Shared heritability and functional enrichment across six solid cancers

ARTICLE Shared heritability and functional enrichment across six solid cancers Xia Jiang et al. # Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/ neck cancer (r g =0.57, p=4.6 × 10−8), breast and ovarian cancer (r g =0.24, p=7×10 −5), breast and lung cancer (r g =0.18, p=1.5 × 10−6) and breast and colorectal cancer (r g =0.15, p=1.1 × 10−4). We also found that multiple cancers are genetically correlated with noncancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis. https://doi.org/10.1038/s41467-018-08054-4 OPEN Correspondence and requests for materials should be addressed to X.J. (email: [email protected]) or to P.K. (email: [email protected]) or to S.Löm. (email: [email protected]). # A full list of authors and their affiliations appears at the end of the paper. NATURE COMMUNICATIONS | (2019) 10:431 | https://doi.org/10.1038/s41467-018-08054-4 | www.nature.com/naturecommunications 1 1234567890():,; Inherited genetic variation plays an important role in cancer etiology. Large twin studies have demonstrated an excess familial risk for cancer sites including, but not limited to, breast, colorectal, head/neck, lung, ovary, and prostate with heritability estimates ranging between 9% (head/neck) to 57% (prostate)1–3. Data from nation-wide and multi-generation registries further show that elevated cancer risks go beyond nuclear families and isolated types, as family history of a specific cancer can increase risk for other cancers4–6. Additional evidence for a shared genetic component have been demonstrated by cross-cancer genome-wide association study (GWAS) meta-analyses, which set out to identify genetic variants associated with more than one cancer type. Fehringer et al. studied breast, colorectal, lung, ovarian, and prostate cancer, and identified a novel locus at 1q22 associated with both breast and lung cancer7. Kar et al. focused on three hormone-related cancers (breast, ovarian, and prostate), and identified seven novel susceptibility loci shared by at least two cancers8. Previous attempts to estimate the genetic correlation across cancers using GWAS data9–12 have mostly relied on restricted maximum likelihood (REML) implemented in GCTA (genomewide complex trait analysis)13 and individual-level genotype data. However, these studies have had limited sample sizes, yielding inconclusive results. Sampson et al. quantified genetic correlations across 13 cancers in European ancestry populations and identified four cancer pairs with nominally significant genetic correlations (bladder–lung, testis–kidney, lymphoma–osteosarcoma, and lymphoma–leukemia)9. They did not observe any significant genetic correlations across common solid tumors including cancers of the breast, lung and prostate9. REML becomes computationally challenging for large sample sizes and is sensitive to technical artifacts. LD score regression (LDSC)14,15 overcomes these issues by leveraging the relationship between association statistics and LD patterns across the genome. We recently used cross-trait LDSC to quantify genetic correlations across six cancers based on a subset of the data included here and found moderate correlations between colorectal and pancreatic cancer, as well as between lung and colorectal cancer16. However, the average sample size was only 11,210 cases and 13,961 controls per cancer, resulting in imprecise estimates with wide confidence intervals. In addition to the development of novel analytical methods tailored to genomic data, several high-quality functional annotations have recently been released into the public domain through large-scale efforts. For example, the ENCODE consortium has built a comprehensive and informative parts list of functional elements in the human genome (http://www.nature. com/encode/#/threads), which allows for the analysis of components of SNP-heritability to unravel the functional architecture of complex traits. Here, we use summary statistics from the largest-to-date European ancestry GWAS of breast, colorectal, head/neck, lung, ovary, and prostate cancer with an average sample size of 49,369 cases and 50,219 controls per cancer, to quantify genetic correlations between cancers and their subtypes. We also use GWAS summary statistics for 38 non-cancer traits (average N =113,808 per trait), to quantify the genetic correlations between the six cancers and other diseases. Furthermore, we assessed the proportion of cancer heritability attributable to specific functional categories, with the goal of identifying functional elements that are enriched for SNP-heritability. Our comprehensive analysis identifies statistically significant genetic correlations between lung and head/neck cancer, breast and ovarian cancer, breast and lung cancer, and breast and colorectal cancer. We also find multiple cancers to be genetically correlated with non-cancer traits including smoking, psychiatric diseases, and metabolic traits. Functional enrichment analysis reveals a significant contribution of conserved and regulatory regions to cancer heritability. Our results suggest that solid tumors arising across tissues share in part a common germline genetic basis. Results Heritability estimates across cancers.Wefirst estimated cancerspecific heritability causally explained by common SNPs (h2 g) using LDSC (note that this quantity is slightly different from the h2 gas defined in Yang et al.17 which estimates the heritability due to genotyped and imputed SNPs) (see Methods). Estimates of h2 g on the liability scale ranged from 0.03 (ovarian) to 0.25 (prostate) (Supplementary Table 1). After removing genome-wide significant (p<5×10 −8) loci, defined as all SNPs within 500 kb of the most significant SNP in a given region (Supplementary Data 1), we observed an ~50% decrease in SNP-heritability for prostate and breast cancer, and ~20% decrease for lung, ovarian, and colorectal cancer, despite the fact that we were only excluding 1% (colorectal cancer) to 5% (breast cancer) of the genome. In contrast, the SNP-heritability for head/neck cancer was not affected by removing genome-wide significant loci (Fig. 1a). For most of the cancers, the GWAS significant loci for that particular cancer explained most of the heritability. For some cancers, however, significant GWAS loci of other cancers also explained a non-trivial part of its heritability. For example, the significant breast cancer GWAS loci explained 10%, 15%, and 22% heritability of colorectal, ovarian and prostate cancer, respectively; the significant colorectal cancer GWAS loci explained 11% heritability of prostate cancer; the significant lung cancer GWAS loci explained 10% heritability of head/neck cancer; and the significant prostate cancer GWAS loci explained 11 and 15% heritability of breast and ovarian cancer, respectively (Supplementary Table 2). Comparing the liability-scale SNP-heritability to corresponding estimates from twin studies suggests that common SNPs can almost entirely explain the classical heritability of head/ neck cancer, whereas for other cancers, only 30–40% of heritability can be explained (Fig. 1b). Genetic correlations between cancers. We then estimated the genetic correlation between cancers using cross-trait LDSC (see Methods). After adjusting for the number of tests (p< 0.05/15 = 0.003), we found multiple significant genetic correlations Fig. 1c and Supplementary Table 1), with the strongest result observed for lung and head/neck cancer (r g =0.57, se =0.10). In addition, colorectal and lung cancer (r g =0.28, se =0.06), breast and ovarian cancer (r g =0.24, se=0.06), breast and lung cancer (r g = 0.18, se =0.04), and breast and colorectal cancer (r g =0.15, se = 0.04) showed statistically