with all but one measure of dose, duration, and intensity in our data, does not support an increased risk of breast cancer from night shift work in women.
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http://dx.doi.org/10.1038/s41416-019-0485-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6738051PMC
July 2019

Epigenome-wide association study for lifetime estrogen exposure identifies an epigenetic signature associated with breast cancer risk.

Clin Epigenetics 2019 04 30;11(1):66. Epub 2019 Apr 30.

International Agency for Research on Cancer (IARC), Lyon, France.

Background: It is well established that estrogens and other hormonal factors influence breast cancer susceptibility. We hypothesized that a woman's total lifetime estrogen exposure accumulates changes in DNA methylation, detectable in the blood, which could be used in risk assessment for breast cancer.

Methods: An estimated lifetime estrogen exposure (ELEE) model was defined using epidemiological data from EPIC-Italy (n = 31,864). An epigenome-wide association study (EWAS) of ELEE was performed using existing Illumina HumanMethylation450K Beadchip (HM450K) methylation data obtained from EPIC-Italy blood DNA samples (n = 216). A methylation index (MI) of ELEE based on 31 CpG sites was developed using HM450K data from EPIC-Italy and the Generations Study and evaluated for association with breast cancer risk in an independent dataset from the Generations Study (n = 440 incident breast cancer cases matched to 440 healthy controls) using targeted bisulfite sequencing. Lastly, a meta-analysis was conducted including three additional cohorts, consisting of 1187 case-control pairs.

Results: We observed an estimated 5% increase in breast cancer risk per 1-year longer ELEE (OR = 1.05, 95% CI 1.04-1.07, P = 3 × 10) in EPIC-Italy. The EWAS identified 694 CpG sites associated with ELEE (FDR Q < 0.05). We report a DNA methylation index (MI) associated with breast cancer risk that is validated in the Generations Study targeted bisulfite sequencing data (OR = 1.77, 95% CI 1.07-2.93, P = 0.027) and in the meta-analysis (OR = 1.43, 95% CI 1.05-2.00, P = 0.024); however, the correlation between the MI and ELEE was not validated across study cohorts.

Conclusion: We have identified a blood DNA methylation signature associated with breast cancer risk in this study. Further investigation is required to confirm the interaction between estrogen exposure and DNA methylation in the blood.
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http://dx.doi.org/10.1186/s13148-019-0664-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6492393PMC
April 2019

Breast cancer risk prediction in women aged 35-50 years: impact of including sex hormone concentrations in the Gail model.

Breast Cancer Res 2019 03 19;21(1):42. Epub 2019 Mar 19.

Department of Population Health, New York University School of Medicine, 650 First Avenue, New York, NY, 10016, USA.

Background: Models that accurately predict risk of breast cancer are needed to help younger women make decisions about when to begin screening. Premenopausal concentrations of circulating anti-Müllerian hormone (AMH), a biomarker of ovarian reserve, and testosterone have been positively associated with breast cancer risk in prospective studies. We assessed whether adding AMH and/or testosterone to the Gail model improves its prediction performance for women aged 35-50.

Methods: In a nested case-control study including ten prospective cohorts (1762 invasive cases/1890 matched controls) with pre-diagnostic serum/plasma samples, we estimated relative risks (RR) for the biomarkers and Gail risk factors using conditional logistic regression and random-effects meta-analysis. Absolute risk models were developed using these RR estimates, attributable risk fractions calculated using the distributions of the risk factors in the cases from the consortium, and population-based incidence and mortality rates. The area under the receiver operating characteristic curve (AUC) was used to compare the discriminatory accuracy of the models with and without biomarkers.

Results: The AUC for invasive breast cancer including only the Gail risk factor variables was 55.3 (95% CI 53.4, 57.1). The AUC increased moderately with the addition of AMH (AUC 57.6, 95% CI 55.7, 59.5), testosterone (AUC 56.2, 95% CI 54.4, 58.1), or both (AUC 58.1, 95% CI 56.2, 59.9). The largest AUC improvement (4.0) was among women without a family history of breast cancer.

