Publications by authors named "Siddhartha Kar"

79 Publications

Large-scale cross-cancer fine-mapping of the 5p15.33 region reveals multiple independent signals.

HGG Adv 2021 Jul 12;2(3). Epub 2021 Jun 12.

Department of Laboratory Medicine and Pathology, Mayo Clinic Comprehensive Cancer Center, Mayo Clinic, Rochester, MN, USA.

Genome-wide association studies (GWASs) have identified thousands of cancer risk loci revealing many risk regions shared across multiple cancers. Characterizing the cross-cancer shared genetic basis can increase our understanding of global mechanisms of cancer development. In this study, we collected GWAS summary statistics based on up to 375,468 cancer cases and 530,521 controls for fourteen types of cancer, including breast (overall, estrogen receptor [ER]-positive, and ER-negative), colorectal, endometrial, esophageal, glioma, head/neck, lung, melanoma, ovarian, pancreatic, prostate, and renal cancer, to characterize the shared genetic basis of cancer risk. We identified thirteen pairs of cancers with statistically significant local genetic correlations across eight distinct genomic regions. Specifically, the 5p15.33 region, harboring the and genes, showed statistically significant local genetic correlations for multiple cancer pairs. We conducted a cross-cancer fine-mapping of the 5p15.33 region based on eight cancers that showed genome-wide significant associations in this region (ER-negative breast, colorectal, glioma, lung, melanoma, ovarian, pancreatic, and prostate cancer). We used an iterative analysis pipeline implementing a subset-based meta-analysis approach based on cancer-specific conditional analyses and identified ten independent cross-cancer associations within this region. For each signal, we conducted cross-cancer fine-mapping to prioritize the most plausible causal variants. Our findings provide a more in-depth understanding of the shared inherited basis across human cancers and expand our knowledge of the 5p15.33 region in carcinogenesis.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.xhgg.2021.100041DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8336922PMC
July 2021

Body size and composition and risk of site-specific cancers in the UK Biobank and large international consortia: A mendelian randomisation study.

PLoS Med 2021 Jul 29;18(7):e1003706. Epub 2021 Jul 29.

Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.

Background: Evidence for the impact of body size and composition on cancer risk is limited. This mendelian randomisation (MR) study investigates evidence supporting causal relationships of body mass index (BMI), fat mass index (FMI), fat-free mass index (FFMI), and height with cancer risk.

Methods And Findings: Single nucleotide polymorphisms (SNPs) were used as instrumental variables for BMI (312 SNPs), FMI (577 SNPs), FFMI (577 SNPs), and height (293 SNPs). Associations of the genetic variants with 22 site-specific cancers and overall cancer were estimated in 367,561 individuals from the UK Biobank (UKBB) and with lung, breast, ovarian, uterine, and prostate cancer in large international consortia. In the UKBB, genetically predicted BMI was positively associated with overall cancer (odds ratio [OR] per 1 kg/m2 increase 1.01, 95% confidence interval [CI] 1.00-1.02; p = 0.043); several digestive system cancers: stomach (OR 1.13, 95% CI 1.06-1.21; p < 0.001), esophagus (OR 1.10, 95% CI 1.03, 1.17; p = 0.003), liver (OR 1.13, 95% CI 1.03-1.25; p = 0.012), and pancreas (OR 1.06, 95% CI 1.01-1.12; p = 0.016); and lung cancer (OR 1.08, 95% CI 1.04-1.12; p < 0.001). For sex-specific cancers, genetically predicted elevated BMI was associated with an increased risk of uterine cancer (OR 1.10, 95% CI 1.05-1.15; p < 0.001) and with a lower risk of prostate cancer (OR 0.97, 95% CI 0.94-0.99; p = 0.009). When dividing cancers into digestive system versus non-digestive system, genetically predicted BMI was positively associated with digestive system cancers (OR 1.04, 95% CI 1.02-1.06; p < 0.001) but not with non-digestive system cancers (OR 1.01, 95% CI 0.99-1.02; p = 0.369). Genetically predicted FMI was positively associated with liver, pancreatic, and lung cancer and inversely associated with melanoma and prostate cancer. Genetically predicted FFMI was positively associated with non-Hodgkin lymphoma and melanoma. Genetically predicted height was associated with increased risk of overall cancer (OR per 1 standard deviation increase 1.09; 95% CI 1.05-1.12; p < 0.001) and multiple site-specific cancers. Similar results were observed in analyses using the weighted median and MR-Egger methods. Results based on consortium data confirmed the positive associations between BMI and lung and uterine cancer risk as well as the inverse association between BMI and prostate cancer, and, additionally, showed an inverse association between genetically predicted BMI and breast cancer. The main limitations are the assumption that genetic associations with cancer outcomes are mediated via the proposed risk factors and that estimates for some lower frequency cancer types are subject to low precision.

Conclusions: Our results show that the evidence for BMI as a causal risk factor for cancer is mixed. We find that BMI has a consistent causal role in increasing risk of digestive system cancers and a role for sex-specific cancers with inconsistent directions of effect. In contrast, increased height appears to have a consistent risk-increasing effect on overall and site-specific cancers.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1371/journal.pmed.1003706DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8320991PMC
July 2021

Pleiotropy-guided transcriptome imputation from normal and tumor tissues identifies candidate susceptibility genes for breast and ovarian cancer.

HGG Adv 2021 Jul 16;2(3). Epub 2021 Jun 16.

Department of Virus, Lifestyle, and Genes, Danish Cancer Society Research Center, Copenhagen, Denmark.