significant genetic correlations. We also observed nominally significant genetic correlations (p< 0.05) between lung and ovarian cancer (r g =0.16, se =0.08), prostate cancer and head/neck (r g =0.15, se =0.08), colorectal (r g =0.11, se =0.05), and breast cancer (r g =0.07, se =0.03) (Fig. 1c). Some cancer pairs showed minimal correlations with estimates close to 0 (ovarian and prostate: r g =0.02, se =0.07; lung and prostate: r g =−0.03, se =0.04; breast and head/neck: r g =0.03, se =0.06). We further calculated the cross-cancer genetic correlation based on data after excluding the GWAS significant regions of each cancer. The estimates were mostly consistent with the results calculated based on all SNPs. We conducted subtype-specific analysis for breast, lung, ovarian, and prostate cancer (Supplementary Table 1). Estrogen receptor positive (ER+) and negative (ER−) breast cancer showed a genetic correlation of 0.60 (se =0.03), indicating that the genetic contributions to these two subtypes are in part distinct. The genetic correlation between the two common lung ARTICLE NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-018-08054-4 2NATURE COMMUNICATIONS | (2019) 10:431 | https://doi.org/10.1038/s41467-018-08054-4 | www.nature.com/naturecommunications cancer subtypes adenocarcinoma and squamous cell carcinoma was similarly 0.58 (se =0.10). Further, we observed a significantly larger genetic correlation of lung cancer with ER−(r g =0.29, se =0.06) than with ER +breast cancer (r g =0.13, se =0.04) (p difference =0.002). This also held true for lung squamous cell carcinoma, which showed statistically stronger genetic correlation with ER−(r g =0.33, se =0.08) than with ER +breast cancer (r g =0.11, se =0.05) (p difference =0.0019). We observed no other statistically significant differential genetic correlations across subtypes (all p difference > 0.1). We then estimated local genetic correlations between cancers using ρ-HESS, dividing the genome into 1703 regions (see Methods) (Fig. 2and Supplementary Fig. 1). We found that although the genome-wide genetic correlation between breast and prostate cancer was modest (r g =0.07), chr10:123M (10q26.13, p=1.0 × 10−7)andchr9:20–22 M (9p21, p=1.0 × 10−6), two previously known pleiotropic regions18,showed significant genetic correlations (r g =−0.00098 and r g = 0.00046). Similarly, although the genome-wide genetic correlation between lung and prostate cancer was negligible (r g = −0.03),twopreviouslyidentified pleiotropic regions (chr6:30–31 M or 6p21.33, p=5.7 × 10−7and chr20:62M or 20q13.33, p=2.8 × 10−6) exhibited significant local genetic correlations (r g =−0.00060 and r g =0.00067). Overall, local genetic correlation analysis reinforced shared effects for 44% (31/71) of previously reported pleiotropic cancer regions (Supplementary Data 2). It also identified novel pleiotropic signals. For example, the breast and prostate cancer pleiotropic region at 2q33.1 showed significant local genetic correlation between breast and ovarian cancer (p=2.3 × 10−6). Additionally, 6p21.32, a region indicated for head/neck and prostate cancer, showed highly significant local genetic correlation for head/neck and lung cancer (p=8.6 × 10−8). Genetic correlations between cancer and other traits. Significant genetic correlations (p< 0.05/228 =0.0002) between the six cancers and 38 non-cancer traits reflected several known associations (Fig. 3and Supplementary Data 3). We observed a strong genetic correlation between smoking and lung cancer (r g =0.56, se =0.06), and similarly for head/neck cancer (r g = 0.47, se =0.08), both cancers having smoking as its primary risk factor19,20. Educational attainment was negatively genetically correlated with colorectal (r g =−0.17, se =0.04), head/neck (r g =−0.42, se =0.07), and lung cancer (r g =−0.39, se=0.04) (all p<5×10 −6). Body mass index (BMI) showed a positive genetic correlation with colorectal cancer (r g =0.15, se =0.03) and also suggestive but weak negative correlations with prostate (r g = −0.07, se =0.03) and breast cancer (r g =−0.06, se =0.03). Lung cancer showed a negative genetic correlation with lung function (r g =−0.15, se =0.04) and age at natural menopause (r g =−0.25, se =0.05), and moderate positive genetic correlations with depressive symptoms (r g =0.25, se=0.06) and waist-to-hip ratio (r g =0.16, se =0.04). Breast cancer showed a positive genetic correlation with schizophrenia (r g =0.14, se =0.03). We did not find evidence of genetic correlations between cancer and several previously suggested risk factors21–23 including cardiovascular traits (coronary artery disease, hypertension, and blood pressure) or sleep characteristics (chronotype, duration, and insomnia). Further, we did not observe genetic correlations between cancer and circulating lipids (HDL, LDL, and triglycerides) or type 2 diabetes-related traits except a significant negative correlation between HDL and lung cancer (r g =−0.14, se =0.04). We observed no significant genetic correlation between breast cancer and age at menarche (r g =−0.03, se =0.03) or age at natural menopause (r g =−0.01, se =0.03). We also did not observe notable genetic correlations between cancer and autoimmune inflammatory diseases or height. 0.25 All SNPs vs. excluding top hits (± 500 kbp) LDSC estimates vs. twin study estimates Cross heritability among the six cancers h2: based on SNPs after excluding top hits ± 500 kbp h2: top hits ± 500 kbp a b c 0.20 45% 20% 0% 25.3% 24.2% 53.9% Prostate 1 0.0241 1 1 1 1 0.15 0.029 –0.067 –0.061 0.18 0.24 0.11 0.15 0.072 0.095 1.0 0.5 –1.0 –0.5 0.0 0.16 –0.026 0.28 0.57 ** ** **** ** * * * * Prostate Ovarian Ovarian Lung Lung 0.15 0.10 0.05 0.00 1.0 0.8 0.6 0.4 0.2 0.0 LDSC heritability LDSC heritability Breast Breast Breast Colorectal Colorectal Colorectal Headneck Headneck Headneck Lung Ovarian Prostate Breast Colorectal Headneck Lung Ovarian Prostate 1.0 0.8 0.6 0.4 0.2 0.0 Twin study heritability Fig. 1 Estimates of SNP-heritability (h2 g) and cross-cancer heritability (r g ) for the six cancer types. SNP-heritability and cross-cancer heritability are calculated based on HapMap3 SNPs using LD score regression (LDSC). aThe solid bar represents overall SNP h2 gon the liability scale, calculated based on all HapMap3 SNPs. The dark green bar represents h2 gcalculated based on non-significant SNPs—the remaining SNPs after excluding genome-wide significant hits (p<5×10 −8) ± 500 kb. The black bar with density texture indicates proportion of h2 g(as reflected by the percentages displayed on top of each bar) that could be explained by top hits ±500 kb surrounded areas. The orange error bars represent 95% confidence intervals. bThe solid blue bar represents overall SNP h2 gin liability scale (no SNP exclusion), with black error bars indicating 95% confidence intervals. The red short lines correspond to classical estimates of h2measured in a twin study of Scandinavian countries (Mucci et al.2). cGenetic correlations between cancers. Estimates withstood Bonferroni corrections (p< 0.05/15) are marked with double asterisk (**), and nominal significant results (p< 0.05) are marked with single asterisk (*) NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-018-08054-4 ARTICLE NATURE COMMUNICATIONS | (2019) 10:431 | https://doi.org/10.1038/s41467-018-08054-4 | www.nature.com/naturecommunications 3 Breast_prostate Lung_prostate Observed –log10 (p) Expected –log10 (p) Expected –log10 (p) Observed –log10 (p) 8 10:123231465–123900544 6:30798168–31571217 20:62190180–62965162 6:26791233–28017818 9:20463534–22206558 11:68005825–69516129 6:28017819–28917607 1:203334734–204681067 2:214014282–215573794 6:25684587–26791232 1:154770403–156336132 7:1353067–2062397 6:28917608–29737970 