Kraft, Peter

In this work related to familial aggregation of familial venous thromboembolism, the investigators report genomic and transcriptomic association of 16 novel susceptibility loci for venous thromboembolism.

AbstractEpidemiologic studies show an increased risk of non‐Hodgkin lymphoma (NHL) in patients with autoimmune disease (AD), due to a combination of shared environmental factors and/or genetic factors, or a causative cascade: chronic inflammation/antigen‐stimulation in one disease leads to another. Here we assess shared genetic risk in genome‐wide‐association‐studies (GWAS).Secondary analysis of GWAS of NHL subtypes (chronic lymphocytic leukemia, diffuse large B‐cell lymphoma, follicular lymphoma, and marginal zone lymphoma) and ADs (rheumatoid arthritis, systemic lupus erythematosus, and multiple sclerosis). Shared genetic risk was assessed by (a) description of regional genetic of overlap, (b) polygenic risk score (PRS), (c)"diseasome", (d)meta‐analysis.Descriptive analysis revealed few shared genetic factors between each AD and each NHL subtype. The PRS of ADs were not increased in NHL patients (nor vice versa). In the diseasome, NHLs shared more genetic etiology with ADs than solid cancers (p = .0041). A meta‐analysis (combing AD with NHL) implicated genes of apoptosis and telomere length.This GWAS‐based analysis four NHL subtypes and three ADs revealed few weakly‐associated shared loci, explaining little total risk. This suggests common genetic variation, as assessed by GWAS in these sample sizes, may not be the primary explanation for the link between these ADs and NHLs.

Abstract Background: Prospective validation of breast cancer risk models integrating classical risk factors and genetic variants is required for risk-stratified prevention and screening strategies. The objective of this study was to validate a breast cancer risk model integrating classical risk factors and a 313-variant polygenic risk score (PRS) in multiple prospective cohort studies, and to project five-year risk of breast cancer in six different countries. Methods: The study population included 7,529 cases and 230,103 controls from 14 prospective cohort studies in Australia, Germany, the Netherlands, Sweden, UK, and USA. We used the Individualized Coherent Absolute Risk Estimator (iCARE) tool for risk model building, validation, and risk projection. Expected five-year risk of invasive or in situ breast cancer was compared to observed risk, overall and within deciles of expected risk using goodness of fit statistics. We evaluated calibration of the relative risk through meta-analysis across cohorts, and of the absolute risk within each cohort. Model discrimination was evaluated using the area under the curve (AUC), and percentages of women crossing risk thresholds. Projections of five-year risk distributions were estimated for women of European ancestry aged 50-70 years in the general populations of these six countries. Results: Analysis showed overall good calibration of the integrated iCARE-based model relative risk for both women younger than 50 years (χ2=14.9, P=0.09) and aged 50 years or older (χ2=14.6, P=0.10), with a small overestimation of risk for women in the highest decile of expected risk (RR = 3.5 expected vs 2.3 (95% CI 1.6 to 3.2) observed for women <50 years; and 2.8 expected vs 2.3 (95% CI 2.0 to 2.7) observed for women 50+ years). The age-adjusted AUCs for the integrated model were 63.1 (95% CI 60.9 to 65.3) and 62.9 (95% CI 61.8 to 64.0), for the two age groups respectively. The calibration of absolute risk showed substantial variation across cohorts, particularly for the older group, but had no systematic bias. Model based projections in the general populations showed that compared to the population average, women in the 1st and 99th percentiles of the integrated risk score had relative risks 0.19 and 3.56 respectively. The proportion of women of European ancestry aged 50-70 years with a five-year risk greater than 3% (threshold for consideration of risk-lowering drugs by U.S. Preventive Services Task Force) ranged from 7.1% in Germany to 18.2% in the US, which corresponds to ~5.5 million women in the US. Conclusions: Five-year risk predictions from a model with classical risk factors and PRS are well calibrated and provide substantial risk stratification across multiple cohorts in six different countries. Further studies are needed to evaluate the clinical utility of the validated model for risk stratified screening and prevention of breast cancer. Citation Format: Parichoy Pal Choudhury, Amber Wilcox, Chi Gao, Brian Carter, Anika Husing, Mark Brook, Mikael Eriksson, Kara Martin, Chris Scott, Min Shi, Thomas Ahearn, Michael Jones, Nick Orr, Minouk Schoemaker, Kamila Czene, Jenny Chang-Claude, Jacques Simard, Doug Easton, Marjanka K. Schmidt, Dale Sandler, Clarice R. Weinberg, Celine Vachon, Roger Milne, Per Hall, Anthony Swerdlow, Rudolph Kaaks, Myrto Barrdahl, Mia Gaudet, Antonis Antoniou, Peter Kraft, Montserrat Garcia-Closas, Nilanjan Chatterjee. Validation of breast cancer risk model incorporating classical risk factors and polygenic risk scores in 14 prospective cohort studies in 6 countries [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 962.