Conclusions: AMH and testosterone moderately increase the discriminatory accuracy of the Gail model among women aged 35-50. We observed the largest AUC increase for women without a family history of breast cancer, the group that would benefit most from improved risk prediction because early screening is already recommended for women with a family history.
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http://dx.doi.org/10.1186/s13058-019-1126-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6425605PMC
March 2019

Genome-wide association study of germline variants and breast cancer-specific mortality.

Br J Cancer 2019 03 21;120(6):647-657. Epub 2019 Feb 21.

Lund University, Department of Cancer Epidemiology, Clinical Sciences, Lund, Sweden.

Background: We examined the associations between germline variants and breast cancer mortality using a large meta-analysis of women of European ancestry.

Methods: Meta-analyses included summary estimates based on Cox models of twelve datasets using ~10.4 million variants for 96,661 women with breast cancer and 7697 events (breast cancer-specific deaths). Oestrogen receptor (ER)-specific analyses were based on 64,171 ER-positive (4116) and 16,172 ER-negative (2125) patients. We evaluated the probability of a signal to be a true positive using the Bayesian false discovery probability (BFDP).

Results: We did not find any variant associated with breast cancer-specific mortality at P < 5 × 10. For ER-positive disease, the most significantly associated variant was chr7:rs4717568 (BFDP = 7%, P = 1.28 × 10, hazard ratio [HR] = 0.88, 95% confidence interval [CI] = 0.84-0.92); the closest gene is AUTS2. For ER-negative disease, the most significant variant was chr7:rs67918676 (BFDP = 11%, P = 1.38 × 10, HR = 1.27, 95% CI = 1.16-1.39); located within a long intergenic non-coding RNA gene (AC004009.3), close to the HOXA gene cluster.

Conclusions: We uncovered germline variants on chromosome 7 at BFDP < 15% close to genes for which there is biological evidence related to breast cancer outcome. However, the paucity of variants associated with mortality at genome-wide significance underpins the challenge in providing genetic-based individualised prognostic information for breast cancer patients.
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http://dx.doi.org/10.1038/s41416-019-0393-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6461853PMC
March 2019

Transcriptome-Wide Association Study Identifies New Candidate Susceptibility Genes for Glioma.

Cancer Res 2019 04 1;79(8):2065-2071. Epub 2019 Feb 1.

Division of Genetics and Epidemiology, The Institute of Cancer Research, London, United Kingdom.

Genome-wide association studies (GWAS) have so far identified 25 loci associated with glioma risk, with most showing specificity for either glioblastoma (GBM) or non-GBM tumors. The majority of these GWAS susceptibility variants reside in noncoding regions and the causal genes underlying the associations are largely unknown. Here we performed a transcriptome-wide association study to search for novel risk loci and candidate causal genes at known GWAS loci using Genotype-Tissue Expression Project (GTEx) data to predict -predicted gene expression in relation to GBM and non-GBM risk in conjunction with GWAS summary statistics on 12,488 glioma cases (6,183 GBM and 5,820 non-GBM) and 18,169 controls. Imposing a Bonferroni-corrected significance level of < 5.69 × 10, we identified 31 genes, including at 12q13.33, as a candidate novel risk locus for GBM (mean = 4.43; = 5.68 × 10). resides at least 55 Mb away from any previously identified glioma risk variant, while all other 30 significantly associated genes were located within 1 Mb of known GWAS-identified loci and were not significant after conditioning on the known GWAS-identified variants. These data identify a novel locus ( at 12q13.33) and 30 genes at 12 known glioma risk loci associated with glioma risk, providing further insights into glioma tumorigenesis. SIGNIFICANCE: This study identifies new genes associated with glioma risk, increasing understanding of how these tumors develop.
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http://dx.doi.org/10.1158/0008-5472.CAN-18-2888DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6522343PMC
April 2019

Genome-wide association study of anti-Müllerian hormone levels in pre-menopausal women of late reproductive age and relationship with genetic determinants of reproductive lifespan.

Hum Mol Genet 2019 04;28(8):1392-1401

Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, UK.