3:87409732–88298372 14:35859593–38667724 3:139954597–141339096 6:28017819–28917607 11:112459488–114257727 1:44969183–46899500 8 6 64 4 2 2 0 0 6 6 4 4 2 2 0 0 Local genetic covariance 0.0007 0.0003 0.0000 –0.0003 –0.0007 –0.0005 –0.0003 –0.0008 0.002 0.001 0 0.001 0.000 0.002 0.0000 0.0008 0.0005 0.0003 –0.0010 0.002 0.001 0.000 0.002 0.001 01 2 3 4 5 6 7 8910111213141516171819202122 1 2 3 4 5 6 7 8910111213141516171819202122 1234567 Local SNP-heritability Local SNP-heritability Local genetic covariance 89 chr9:20463534–22206558 chr10:123231465-123900544 chr6:26791233–28017818 chr20:62190180–62965162 chr6:30798168–31571217 10 11 12 13 14 15 16 17 18 19 20 21 22 1 2 3 4 5 6 7 8910111213141516171819202122 1 2 3 4 5 6 7 8910111213141516171819202122 1 2 3 4 5 6 7 8910111213141516171819202122 Breast Breast & prostateLung & prostate Prostate Prostate Lung a c b d Fig. 2 Local genetic correlation between breast, lung and prostate cancer. The region-specificp-values for the local genetic covariance for breast and prostate cancer are shown in a, and for lung and prostate cancer in b. Each dot presents a specific genomic region. In the QQ plots, red color indicates significance after multiple corrections (p< 0.05/1703 regions compared), and blue color indicates nominal significance (p< 0.05/15 pairs of cancers compared). Manhattan-style plots showing the estimates of local genetic covariance for breast and prostate cancer (c), and for lung and prostate cancer (d). Although breast and prostate cancer only show modest genome-wide genetic correlation, two loci exhibit significant local genetic covariance. Similarly, albeit the negligible overall genetic correlation for lung and prostate cancer, three loci present significant local genetic covariance. In the Manhattan plots, red color indicates even number chromosomes and blue color indicates odd number chromosomes ARTICLE NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-018-08054-4 4NATURE COMMUNICATIONS | (2019) 10:431 | https://doi.org/10.1038/s41467-018-08054-4 | www.nature.com/naturecommunications Subtype analysis revealed that smoking and educational attainment showed genetic correlations with all lung cancer subtypes (Supplementary Data 3). Educational attainment, forced vital capacity and depressive symptoms showed genetic correlations with ER−but not ER +breast cancer, whilst the observed genetic correlation between schizophrenia and breast cancer was limited to ER +disease, and the genetic correlation between depressive symptoms and lung cancer was observed only for lung squamous cell carcinoma. We further assessed the support for mediated or pleiotropic causal models for non-cancer traits and cancer using the correlation between trait-specific effect sizes of genome-wide significant SNPs for pairs of phenotypes. We detected four putative directional genetic correlations (defined as p< 0.05 from a likelihood ratio (LR) comparing the best non-causal model to the best causal model) (Fig. 4), where SNPs associated with the non-cancer trait showed correlated effect estimates with cancer but the reverse was not true (circulating HDL concentrations and breast cancer, LR non-causal vs. causal =0.04, schizophrenia and breast cancer, LR non-causal vs. causal =0.003, age at natural menopause and breast cancer, LR non-causal vs. causal =0.04, and lupus and prostate cancer, LR non-causal vs. causal =0.0006). Functional enrichment analysis of cancer heritability. Finally, we partitioned SNP-heritability of each cancer by using 24 genomic functional annotations (the baseline-LD model described in Gazal et al.24) and 220 cell-type-specific histone mark annotations (the cell-type-specific model described in Finucane et al.14). Meta-analysis across the six cancers revealed statistically significant enrichments for multiple functional categories. We observed the highest enrichment for conserved regions (Table 1, Supplementary Table 3) which overlapped with only 2.6% of SNPs but explained 25% of cancer SNP-heritability Insomnia –0.17 0.47 0.14 0.09 0.11 0.14 0.25 0.13 0.11 –0.17 –0.14 0.16 0.15 0.38 0.19 1.0 0.5 0.0 –0.5 –1.0 –0.07 *P < 0.01 **P < 0.05/228 Bonferroni correction 0.18 0.56 ** ** ** **** ** ** * * * ** ** ** * ** * * * * ** * ** –0.42 –0.39 –0.25 –0.15 –0.19 Common phenotypes Psychiatric traits Metabolism/cardiovascular traits Systolic blood pressure Diastolic blood pressure a cd b Hypertension Coronary artery disease Type 2 diabetes Fasting glucose Waist hip ratio adjusted for BMI Body mass index Triglycerides Low-density lipoprotein High-density lipoprotein Ulcerative colitis Autoimmune/inflammatory traits Rheumatoid arthritis Primary biliary cirrhosis Lupus Inflammatory bowel disease Eczema Crohns disease Celiac disease Asthma Sleep duration Sleep chronotype Years of education Age at menopause Age at menarche Heel T score Smoking status Forced vital capacity FEV1/FVC ratio Height Subjective well being Schizophrenia Neuroticism Depressive symptoms Bipolar disorder Autism Anorexia Breast Colorectal Headneck Lung Ovarian Prostate Breast Colorectal Headneck Lung Ovarian Prostate Breast Colorectal Headneck Lung Ovarian Prostate Breast Colorectal Headneck Lung Ovarian Prostate Fig. 3 Cross-trait genetic correlation (r g ) analysis between cancers and non-cancer traits. The traits were divided into four categories: aCommon phenotypes, bMetabolic or cardiovascular related traits, cPsychiatric traits, dAutoimmune inflammatory diseases. Pair-wise genetic correlations withstood Bonferroni corrections (228 tests) are marked with double asterisk (**), with estimates of correlation shown in the cells. Pair-wise genetic correlations with significance at p< 0.01 are marked with a single asterisk (*). The color of cells represents the magnitude of correlation NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-018-08054-4 ARTICLE NATURE COMMUNICATIONS | (2019) 10:431 | https://doi.org/10.1038/s41467-018-08054-4 | www.nature.com/naturecommunications 5 (9.8-fold enrichment, p=2.3 × 10−5). Transcription factor binding sites showed the second highest enrichment (4.0-fold, 13% of SNPs explaining 40% of SNP-heritability, p=1.4 × 10−7). Further, super-enhancers (groups of putative enhancers in close genomic proximity with unusually high levels of mediator binding) showed a significant 2.6-fold enrichment (p=2.0 × 10−20). Additional enhancers, including regular enhancers (3.2-fold), weak enhancers (3.1-fold) and FANTOM5 enhancers (3.1-fold), presented similar enrichments but were not statistically significant. In addition, multiple histone modifications of epigenetic markers H3K9ac, H3K4me3, and H3K27ac, were all significantly enriched for cancer heritability. Repressed regions exhibited depletion (0.34-fold, p=1.2 × 10−6). Enrichment analysis of functional categories for each cancer and cancer subtype are shown in Fig. 5and Supplementary Table 4. Overall, cell-type-specific analysis of histone marks identified significant enrichments specific to individual cancers (Supplementary Fig. 2). For breast cancer, 3 out of 8 statistically significant tissues were adipose nuclei (H3K4me1, H3K9ac) and breast myoepithelial (H3K4me1) cells. For colorectal cancer, 15 out of the 18 statistically significant enrichments were observed in either colon or rectal tissues (colon/rectal mucosa, duodenum mucosa, small/large intestine, and colon smooth muscle). We observed no significant enrichments for head/neck, lung, and ovarian cancer, but we noted that for both lung (9 out of 10) and ovarian cancer (6 out of 10), the most enriched cell types were immune cells; while in head/neck cancer, 6 out of 10 most highly enriched cell types belonged to CNS (Supplementary Fig. 3, Supplementary Data 4). Cell-type-specific analysis