| 1. |
- Ahearn, Thomas U., et al.
(author)
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Common variants in breast cancer risk loci predispose to distinct tumor subtypes
- 2022
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In: Breast Cancer Research. - : Springer Nature. - 1465-5411 .- 1465-542X. ; 24:1
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Journal article (peer-reviewed)abstract
- BackgroundGenome-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.MethodsAmong 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.ResultsEighty-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.ConclusionThis 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.
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| 2. |
- Bowes, John, et al.
(author)
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PTPN22 is associated with susceptibility to psoriatic arthritis but not psoriasis : evidence for a further PsA-specific risk locus
- 2015
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In: Annals of the Rheumatic Diseases. - : BMJ. - 0003-4967 .- 1468-2060. ; 74:10, s. 1882-1885
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Journal article (peer-reviewed)abstract
- Objectives Psoriatic arthritis (PsA) is a chronic inflammatory arthritis associated with psoriasis; it has a higher estimated genetic component than psoriasis alone, however most genetic susceptibility loci identified for PsA to date are also shared with psoriasis. Here we attempt to validate novel single nucleotide polymorphisms selected from our recent PsA Immunochip study and determine specificity to PsA. Methods A total of 15 single nucleotide polymorphisms were selected (P-Immunochip <1x10(-4)) for validation genotyping in 1177 cases and 2155 controls using TaqMan. Meta-analysis of Immunochip and validation data sets consisted of 3139 PsA cases and 11 078 controls. Novel PsA susceptibility loci were compared with data from two large psoriasis studies (WTCCC2 and Immunochip) to determine PsA specificity. Results We found genome-wide significant association to rs2476601, mapping to PTPN22 (p=1.49x10(-9), OR=1.32), but no evidence for association in the psoriasis cohort (p=0.34) and the effect estimates were significantly different between PsA and psoriasis (p=3.2x10(-4)). Additionally, we found genome-wide significant association to the previously reported psoriasis risk loci; NOS2 (rs4795067, p=5.27x10(-9)). Conclusions For the first time, we report genome-wide significant association of PTPN22 (rs2476601) to PsA susceptibility, but no evidence for association to psoriasis.
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| 3. |
- Dixon-Suen, Suzanne C, et al.
(author)
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Physical activity, sedentary time and breast cancer risk : a Mendelian randomisation study
- 2022
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In: British Journal of Sports Medicine. - : BMJ Publishing Group Ltd. - 0306-3674 .- 1473-0480. ; 56:20, s. 1157-1170
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Journal article (peer-reviewed)abstract
- OBJECTIVES: Physical inactivity and sedentary behaviour are associated with higher breast cancer risk in observational studies, but ascribing causality is difficult. Mendelian randomisation (MR) assesses causality by simulating randomised trial groups using genotype. We assessed whether lifelong physical activity or sedentary time, assessed using genotype, may be causally associated with breast cancer risk overall, pre/post-menopause, and by case-groups defined by tumour characteristics.METHODS: We performed two-sample inverse-variance-weighted MR using individual-level Breast Cancer Association Consortium case-control data from 130 957 European-ancestry women (69 838 invasive cases), and published UK Biobank data (n=91 105-377 234). Genetic instruments were single nucleotide polymorphisms (SNPs) associated in UK Biobank with wrist-worn accelerometer-measured overall physical activity (nsnps=5) or sedentary time (nsnps=6), or accelerometer-measured (nsnps=1) or self-reported (nsnps=5) vigorous physical activity.RESULTS: Greater genetically-predicted overall activity was associated with lower breast cancer overall risk (OR=0.59; 95% confidence interval (CI) 0.42 to 0.83 per-standard deviation (SD;~8 milligravities acceleration)) and for most case-groups. Genetically-predicted vigorous activity was associated with lower risk of pre/perimenopausal breast cancer (OR=0.62; 95% CI 0.45 to 0.87,≥3 vs. 0 self-reported days/week), with consistent estimates for most case-groups. Greater genetically-predicted sedentary time was associated with higher hormone-receptor-negative tumour risk (OR=1.77; 95% CI 1.07 to 2.92 per-SD (~7% time spent sedentary)), with elevated estimates for most case-groups. Results were robust to sensitivity analyses examining pleiotropy (including weighted-median-MR, MR-Egger).CONCLUSION: Our study provides strong evidence that greater overall physical activity, greater vigorous activity, and lower sedentary time are likely to reduce breast cancer risk. More widespread adoption of active lifestyles may reduce the burden from the most common cancer in women.