Familial, sequencing, and genome-wide association studies (GWASs) and genetic correlation analyses have progressively unraveled the shared or pleiotropic germline genetics of breast and ovarian cancer. In this study, we aimed to leverage this shared germline genetics to improve the power of transcriptome-wide association studies (TWASs) to identify candidate breast cancer and ovarian cancer susceptibility genes. We built gene expression prediction models using the PrediXcan method in 681 breast and 295 ovarian tumors from The Cancer Genome Atlas and 211 breast and 99 ovarian normal tissue samples from the Genotype-Tissue Expression project and integrated these with GWAS meta-analysis data from the Breast Cancer Association Consortium (122,977 cases/105,974 controls) and the Ovarian Cancer Association Consortium (22,406 cases/40,941 controls). The integration was achieved through application of a pleiotropy-guided conditional/conjunction false discovery rate (FDR) approach in the setting of a TWASs. This identified 14 candidate breast cancer susceptibility genes spanning 11 genomic regions and 8 candidate ovarian cancer susceptibility genes spanning 5 genomic regions at conjunction FDR < 0.05 that were >1 Mb away from known breast and/or ovarian cancer susceptibility loci. We also identified 38 candidate breast cancer susceptibility genes and 17 candidate ovarian cancer susceptibility genes at conjunction FDR < 0.05 at known breast and/or ovarian susceptibility loci. The 22 genes identified by our cross-cancer analysis represent promising candidates that further elucidate the role of the transcriptome in mediating germline breast and ovarian cancer risk.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.xhgg.2021.100042DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8312632PMC
July 2021

Assessing the role of cortisol in cancer: a wide-ranged Mendelian randomisation study.

Br J Cancer 2021 Jul 27. Epub 2021 Jul 27.

BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.

Background: Cortisol's immunosuppressive, obesogenic, and hyperglycaemic effects suggest that it may play a role in cancer development. However, whether cortisol increases cancer risk is not known. We investigated the potential causal association between plasma cortisol and risk of overall and common site-specific cancers using Mendelian randomisation.

Methods: Three genetic variants associated with morning plasma cortisol levels at the genome-wide significance level (P < 5 × 10) in the Cortisol Network consortium were used as genetic instruments. Summary-level genome-wide association study data for the cancer outcomes were obtained from large-scale cancer consortia, the UK Biobank, and the FinnGen consortium. Two-sample Mendelian randomisation analyses were performed using the fixed-effects inverse-variance weighted method. Estimates across data sources were combined using meta-analysis.

Results: A standard deviation increase in genetically predicted plasma cortisol was associated with increased risk of endometrial cancer (odds ratio 1.50, 95% confidence interval 1.13-1.99; P = 0.005). There was no significant association between genetically predicted plasma cortisol and risk of other common site-specific cancers, including breast, ovarian, prostate, colorectal, lung, or malignant skin cancer, or overall cancer.

Conclusions: These results indicate that elevated plasma cortisol levels may increase the risk of endometrial cancer but not other cancers. The mechanism by which this occurs remains to be investigated.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41416-021-01505-8DOI Listing
July 2021

Genetically predicted circulating B vitamins in relation to digestive system cancers.

Br J Cancer 2021 Jun 9;124(12):1997-2003. Epub 2021 Apr 9.

Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.

Background: Folate, vitamin B6 and vitamin B12 have been associated with digestive system cancers. We conducted a two-sample Mendelian randomisation study to assess the causality of these associations.

Methods: Two, one and 14 independent single nucleotide polymorphisms associated with serum folate, vitamin B6 and vitamin B12 at the genome-wide significance threshold were selected as genetic instruments. Summary-level data for the associations of the vitamin-associated genetic variants with cancer were obtained from the UK Biobank study including 367,561 individuals and FinnGen consortium comprising up to 176,899 participants.

Results: Genetically predicted folate and vitamin B6 concentrations were not associated with overall cancer, overall digestive system cancer or oesophageal, gastric, colorectal or pancreatic cancer. Genetically predicted vitamin B12 concentrations were positively associated with overall digestive system cancer (OR, 1.12; 95% CI 1.04, 1.21, p = 0.003) and colorectal cancer (OR 1.16; 95% CI 1.06, 1.26, p = 0.001) in UK Biobank. Results for colorectal cancer were consistent in FinnGen and the combined OR was 1.16 (95% CI 1.08, 1.25, p < 0.001). There was no association of genetically predicted vitamin B12 with any other site-specific digestive system cancers or overall cancer.

Conclusions: These results provide evidence to suggest that elevated serum vitamin B12 concentrations are associated with colorectal cancer.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41416-021-01383-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8184856PMC
June 2021

Germline and Somatic Genetic Variants in the p53 Pathway Interact to Affect Cancer Risk, Progression, and Drug Response.

Cancer Res 2021 04 8;81(7):1667-1680. Epub 2021 Feb 8.

Target Discovery Institute, University of Oxford, Nuffield Department of Medicine, Oxford, United Kingdom.

Insights into oncogenesis derived from cancer susceptibility loci (SNP) hold the potential to facilitate better cancer management and treatment through precision oncology. However, therapeutic insights have thus far been limited by our current lack of understanding regarding both interactions of these loci with somatic cancer driver mutations and their influence on tumorigenesis. For example, although both germline and somatic genetic variation to the p53 tumor suppressor pathway are known to promote tumorigenesis, little is known about the extent to which such variants cooperate to alter pathway activity. Here we hypothesize that cancer risk-associated germline variants interact with somatic mutational status to modify cancer risk, progression, and response to therapy. Focusing on a cancer risk SNP (rs78378222) with a well-documented ability to directly influence p53 activity as well as integration of germline datasets relating to cancer susceptibility with tumor data capturing somatically-acquired genetic variation provided supportive evidence for this hypothesis. Integration of germline and somatic genetic data enabled identification of a novel entry point for therapeutic manipulation of p53 activities. A cluster of cancer risk SNPs resulted in increased expression of prosurvival p53 target gene and attenuation of p53-mediated responses to genotoxic therapies, which were reversed by pharmacologic inhibition of the prosurvival c-KIT signal. Together, our results offer evidence of how cancer susceptibility SNPs can interact with cancer driver genes to affect cancer progression and identify novel combinatorial therapies. SIGNIFICANCE: These results offer evidence of how cancer susceptibility SNPs can interact with cancer driver genes to affect cancer progression and present novel therapeutic targets.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1158/0008-5472.CAN-20-0177DOI Listing
April 2021

Genetically proxied milk consumption and risk of colorectal, bladder, breast, and prostate cancer: a two-sample Mendelian randomization study.