Abstract Background: Understanding the joint effect on breast cancer risk of rare pathogenic variants in cancer predisposition genes and polygenic risk scores (PRS) from common variants can enable a precision approach to breast cancer management. Previous work found that PRS were associated with breast cancer risk in BRCA1 and BRCA2 mutation carriers recruited from cancer genetics clinics (Kuchenbaecker et al. JNCI 2017). The joint effects of pathogenic variants and PRS have not been studied in samples drawn from the general population. There is also no existing study evaluating the effect of PRS in mutation carriers in genes other than BRCA1/2. Here we evaluate the joint effects of PRS and pathogenic mutations in established cancer predisposition genes in a population-based case-control sample. Method: We analyzed 53,199 European-ancestry individuals (20,730 controls and 21,272 cases) drawn from 7 cohorts and 2 population-based case-control studies in the CAnceR RIsk Estimates Related to Susceptibility” (CARRIERS) consortium. Targeted sequencing was performed using dual bar-coded QIAseq. Mutation calling was conducted with Haplotype Caller and Vardict. We sequenced 18 breast cancer predisposition genes: ATM, BARD1, BRCA1, BRCA2, BRIP1, CDH1, CDKN2A, CHECK2, FANCC, MLH1, MSH2, MSH6, NF1, PALB2, PTEN, RAD51C, RAD51D and TP53. The PRS was calculated based on 128 common variants using effect estimates from the largest published breast cancer GWAS. The PRS was standardized to a mean of 0 and standard deviation of 1. Logistic regression was performed to assess the combined effect of identified mutation and common variants (including main and interaction effects for carrier status and PRS). Results: A total of 1,770 pathogenic mutations were observed. About 1% of the study sample had mutations in either BRCA1 (n=209) or BRCA2 gene (n=305), and 2.2% had mutations in other genes (n=1,176). The effect of PRS in BRCA1 carriers was OR= 0.97 (95%CI: 0.62, 1.52); however, this is not statistically significantly different from the PRS in non-carriers [OR=1.23 (95%CI: 1.20, 1.25)] or previous estimates in carriers [OR: 1.14, 95%CI: 1.11-1.17]. The effect of PRS in BRCA2 carriers was OR=1.87 (95%CI: 1.31, 2.78) which was statistically significantly different from that of the non-carriers. Among the mutation carriers in genes other than BRCA, the effect of PRS on breast cancer was OR=1.00 (95%CI: 0.88,1.15). Conclusion: Consistent with previous studies, we did not find evidence that the effect of the PRS among BRCA1 carriers was statistically significantly different than non-carriers. We found some evidence that the PRS effect may be larger among BRCA2 carriers than non-carriers. Our results also suggest that PRS may not have a strong effect on breast cancer risk in mutation carriers of other predisposition genes; further work is needed for verification. Citation Format: Chi Gao, Chunling Hu, Steven N. Hart, Rohan Gnanaolivu, Kun Y. Lee, Jenna Lilyquist, Nicholas J. Boddicker, Bruce Eckloff, Raed Samara, Josh Klebba, Paul Auer, Leslie Bernstein, Mia Gaudet, Hoda Anton-Culver, Amy Trentham-Dietz, Julie R. Palmer, Song Yao, Christopher Haiman, Janet E. Olson, Susan Domchek, Jeffrey Weitzel, David Goldgar, Katherine L. Nathanson, Eric C. Polley, Fergus J. Couch, Peter Kraft. The joint effects of polygenic risk scores and pathogenic variants in cancer predisposition genes on breast cancer risk in the general population: results from the CARRIERS study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4177.