for cancer subtypes are shown in Supplementary Data 5. Comparing 0.2 Directional correlation analysis Positive effect Negative effect Breast cancer Breast cancer Breast cancer Prostate cancer Schizophrenia Age at menopause Systemic lupus HDL a b c d 0.1 0.0 –0.1 0.2 0.2 0.2 0.3 0.3 0.2 –0.06 –0.02 0.06 HDL ascertainment Schizophrenia ascertainment Menopause age ascertainment Systemic lupus ascertainment Breast cancer ascertainment Breast cancer ascertainment Breast cancer ascertainment Prostate cancer ascertainment 0.02 0.2 0.2 0.4 0.8 0.6 1.0 0.1 1.2 –0.2 –0.1 –0.2 –0.3 –0.4 0.1 0.1 0.1 0.1 0.0 0.0 0.0 0.5 1.0 –1.0 –0.5 –0.5 0.0 0.0 0.0 0.0 0.0 –0.1 –0.1 –0.1 –0.1 –0.2 –0.2 0.2 0.2 0.3 0.4 0.10.0 0.0 –0.1–0.2 –0.2 –0.2 –0.3 –0.08 –0.06 –0.04 –0.05 0.00 0.05 0.05 0.5 0.10 –0.05 –0.05 0.00 0.00 0.05 –0.02 0.00 0.02 0.04 0.06 Fig. 4 Putative directional relationships between cancers and traits. For each cancer–trait pair identified as candidates to be related in a causal manner, the plots show trait-specific effect sizes (beta coefficients) of the included genetic variants. Gray lines represent the relevant standard errors. aHDL and breast cancer. Trait-specific effect sizes for HDL and breast cancer are shown for SNPs associated with HDL levels (left) and breast cancer (right). bSchizophrenia and breast cancer. Trait-specific effect sizes for schizophrenia and breast cancer are shown for SNPs associated with schizophrenia (left) and breast cancer (right). cAge at natural menopause and breast cancer. Trait-specific effect sizes for age at natural menopause and breast cancer are shown for SNPs associated with age at natural menopause (left) and breast cancer (right). dLupus and prostate cancer. Trait-specific effect sizes for lupus and prostate cancer are shown for SNPs associated with lupus (left) and prostate cancer (right) ARTICLE NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-018-08054-4 6NATURE COMMUNICATIONS | (2019) 10:431 | https://doi.org/10.1038/s41467-018-08054-4 | www.nature.com/naturecommunications cell-type-specific enrichment for cancers to the additional 38 non-cancer traits revealed notably differential clustering patterns (Supplementary Fig. 4). Breast, colorectal, and prostate cancer showed enrichment mostly for adipose and epithelial tissues, in contrast to autoimmune diseases (enriched for immune/hematopoietic cells) or psychiatric disorders (enriched for brain tissues). Discussion We performed a comprehensive analysis quantifying the heritability and genetic correlation of six cancers, leveraging summary statistics from the largest cancer GWAS conducted to date. Our study demonstrates shared genetic components across multiple cancer types. These results contrast with a prior study conducted by Sampson et al. which reported an overall negligible genetic correlation among common solid tumors9. Our results are, however, in line with a recent study,16 which analyzed a subset of the data included here, and identified a significant genetic correlation between lung and colorectal cancer. Our data support, and for the first time quantify, the strong genetic correlation (r g =0.57) between lung and head/neck cancer, two cancers linked to tobacco use20,25. We also for the first time observed a significant genetic correlation between breast and ovarian cancer (r g =0.24), two cancers that are known to share rare genetic factors including BRCA1/2mutations, and environmental exposures associated with endogenous and exogenous hormone exposures26. Prostate cancer is also considered as hormone-dependent and associated with BRCA1/2 mutations, but interestingly, we only observed a nominally significant and modest (r g =0.07) genetic correlation between breast and prostate cancer, while ovarian and prostate cancer showed no genetic correlation (r g =0.02, se =0.07). Our large sample sizes allowed us to conduct well-powered analyses for cancer subtypes. While head/neck cancer showed negligible genetic correlation with overall (r g =0.03, se =0.06) and ER +breast cancer (r g =−0.02, se =0.07), it showed a stronger genetic correlation with ER−breast cancer (r g =0.21, se =0.09). Similarly, lung cancer showed a statistically more pronounced genetic correlation with ER−(r g =0.29, se =0.06) than ER +breast cancer (r g =0.13, se =0.04). A recent pooled analysis of smoking and breast cancer risk demonstrated a smoking-related increased risk for ER +but not for ER−breast cancer27, and thus it is unlikely that the stronger genetic correlation between ER−subtype and lung and head/neck cancer is due to smoking behavior. Perhaps surprisingly, despite literature suggesting substantial similarities between ER−breast cancer and serous ovarian cancer in particular28, we did not observe statistically significant different genetic correlations between ER−or ER +breast cancer and serous ovarian cancer (r g =0.17, se = 0.08 vs. r g =0.11, se =0.06). This suggests that rare high penetrance variants may play a more important role in driving the similarities behind ER−breast cancer and serous ovarian cancer than common genetic variation. Heritability analysis confirms that common cancers have a polygenic component that involves a large number of variants. Although susceptibility variants identified at genome-wide significance explain an appreciable fraction of the heritability for some cancers, we estimate that the majority of the polygenic effect is attributable to other, yet undiscovered variants, presumably with effects that are too weak to have been identified with current sample sizes. We found the genetic component that could be attributed to genome-wide significant loci varied greatly from ~0% for head/neck cancer to ~50% for breast and prostate cancer. These results reflect in part the strong correlation between number of GWAS-identified loci and sample size, as we had more than twice as many breast and prostate cancer samples compared to the other cancers. One corollary is that larger GWAS are likely to identify new susceptibility loci that could help our understanding of disease development, improve prediction power of genetic risk scores and hence contribute to screening and personalized risk prediction29. Among the genetic correlations between cancer and noncancer traits, we observed positive correlations for psychiatric disorders (depressive symptoms, schizophrenia) with lung and breast cancer, where findings from epidemiological studies have been suggestive but inconclusive. It has been proposed that the linkage between psychiatric traits and cancers are more likely to be mediated through cancer-associated risk phenotypes such as smoking, excessive alcohol consumption in depressed populations30, and reduced fertility patterns (e.g., nulliparous) in psychiatric populations31. Detailed analyses considering confounding traits like reproductive history and smoking are needed to make inference about the mechanisms involved. GWAS have identified pleiotropic regions influencing both lung cancer and nicotine dependence, such as 15q25.132,33. In line with those results, we identified a strong genetic correlation between smoking and both lung (r g =0.56) and head/neck cancer (r g =0.47). It remains unclear whether this genetic correlation is completely explained by the direct influence of smoking or if the shared genetic component affects the traits through separate pathways. Interestingly, a genetic correlation (r g =0.35, se =0.14) between lung and bladder cancer, another smoking-associated cancer, has been identified previously9. Due to the small numbers of GWASidentified smoking-associated SNPs, we were unable to assess a directional correlation between smoking and cancer, but we expect such analyses to become feasible as additional