ORCID Profile
0000-0002-5640-9126
Current Organisations
Karolinska Institutet
,
Södersjukhuset
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Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/0008-5472.22425330.V1
Abstract: Univariate ACE estimates among women who did not develop breast cancer during follow-up
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/0008-5472.22425339
Abstract: Model fitting from univariate analyses after re-randomisation of siblings
Publisher: Oxford University Press (OUP)
Date: 20-06-2022
DOI: 10.1093/JNCI/DJAC117
Abstract: 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. 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 breast cancer) and by invasiveness. All statistical tests were 2-sided. Compared with 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 to less than 25 years after last birth and 45 to less than 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 less than 30 years after last birth). Older age at first birth (Pheterogeneity & .001 for triple-negative compared with luminal A-like breast cancer) and breastfeeding (Pheterogeneity & .001 for triple-negative compared with luminal A-like breast cancer) were associated with lower risk of triple-negative breast cancer 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. This large and comprehensive study demonstrates a distinct reproductive risk factor profile for triple-negative breast cancer compared with other subtypes, with implications for the understanding of disease etiology and risk prediction.
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/0008-5472.22425333
Abstract: Univariate ACE estimates for % mammographic density
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/0008-5472.22425336
Abstract: Univariate ACE estimates after re-randomisation of siblings
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/0008-5472.22425324.V1
Abstract: Association between a genetic predisposition to breast cancer and mammographic features among women who did not develop breast cancer during follow-up
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/0008-5472.22425330
Abstract: Univariate ACE estimates among women who did not develop breast cancer during follow-up
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/0008-5472.C.6512010.V1
Abstract: Abstract Mammographic features influence breast cancer risk and are used in risk prediction models. Understanding how genetics influence mammographic features is important because the mechanisms through which they are associated with breast cancer are not well known. Here, using mammographic screening history and detailed questionnaire data from 56,820 women from the KARMA prospective cohort study, we investigated the association between a genetic predisposition to breast cancer and mammographic features among women with a family history of breast cancer ( i N /i = 49,674) and a polygenic risk score (PRS, i N /i = 9,365). The heritability of mammographic features such as dense area (MD), microcalcifications, masses, and density change (MDC, cm sup /sup /year) was estimated using 1,940 sister pairs. Heritability was estimated at 58% [95% confidence interval (CI), 48%–67%) for MD, 23% (2%–45%) for microcalcifications, and 13% (1%–25%)] for masses. The estimated heritability for MDC was essentially null (2% 95% CI, −8% to 12%). The association between a genetic predisposition to breast cancer (using PRS) and MD and microcalcifications was positive, while for masses this was borderline significant. In addition, for MDC, having a family history of breast cancer was associated with slightly greater MD reduction. In summary, we have confirmed previous findings of heritability in MD, and also established heritability of the number of microcalcifications and masses at baseline. Because these features are associated with breast cancer risk and can improve detecting women at short-term risk of breast cancer, further investigation of common loci associated with mammographic features is warranted to better understand the etiology of breast cancer. Significance: These findings provide novel data on the heritability of microcalcifications, masses, and density change, which are all associated with breast cancer risk and can indicate women at short-term risk. /
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2767-9764.22544801
Abstract: Quantile-Quantile plot (Q-Q plot) of the aMiSTi p-values for each set of the GxE interactions.
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2767-9764.22544801.V1
Abstract: Quantile-Quantile plot (Q-Q plot) of the aMiSTi p-values for each set of the GxE interactions.
Publisher: American Association for Cancer Research (AACR)
Date: 08-04-2022
DOI: 10.1158/2767-9764.CRC-21-0119
Abstract: Genome-wide association studies (GWAS) have identified more than 200 susceptibility loci for breast cancer, but these variants explain less than a fifth of the disease risk. Although gene–environment interactions have been proposed to account for some of the remaining heritability, few studies have empirically assessed this. We obtained genotype and risk factor data from 46,060 cases and 47,929 controls of European ancestry from population-based studies within the Breast Cancer Association Consortium (BCAC). We built gene expression prediction models for 4,864 genes with a significant (P & 0.01) heritable component using the transcriptome and genotype data from the Genotype-Tissue Expression (GTEx) project. We leveraged predicted gene expression information to investigate the interactions between gene-centric genetic variation and 14 established risk factors in association with breast cancer risk, using a mixed-effects score test. After adjusting for number of tests using Bonferroni correction, no interaction remained statistically significant. The strongest interaction observed was between the predicted expression of the C13orf45 gene and age at first full-term pregnancy (PGXE = 4.44 × 10−6). In this transcriptome-informed genome-wide gene–environment interaction study of breast cancer, we found no strong support for the role of gene expression in modifying the associations between established risk factors and breast cancer risk. Our study suggests a limited role of gene–environment interactions in breast cancer risk.