Abstract Clinical germline genetic testing of cancer predisposition gene panels is used to identify women at increased risk for breast cancer. Pathogenic mutations in cancer predisposition genes are associated with established risks of breast cancer and are actively used for risk management of breast cancer for women qualifying for genetic testing because of a family history of breast and/or ovarian cancer or young age of diagnosis. However, the risks of breast cancer associated with mutations in these genes have likely been overestimated for many women in the general population. The goal of the “CAnceR RIsk Estimates Related to Susceptibility” (CARRIERS) study was to estimate breast cancer risks associated with mutations in hereditary cancer panel genes. Germline DNA from 32,298 breast cancer patients and 31,869 matched unaffected controls enrolled in cohorts and population-based case-control studies were sequenced to identify pathogenic mutations in 37 cancer predisposition genes.The average age at diagnosis was 61.2 years and the average age of last follow-up was 62.1 years. DNA was subjected to dual bar-coded QIAseq multiplex PCR-based amplification of 1733 target regions in 37 predisposition genes. Products from 768 samples were pooled and sequenced in a single lane of a HiSeq 4000 system. Mutations were called by GATK Haplotype Caller and Vardict.High quality sequence data was obtained for 99.3% of target regions. Pathogenic mutations in 12 known breast cancer predisposition genes were identified in 6.2% of all breast cancer cases and 2.1% of controls; and in 6.7% of African American breast cancer cases and 1.8% of controls. In case-control association analyses adjusted for age at diagnosis or last follow up and family history of breast and ovarian cancer, mutations in BRCA1, BRCA2, and PALB2 were associated with high risks of breast cancer (odds ratio (OR)>4.0). Mutations in CHEK2 and BARD1 were associated with moderate risks of breast cancer (OR>2.0), whereas mutations in ATM had lower clinical relevance (OR=1.6). Stratification by ER, PR, and HER2 status of tumors found that BRCA1, BRCA2, PALB2 and TP53 were associated with high risks of studies of triple negative breast cancer (TNBC), and that BARD1, BRIP1, FANCM, and RAD51C were associated with moderate risks of TNBC. Overall, results from the CARRIERS study establish that mutations in predisposition genes are associated with lower risks of breast cancer in the general population than in high-risk families. The age-related estimates of breast cancer risk for each of the hereditary cancer panel genes in this study may inform on the use of cancer screening and other risk management strategies for women in the general population with mutations in predisposition genes. Citation Format: Fergus J. Couch, Chunling Hu, Steven N. Hart, Rohan Gnanaolivu, Jenna Lilyquist, Kun Y. Lee, Chi Gao, Bruce Eckloff, Hoda Anton-Culver, Paul Auer, Leslie Bernstein, Mia Gaudet, Christopher Haiman, Julie Palmer, Amy Tentham-Dietz, Song Yao, Susan Domchek, Jeffrey N. Weitzel, David E. Goldgar, Katherine L. Nathanson, Peter Kraft, Eric C. Polley. Population-based breast cancer risk estimates associated with cancer predisposition gene mutations from 32,298 breast cancer patients and 31,869 matched unaffected controls from the CARRIERS study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4169.

Abstract Pancreatic Ductal Adenocarcinoma (PDAC) is the third leading cause of cancer-related deaths in United States with a 5-year survival rate of only 8%. Inherited predisposition plays an important role in PDAC risk. Rare, moderately to highly penetrant mutations in hereditary cancer and pancreatitis genes, identified in families with a high incidence of disease, account for a small fraction of cases. At the other end of the spectrum, common risk variants of low penetrance have been discovered through genome-wide association studies (GWAS). Currently, over 20 common PDAC risk signals have been identified through GWAS in populations of European ancestry. However, these loci explain only a small fraction of genetic heritability for PDAC, and the causal genes for the large majority of these are unknown. Most susceptibility alleles discovered through GWAS are located in noncoding regions of the genome and are likely to function through allele specific regulation of gene expression. Transcriptome-wide association studies integrate expression quantitative trait loci (eQTL) with GWAS data to discover genes whose cis-regulated expression is associated with complex traits. To identify novel susceptibility loci and likely causal genes, we applied this approach to PDAC. Firstly, we used two reference datasets generated from histologically normal pancreatic tissue samples from individuals of European ancestry, the DCEG/LTG (n=95) and Genotype-Tissue Expression (GTEx v7, n=174), to build robust predictors for gene expression (n=2,872-5,906; r2>0.01), using 5 different models (Top1, Lasso, Enet, Blup and Bslmm) in FUSION and PrediXcan. Gene expression predictors (n=2,043-21,422) were also generated by Enet in 48 different tissues (n=74-421 samples) from 608 individuals of European ancestry (GTEx). We then applied these predictor models to PDAC GWAS summary statistics from 9,040 PC cases and 12,496 controls. We discovered 24 genes whose genetically predicted expression is significantly associated with PDAC risk (FDR < 0.05), including 13 candidate genes at 10 novel loci (CELA3B, SMC2, SMC2-AS1, RP11-80H5.9, SMUG1, BTBD6, RCCD1, PNMT, CDK12, PGAP3, SUPT4H1, RP11-888D10.3 and PGPEP1) and 11 at 5 known risk loci (TERT, CLPTM1L, ZDHHC11B, INHBA, ABO, PDX1, KLF5, WDR59, CFDP1, BCAR1 and TMEM170A). Pathway enrichment analysis for genes differentially expressed in the top vs. bottom quartile of CELA3B expression highlighted higher expression of inflammatory and immune response genes in both the DCEG/LTG and GTEx pancreatic transcriptome datasets, indicating that low expression of this gene may be associated with an inflammatory state in the pancreas. Our findings showcase the utility of integrating multiple datasets to generate hypotheses and provide novel clues for the genetic mechanisms underlying pancreatic cancer risk. Citation Format: Jun Zhong, Ashley Jermusyk, Lang Wu, Jason W. Hoskins, Irene Collins, Mingfeng Zhang, Song Lei, Charles C. Chung, Tongwu Zhang, Wenming Xiao, Rachael Stolzenberg-Solomon, Alison P. Klein, Brian M. Wolpin, Xiao-Ou Shu, Stephen J. Chanock, Sara Olson, Nilanjan Chatterjee, Jill Smith, Jianxin Shi, Peter Kraft, Gloria M. Petersen, Wei Zheng, Laufey T. Amundadottir. Large-scale transcriptome-wide association study (TWAS) identifies novel candidate susceptibility genes for pancreatic cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1591.