BMC Med 2020 12 2;18(1):370. Epub 2020 Dec 2.

Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.

Background: Observational studies have shown that milk consumption is inversely associated with colorectal, bladder, and breast cancer risk, but positively associated with prostate cancer. However, whether the associations reflect causality remains debatable. We investigated the potential causal associations of milk consumption with the risk of colorectal, bladder, breast, and prostate cancer using a genetic variant near the LCT gene as proxy for milk consumption.

Methods: We obtained genetic association estimates for cancer from the UK Biobank (n = 367,643 women and men), FinnGen consortium (n = 135,638 women and men), Breast Cancer Association Consortium (n = 228,951 women), and Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome consortium (n = 140,254 men). Milk consumption was proxied by a genetic variant (rs4988235 or rs182549) upstream of the gene encoding lactase, which catalyzes the breakdown of lactose.

Results: Genetically proxied milk consumption was associated with a reduced risk of colorectal cancer. The odds ratio (OR) for each additional milk intake increasing allele was 0.95 (95% confidence interval [CI] 0.91-0.99; P = 0.009). There was no overall association of genetically predicted milk consumption with bladder (OR 0.99; 95% CI 0.94-1.05; P = 0.836), breast (OR 1.01; 95% CI 1.00-1.02; P = 0.113), and prostate cancer (OR 1.01; 95% CI 0.99-1.02; P = 0.389), but a positive association with prostate cancer was observed in the FinnGen consortium (OR 1.07; 95% CI 1.01-1.13; P = 0.026).

Conclusions: Our findings strengthen the evidence for a protective role of milk consumption on colorectal cancer risk. There was no or limited evidence that milk consumption affects the risk of bladder, breast, and prostate cancer.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1186/s12916-020-01839-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7709312PMC
December 2020

Genetically predicted circulating protein biomarkers and ovarian cancer risk.

Gynecol Oncol 2021 02 25;160(2):506-513. Epub 2020 Nov 25.

MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK. Electronic address:

Objective: Most women with epithelial ovarian cancer (EOC) are diagnosed after the disease has metastasized and survival in this group remains poor. Circulating proteins associated with the risk of developing EOC have the potential to serve as biomarkers for early detection and diagnosis. We integrated large-scale genomic and proteomic data to identify novel plasma proteins associated with EOC risk.

Methods: We used the germline genetic variants most strongly associated (P <1.5 × 10) with plasma levels of 1329 proteins in 3301 healthy individuals from the INTERVAL study to predict circulating levels of these proteins in 22,406 EOC cases and 40,941 controls from the Ovarian Cancer Association Consortium (OCAC). Association testing was performed by weighting the beta coefficients and standard errors for EOC risk from the OCAC study by the inverse of the beta coefficients from INTERVAL.

Results: We identified 26 proteins whose genetically predicted circulating levels were associated with EOC risk at false discovery rate < 0.05. The 26 proteins included MFAP2, SEMG2, DLK1, and NTNG1 and a group of 22 proteins whose plasma levels were predicted by variants at chromosome 9q34.2. All 26 protein association signals identified were driven by association with the high-grade serous histotype that comprised 58% of the EOC cases in OCAC. Regional genomic plots confirmed overlap of the genetic association signal underlying both plasma protein level and EOC risk for the 26 proteins. Pathway analysis identified enrichment of seven biological pathways among the 26 proteins (P <0.05), highlighting roles for Focal Adhesion-PI3K-Akt-mTOR and Notch signaling.

Conclusion: The identified proteins further illuminate the etiology of EOC and represent promising new EOC biomarkers for targeted validation by studies involving direct measurement of plasma proteins in EOC patient cohorts.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.ygyno.2020.11.016DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7855757PMC
February 2021

Breast cancer risk factors and their effects on survival: a Mendelian randomisation study.

BMC Med 2020 11 17;18(1):327. Epub 2020 Nov 17.

Division of Molecular Pathology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands.

Background: Observational studies have investigated the association of risk factors with breast cancer prognosis. However, the results have been conflicting and it has been challenging to establish causality due to potential residual confounding. Using a Mendelian randomisation (MR) approach, we aimed to examine the potential causal association between breast cancer-specific survival and nine established risk factors for breast cancer: alcohol consumption, body mass index, height, physical activity, mammographic density, age at menarche or menopause, smoking, and type 2 diabetes mellitus (T2DM).

Methods: We conducted a two-sample MR analysis on data from the Breast Cancer Association Consortium (BCAC) and risk factor summary estimates from the GWAS Catalog. The BCAC data included 86,627 female patients of European ancestry with 7054 breast cancer-specific deaths during 15 years of follow-up. Of these, 59,378 were estrogen receptor (ER)-positive and 13,692 were ER-negative breast cancer patients. For the significant association, we used sensitivity analyses and a multivariable MR model. All risk factor associations were also examined in a model adjusted by other prognostic factors.

Results: Increased genetic liability to T2DM was significantly associated with worse breast cancer-specific survival (hazard ratio [HR] = 1.10, 95% confidence interval [CI] = 1.03-1.17, P value [P] = 0.003). There were no significant associations after multiple testing correction for any of the risk factors in the ER-status subtypes. For the reported significant association with T2DM, the sensitivity analyses did not show evidence for violation of the MR assumptions nor that the association was due to increased BMI. The association remained significant when adjusting by other prognostic factors.

Conclusions: This extensive MR analysis suggests that T2DM may be causally associated with worse breast cancer-specific survival and therefore that treating T2DM may improve prognosis.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1186/s12916-020-01797-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7670589PMC
November 2020

Predicting the effect of statins on cancer risk using genetic variants from a Mendelian randomization study in the UK Biobank.