smokingrelated SNPs are identified. We found modest positive, yet significant genetic correlations between adiposity-related measures (as reflected by waist-to-hip ratio, circulating HDL levels and BMI) and both colorectal and lung cancer, but negative genetic correlations between BMI and prostate and breast cancer, consistent with previous reported findings34 and reinforce the complex dynamics between obesity and cancer where multiple factors including age, smoking, endogenous hormones and reproductive status play a role. We did not observe genetic correlations between breast cancer and age at menarche or age at natural menopause. These null observations were largely driven by ER +breast cancer (ER +: r g =0.006, se =0.03 vs. ER−:r g =−0.09, se =0.04 for age at menarche. ER +:r g =0.0005, se =0.04 vs. ER−:r g =−0.10, se =0.05 for age at natural menopause), and were unexpected given that both factors play pivotal roles in breast cancer etiology35 and previous Mendelian randomization (MR) analyses have identified a link36,37. An important difference between genetic Table 1 Significant enrichment estimates of genomic functional categories, meta-analyzed across six cancer sites Category Enrichment (95% CI) P-value Conserved region 9.78 (5.72–13.84) 2.28 × 10−5 TFBS 4.04 (2.91–5.17) 1.43 × 10−7 H3K9ac 3.41 (2.14–4.69) 2.04 × 10−4 H3K4me3 3.23 (2.47–4.00) 8.91 × 10−9 Super Enhancer 2.56 (2.23–2.89) 1.99 × 10−20 H3K27ac (PGC) 2.36 (1.91–2.80) 2.12 × 10−9 H3K27ac (Hnisz) 1.90 (1.65–2.15) 1.86 × 10−12 H3K4me1 1.84 (1.56–2.12) 2.57 × 10−9 Repressed region 0.34 (0.07–0.61) 1.15 × 10−6 The meta-analysis was performed based on the enrichment estimates and standard errors calculated using LD score regression in each individual cancer type. P-values were significant after Bonferroni correction (P< 0.05/24) TFBS transcription factor binding sites NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-018-08054-4 ARTICLE NATURE COMMUNICATIONS | (2019) 10:431 | https://doi.org/10.1038/s41467-018-08054-4 | www.nature.com/naturecommunications 7 10.0 7.5 5.0 2.5 0.0 10.0 7.5 5.0 2.5 0.0 10.0 7.5 5.0 2.5 0.0 10.0 7.5 5.0 2.5 0.0 10.0 7.5 5.0 2.5 0.0 10.0 7.5 5.0 2.5 0.0 –log10 (enrichment_p-values) Breast cancer Colorectal cancer Headneck cancer Lung cancer Ovarian cancer Prostate cancer 3′ UTR 5′ UTR Coding CTCF Conserved DGF DHS Enhancer FANTOM5 enhancer Fetal DHS H3K27ac (Hnisz) H3K27ac (PGC2) H3K4me1 H3K4me3 H3K9ac Intron Promoter Promoter flanking Repressed Super enhancer Weak enhancer TFBS TSS Transcribed 24_main_annotation Fig. 5 Enrichment p-values of 24 non-cell-type-specific functional categories over six cancer types. The x-axis represents each of the 24 functional categories, y-axis represents log-transformed p-values of enrichment. Annotations with statistical significance after Bonferroni corrections (p< 0.05/24) were plotted in orange, otherwise blue. The horizontal gray dash line indicates p-threshold of 0.05; horizontal red dash line indicates p-threshold of 0.05/ 24. From top to bottom are six panels representing six cancers: breast cancer, colorectal cancer, head/neck cancer, lung cancer, ovarian cancer, and prostate cancer. TSS transcription start site, UTR untranslated region, TFBS transcription factor binding sites, DHS DNase I hypersensitive sites, DGF digital genomic foot printing, CTCF CCCTC-binding factor ARTICLE NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-018-08054-4 8NATURE COMMUNICATIONS | (2019) 10:431 | https://doi.org/10.1038/s41467-018-08054-4 | www.nature.com/naturecommunications correlation and MR analyses is that the latter only considers genome-wide significant SNPs while the former incorporates the entire genome. It is possible that a relatively small overlap in strongly associated SNPs can result in significant MR results despite low evidence of an overall genetic correlation. Indeed, the directional genetic correlations we observed for age at natural menopause, schizophrenia, and HDL with breast cancer, and for lupus with prostate cancer, highlight again that although an overall genetic correlation may be negligible, there can still be genetic links between traits. It is important to note that we cannot rule out unmeasured confounding, including the possibility that these genetic variants affect an intermediate phenotype that is pleiotropic for both target traits. Given the observational nature of our data, these putative causal directions should be interpreted with caution. Pan-cancer tumor-based studies have demonstrated that different cancers are sometimes driven by similar somatic functional events such as specific copy number abnormalities and mutations38,39. Our enrichment results of germline genetic across functional annotation data shed new light on the biological mechanisms leading to cancer development. The more pronounced enrichment identified for conserved regions compared with coding regions provides evidence for the biological importance of the former, which has been shown to be true for multiple traits14,40. Even though the biochemical function of many conserved regions remains uncharacterized, transcribed ultraconserved regions have been found to be frequently located at fragile sites. Compared to normal cells, cancer cells have a unique spectrum of transcribed ultra-conservative regions, suggesting that variation in expression of these regions are involved in the malignant process41,42. These results bridge the link between germline and somatic genetics in cancer development, which was also observed in a recent breast cancer GWAS that has demonstrated a strong overlap between target genes for GWAS hits and somatic driver genes in breast tumors43. We also found a fourfold enrichment for transcription factor binding sites and a threefold enrichment for super-enhancers, consistent with prior observations that breast cancer GWAS loci fall in enhancer regions involved in distal regulation of target genes43. Cell-typespecific analysis of histone marks demonstrated the importance of tissue specificity, primarily for colorectal and breast cancer. Further, our results suggest that immune cells are important for ovarian and lung cancer whilst CNS is important to head/neck cancer. Unfortunately, we did not have data on prostate-specific tissues, but we note that tissue-specific enrichment of prostate cancer heritability for epigenetic markers has been observed previously10. We note that generation of rich functional annotation is ongoing and we expect to include additional tissuespecific functional elements in our future work. Our study has several strengths. We were able to robustly quantify pair-wise genetic correlations between multiple cancers using the largest available cancer GWAS, comprising almost 600,000 samples across six major cancers and subtypes. We were also able to systematically assess the genetic correlations between cancer and 38 non-cancer traits. Notwithstanding the large sample sizes, several limitations need to be acknowledged. We did not have the sample sizes required to assess relevant cancer subgroups including oropharyngeal cancer, clear cell, mucinous and endometrioid ovarian cancer, or lung cancer among never smokers (each with ~2000 cases). In addition, we did not have access to GWAS summary statistics for prevs. post-menopausal breast cancer. We were not able to consider all cancer risk factors when selecting non-cancer traits, since some of the wellestablished risk factors such as infection were either not available, showed no evidence of heritability or were not based on adequate sample sizes for robust analyses. SNP-heritability varies with minor allele frequency, linkage disequilibrium, and genotype certainty; we note that approaches to estimate heritability leveraging