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| 4. |
- Escala-Garcia, Maria, et al.
(author)
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A network analysis to identify mediators of germline-driven differences in breast cancer prognosis
- 2020
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In: Nature Communications. - : NATURE PUBLISHING GROUP. - 2041-1723. ; 11:1
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Journal article (peer-reviewed)abstract
- Identifying the underlying genetic drivers of the heritability of breast cancer prognosis remains elusive. We adapt a network-based approach to handle underpowered complex datasets to provide new insights into the potential function of germline variants in breast cancer prognosis. This network-based analysis studies similar to 7.3 million variants in 84,457 breast cancer patients in relation to breast cancer survival and confirms the results on 12,381 independent patients. Aggregating the prognostic effects of genetic variants across multiple genes, we identify four gene modules associated with survival in estrogen receptor (ER)-negative and one in ER-positive disease. The modules show biological enrichment for cancer-related processes such as G-alpha signaling, circadian clock, angiogenesis, and Rho-GTPases in apoptosis.
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| 5. |
- Gurke, Robert, et al.
(author)
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Omics and Multi-Omics Analysis for the Early Identification and Improved Outcome of Patients with Psoriatic Arthritis
- 2022
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In: Biomedicines. - : MDPI AG. - 2227-9059. ; 10:10
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Research review (peer-reviewed)abstract
- The definitive diagnosis and early treatment of many immune-mediated inflammatory diseases (IMIDs) is hindered by variable and overlapping clinical manifestations. Psoriatic arthritis (PsA), which develops in similar to 30% of people with psoriasis, is a key example. This mixed-pattern IMID is apparent in entheseal and synovial musculoskeletal structures, but a definitive diagnosis often can only be made by clinical experts or when an extensive progressive disease state is apparent. As with other IMIDs, the detection of multimodal molecular biomarkers offers some hope for the early diagnosis of PsA and the initiation of effective management and treatment strategies. However, specific biomarkers are not yet available for PsA. The assessment of new markers by genomic and epigenomic profiling, or the analysis of blood and synovial fluid/tissue samples using proteomics, metabolomics and lipidomics, provides hope that complex molecular biomarker profiles could be developed to diagnose PsA. Importantly, the integration of these markers with high-throughput histology, imaging and standardized clinical assessment data provides an important opportunity to develop molecular profiles that could improve the diagnosis of PsA, predict its occurrence in cohorts of individuals with psoriasis, differentiate PsA from other IMIDs, and improve therapeutic responses. In this review, we consider the technologies that are currently deployed in the EU IMI2 project HIPPOCRATES to define biomarker profiles specific for PsA and discuss the advantages of combining multi-omics data to improve the outcome of PsA patients.
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| 6. |
- Jung, Audrey Y, et al.