Elife 2020 10 13;9. Epub 2020 Oct 13.

Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.

Laboratory studies have suggested oncogenic roles of lipids, as well as anticarcinogenic effects of statins. Here we assess the potential effect of statin therapy on cancer risk using evidence from human genetics. We obtained associations of lipid-related genetic variants with the risk of overall and 22 site-specific cancers for 367,703 individuals in the UK Biobank. In total, 75,037 individuals had a cancer event. Variants in the gene region, which represent proxies for statin treatment, were associated with overall cancer risk (odds ratio [OR] per one standard deviation decrease in low-density lipoprotein [LDL] cholesterol 0.76, 95% confidence interval [CI] 0.65-0.88, p=0.0003) but variants in gene regions representing alternative lipid-lowering treatment targets (, , , , ) were not. Genetically predicted LDL-cholesterol was not associated with overall cancer risk (OR per standard deviation increase 1.01, 95% CI 0.98-1.05, p=0.50). Our results predict that statins reduce cancer risk but other lipid-lowering treatments do not. This suggests that statins reduce cancer risk through a cholesterol independent pathway.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.7554/eLife.57191DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7553780PMC
October 2020

Assessing the protective role of allergic disease in gastrointestinal tract cancers using Mendelian randomization analysis.

Allergy 2021 05 21;76(5):1559-1562. Epub 2020 Oct 21.

Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.

View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1111/all.14616DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8411419PMC
May 2021

Sleep duration and risk of overall and 22 site-specific cancers: A Mendelian randomization study.

Int J Cancer 2021 02 14;148(4):914-920. Epub 2020 Sep 14.

Unit of Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.

Studies of sleep duration in relation to the risk of site-specific cancers other than breast cancer are scarce. Furthermore, the available results are inconclusive and the causality remains unclear. We aimed to investigate the potential causal associations of sleep duration with overall and site-specific cancers using the Mendelian randomization (MR) design. Single-nucleotide polymorphisms associated with the sleep traits identified from a genome-wide association study were used as instrumental variables to estimate the association with overall cancer and 22 site-specific cancers among 367 586 UK Biobank participants. A replication analysis was performed using data from the FinnGen consortium (up to 121 579 individuals). There was suggestive evidence that genetic liability to short-sleep duration was associated with higher odds of cancers of the stomach (odds ratio [OR], 2.22; 95% confidence interval [CI], 1.15-4.30; P = .018), pancreas (OR, 2.18; 95% CI, 1.32-3.62; P = .002) and colorectum (OR, 1.48; 95% CI, 1.12-1.95; P = .006), but with lower odds of multiple myeloma (OR, 0.47; 95% CI, 0.22-0.99; P = .047). Suggestive evidence of association of genetic liability to long-sleep duration with lower odds of pancreatic cancer (OR, 0.44; 95% CI, 0.25-0.79; P = .005) and kidney cancer (OR, 0.44; 95% CI, 0.21-0.90; P = .025) was observed. However, none of these associations passed the multiple comparison threshold and two-sample MR analysis using FinnGen data did not confirm these findings. In conclusion, this MR study does not provide strong evidence to support causal associations of sleep duration with risk of overall and site-specific cancers. Further MR studies are required.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1002/ijc.33286DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7821333PMC
February 2021

eQTL Colocalization Analyses Identify NTN4 as a Candidate Breast Cancer Risk Gene.

Am J Hum Genet 2020 10 31;107(4):778-787. Epub 2020 Aug 31.

Cancer Division, QIMR Berghofer Medical Research Institute, Brisbane, QLD 4029, Australia.

Breast cancer genome-wide association studies (GWASs) have identified 150 genomic risk regions containing more than 13,000 credible causal variants (CCVs). The CCVs are predominantly noncoding and enriched in regulatory elements. However, the genes underlying breast cancer risk associations are largely unknown. Here, we used genetic colocalization analysis to identify loci at which gene expression could potentially explain breast cancer risk phenotypes. Using data from the Breast Cancer Association Consortium (BCAC) and quantitative trait loci (QTL) from the Genotype-Tissue Expression (GTEx) project and The Cancer Genome Project (TCGA), we identify shared genetic relationships and reveal novel associations between cancer phenotypes and effector genes. Seventeen genes, including NTN4, were identified as potential mediators of breast cancer risk. For NTN4, we showed the rs61938093 CCV at this region was located within an enhancer element that physically interacts with the NTN4 promoter, and the risk allele reduced NTN4 promoter activity. Furthermore, knockdown of NTN4 in breast cells increased cell proliferation in vitro and tumor growth in vivo. These data provide evidence linking risk-associated variation to genes that may contribute to breast cancer predisposition.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.ajhg.2020.08.006DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7536644PMC
October 2020

Effects of tumour necrosis factor on cardiovascular disease and cancer: A two-sample Mendelian randomization study.

EBioMedicine 2020 Sep 14;59:102956. Epub 2020 Aug 14.

Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm 17177, Sweden; Department of Surgical Sciences, Uppsala University, Uppsala, Sweden. Electronic address:

Background: Tumour necrosis factor (TNF) inhibitors are used in the treatment of certain autoimmune diseases but given the role of TNF in tumour biology and atherosclerosis, such therapies may influence the risk of cancer and cardiovascular disease. We conducted a Mendelian randomization study to explore whether TNF levels are causally related to cardiovascular disease and cancer.

Methods: Single-nucleotide polymorphisms associated with TNF levels at genome-wide significance were identified from a genome-wide association study of 30 912 European-ancestry individuals. Three TNF-associated single-nucleotide polymorphisms associated with higher risk of autoimmune diseases were used as instrumental variables. Summary-level data for 14 cardiovascular diseases, overall cancer and 14 site-specific cancers were obtained from UK Biobank and consortia.