GWAS data are constantly evolving. We also note that estimate variability needs to be taken into account when comparing the SNP-heritability with the classical twin-heritability, in particular for cancers with small sample sizes such as head/neck cancer (SNP-heritability varied between 5–14% and twinheritability varied between 0–60%, although both point estimates were 9%). Further, our data were based on GWAS metaanalysis from multiple individual GWAS across European ancestry populations from Europe, Australia and the US. IntraEuropean ancestry differences are likely to be a source of bias. However, since we limited our analysis to SNPs with MAF > 1% and HapMap3 SNPs (which have proven to be well imputed across European ancestry populations), we believe that any population structure across cancers will have minimal effect on our results. Finally, as more non-European and multi-ethnic GWAS data become available, it is important to examine transethnic genetic correlation in cancer. In conclusion, results from our comprehensive analysis of heritability and genetic correlations across six cancer types indicate that solid tumors arising from different tissues share common germline genetic influences. Our results also demonstrate evidence for common genetic risk sharing between cancers and smoking, psychiatric, and metabolic traits. In addition, functional components of the genome, particularly conserved and regulatory regions, are significant contributors to cancer heritability across multiple cancer types. Our results provide a basis and direction for future cross-cancer studies aiming to further explore the biological mechanisms underlying cancer development. Methods Studies and quality control. We used summary statistics from six cancer GWASs based on a total of 597,534 participants of European ancestry. Cancer-specific sample sizes were: breast cancer: 122,977 cases/105,974 controls; colorectal cancer: 36,948/30,864; head/neck cancer (oral and oropharyngeal cancers): 5452/5984; lung cancer: 29,266/56,450; ovarian cancer: 22,406/40,941; prostate cancer: 79,166/ 61,106. These data were generated through the joint efforts of multiple consortia. Details on study characteristics and subjects contributed to each cancer-specific GWAS summary dataset have been described elsewhere43–49. SNPs were imputed to the 1000 Genomes Project reference panel (1KGP) using a standardized protocol for all cancer types18. We included autosomal SNPs with a minor allele frequency (MAF) larger than 1% and present in HapMap3 (N SNPs =~1 million) because those SNPs are usually well imputed in most studies (note that excluding sex chromosomes could reduce the overall heritability estimates). A brief overview of the quality control in each cancer dataset are presented in Supplementary Table 5. For some of the cancers, we further obtained summary statistics data on subtypes (ER +and ER−breast cancer; lung adenocarcinoma, and squamous cell carcinoma; serous invasive ovarian cancer and advanced stage prostate cancer, defined as metastatic disease or Gleason score ≥8 or PSA > 100 or prostate cancer death). Sample sizes and more details shown in Supplementary Table 1. We additionally assembled European ancestry GWAS summary statistics from 38 traits, which spanned a wide range of phenotypes including anthropometric (e.g., height and body mass index (BMI)), psychiatric disorder (e.g., depressive symptoms and schizophrenia), and autoimmune disease (e.g., rheumatoid arthritis and celiac disease) (Supplementary Table 6). We calculated trait-specific SNPheritability and restricted our analysis to traits with a heritable component (Supplementary Table 7)14. We removed the major histocompatibility complex (MHC) region from all analysis because of its unusual LD and genetic architecture. Estimation of SNP-heritability and genetic correlation. We estimated the SNPheritability due to genotyped and imputed SNPs (h2 g, the proportion of phenotypic variance causally explained by common SNPs) of each cancer using LDSC15. Briefly, this method is based on the relationship between LD score and χ2-statistics: Eχ2 j hi Njh2 g Mljþ1ð1Þ where Eχ2 j hi denotes the expected χ2-statistics for the association between the outcome and SNP j,N j is the study sample size available for SNP j,Mis the total numbers of variants and l j denotes the LD score of SNP jdefined as lj¼P k r2j;kðÞ (kdenotes other variants within the LD region). Note that the quantity estimated by LDSC is the causal heritability of common SNPs, which is different from the NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-018-08054-4 ARTICLE NATURE COMMUNICATIONS | (2019) 10:431 | https://doi.org/10.1038/s41467-018-08054-4 | www.nature.com/naturecommunications 9 (NCATS) (ULTR000445); CAM: National Institutes of Health Research Cambridge Biomedical Research Centre and Cancer Research UK Cambridge Cancer Centre; CHA: Innovative Research Team in University (PCSIRT) in China (IRT1076); CNI: Instituto de Salud Carlos III (PI12/01319); Ministerio de Economía y Competitividad (SAF2012); COE: Department of Defense (W81XWH-11-2-0131); CON: National Institutes of Health (R01-CA063678, R01-CA074850; and R01-CA080742); DKE: Ovarian Cancer Research Fund; DOV: National Institutes of Health R01-CA112523 and R01-CA87538; EMC: Dutch Cancer Society (EMC 2014-6699); EPC: The coordination of EPIC is financially supported by the European Commission (DG-SANCO) and the International Agency for Research on Cancer. The national cohorts are supported by Danish Cancer Society (Denmark); Ligue Contre le Cancer, Institut Gustave Roussy, Mutuelle Générale de l’Education Nationale, Institut National de la Santé et de la Recherche Médicale (INSERM) (France); German Cancer Aid, German Cancer Research Center (DKFZ), Federal Ministry of Education and Research (BMBF) (Germany); the Hellenic Health Foundation (Greece); Associazione Italiana per la Ricerca sul Cancro-AIRC-Italy and National Research Council (Italy); Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF), Statistics Netherlands (The Netherlands); ERC-2009-AdG 232997 and Nordforsk, Nordic Centre of Excellence programme on Food, Nutrition and Health (Norway); Health Research Fund (FIS), PI13/00061 to Granada, PI13/01162 to EPIC-Murcia, Regional Governments of Andalucía, Asturias, Basque Country, Murcia and Navarra, ISCIII RETIC (RD06/0020) (Spain); Swedish Cancer Society, Swedish Research Council and County Councils of Skåne and Västerbotten (Sweden); Cancer Research UK (14136 to EPICNorfolk; C570/A16491 and C8221/A19170 to EPIC-Oxford), Medical Research Council (1000143 to EPIC-Norfolk, MR/M012190/1 to EPIC-Oxford) (United Kingdom); GER: German Federal Ministry of Education and Research, Programme of Clinical Biomedical Research (01 GB 9401) and the German Cancer Research Center (DKFZ); GRC: This research has been co-financed by the European Union (European Social Fund—ESF) and Greek national funds through the Operational Program “Education and Lifelong Learning”of the National Strategic Reference Framework (NSRF)—Research Funding Program of the General Secretariat for Research & Technology: SYN11_10_19 NBCA. Investing in knowledge society through the European Social Fund; GRR: Roswell Park Cancer Institute Alliance Foundation, P30 CA016056; HAW: U.S. National Institutes of Health (R01CA58598, N01-CN-55424, and N01-PC-67001); HJO: Intramural funding; RudolfBartling Foundation; HMO: Intramural funding; Rudolf-Bartling Foundation; HOC: Helsinki University Research Fund; HOP: Department of Defense (DAMD17-02-1-0669) and NCI (K07-CA080668, R01-CA95023, P50-CA159981 MO1-RR000056 R01CA126841); HUO: Intramural funding; Rudolf-Bartling Foundation; JGO: JSPS KAKENHI grant; JPN: Grant-in-Aid for the Third