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/0008-5472.22425342.V1
Abstract: Illustration of microcalcifications and masses in the breast
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/0008-5472.22425339.V1
Abstract: Model fitting from univariate analyses after re-randomisation of siblings
Publisher: American Association for Cancer Research (AACR)
Date: 26-01-2021
DOI: 10.1158/1055-9965.EPI-20-0924
Abstract: It is not known whether modifiable lifestyle factors that predict survival after invasive breast cancer differ by subtype. We analyzed data for 121,435 women diagnosed with breast cancer from 67 studies in the Breast Cancer Association Consortium with 16,890 deaths (8,554 breast cancer specific) over 10 years. Cox regression was used to estimate associations between risk factors and 10-year all-cause mortality and breast cancer–specific mortality overall, by estrogen receptor (ER) status, and by intrinsic-like subtype. There was no evidence of heterogeneous associations between risk factors and mortality by subtype (Padj & 0.30). The strongest associations were between all-cause mortality and BMI ≥30 versus 18.5–25 kg/m2 [HR (95% confidence interval (CI), 1.19 (1.06–1.34)] current versus never smoking [1.37 (1.27–1.47)], high versus low physical activity [0.43 (0.21–0.86)], age ≥30 years versus & years at first pregnancy [0.79 (0.72–0.86)] & –& years versus ≥10 years since last full-term birth [1.31 (1.11–1.55)] ever versus never use of oral contraceptives [0.91 (0.87–0.96)] ever versus never use of menopausal hormone therapy, including current estrogen–progestin therapy [0.61 (0.54–0.69)]. Similar associations with breast cancer mortality were weaker for ex le, 1.11 (1.02–1.21) for current versus never smoking. We confirm associations between modifiable lifestyle factors and 10-year all-cause mortality. There was no strong evidence that associations differed by ER status or intrinsic-like subtype. Given the large dataset and lack of evidence that associations between modifiable risk factors and 10-year mortality differed by subtype, these associations could be cautiously used in prognostication models to inform patient-centered care.
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/0008-5472.22425321.V1
Abstract: Association between a genetic predisposition to breast cancer (using family history of breast cancer and estrogen-receptor specific polygenic risk scores) among women withour breast cancer
Publisher: Elsevier BV
Date: 09-2022
DOI: 10.1016/J.EJCA.2022.06.011
Abstract: Predict Breast (www.predict.nhs.uk) is an online prognostication and treatment benefit tool for early invasive breast cancer. The aim of this study was to incorporate the prognostic effect of progesterone receptor (PR) status into a new version of PREDICT and to compare its performance to the current version (2.2). The prognostic effect of PR status was based on the analysis of data from 45,088 European patients with breast cancer from 49 studies in the Breast Cancer Association Consortium. Cox proportional hazard models were used to estimate the hazard ratio for PR status. Data from a New Zealand study of 11,365 patients with early invasive breast cancer were used for external validation. Model calibration and discrimination were used to test the model performance. Having a PR-positive tumour was associated with a 23% and 28% lower risk of dying from breast cancer for women with oestrogen receptor (ER)-negative and ER-positive breast cancer, respectively. The area under the ROC curve increased with the addition of PR status from 0.807 to 0.809 for patients with ER-negative tumours (p = 0.023) and from 0.898 to 0.902 for patients with ER-positive tumours (p = 2.3 × 10 -6 ) in the New Zealand cohort. Model calibration was modest with 940 observed deaths compared to 1151 predicted. The inclusion of the prognostic effect of PR status to PREDICT Breast has led to an improvement of model performance and more accurate absolute treatment benefit predictions for in idual patients. Further studies should determine whether the baseline hazard function requires recalibration.