Anti-Müllerian hormone (AMH) is required for sexual differentiation in the fetus, and in adult females AMH is produced by growing ovarian follicles. Consequently, AMH levels are correlated with ovarian reserve, declining towards menopause when the oocyte pool is exhausted. A previous genome-wide association study identified three genetic variants in and around the AMH gene that explained 25% of variation in AMH levels in adolescent males but did not identify any genetic associations reaching genome-wide significance in adolescent females. To explore the role of genetic variation in determining AMH levels in women of late reproductive age, we carried out a genome-wide meta-analysis in 3344 pre-menopausal women from five cohorts (median age 44-48 years at blood draw). A single genetic variant, rs16991615, previously associated with age at menopause, reached genome-wide significance at P = 3.48 × 10-10, with a per allele difference in age-adjusted inverse normal AMH of 0.26 standard deviations (SD) (95% confidence interval (CI) [0.18,0.34]). We investigated whether genetic determinants of female reproductive lifespan were more generally associated with pre-menopausal AMH levels. Genetically-predicted age at menarche had no robust association but genetically-predicted age at menopause was associated with lower AMH levels by 0.18 SD (95% CI [0.14,0.21]) in age-adjusted inverse normal AMH per one-year earlier age at menopause. Our findings provide genetic support for the well-established use of AMH as a marker of ovarian reserve.
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http://dx.doi.org/10.1093/hmg/ddz015DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6452199PMC
April 2019

Brain and Salivary Gland Tumors and Mobile Phone Use: Evaluating the Evidence from Various Epidemiological Study Designs.

Annu Rev Public Health 2019 04 11;40:221-238. Epub 2019 Jan 11.

Institute of Environmental Medicine, Karolinska Institutet, 171 77 Stockholm, Sweden.

Mobile phones (MPs) are the most relevant source of radiofrequency electromagnetic field (RF-EMF) exposure to the brain and the salivary gland. Whether this exposure implies a cancer risk has been addressed in several case-control and few cohort studies. A meta-analysis of these studies does not show increased risks for meningioma, pituitary, and salivary gland tumors. For glioma and acoustic neuroma, the results are heterogeneous, with few case-control studies reporting substantially increased risks. However, these elevated risks are not coherent with observed incidence time trends, which are considered informative for this specific topic owing to the steep increase in MP use, the availability of virtually complete cancer registry data from many countries, and the limited number of known competing environmental risk factors. In conclusion, epidemiological studies do not suggest increased brain or salivary gland tumor risk with MP use, although some uncertainty remains regarding long latency periods (>15 years), rare brain tumor subtypes, and MP usage during childhood.
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http://dx.doi.org/10.1146/annurev-publhealth-040218-044037DOI Listing
April 2019

Exposure to loud noise and risk of vestibular schwannoma: results from the INTERPHONE international case‒control study.

Scand J Work Environ Health 2019 03 5;45(2):183-193. Epub 2018 Nov 5.

International Agency for Research on Cancer (IARC), Lyon, France.

Objective Studies of loud noise exposure and vestibular schwannomas (VS) have shown conflicting results. The population-based INTERPHONE case‒control study was conducted in 13 countries during 2000-2004. In this paper, we report the results of analyses on the association between VS and self-reported loud noise exposure. Methods Self-reported noise exposure was analyzed in 1024 VS cases and 1984 matched controls. Life-long noise exposure was estimated through detailed questions. Odds ratios (OR) and 95% confidence intervals (CI) were estimated using adjusted conditional logistic regression for matched sets. Results The OR for total work and leisure noise exposure was 1.6 (95% CI 1.4-1.9). OR were 1.5 (95% CI 1.3-1.9) for only occupational noise, 1.9 (95% CI 1.4-2.6) for only leisure noise and 1.7 (95% CI 1.2-2.2) for exposure in both contexts. OR increased slightly with increasing lag-time. For occupational exposures, duration, time since exposure start and a metric combining lifetime duration and weekly exposure showed significant trends of increasing risk with increasing exposure. OR did not differ markedly by source or other characteristics of noise. Conclusion The consistent associations seen are likely to reflect either recall bias or a causal association, or potentially indicate a mixture of both.
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http://dx.doi.org/10.5271/sjweh.3781DOI Listing
March 2019
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