Term Comprehensive 10-Year Strategy for Cancer Control from the Ministry of Health, Labour and Welfare; KRA: This study (Ko-EVE) was supported by a grant from the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), and the National R&D Program for Cancer Control, Ministry of Health & Welfare, Republic of Korea (HI16C1127; 0920010); LAX: American Cancer Society Early Detection Professorship (SIOP-06-258-01-COUN) and the National Center for Advancing Translational Sciences (NCATS), Grant UL1TR000124; LUN: ERC-2011-AdG 294576-risk factors cancer, Swedish Cancer Society, Swedish Research Council, Beta Kamprad Foundation; MAC: National Institutes of Health (R01-CA122443, P30-CA15083, P50-CA136393); Mayo Foundation; Minnesota Ovarian Cancer Alliance; Fred C. and Katherine B. Andersen Foundation; Fraternal Order of Eagles; MAL: Funding for this study was provided by research grant R01CA61107 from the National Cancer Institute, Bethesda, MD, research grant 94 222 52 from the Danish Cancer Society, Copenhagen, Denmark; and the Mermaid I project; MAS: Malaysian Ministry of Higher Education (UM.C/HlR/MOHE/06) and Cancer Research Initiatives Foundation; MAY: National Institutes of Health (R01CA122443, P30-CA15083, and P50-CA136393); Mayo Foundation; Minnesota Ovarian Cancer Alliance; Fred C. and Katherine B. Andersen Foundation; MCC: Cancer Council Victoria, National Health and Medical Research Council of Australia (NHMRC) grants number 209057, 251533, 396414, and 504715; MDA: DOD Ovarian Cancer Research Program (W81XWH-07-0449); MEC: NIH (CA54281, CA164973, CA63464); MOF: Moffitt Cancer Center, Merck Pharmaceuticals, the state of Florida, Hillsborough County, and the city of Tampa; NCO: National Institutes of Health (R01-CA76016) and the Department of Defense (DAMD17-02-1-0666); NEC: National Institutes of Health R01CA54419 and P50-CA105009 and Department of Defense W81XWH-10-1-02802; NHS: UM1 CA186107, P01 CA87969, R01 CA49449, R01-CA67262, UM1 CA176726; NJO: National Cancer Institute (NIH-K07 CA095666, R01-CA83918, NIH-K22-CA138563, and P30-CA072720) and the Cancer Institute of New Jersey; If Sara Olson and/or Irene Orlow is a co-author, please add NCI CCSG award (P30-CA008748) to the funding sources; NOR: Helse Vest, The Norwegian Cancer Society, The Research Council of Norway; NTH: Radboud University Medical Centre; OPL: National Health and Medical Research Council (NHMRC) of Australia (APP1025142) and Brisbane Women’s Club; ORE: OHSU Foundation; OVA: This work was supported by Canadian Institutes of Health Research grant (MOP-86727) and by NIH/NCI 1 R01CA160669-01A1; PLC: Intramural Research Program of the National Cancer Institute; POC: Pomeranian Medical University; POL: Intramural Research Program of the National Cancer Institute; PVD: Canadian Cancer Society and Cancer Research Society GRePEC Program; RBH: National Health and Medical Research Council of Australia; RMH: Cancer Research UK, Royal Marsden Hospital; RPC: National Institute of Health (P50-CA159981, R01-CA126841); SEA: Cancer Research UK (C490/A10119 C490/A10124); UK National Institute for Health Research Biomedical Research Centres at the University of Cambridge; SIS: NIH, National Institute of Environmental Health Sciences, Z01-ES044005 and Z01-ES049033; SMC: The bbSwedish Research Council-SIMPLER infrastructure; the Swedish Cancer Foundation; SON: National Health Research and Development Program, Health Canada, grant 6613-1415-53; SRO: Cancer Research UK (C536/A13086, C536/A6689) and Imperial Experimental Cancer Research Centre (C1312/A15589); STA: NIH grants U01 CA71966 and U01 CA69417; SWE: Swedish Cancer foundation, WeCanCureCancer and VårKampMotCancer foundation; SWH: NIH (NCI) grant R37-CA070867; TBO: National Institutes of Health (R01-CA106414-A2), American Cancer Society (CRTG-00-196-01CCE), Department of Defense (DAMD17-98-1-8659), Celma Mastery Ovarian Cancer Foundation; TOR: NIH grants R01-CA063678 and R01 CA063682; UCI: NIH R01CA058860 and the Lon V Smith Foundation grant LVS39420; UHN: Princess Margaret Cancer Centre Foundation-Bridge for the Cure; UKO: The UKOPS study was funded by The Eve Appeal (The Oak Foundation) and supported by the National Institute for Health Research University College London Hospitals Biomedical Research Centre; UKR: Cancer Research UK (C490/A6187), UK National Institute for Health Research Biomedical Research Centres at the University of Cambridge; USC: P01CA17054, P30CA14089, R01CA61132, N01PC67010, R03CA113148, R03CA115195, N01CN025403, and California Cancer Research Program (00-01389V-20170, 2II0200); VAN: BC Cancer Foundation, VGH & UBC Hospital Foundation; VTL: NIH K05-CA154337; WMH: National Health and Medical Research Council of Australia, Enabling Grants ID 310670 & ID 628903. Cancer Institute NSW Grants 12/RIG/1-17 & 15/RIG/1-16; WOC: National Science Centren (N N301 5645 40). The Maria Sklodowska-Curie Memorial Cancer Center and Institute of Oncology, Warsaw, Poland. The University of Cambridge has received salary support for PDPP from the NHS in the East of England through the Clinical Academia Reserve. The prostate cancer genome-wide association analyses: we pay tribute to Brian Henderson, who was a driving force behind the OncoArray project, for his vision and leadership, and who sadly passed away before seeing its fruition. We also thank the individuals who participated in these studies enabling this work. The ELLIPSE/ PRACTICAL (http//:practical.icr.ac.uk) prostate cancer consortium and his collaborating partners were supported by multiple funding mechanisms enabling this current work. ELLIPSE/PRACTICAL Genotyping of the OncoArray was funded by the US National Institutes of Health (NIH) (U19 CA148537 for ELucidating Loci Involved in Prostate Cancer SuscEptibility (ELLIPSE) project and X01HG007492 to the Center for Inherited Disease Research (CIDR) under contract number HHSN268201200008I). Additional analytical support was provided by NIH NCI U01 CA188392 (F.R.S.). Funding for the iCOGS infrastructure came from the European Community’s Seventh Framework Programme under grant agreement n° 223175 (HEALTH-F2-2009-223175) (COGS), Cancer Research UK (C1287/A10118, C1287/A 10710, C12292/A11174, C1281/A12014, C5047/ A8384, C5047/A15007, C5047/A10692, and C8197/A16565), the National Institutes of Health (CA128978) and Post-Cancer GWAS initiative (1U19 CA148537, 1U19 CA148065, and 1U19 CA148112; the GAME-ON initiative), the Department of Defense (W81XWH-10-1-0341), the Canadian Institutes of Health Research (CIHR) for the CIHR Team in Familial Risks of Breast Cancer, Komen Foundation for the Cure, the Breast Cancer Research Foundation, and the Ovarian Cancer Research Fund. This work was supported by the Canadian Institutes of Health Research, European Commission’s Seventh Framework Programme grant agreement n° 223175 (HEALTH-F2-2009-223175), Cancer Research UK Grants C5047/A7357, C1287/A10118, C1287/A16563, C5047/ A3354, C5047/A10692, C16913/A6135, C5047/A21332 and The National Institute of Health (NIH) Cancer Post-Cancer GWAS initiative grant: No. 1 U19 CA148537-01 (the GAME-ON initiative). We also thank the following for funding support: The Institute of Cancer Research and The Everyman Campaign, The Prostate Cancer Research Foundation, Prostate Research Campaign UK (now Prostate Action), The Orchid Cancer Appeal, The National Cancer Research Network UK, and The National Cancer Research Institute (NCRI) UK. We are grateful for support of NIHR funding to the NIHR Biomedical Research Centre at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust. The Prostate Cancer Program of Cancer Council Victoria also acknowledge grant support from The National Health and Medical Research Council, Australia (126402, 209057, 251533, 