Publisher: Oxford University Press (OUP)
Date: 02-05-2020
DOI: 10.1093/JNCI/DJAA056
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 in idual 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.
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2767-9764.22544795.V1
Abstract: Supplementary Table 1. S le Size of each participated study, by case-control status and genotype platform. Supplementary Table 2. Association between fourteen environmental factors and the risk of breast cancer. Supplementary Table 3. Interactions between genes and fourteen environmental factors.
Publisher: American Society of Clinical Oncology (ASCO)
Date: 04-2023
DOI: 10.1200/JCO.22.01978
Abstract: A polygenic risk score (PRS) consisting of 313 common genetic variants (PRS 313 ) is associated with risk of breast cancer and contralateral breast cancer. This study aimed to evaluate the association of the PRS 313 with clinicopathologic characteristics of, and survival following, breast cancer. Women with invasive breast cancer were included, 98,397 of European ancestry and 12,920 of Asian ancestry, from the Breast Cancer Association Consortium (BCAC), and 683 women from the European MINDACT trial. Associations between PRS 313 and clinicopathologic characteristics, including the 70-gene signature for MINDACT, were evaluated using logistic regression analyses. Associations of PRS 313 (continuous, per standard deviation) with overall survival (OS) and breast cancer–specific survival (BCSS) were evaluated with Cox regression, adjusted for clinicopathologic characteristics and treatment. The PRS 313 was associated with more favorable tumor characteristics. In BCAC, increasing PRS 313 was associated with lower grade, hormone receptor–positive status, and smaller tumor size. In MINDACT, PRS 313 was associated with a low risk 70-gene signature. In European women from BCAC, higher PRS 313 was associated with better OS and BCSS: hazard ratio (HR) 0.96 (95% CI, 0.94 to 0.97) and 0.96 (95% CI, 0.94 to 0.98), but the association disappeared after adjustment for clinicopathologic characteristics (and treatment): OS HR, 1.01 (95% CI, 0.98 to 1.05) and BCSS HR, 1.02 (95% CI, 0.98 to 1.07). The results in MINDACT and Asian women from BCAC were consistent. An increased PRS 313 is associated with favorable tumor characteristics, but is not independently associated with prognosis. Thus, PRS 313 has no role in the clinical management of primary breast cancer at the time of diagnosis. Nevertheless, breast cancer mortality rates will be higher for women with higher PRS 313 as increasing PRS 313 is associated with an increased risk of disease. This information is crucial for modeling effective stratified screening programs.
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/0008-5472.22425327
Abstract: Association between a genetic predisposition to breast cancer and % mammographic density
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2767-9764.22544795
Abstract: Supplementary Table 1. S le Size of each participated study, by case-control status and genotype platform. Supplementary Table 2. Association between fourteen environmental factors and the risk of breast cancer. Supplementary Table 3. Interactions between genes and fourteen environmental factors.
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/0008-5472.22425327.V1
Abstract: Association between a genetic predisposition to breast cancer and % mammographic density
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/0008-5472.22425324
Abstract: Association between a genetic predisposition to breast cancer and mammographic features among women who did not develop breast cancer during follow-up
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/0008-5472.22425333.V1
Abstract: Univariate ACE estimates for % mammographic density
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/0008-5472.C.6512010
Abstract: Abstract Mammographic features influence breast cancer risk and are used in risk prediction models. Understanding how genetics influence mammographic features is important because the mechanisms through which they are associated with breast cancer are not well known. Here, using mammographic screening history and detailed questionnaire data from 56,820 women from the KARMA prospective cohort study, we investigated the association between a genetic predisposition to breast cancer and mammographic features among women with a family history of breast cancer ( i N /i = 49,674) and a polygenic risk score (PRS, i N /i = 9,365). The heritability of mammographic features such as dense area (MD), microcalcifications, masses, and density change (MDC, cm sup /sup /year) was estimated using 1,940 sister pairs. Heritability was estimated at 58% [95% confidence interval (CI), 48%–67%) for MD, 23% (2%–45%) for microcalcifications, and 13% (1%–25%)] for masses. The estimated heritability for MDC was essentially null (2% 95% CI, −8% to 12%). The association between a genetic predisposition to breast cancer (using PRS) and MD and microcalcifications was positive, while for masses this was borderline significant. In addition, for MDC, having a family history of breast cancer was associated with slightly greater MD reduction. In summary, we have confirmed previous findings of heritability in MD, and also established heritability of the number of microcalcifications and masses at baseline. Because these features are associated with breast cancer risk and can improve detecting women at short-term risk of breast cancer, further investigation of common loci associated with mammographic features is warranted to better understand the etiology of breast cancer. Significance: These findings provide novel data on the heritability of microcalcifications, masses, and density change, which are all associated with breast cancer risk and can indicate women at short-term risk. /
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/0008-5472.22425321
Abstract: Association between a genetic predisposition to breast cancer (using family history of breast cancer and estrogen-receptor specific polygenic risk scores) among women withour breast cancer
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/0008-5472.22425342
Abstract: Illustration of microcalcifications and masses in the breast
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2767-9764.22544798
Abstract: Funding and acknowledgements.