104 Background: The identification of pathogenic mutations in breast cancer susceptibility genes through clinical genetic testing leads to focused screening and prevention strategies for women at increased risk of cancer. However, the frequency of mutations and the risks of cancer associated with breast cancer predisposition genes has not been established for the African American population. Methods: Germline DNA samples from African American women (5,054 breast cancer cases and 4,993 age-matched unaffected controls) from 10 U.S. studies were tested for mutations in 20 established breast cancer predisposition genes using a QIAseq multiplex amplicon panel as part of the “CAnceR RIsk Estimates Related to Susceptibility” (CARRIERS) study. The frequency of mutations in each gene and associations between mutations and breast cancer risk, adjusted for study design, age, and first-degree family history of breast cancer, were evaluated. Results: The mean age at diagnosis of breast cancer cases was 54.4 years and the mean age of controls was 55.2 years. 18.2% of cases and 10.8% of controls reported a first-degree family history of breast cancer. Pathogenic mutations in any of the 20 breast cancer predisposition genes were identified in 7.6% of breast cancer cases and 2.4% of controls. In multivariable analyses, mutations in BRCA1, BRCA2, and PALB2 were associated with high risks of breast cancer (odds ratio (OR) > 5.0). Mutations in CHEK2 were associated with moderate risks of breast cancer (OR > 2.0), whereas mutations in ATM had lower clinical relevance (OR = 1.8). Mutations in BRCA1, BRCA2, PALB2, and RAD51D, but not CHEK2 or ATM, were associated with increased risks of estrogen receptor negative breast cancer. Conclusions: Cancer predisposition genes confer similar risks of breast cancer in the African American population as in non-Hispanic Whites. These studies provide important insights into the risks of breast cancer associated with predisposition gene mutations in the African American population.