Findings: Genetically-predicted TNF levels were positively associated with coronary artery disease (odds ratio (OR) 2.25; 95% confidence interval (CI) 1.50, 3.37) and ischaemic stroke (OR 2.27; 95% CI 1.50, 3.43), and inversely associated with overall cancer (OR 0.54; 95% CI 0.42, 0.69), breast cancer (OR 0.51; 95% CI 0.39, 0.67), and colorectal cancer (OR 0.20; 95% CI 0.09, 0.45). There were suggestive associations of TNF with venous thromboembolism (OR 2.18; 95% CI 1.32, 3.59), endometrial cancer (OR 0.25; 95% CI 0.07, 0.94), and lung cancer (OR 0.45; 95% CI 0.21, 0.94).

Interpretation: This study found evidence of causal associations of increased TNF levels with higher risk of common cardiovascular diseases and lower risk of overall and certain cancers.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.ebiom.2020.102956DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7452586PMC
September 2020

Insulin-like growth factor-1 and site-specific cancers: A Mendelian randomization study.

Cancer Med 2020 09 27;9(18):6836-6842. Epub 2020 Jul 27.

Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.

Insulin-like growth factor-1 (IGF-1) is involved in several processes relevant to carcinogenesis. We used 416 single-nucleotide polymorphisms robustly associated with serum IGF-1 levels to assess the potential causal associations between this hormone and site-specific cancers through Mendelian randomization. Summary-level genetic association estimates for prostate, breast, ovarian, and lung cancer were obtained from large-scale consortia including individuals of European-descent. Furthermore, we estimated genetic associations with 14 site-specific cancers in European-descent individuals in UK Biobank. Supplementary analyses were conducted for six site-specific cancers using summary-level data from the BioBank Japan Project. Genetically predicted serum IGF-1 levels were associated with colorectal cancer. The odds ratio (OR) per standard deviation increase of IGF-1 levels was 1.11 (95% confidence interval [CI] 1.01-1.22; P = .03) in UK Biobank and 1.22 (95% CI 1.09-1.36; P = 3.9 × 10 ) in the BioBank Japan Project. For prostate cancer, the corresponding OR was 1.10 (95% CI 1.01-1.21; P = .04) in UK Biobank, 1.03 (95% CI 0.97-1.09; P = .41) in the prostate cancer consortium, and 1.08 (95% CI 0.95-1.22; P = .24) in the BioBank Japan Project. For breast cancer, the corresponding OR was 0.99 (95% CI 0.92-1.07; P = .85) in UK Biobank and 1.08 (95% CI 1.02-1.13; P = 4.4 × 10 ) in the Breast Cancer Association Consortium. There was no statistically significant association between genetically predicted IGF-1 levels and 14 other cancers. This study found some support for a causal association between elevated serum IGF-1 levels and increased risk of colorectal cancer. There was inconclusive or no evidence of a causal association of IGF-1 levels with prostate, breast, and other cancers.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1002/cam4.3345DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7520358PMC
September 2020

Smoking, alcohol consumption, and cancer: A mendelian randomisation study in UK Biobank and international genetic consortia participants.

PLoS Med 2020 07 23;17(7):e1003178. Epub 2020 Jul 23.

Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.

Background: Smoking is a well-established cause of lung cancer and there is strong evidence that smoking also increases the risk of several other cancers. Alcohol consumption has been inconsistently associated with cancer risk in observational studies. This mendelian randomisation (MR) study sought to investigate associations in support of a causal relationship between smoking and alcohol consumption and 19 site-specific cancers.

Methods And Findings: We used summary-level data for genetic variants associated with smoking initiation (ever smoked regularly) and alcohol consumption, and the corresponding associations with lung, breast, ovarian, and prostate cancer from genome-wide association studies consortia, including participants of European ancestry. We additionally estimated genetic associations with 19 site-specific cancers among 367,643 individuals of European descent in UK Biobank who were 37 to 73 years of age when recruited from 2006 to 2010. Associations were considered statistically significant at a Bonferroni corrected p-value below 0.0013. Genetic predisposition to smoking initiation was associated with statistically significant higher odds of lung cancer in the International Lung Cancer Consortium (odds ratio [OR] 1.80; 95% confidence interval [CI] 1.59-2.03; p = 2.26 × 10-21) and UK Biobank (OR 2.26; 95% CI 1.92-2.65; p = 1.17 × 10-22). Additionally, genetic predisposition to smoking was associated with statistically significant higher odds of cancer of the oesophagus (OR 1.83; 95% CI 1.34-2.49; p = 1.31 × 10-4), cervix (OR 1.55; 95% CI 1.27-1.88; p = 1.24 × 10-5), and bladder (OR 1.40; 95% CI 1.92-2.65; p = 9.40 × 10-5) and with statistically nonsignificant higher odds of head and neck (OR 1.40; 95% CI 1.13-1.74; p = 0.002) and stomach cancer (OR 1.46; 95% CI 1.05-2.03; p = 0.024). In contrast, there was an inverse association between genetic predisposition to smoking and prostate cancer in the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome consortium (OR 0.90; 95% CI 0.83-0.98; p = 0.011) and in UK Biobank (OR 0.90; 95% CI 0.80-1.02; p = 0.104), but the associations did not reach statistical significance. We found no statistically significant association between genetically predicted alcohol consumption and overall cancer (n = 75,037 cases; OR 0.95; 95% CI 0.84-1.07; p = 0.376). Genetically predicted alcohol consumption was statistically significantly associated with lung cancer in the International Lung Cancer Consortium (OR 1.94; 95% CI 1.41-2.68; p = 4.68 × 10-5) but not in UK Biobank (OR 1.12; 95% CI 0.65-1.93; p = 0.686). There was no statistically significant association between alcohol consumption and any other site-specific cancer. The main limitation of this study is that precision was low in some analyses, particularly for analyses of alcohol consumption and site-specific cancers.