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2767-9764.C.6550751.V1
Abstract: Genome-wide association studies (GWAS) have identified more than 200 susceptibility loci for breast cancer, but these variants explain less than a fifth of the disease risk. Although gene–environment interactions have been proposed to account for some of the remaining heritability, few studies have empirically assessed this. We obtained genotype and risk factor data from 46,060 cases and 47,929 controls of European ancestry from population-based studies within the Breast Cancer Association Consortium (BCAC). We built gene expression prediction models for 4,864 genes with a significant ( i P /i 0.01) heritable component using the transcriptome and genotype data from the Genotype-Tissue Expression (GTEx) project. We leveraged predicted gene expression information to investigate the interactions between gene-centric genetic variation and 14 established risk factors in association with breast cancer risk, using a mixed-effects score test. After adjusting for number of tests using Bonferroni correction, no interaction remained statistically significant. The strongest interaction observed was between the predicted expression of the i C13orf45 /i gene and age at first full-term pregnancy (P sub GXE /sub = 4.44 × 10 sup −6 /sup ). In this transcriptome-informed genome-wide gene–environment interaction study of breast cancer, we found no strong support for the role of gene expression in modifying the associations between established risk factors and breast cancer risk. Our study suggests a limited role of gene–environment interactions in breast cancer risk. /
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/0008-5472.22425336.V1
Abstract: Univariate ACE estimates after re-randomisation of siblings
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2767-9764.C.6550751
Abstract: Genome-wide association studies (GWAS) have identified more than 200 susceptibility loci for breast cancer, but these variants explain less than a fifth of the disease risk. Although gene–environment interactions have been proposed to account for some of the remaining heritability, few studies have empirically assessed this. We obtained genotype and risk factor data from 46,060 cases and 47,929 controls of European ancestry from population-based studies within the Breast Cancer Association Consortium (BCAC). We built gene expression prediction models for 4,864 genes with a significant ( i P /i 0.01) heritable component using the transcriptome and genotype data from the Genotype-Tissue Expression (GTEx) project. We leveraged predicted gene expression information to investigate the interactions between gene-centric genetic variation and 14 established risk factors in association with breast cancer risk, using a mixed-effects score test. After adjusting for number of tests using Bonferroni correction, no interaction remained statistically significant. The strongest interaction observed was between the predicted expression of the i C13orf45 /i gene and age at first full-term pregnancy (P sub GXE /sub = 4.44 × 10 sup −6 /sup ). In this transcriptome-informed genome-wide gene–environment interaction study of breast cancer, we found no strong support for the role of gene expression in modifying the associations between established risk factors and breast cancer risk. Our study suggests a limited role of gene–environment interactions in breast cancer risk. /
Publisher: American Association for Cancer Research (AACR)
Date: 04-2020
DOI: 10.1158/0008-5472.CAN-19-2455
Abstract: These findings provide novel data on the heritability of microcalcifications, masses, and density change, which are all associated with breast cancer risk and can indicate women at short-term risk.
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2767-9764.22544798.V1
Abstract: Funding and acknowledgements.
Location: No location found
No related grants have been discovered for Per Hall.