(author)
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Distinct reproductive risk profiles for intrinsic-like breast cancer subtypes : pooled analysis of population-based studies
- 2022
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In: Journal of the National Cancer Institute. - : Oxford University Press. - 0027-8874 .- 1460-2105. ; 114:12, s. 1706-1719
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Journal article (peer-reviewed)abstract
- BACKGROUND: Reproductive factors have been shown to be differentially associated with risk of estrogen receptor (ER) positive and ER-negative breast cancer. However, their associations with intrinsic-like subtypes are less clear.METHODS: Analyses included up to 23,353 cases, and 71,072 controls pooled from 31 population-based case-control or cohort studies in the Breast Cancer Association Consortium across 16 countries on 4 continents. Polytomous logistic regression was used to estimate the association between reproductive factors and risk of breast cancer by intrinsic-like subtypes (luminal A-like, luminal B-like, luminal B-HER2-like, HER2-enriched-like, and triple-negative) and by invasiveness. All statistical tests were 2-sided.RESULTS: Compared to nulliparous women, parous women had a lower risk of luminal A-like, luminal B-like, luminal B-HER2-like and HER2-enriched-like disease. This association was apparent only after approximately 10 years since last birth and became stronger with increasing time (odds ratio [OR] = 0.59, 95% confidence interval [CI] = 0.49 to 0.71; and OR = 0.36, 95% CI = 0.28 to 0.46; for multiparous women with luminal A-like tumors 20-<25 years after last birth and 45-<50 years after last birth, respectively). In contrast, parous women had a higher risk of triple-negative breast cancer right after their last birth (for multiparous women: OR = 3.12, 95%CI = 2.02 to 4.83) that was attenuated with time but persisted for decades (OR = 1.03, 95%CI = 0.79 to 1.34, for multiparous women 25 to < 30 years after last birth). Older age at first birth (P-heterogeneity<.001 for triple-negative compared to luminal-A like) and breastfeeding (P-heterogeneity<.001 for triple-negative compared to luminal-A like) were associated with lower risk of triple-negative but not with other disease subtypes. Younger age at menarche was associated with higher risk of all subtypes; older age at menopause was associated with higher risk of luminal A-like but not triple-negative breast cancer. Associations for in situ tumors were similar to luminal A-like.CONCLUSION: This large and comprehensive study demonstrates a distinct reproductive risk factor profile for triple-negative breast cancer compared to other subtypes, with implications for the understanding of disease etiology and risk prediction.
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| 7. |
- Kapoor, Pooja Middha, et al.
(author)
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Assessment of interactions between 205 breast cancer susceptibility loci and 13 established risk factors in relation to breast cancer risk, in the Breast Cancer Association Consortium
- 2020
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In: International Journal of Epidemiology. - : Oxford University Press (OUP). - 0300-5771 .- 1464-3685. ; 49:1, s. 216-232
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Journal article (peer-reviewed)abstract
- Background: Previous gene-environment interaction studies of breast cancer risk have provided sparse evidence of interactions. Using the largest available dataset to date, we performed a comprehensive assessment of potential effect modification of 205 common susceptibility variants by 13 established breast cancer risk factors, including replication of previously reported interactions. Methods: Analyses were performed using 28 176 cases and 32 209 controls genotyped with iCOGS array and 44 109 cases and 48 145 controls genotyped using OncoArray from the Breast Cancer Association Consortium (BCAC). Gene-environment interactions were assessed using unconditional logistic regression and likelihood ratio tests for breast cancer risk overall and by estrogen-receptor (ER) status. Bayesian false discovery probability was used to assess the noteworthiness of the meta-analysed array-specific interactions. Results: Noteworthy evidence of interaction at ≤1% prior probability was observed for three single nucleotide polymorphism (SNP)-risk factor pairs. SNP rs4442975 was associated with a greater reduction of risk of ER-positive breast cancer [odds ratio (OR)int = 0.85 (0.78-0.93), Pint = 2.8 x 10-4] and overall breast cancer [ORint = 0.85 (0.78-0.92), Pint = 7.4 x 10-5) in current users of estrogen-progesterone therapy compared with non-users. This finding was supported by replication using OncoArray data of the previously reported interaction between rs13387042 (r2 = 0.93 with rs4442975) and current estrogen-progesterone therapy for overall disease (Pint = 0.004). The two other interactions suggested stronger associations between SNP rs6596100 and ER-negative breast cancer with increasing parity and younger age at first birth. Conclusions: Overall, our study does not suggest strong effect modification of common breast cancer susceptibility variants by established risk factors.
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| 8. |
- Kapoor, Pooja Middha, et al.
(author)
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Combined associations of a polygenic risk score and classical risk factors with breast cancer risk
- 2021
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In: Journal of the National Cancer Institute. - : Oxford University Press (OUP). - 0027-8874 .- 1460-2105. ; 113:3, s. 329-337
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Journal article (peer-reviewed)abstract
- 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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| 9. |
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| 10. |
- Martin, S., et al.