Conclusions: Our findings support the well-established relationship between smoking and lung cancer and suggest that smoking may also be a risk factor for cancer of the head and neck, oesophagus, stomach, cervix, and bladder. We found no evidence supporting a relationship between alcohol consumption and overall or site-specific cancer risk.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1371/journal.pmed.1003178DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7377370PMC
July 2020

Is Type 2 Diabetes Causally Associated With Cancer Risk? Evidence From a Two-Sample Mendelian Randomization Study.

Diabetes 2020 07 29;69(7):1588-1596. Epub 2020 Apr 29.

Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden

We conducted a two-sample Mendelian randomization study to investigate the causal associations of type 2 diabetes mellitus (T2DM) with risk of overall cancer and 22 site-specific cancers. Summary-level data for cancer were extracted from the Breast Cancer Association Consortium and UK Biobank. Genetic predisposition to T2DM was associated with higher odds of pancreatic, kidney, uterine, and cervical cancer and lower odds of esophageal cancer and melanoma but not associated with 16 other site-specific cancers or overall cancer. The odds ratios (ORs) were 1.13 (95% CI 1.04, 1.22), 1.08 (1.00, 1.17), 1.08 (1.01, 1.15), 1.07 (1.01, 1.15), 0.89 (0.81, 0.98), and 0.93 (0.89, 0.97) for pancreatic, kidney, uterine, cervical, and esophageal cancer and melanoma, respectively. The association between T2DM and pancreatic cancer was also observed in a meta-analysis of this and a previous Mendelian randomization study (OR 1.08; 95% CI 1.02, 1.14; = 0.009). There was limited evidence supporting causal associations between fasting glucose and cancer. Genetically predicted fasting insulin levels were positively associated with cancers of the uterus, kidney, pancreas, and lung. The current study found causal detrimental effects of T2DM on several cancers. We suggest reinforcing the cancer screening in T2DM patients to enable the early detection of cancer.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.2337/db20-0084DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7306131PMC
July 2020

Causal associations of thyroid function and dysfunction with overall, breast and thyroid cancer: A two-sample Mendelian randomization study.

Int J Cancer 2020 10 3;147(7):1895-1903. Epub 2020 Apr 3.

Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.

Whether thyroid dysfunction plays a causal role in the development of cancer remains inconclusive. We conducted a two-sample Mendelian randomization study to investigate the associations between genetic predisposition to thyroid dysfunction and 22 site-specific cancers. Single-nucleotide polymorphisms associated with four traits of thyroid function were selected from a genome-wide association meta-analysis with up to 72,167 European-descent individuals. Summary-level data for breast cancer and 21 other cancers were extracted from the Breast Cancer Association Consortium (122,977 breast cancer cases and 105,974 controls) and UK Biobank (367,643 individuals). For breast cancer, a meta-analysis was performed using data from both sources. Genetically predicted thyroid dysfunction was associated with breast cancer, with similar patterns of associations in the Breast Cancer Association Consortium and UK Biobank. The combined odds ratios of breast cancer were 0.94 (0.91-0.98; p = 0.007) per genetically predicted one standard deviation increase in TSH levels, 0.96 (0.91-1.00; p = 0.053) for genetic predisposition to hypothyroidism, 1.04 (1.01-1.07; p = 0.005) for genetic predisposition to hyperthyroidism and 1.07 (1.02-1.12; p = 0.003) per genetically predicted one standard deviation increase in free thyroxine levels. Genetically predicted TSH levels and hypothyroidism were inversely with thyroid cancer; the odds ratios were 0.47 (0.30-0.73; p = 0.001) and 0.70 (0.51-0.98; p = 0.038), respectively. Our study provides evidence of a causal association between thyroid dysfunction and breast cancer (mainly ER-positive tumors) risk. The role of TSH and hypothyroidism for thyroid cancer and the associations between thyroid dysfunction and other cancers need further exploration.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1002/ijc.32988DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7611568PMC
October 2020

Iron Status and Cancer Risk in UK Biobank: A Two-Sample Mendelian Randomization Study.

Nutrients 2020 Feb 19;12(2). Epub 2020 Feb 19.

Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, SE-171 77 Stockholm, Sweden.

We conducted a two-sample Mendelian randomization study to explore the associations of iron status with overall cancer and 22 site-specific cancers. Single-nucleotide polymorphisms for iron status were obtained from a genome-wide association study of 48,972 European-descent individuals. Summary-level data for breast and other cancers were obtained from the Breast Cancer Association Consortium and UK Biobank. Genetically predicted iron status was positively associated with liver cancer and inversely associated with brain cancer but not associated with overall cancer or the other 20 studied cancer sites at < 0.05. The odds ratios of liver cancer were 2.45 (95% CI, 0.81, 7.45; = 0.11), 2.11 (1.16, 3.83; = 0.02), 10.89 (2.44, 48.59; = 0.002) and 0.30 (0.17, 0.53; = 2 × 10) for one standard deviation increment of serum iron, transferrin saturation, ferritin and transferrin levels, respectively. For brain cancer, the corresponding odds ratios were 0.69 (0.48, 1.00; = 0.05), 0.75 (0.59, 0.97; = 0.03), 0.41 (0.20, 0.88; = 0.02) and 1.49 (1.04, 2.14; = 0.03). Genetically high iron status was positively associated with liver cancer and inversely associated with brain cancer.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3390/nu12020526DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7071358PMC
February 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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41588-019-0537-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6974400PMC
January 2020

Genetic predisposition to mosaic Y chromosome loss in blood.

Nature 2019 11 20;575(7784):652-657. Epub 2019 Nov 20.

