SwePub
Sök i SwePub databas

  form:Ext_t

Träfflista för sökning "WFRF:(Tamimi Rulla M) "

form:Search_simp_t: WFRF:(Tamimi Rulla M)

  • navigation:Result_t 1-10 navigation:of_t 35
hitlist:Modify_result_t
   
hitlist:Enumeration_thitlist:Reference_thitlist:Reference_picture_thitlist:Find_Mark_t
1.
  • Couch, Fergus J., et al. (creator_code:aut_t)
  • Identification of four novel susceptibility loci for oestrogen receptor negative breast cancer
  • 2016
  • record:In_t: Nature Communications. - : NATURE PUBLISHING GROUP. - 2041-1723. ; 7:11375, s. 1-13
  • swepub:Mat_article_t (swepub:level_refereed_t)abstract
    • Common variants in 94 loci have been associated with breast cancer including 15 loci with genome-wide significant associations (P<5 x 10(-8)) with oestrogen receptor (ER)-negative breast cancer and BRCA1-associated breast cancer risk. In this study, to identify new ER-negative susceptibility loci, we performed a meta-analysis of 11 genome-wide association studies (GWAS) consisting of 4,939 ER-negative cases and 14,352 controls, combined with 7,333 ER-negative cases and 42,468 controls and 15,252 BRCA1 mutation carriers genotyped on the iCOGS array. We identify four previously unidentified loci including two loci at 13q22 near KLF5, a 2p23.2 locus near WDR43 and a 2q33 locus near PPIL3 that display genome-wide significant associations with ER-negative breast cancer. In addition, 19 known breast cancer risk loci have genome-wide significant associations and 40 had moderate associations (P<0.05) with ER-negative disease. Using functional and eQTL studies we implicate TRMT61B and WDR43 at 2p23.2 and PPIL3 at 2q33 in ER-negative breast cancer aetiology. All ER-negative loci combined account for similar to 11% of familial relative risk for ER-negative disease and may contribute to improved ER-negative and BRCA1 breast cancer risk prediction.
  •  
2.
  • Shu, Xiang, et al. (creator_code:aut_t)
  • Associations of obesity and circulating insulin and glucose with breast cancer risk : a Mendelian randomization analysis
  • 2019
  • record:In_t: International Journal of Epidemiology. - : OXFORD UNIV PRESS. - 0300-5771 .- 1464-3685. ; 48:3, s. 795-806
  • swepub:Mat_article_t (swepub:level_refereed_t)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.
  •  
3.
  • Ahearn, Thomas U., et al. (creator_code:aut_t)
  • Common variants in breast cancer risk loci predispose to distinct tumor subtypes
  • 2022
  • record:In_t: Breast Cancer Research. - : Springer Nature. - 1465-5411 .- 1465-542X. ; 24:1
  • swepub:Mat_article_t (swepub:level_refereed_t)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.
  •  
4.
  • Mavaddat, Nasim, et al. (creator_code:aut_t)
  • Prediction of Breast Cancer Risk Based on Profiling With Common Genetic Variants
  • 2015
  • record:In_t: Journal of the National Cancer Institute. - : Oxford University Press (OUP). - 1460-2105 .- 0027-8874. ; 107:5, s. 036-036
  • swepub:Mat_article_t (swepub:level_refereed_t)abstract
    • Background: Data for multiple common susceptibility alleles for breast cancer may be combined to identify women at different levels of breast cancer risk. Such stratification could guide preventive and screening strategies. However, empirical evidence for genetic risk stratification is lacking. Methods: We investigated the value of using 77 breast cancer-associated single nucleotide polymorphisms (SNPs) for risk stratification, in a study of 33 673 breast cancer cases and 33 381 control women of European origin. We tested all possible pair-wise multiplicative interactions and constructed a 77-SNP polygenic risk score (PRS) for breast cancer overall and by estrogen receptor (ER) status. Absolute risks of breast cancer by PRS were derived from relative risk estimates and UK incidence and mortality rates. Results: There was no strong evidence for departure from a multiplicative model for any SNP pair. Women in the highest 1% of the PRS had a three-fold increased risk of developing breast cancer compared with women in the middle quintile (odds ratio [OR] = 3.36, 95% confidence interval [CI] = 2.95 to 3.83). The ORs for ER-positive and ER-negative disease were 3.73 (95% CI = 3.24 to 4.30) and 2.80 (95% CI = 2.26 to 3.46), respectively. Lifetime risk of breast cancer for women in the lowest and highest quintiles of the PRS were 5.2% and 16.6% for a woman without family history, and 8.6% and 24.4% for a woman with a first-degree family history of breast cancer. Conclusions: The PRS stratifies breast cancer risk in women both with and without a family history of breast cancer. The observed level of risk discrimination could inform targeted screening and prevention strategies. Further discrimination may be achievable through combining the PRS with lifestyle/environmental factors, although these were not considered in this report.