(author)
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ALCHEMI, an ALMA Comprehensive High-resolution Extragalactic Molecular Inventory: Survey presentation and first results from the ACA array
- 2021
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In: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 656
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Journal article (peer-reviewed)abstract
- Context. The interstellar medium is the locus of physical processes affecting the evolution of galaxies which drive or are the result of star formation activity, supermassive black hole growth, and feedback. The resulting physical conditions determine the observable chemical abundances that can be explored through molecular emission observations at millimeter and submillimeter wavelengths. Aims. Our goal is to unveiling the molecular richness of the central region of the prototypical nearby starburst galaxy NGC 253 at an unprecedented combination of sensitivity, spatial resolution, and frequency coverage. Methods. We used the Atacama Large Millimeter/submillimeter Array (ALMA), covering a nearly contiguous 289 GHz frequency range between 84.2 and 373.2 GHz, to image the continuum and spectral line emission at 1.6″(∼28 pc) resolution down to a sensitivity of 30 - 50 mK. This article describes the ALMA Comprehensive High-resolution Extragalactic Molecular Inventory (ALCHEMI) large program. We focus on the analysis of the spectra extracted from the 15″ (∼255 pc) resolution ALMA Compact Array data. Results. We modeled the molecular emission assuming local thermodynamic equilibrium with 78 species being detected. Additionally, multiple hydrogen and helium recombination lines are identified. Spectral lines contribute 5 to 36% of the total emission in frequency bins of 50 GHz. We report the first extragalactic detections of C2H5OH, HOCN, HC3HO, and several rare isotopologues. Isotopic ratios of carbon, oxygen, sulfur, nitrogen, and silicon were measured with multiple species. Concluison. Infrared pumped vibrationaly excited HCN, HNC, and HC3N emission, originating in massive star formation locations, is clearly detected at low resolution, while we do not detect it for HCO+. We suggest high temperature conditions in these regions driving a seemingly "carbon-rich"chemistry which may also explain the observed high abundance of organic species close to those in Galactic hot cores. The Lvib/LIR ratio was used as a proxy to estimate a 3% contribution from the proto super star cluster to the global infrared emission. Measured isotopic ratios with high dipole moment species agree with those within the central kiloparsec of the Galaxy, while those derived from 13C/18O are a factor of five larger, confirming the existence of multiple interstellar medium components within NGC 253 with different degrees of nucleosynthesis enrichment. The ALCHEMI data set provides a unique template for studies of star-forming galaxies in the early Universe.
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| 11. |
- Middha, Pooja K., et al.
(author)
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A genome-wide gene-environment interaction study of breast cancer risk for women of European ancestry
- 2023
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In: Breast Cancer Research. - : BioMed Central (BMC). - 1465-5411 .- 1465-542X. ; 25:1
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Journal article (peer-reviewed)abstract
- Background Genome-wide studies of gene-environment interactions (GxE) may identify variants associated with disease risk in conjunction with lifestyle/environmental exposures. We conducted a genome-wide GxE analysis of similar to 7.6 million common variants and seven lifestyle/environmental risk factors for breast cancer risk overall and for estrogen receptor positive (ER +) breast cancer. Methods Analyses were conducted using 72,285 breast cancer cases and 80,354 controls of European ancestry from the Breast Cancer Association Consortium. Gene-environment interactions were evaluated using standard unconditional logistic regression models and likelihood ratio tests for breast cancer risk overall and for ER + breast cancer. Bayesian False Discovery Probability was employed to assess the noteworthiness of each SNP-risk factor pairs. Results Assuming a 1 x 10(-5) prior probability of a true association for each SNP-risk factor pairs and a Bayesian False Discovery Probability < 15%, we identified two independent SNP-risk factor pairs: rs80018847(9p13)-LINGO2 and adult height in association with overall breast cancer risk (ORint = 0.94, 95% CI 0.92-0.96), and rs4770552(13q12)-SPATA13 and age at menarche for ER + breast cancer risk (ORint = 0.91, 95% CI 0.88-0.94). Conclusions Overall, the contribution of GxE interactions to the heritability of breast cancer is very small. At the population level, multiplicative GxE interactions do not make an important contribution to risk prediction in breast cancer.
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| 12. |
- Mueller, Stefanie H., et al.