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

Mosaic loss of chromosome Y (LOY) in circulating white blood cells is the most common form of clonal mosaicism, yet our knowledge of the causes and consequences of this is limited. Here, using a computational approach, we estimate that 20% of the male population represented in the UK Biobank study (n = 205,011) has detectable LOY. We identify 156 autosomal genetic determinants of LOY, which we replicate in 757,114 men of European and Japanese ancestry. These loci highlight genes that are involved in cell-cycle regulation and cancer susceptibility, as well as somatic drivers of tumour growth and targets of cancer therapy. We demonstrate that genetic susceptibility to LOY is associated with non-haematological effects on health in both men and women, which supports the hypothesis that clonal haematopoiesis is a biomarker of genomic instability in other tissues. Single-cell RNA sequencing identifies dysregulated expression of autosomal genes in leukocytes with LOY and provides insights into why clonal expansion of these cells may occur. Collectively, these data highlight the value of studying clonal mosaicism to uncover fundamental mechanisms that underlie cancer and other ageing-related diseases.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41586-019-1765-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6887549PMC
November 2019

A transcriptome-wide association study of high-grade serous epithelial ovarian cancer identifies new susceptibility genes and splice variants.

Nat Genet 2019 05 1;51(5):815-823. Epub 2019 May 1.

Center for Bioinformatics and Functional Genomics, Department of Biomedical Sciences, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA.

We sought to identify susceptibility genes for high-grade serous ovarian cancer (HGSOC) by performing a transcriptome-wide association study of gene expression and splice junction usage in HGSOC-relevant tissue types (N = 2,169) and the largest genome-wide association study available for HGSOC (N = 13,037 cases and 40,941 controls). We identified 25 transcriptome-wide association study significant genes, 7 at the junction level only, including LRRC46 at 19q21.32, (P = 1 × 10), CHMP4C at 8q21 (P = 2 × 10) and a PRC1 junction at 15q26 (P = 7 × 10). In vitro assays for CHMP4C showed that the associated variant induces allele-specific exon inclusion (P = 0.0024). Functional screens in HGSOC cell lines found evidence of essentiality for three of the new genes we identified: HAUS6, KANSL1 and PRC1, with the latter comparable to MYC. Our study implicates at least one target gene for 6 out of 13 distinct genome-wide association study regions, identifying 23 new candidate susceptibility genes for HGSOC.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41588-019-0395-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6548545PMC
May 2019

Genome-wide association studies identify susceptibility loci for epithelial ovarian cancer in east Asian women.

Gynecol Oncol 2019 05 19;153(2):343-355. Epub 2019 Mar 19.

Department of Obstetrics and Gynaecology,Hebei Medical University, Fourth Hospital, Shijiazhuang, China.

Objective: Genome-wide association studies (GWASs) for epithelial ovarian cancer (EOC) have focused largely on populations of European ancestry. We aimed to identify common germline variants associated with EOC risk in Asian women.

Methods: Genotyping was performed as part of the OncoArray project. Samples with >60% Asian ancestry were included in the analysis. Genotyping was performed on 533,631 SNPs in 3238 Asian subjects diagnosed with invasive or borderline EOC and 4083 unaffected controls. After imputation, genotypes were available for 11,595,112 SNPs to identify associations.

Results: At chromosome 6p25.2, SNP rs7748275 was associated with risk of serous EOC (odds ratio [OR] = 1.34, P = 8.7 × 10) and high-grade serous EOC (HGSOC) (OR = 1.34, P = 4.3 × 10). SNP rs6902488 at 6p25.2 (r = 0.97 with rs7748275) lies in an active enhancer and is predicted to impact binding of STAT3, P300 and ELF1. We identified additional risk loci with low Bayesian false discovery probability (BFDP) scores, indicating they are likely to be true risk associations (BFDP <10%). At chromosome 20q11.22, rs74272064 was associated with HGSOC risk (OR = 1.27, P = 9.0 × 10). Overall EOC risk was associated with rs10260419 at chromosome 7p21.3 (OR = 1.33, P = 1.2 × 10) and rs74917072 at chromosome 2q37.3 (OR = 1.25, P = 4.7 × 10). At 2q37.3, expression quantitative trait locus analysis in 404 HGSOC tissues identified ESPNL as a putative candidate susceptibility gene (P = 1.2 × 10).

Conclusion: While some risk loci were shared between East Asian and European populations, others were population-specific, indicating that the landscape of EOC risk in Asian women has both shared and unique features compared to women of European ancestry.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.ygyno.2019.02.023DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6754211PMC
May 2019

The association between weight at birth and breast cancer risk revisited using Mendelian randomisation.

Eur J Epidemiol 2019 Jun 8;34(6):591-600. Epub 2019 Feb 8.

Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.

Observational studies suggest that higher birth weight (BW) is associated with increased risk of breast cancer in adult life. We conducted a two-sample Mendelian randomisation (MR) study to assess whether this association is causal. Sixty independent single nucleotide polymorphisms (SNPs) known to be associated at P < 5 × 10 with BW were used to construct (1) a 41-SNP instrumental variable (IV) for univariable MR after removing SNPs with pleiotropic associations with other breast cancer risk factors and (2) a 49-SNP IV for multivariable MR after filtering SNPs for data availability. BW predicted by the 41-SNP IV was not associated with overall breast cancer risk in inverse-variance weighted (IVW) univariable MR analysis of genetic association data from 122,977 breast cancer cases and 105,974 controls (odds ratio = 0.86 per 500 g higher BW; 95% confidence interval 0.73-1.01). Sensitivity analyses using four alternative methods and three alternative IVs, including an IV with 59 of the 60 BW-associated SNPs, yielded similar results. Multivariable MR adjusting for the effects of the 49-SNP IV on birth length, adult height, adult body mass index, age at menarche, and age at menopause using IVW and MR-Egger methods provided estimates consistent with univariable analyses. Results were also similar when all analyses were repeated after restricting to estrogen receptor-positive or -negative breast cancer cases. Point estimates of the odds ratios from most analyses performed indicated an inverse relationship between genetically-predicted BW and breast cancer, but we are unable to rule out an association between the non-genetically-determined component of BW and breast cancer. Thus, genetically-predicted higher BW was not associated with an increased risk of breast cancer in adult life in our MR study.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1007/s10654-019-00485-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6497616PMC
June 2019

Genetic Data from Nearly 63,000 Women of European Descent Predicts DNA Methylation Biomarkers and Epithelial Ovarian Cancer Risk.