  •  
5.
  • Dixon-Suen, Suzanne C, et al. (creator_code:aut_t)
  • Physical activity, sedentary time and breast cancer risk : a Mendelian randomisation study
  • 2022
  • record:In_t: British Journal of Sports Medicine. - : BMJ Publishing Group Ltd. - 0306-3674 .- 1473-0480. ; 56:20, s. 1157-1170
  • swepub:Mat_article_t (swepub:level_refereed_t)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.
  •  
6.
  • Escala-Garcia, Maria, et al. (creator_code:aut_t)
  • A network analysis to identify mediators of germline-driven differences in breast cancer prognosis
  • 2020
  • record:In_t: Nature Communications. - : NATURE PUBLISHING GROUP. - 2041-1723. ; 11:1
  • swepub:Mat_article_t (swepub:level_refereed_t)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.
  •  
7.
  • Kapoor, Pooja Middha, et al. (creator_code:aut_t)
  • Combined associations of a polygenic risk score and classical risk factors with breast cancer risk
  • 2021
  • record:In_t: Journal of the National Cancer Institute. - : Oxford University Press (OUP). - 0027-8874 .- 1460-2105. ; 113:3, s. 329-337
  • swepub:Mat_article_t (swepub:level_refereed_t)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. 
  •  
8.
  • Mueller, Stefanie H., et al. (creator_code:aut_t)
  • Aggregation tests identify new gene associations with breast cancer in populations with diverse ancestry
  • 2023
  • record:In_t: Genome Medicine. - : BioMed Central (BMC). - 1756-994X .- 1756-994X. ; 15
  • swepub:Mat_article_t (swepub:level_refereed_t)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.
  •  
9.
  •  
10.
  • Middha, Pooja K., et al. (creator_code:aut_t)
  • A genome-wide gene-environment interaction study of breast cancer risk for women of European ancestry
  • 2023
  • record:In_t: Breast Cancer Research. - : BioMed Central (BMC). - 1465-5411 .- 1465-542X. ; 25:1
  • swepub:Mat_article_t (swepub:level_refereed_t)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.
  •  
Skapa referenser, mejla, bekava och länka
  • navigation:Result_t 1-10 navigation:of_t 35
swepub:Mat_t
swepub:mat_article_t (34)
swepub:mat_researchreview_t (1)
swepub:Level_t
swepub:level_refereed_t (34)
swepub:level_scientificother_t (1)
swepub:Hitlist_author_t
Tamimi, Rulla M. (29)
Milne, Roger L. (21)
Giles, Graham G (20)
Kaaks, Rudolf (18)
Kraft, Peter (17)
Wolk, Alicja (16)
deldatabas:search_more_t
Chang-Claude, Jenny (15)
Haiman, Christopher ... (15)
Czene, Kamila (15)
Zheng, Wei (15)
Hall, Per (14)
Hamann, Ute (14)
Kitahara, Cari M. (14)
Easton, Douglas F. (14)
Brenner, Hermann (13)
Bolla, Manjeet K. (13)
Dunning, Alison M. (13)
Andrulis, Irene L. (13)
Guenel, Pascal (13)
Sandler, Dale P. (13)
Wang, Qin (12)
Chanock, Stephen J (12)
Canzian, Federico (12)
Bojesen, Stig E. (12)
Hopper, John L. (12)
Southey, Melissa C. (12)
Swerdlow, Anthony J. (12)
Couch, Fergus J. (12)
Pharoah, Paul D. P. (12)
John, Esther M (11)
Arndt, Volker (11)
Michailidou, Kyriaki (11)
Dennis, Joe (11)
Anton-Culver, Hoda (11)
Fasching, Peter A. (11)
Jones, Michael E. (11)
Lambrechts, Diether (11)
Mannermaa, Arto (11)
Nevanlinna, Heli (10)
Gago Dominguez, Manu ... (10)
Rennert, Gad (10)
Aronson, Kristan J. (10)
Benitez, Javier (10)
Cox, Angela (10)
Cross, Simon S. (10)
Howell, Anthony (10)
Margolin, Sara (10)
Troester, Melissa A. (10)
Weinberg, Clarice R. (10)
Simard, Jacques (10)
deldatabas:search_less_t
swepub:Hitlist_uni_t
swepub_uni:ki_t (18)
swepub_uni:uu_t (17)
swepub_uni:lu_t (10)
swepub_uni:umu_t (9)
swepub_uni:oru_t (7)
swepub_uni:gu_t (2)
deldatabas:search_more_t
swepub_uni:liu_t (1)
deldatabas:search_less_t
hitlist:Language_t
language:Eng_t (35)
hitlist:HSV_t
hsv:Cat_3_t (34)

hitlist:Year_t

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt tools:Close_t

tools:Permalink_label_t