Abstract Background: Clinical germline genetic testing of cancer predisposition gene panels is used to identify women at increased risk for breast cancer. The identification of pathogenic mutations in established high and moderate predisposition genes may result in improved risk management of breast cancer for tested patients and their family members through tailored screening, prophylactic surgeries, or chemoprevention. However, the risks of breast cancer associated with mutations in these genes have likely been overestimated for many women in the general population because previous studies have focused on individuals with a family history of breast and/or ovarian cancer, early onset disease, or triple negative breast cancer. The goal of the “CAnceR RIsk Estimates Related to Susceptibility” (CARRIERS) study is to estimate breast cancer risks associated with mutations in hereditary cancer panel genes in the general population. Methods: Germline DNA samples from blood or saliva were obtained from 39,439 breast cancer patients and matched unaffected controls from six US-based cohorts (BWHS, CPSII, CTS, MEC, NHS1, NHS2, WHI). DNA was subjected to dual bar-coded QIAseq multiplex PCR-based amplification of 1733 target regions covering all coding regions of 37 cancer predisposition genes and sequenced. Mutation calling was conducted with Haplotype Caller and Vardict. Results: High quality sequence data was obtained for 38,990 of 39,439 samples (98.9%) and for 99.3% of target regions. Pathogenic mutations in 12 known breast cancer predisposition genes were identified 4.5% of all breast cancer cases and 2.1% of controls; and in 6.7% of African American breast cancer cases and 1.8% of controls. Differences in mutation frequencies were observed by age with mutations in 7.8% of cases diagnosed £50 years of age and 4.0% of cases diagnosed over age 50. Mutations in ATM, BRCA1, BRCA2, and PALB2 were enriched 2 to 3-fold in cases diagnosed under age 50 relative to older cases. No change in frequency of CHEK2 mutations by age was observed. In case-control analyses mutations in BRCA1, BRCA2 and PALB2 were significantly associated with a high risk of breast cancer (odds ratio (OR)>4.0). Of these, BRCA1 and BRCA2 displayed ORs of 13.5 and 16.6 in the £50 age group, but only 5.7 and 3.2 in the >50 age group. Only minor age-specific effects were observed for PALB2. Mutations in ATM and CHEK2 were associated with moderate risks of breast cancer (OR=2.0 to 4.0) in the younger age group, but not in the older age group. Conclusions: Results from the CARRIERS cohort-based study establish that mutations in known breast cancer predisposition genes are associated with only moderate risks of breast cancer in the general population. However, risks are substantially increased for BRCA1 and BRCA2 but not ATM, CHEK2 or PALB2 mutations in those £50 years of age. The age-related estimates of breast cancer risk for each of the hereditary cancer panel genes in this study may inform selection of individuals in the general population who may benefit from genetic testing and associated risk management strategies. Citation Format: Couch FJ, Hu C, Hart SN, Gnanaolivu RD, Lilyquist J, Lee KY, Gao C, Eckloff B, Samara R, Klebba J, Auer P, Bernstein L, Gaudet M, Haiman C, Palmer JR, Yao S, Domchek SM, Weitzel JN, Goldgar DE, Nathanson KL, Kraft P, Polley EC. Age-related breast cancer risk estimates for the general population based on sequencing of cancer predisposition genes in 19,228 breast cancer patients and 20,211 matched unaffected controls from US based cohorts in the CARRIERS study [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr GS2-01.

Abstract Objective Genome-wide association studies (GWAS) identify associations of individual SNPs with cancer risk but usually only explain a fraction of the inherited variability. Pathway analysis of genetic variants has been shown for many disorders to be a powerful tool in discovering novel networks of susceptibility genes. Design We have conducted a large agnostic pathway-based meta-analysis of GWAS data using the summary-based adaptive rank truncated product (sARTP) method to identify novel gene sets and pathways associated with pancreatic ductal adenocarcinoma (PDA) in 9,040 cases and 12,495 controls. We performed expression quantitative trait loci (eQTL) analysis and functional annotation of the top SNPs in genes identified in PDA-associated gene sets and pathways. Results We identified 14 gene sets and pathways associated with PDA at FDR < 0.05. Five of the strongest signals (P-value ≤ 1.3x10-5 Bonferroni corrected) were in genes from KEGG maturity onset diabetes of the young, Reactome regulation of beta cell development, Biocarta role of epidermal growth factor (EGF) receptor transactivation by G-protein-coupled receptors in cardiac hypertrophy pathway, Nikolsky breast cancer chr17q11-q21 amplicon gene set, and Pujana ATM Pearson correlation coefficient (PCC) network gene set. We identified and validated rs876493 and three correlated SNPs (PGAP3) and rs3124737 (CASP7) as eQTLs in two normal derived pancreas tissue datasets. Conclusion Our agnostic gene set and pathway analysis integrated with functional annotation and eQTL analysis provides novel insight into genes and pathways that may be biologically relevant for risk of PDA. Citation Format: Naomi Walsh, Han Zhang, Paula L. Hyland, Qi Yang, Evelina Mocci, Mingfeng Zhang, Erica J. Childs, Zhaoming Wang, Stephen Chanock, Patricia Hartge, Robert Hoover, Peter Kraft, Donghui Li, Eric J. Jacobs, Gloria M. Petersen, Brian M. Wolpin, Harvey A. Risch, Laufey T. Amundadottir, Kai Yu, Alison P. Klein, Rachael Z. Stolzenberg-Solomon. Large pathway and gene set analysis of GWAS data identifies novel associations for pancreatic cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 242.