(author)
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Aggregation tests identify new gene associations with breast cancer in populations with diverse ancestry
- 2023
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In: Genome Medicine. - : BioMed Central (BMC). - 1756-994X. ; 15
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Journal article (peer-reviewed)abstract
- Background: Low-frequency variants play an important role in breast cancer (BC) susceptibility. Gene-based methods can increase power by combining multiple variants in the same gene and help identify target genes.Methods: We evaluated the potential of gene-based aggregation in the Breast Cancer Association Consortium cohorts including 83,471 cases and 59,199 controls. Low-frequency variants were aggregated for individual genes' coding and regulatory regions. Association results in European ancestry samples were compared to single-marker association results in the same cohort. Gene-based associations were also combined in meta-analysis across individuals with European, Asian, African, and Latin American and Hispanic ancestry.Results: In European ancestry samples, 14 genes were significantly associated (q < 0.05) with BC. Of those, two genes, FMNL3 (P = 6.11 x 10(-6)) and AC058822.1 (P = 1.47 x 10(-4)), represent new associations. High FMNL3 expression has previously been linked to poor prognosis in several other cancers. Meta-analysis of samples with diverse ancestry discovered further associations including established candidate genes ESR1 and CBLB. Furthermore, literature review and database query found further support for a biologically plausible link with cancer for genes CBLB, FMNL3, FGFR2, LSP1, MAP3K1, and SRGAP2C.Conclusions: Using extended gene-based aggregation tests including coding and regulatory variation, we report identification of plausible target genes for previously identified single-marker associations with BC as well as the discovery of novel genes implicated in BC development. Including multi ancestral cohorts in this study enabled the identification of otherwise missed disease associations as ESR1 (P = 1.31 x 10(-5)), demonstrating the importance of diversifying study cohorts.
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| 13. |
- Shu, Xiang, et al.
(author)
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Associations of obesity and circulating insulin and glucose with breast cancer risk : a Mendelian randomization analysis
- 2019
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In: International Journal of Epidemiology. - : OXFORD UNIV PRESS. - 0300-5771 .- 1464-3685. ; 48:3, s. 795-806
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Journal article (peer-reviewed)abstract
- Background: In addition to the established association between general obesity and breast cancer risk, central obesity and circulating fasting insulin and glucose have been linked to the development of this common malignancy. Findings from previous studies, however, have been inconsistent, and the nature of the associations is unclear. Methods: We conducted Mendelian randomization analyses to evaluate the association of breast cancer risk, using genetic instruments, with fasting insulin, fasting glucose, 2-h glucose, body mass index (BMI) and BMI-adjusted waist-hip-ratio (WHRadj BMI). We first confirmed the association of these instruments with type 2 diabetes risk in a large diabetes genome-wide association study consortium. We then investigated their associations with breast cancer risk using individual-level data obtained from 98 842 cases and 83 464 controls of European descent in the Breast Cancer Association Consortium. Results: All sets of instruments were associated with risk of type 2 diabetes. Associations with breast cancer risk were found for genetically predicted fasting insulin [odds ratio (OR) = 1.71 per standard deviation (SD) increase, 95% confidence interval (CI) = 1.26-2.31, p = 5.09 x 10(-4)], 2-h glucose (OR = 1.80 per SD increase, 95% CI = 1.3 0-2.49, p = 4.02 x 10(-4)), BMI (OR = 0.70 per 5-unit increase, 95% CI = 0.65-0.76, p = 5.05 x 10(-19)) and WHRadj BMI (OR = 0.85, 95% CI = 0.79-0.91, p = 9.22 x 10(-6)). Stratified analyses showed that genetically predicted fasting insulin was more closely related to risk of estrogen-receptor [ER]-positive cancer, whereas the associations with instruments of 2h glucose, BMI and WHRadj BMI were consistent regardless of age, menopausal status, estrogen receptor status and family history of breast cancer. Conclusions: We confirmed the previously reported inverse association of genetically predicted BMI with breast cancer risk, and showed a positive association of genetically predicted fasting insulin and 2-h glucose and an inverse association of WHRadj BMI with breast cancer risk. Our study suggests that genetically determined obesity and glucose/insulin-related traits have an important role in the aetiology of breast cancer.
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