Cancer Res 2019 02 17;79(3):505-517. Epub 2018 Dec 17.

The Center for Bioinformatics and Functional Genomics at the Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, California.

DNA methylation is instrumental for gene regulation. Global changes in the epigenetic landscape have been recognized as a hallmark of cancer. However, the role of DNA methylation in epithelial ovarian cancer (EOC) remains unclear. In this study, high-density genetic and DNA methylation data in white blood cells from the Framingham Heart Study ( = 1,595) were used to build genetic models to predict DNA methylation levels. These prediction models were then applied to the summary statistics of a genome-wide association study (GWAS) of ovarian cancer including 22,406 EOC cases and 40,941 controls to investigate genetically predicted DNA methylation levels in association with EOC risk. Among 62,938 CpG sites investigated, genetically predicted methylation levels at 89 CpG were significantly associated with EOC risk at a Bonferroni-corrected threshold of < 7.94 × 10. Of them, 87 were located at GWAS-identified EOC susceptibility regions and two resided in a genomic region not previously reported to be associated with EOC risk. Integrative analyses of genetic, methylation, and gene expression data identified consistent directions of associations across 12 CpG, five genes, and EOC risk, suggesting that methylation at these 12 CpG may influence EOC risk by regulating expression of these five genes, namely , and . We identified novel DNA methylation markers associated with EOC risk and propose that methylation at multiple CpG may affect EOC risk via regulation of gene expression. SIGNIFICANCE: Identification of novel DNA methylation markers associated with EOC risk suggests that methylation at multiple CpG may affect EOC risk through regulation of gene expression.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1158/0008-5472.CAN-18-2726DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6359948PMC
February 2019

Association analysis identifies 65 new breast cancer risk loci.

Nature 2017 11 23;551(7678):92-94. Epub 2017 Oct 23.

Department of Clinical Genetics, VU University Medical Center, Amsterdam, The Netherlands.

Breast cancer risk is influenced by rare coding variants in susceptibility genes, such as BRCA1, and many common, mostly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. Here we report the results of a genome-wide association study of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry. We identified 65 new loci that are associated with overall breast cancer risk at P < 5 × 10. The majority of credible risk single-nucleotide polymorphisms in these loci fall in distal regulatory elements, and by integrating in silico data to predict target genes in breast cells at each locus, we demonstrate a strong overlap between candidate target genes and somatic driver genes in breast tumours. We also find that heritability of breast cancer due to all single-nucleotide polymorphisms in regulatory features was 2-5-fold enriched relative to the genome-wide average, with strong enrichment for particular transcription factor binding sites. These results provide further insight into genetic susceptibility to breast cancer and will improve the use of genetic risk scores for individualized screening and prevention.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/nature24284DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5798588PMC
November 2017

Identification of ten variants associated with risk of estrogen-receptor-negative breast cancer.

Nat Genet 2017 Dec 23;49(12):1767-1778. Epub 2017 Oct 23.

Department of Epidemiology, University of California, Irvine, Irvine, California, USA.

Most common breast cancer susceptibility variants have been identified through genome-wide association studies (GWAS) of predominantly estrogen receptor (ER)-positive disease. We conducted a GWAS using 21,468 ER-negative cases and 100,594 controls combined with 18,908 BRCA1 mutation carriers (9,414 with breast cancer), all of European origin. We identified independent associations at P < 5 × 10 with ten variants at nine new loci. At P < 0.05, we replicated associations with 10 of 11 variants previously reported in ER-negative disease or BRCA1 mutation carrier GWAS and observed consistent associations with ER-negative disease for 105 susceptibility variants identified by other studies. These 125 variants explain approximately 16% of the familial risk of this breast cancer subtype. There was high genetic correlation (0.72) between risk of ER-negative breast cancer and breast cancer risk for BRCA1 mutation carriers. These findings may lead to improved risk prediction and inform further fine-mapping and functional work to better understand the biological basis of ER-negative breast cancer.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/ng.3785DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5808456PMC
December 2017

Germline whole exome sequencing and large-scale replication identifies as a likely high grade serous ovarian cancer susceptibility gene.

Oncotarget 2017 Aug 3;8(31):50930-50940. Epub 2017 Mar 3.

Department of Health Research and Policy - Epidemiology, Stanford University School of Medicine, Stanford, California, USA.

We analyzed whole exome sequencing data in germline DNA from 412 high grade serous ovarian cancer (HGSOC) cases from The Cancer Genome Atlas Project and identified 5,517 genes harboring a predicted deleterious germline coding mutation in at least one HGSOC case. Gene-set enrichment analysis showed enrichment for genes involved in DNA repair (p = 1.8×10). Twelve DNA repair genes - and - were prioritized for targeted sequencing in up to 3,107 HGSOC cases, 1,491 cases of other epithelial ovarian cancer (EOC) subtypes and 3,368 unaffected controls of European origin. We estimated mutation prevalence for each gene and tested for associations with disease risk. Mutations were identified in both cases and controls in all genes except , where we found no evidence of mutations in controls. In we observed a higher mutation frequency in HGSOC cases compared to controls (29/3,107 cases, 0.96 percent; 13/3,368 controls, 0.38 percent; P=0.008) with little evidence for association with other subtypes (6/1,491, 0.40 percent; P=0.82). The relative risk of HGSOC associated with deleterious mutations was estimated to be 2.5 (95% CI 1.3 - 5.0; P=0.006). In summary, whole exome sequencing of EOC cases with large-scale replication in case-control studies has identified as a likely novel susceptibility gene for HGSOC, with mutations associated with a moderate increase in risk. These data may have clinical implications for risk prediction and prevention approaches for high-grade serous ovarian cancer in the future and a significant impact on reducing disease mortality.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.18632/oncotarget.15871DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5584218PMC
August 2017
-->