396414, 450104, 504700, 504702, 504715, 623204, 940394, and 614296), VicHealth, Cancer Council Victoria, The Prostate Cancer Foundation of Australia, The Whitten Foundation, PricewaterhouseCoopers, and Tattersall’s. E.A.O., D.M.K., and E.M.K. acknowledge the Intramural Program of the National Human Genome Research Institute for their support. The BPC3 was supported by the U.S. National Institutes of Health, National Cancer Institute (cooperative agreements U01CA98233 to D.J.H., U01-CA98710 to S.M.G., U01-CA98216 to E.R., and U01-CA98758 to B.E.H., and Intramural Research Program of NIH/National Cancer Institute, Division of Cancer Epidemiology and Genetics). CAPS GWAS study was supported by the Swedish Cancer Foundation (grant no 09-0677, 11-484, 12-823), the Cancer Risk Prediction Center (CRisP; www.crispcenter.org), a Linneus Centre (Contract ID 70867902) financed by the Swedish Research Council, Swedish Research Council (grant no K2010-70 × - 20430-04-3, 2014-2269). The Hannover Prostate Cancer Study was supported by the Lower Saxonian Cancer Society. PEGASUS was supported by the Intramural Research Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health. RAPPER was supported by the NIHR Manchester Biomedical Research Center, Cancer Research UK (C147/A25254, C1094/A18504) and the EU’s7 th Framework Programme Grant/Agreement no 60186. Overall: this research has been conducted using the UK Biobank Resource (application number 16549). NHS is supported by UM1 CA186107 (NHS cohort infrastructure grant), P01 CA87969, and R01 CA49449. NHSII is supported by UM1 CA176726 (NHSII cohort infrastructure grant), ARTICLE NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-018-08054-4 16 NATURE COMMUNICATIONS | (2019) 10:431 | https://doi.org/10.1038/s41467-018-08054-4 | www.nature.com/naturecommunications and R01-CA67262. A.L.K. is supported by R01 MH107649. We would like to thank the participants and staff of the NHS and NHSII for their valuable contributions as well as the following state cancer registries for their help: AL, AZ, AR, CA, CO, CT, DE, FL, GA, ID, IL, IN, IA, KY, LA, ME, MD, MA, MI, NE, NH, NJ, NY, NC, ND, OH, OK, OR, PA, RI, SC, TN, TX, VA, WA, WY. The authors assume full responsibility for analyses and interpretation of these data. Author Contribution All authors reviewed and commented on the manuscript, as well as approved the submission. Writing group: X.J., H.K.F., F.R.S., S.L.S., J.P.T., Y. Han., K. Michailidou, C.L., K.B.K., J.D., D.V.C., G. Casey, M.M.G., J. Huyghe, D. Thomas, R.J. Hung, B.D., J.M., U.P., L.H., M. Garcia-Closas, R.A.E., G. Chenevix-Trench, P.J.B., C.A.H., J. Schleutker, D.F.E., S.B.G., P.D.P., A.L.P., B.P., C.I.A., P.K., S. Lindström. Interpret results: A.A., I.L.A., A.C.A., N.N.A., S.A., B.K.A., R.B.B., J. Batra, A.B., S.I.B., S.A.B., C.B., S.E.B., M.K.B., J. Benitez, R.B., G. Cadoni, T.C., P.T.C., G. Cancel-Tassin, D.C., A.T.C., J. Chang-Claude, D.C.C., J.M. Collee, F.J.C., A.C., J.M. Cunningham, C. Chen, M.B.D., P.D., O.D., J.L.D., T.D., E.D., C.K.E., D.V.E., D.G.E., P.A.F., R.T.F., F.F., S.F., E.F., J. Garber, S.A.G., G.G.G., D.E.G., M.T.G., G.G., K.G., P.G., U.H., J. Huyghe, F.H., R. Herrero, P. Hall, M.H., D.G.H., G.I., E.N.I., C.I., P.J., M.A. Jakubowska, A. Joshi, L.E.K., T.K., E.K., A.S.K., L.A.K., J. Kim, M.K., V.N.K., P.L., N.D.L., F. Loupakis, H.L., G. Liu, D. Lambrechts, D.A.L., C.I.L., A.L., N.M.L., G. Leslie, J. Lester, L. Maehle, C.M., L.L.M., S.M., L. McGuffog, A. Mannermaa, P.M., F.M., M.M., V.M., K.B.M., L. Mucci, K. Muir, F.C.N., B.G.N., R.L.N., K.O., O.I.O., H.O., A.O., H.P., J.Y.P., M.T.P., T.P., C.M.P., A.I.P., D. Plaseska-Karanfilska, M.P., K. Stefansson, S.J.R., L.R., H.S.R., M.J. Riggan, M.A.R., K.D.R., E.S., E.J.S., M.B.S., M.K.S., V.W.S., E.M.S., M.L.S., K.D.S., M.C.S., A.B.S., V.L.S., S.S., J. Stone, K. Sundfeldt, A.T., J.A.T., M.R.T., M.B.T., K.L.T., L.B., A.E.T., P.A.T., R.C.T., N.T., C.V., A.V., Q.W., S.W., J.N.W., E.W., A.S.W., F.W., R.W., X.W., D.Y., W.Z., A.Z., J.M.L. Oversee consortium dataset: F.R.S., M.K.B., J.M.L., R. Saxena, R.J. Hung, U.P., R.A.E., G. Chenevix-Trench, D.F.E., S.B.G., C.I.A., P.K. Develop and review the analysis plan and statistical analysis: X.J., H.K.F., A.L.P., B.P., C.I.A., P.K., S. Lindström. Design and manage individual study: D.A., M.C.A., I.L.A., H.A.-C., N.N.A., K.J.A., E.V.B., D.D.B., J. Brenton, M.W.B., S. Benlloch, H. Bickeboller, S. Boccia, N.V.B., H. Brauch, H. Brenner, J. Brunet, M.B., H. Brunnstrom, D.R.B., B.B., M.A.C., I.C., L.C., N.C., A.L.C., J. Clements, S.J.C., C. Cybulski, K.B.C., F.C., J. Chang-Claude, M.C.C., K.C., A.d., M. Gago-Dominguez, J.L.D., A.M.D., M.D., D.M.E., C.E., R.L.F., T.L., J.C.F., O.F., S.J.G., P.A.G., J.A.G., G.G.G., A.K.G., M.S.G., E.L.G., M.T.G., K.G., M.H.G., H.G., J. Gronwald, N.H., P. Hillemanns, F.C.H., R.J. Hamilton, J. Hampe, A.H., E.H., Y. Hong, J.L.H., R. Houlston, P.J.H., D.J.H., E.N.I., S.A.I., A.J., P.J., Mattias. Johansson, Mikael. Johansson, E.M.J., R.K., B.Y.K., K.K., S.K.K., J.A.K., Z.K., S.K., J. Kupryjanczyk, M.L., S. Lam, D. Lessel, M.T.L., E.L., J. Lubinski, L.L., F. Lejbkowicz, J. Lubinski, A. Meindl, T.M., P.M., A. Miller, R.L.M., R.J.M., M.M., A.M.M., K.L.N., D.E.N., A.R.N., S.L.N., H.N., P.A.N., L.F.N., L.N., K.O., E.O., A.A.A.O., O.I.O., A.F.O., H.P., J.Y.P., N.P., K.L.P., W.H.P., C.M.P., D. Prokofieva, P.R., G.R., E.J.v.R., H.A.R., A.R., M.J. Roobol, B.R., K.D.R., D.P.S., J. Simard, V.W.S., H.S., E.M.S., W.S., C.F.S., J.L.S., V.L.S., R. Sutphen, A.J.S., E.H.T., C.M.T., M.D.T., S.N.T., M. Thomassen, M. Tischkowitz, D. Torres, S.S.T., C.M.U., N.U., E.V.N., M.E.A., P.M.W., C.R.W., S.W., M.C.W., C.W., H.W., F.W., A.W., P.W., M.W., A.H.W., X.W., S.Z., K.K.Z., R. Saxena. Additional information Supplementary Information accompanies this paper at https://doi.org/10.1038/s41467018-08054-4. Competing interests: The authors declare no competing interests. Reprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ Journal peer review information: Nature Communications thanks the anonymous reviewers for their contribution to the peer review of this work. Peer reviewer reports are available. Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. © The Author(s) 2019 Xia Jiang 1,2 , Hilary K. Finucane 3,4 , Fredrick R. Schumacher 5,6 , Stephanie L. Schmit 7,8 , Jonathan P. Tyrer 9 , Younghun Han 10 , Kyriaki Michailidou 11,12 , Corina Lesseur 13,14 , Karoline B. Kuchenbaecker 15,16 , Joe Dennis 11 , David V. Conti 17 , Graham Casey 18,19 , Mia M. Gaudet 20 , Jeroen R. Huyghe 21 , Demetrius Albanes 22 , Melinda C. Aldrich 23 , Angeline S. Andrew 24 , Irene L. Andrulis 25,26 , Hoda Anton-Culver 27 , Antonis C. Antoniou 11 , Natalia N. Antonenkova 28 , Susanne M. Arnold 29 , Kristan J. Aronson 30 , Banu K. Arun 31 , Elisa V. Bandera 32 , Rosa B. Barkardottir 33,34 , Daniel R. Barnes 11 , Jyotsna Batra 35,36 , Matthias W. Beckmann 37 , Javier Benitez 38,39 , Sara Benlloch 11,40 , Andrew Berchuck 41 , Sonja I. Berndt 22 , Heike Bickeböller 42 , Stephanie A. Bien 21,43 , Carl Blomqvist 44,45 , Stefania Boccia 46,47 , Natalia V. Bogdanova 28,48,49 , Stig E. Bojesen 50,51,52 , Manjeet K. Bolla 11 , Hiltrud Brauch 53,54,55 , Hermann Brenner 55,56,57 , James D. Brenton 58 , Mark N. Brook 40 , Joan Brunet 59 , Hans Brunnström 60,61 , Daniel D. Buchanan 62,63,64 , Barbara Burwinkel 65,66 , Ralf Butzow 67 , Gabriella Cadoni 46,47 , Trinidad Caldés 68 , Maria A. Caligo 69 , Ian Campbell 70,71 , Peter T. Campbell 20 , Géraldine Cancel-Tassin 72,73 , Lisa Cannon-Albright 74,75 , Daniele Campa 76,77 , Neil Caporaso 22 , André L. Carvalho 78,79 , Andrew T. Chan 80,81 , Jenny Chang-Claude 76,82 , Stephen J. Chanock 22 , Chu Chen 83 , David C. Christiani 3 , Kathleen B.M. Claes 84 , Frank Claessens 85 , Judith Clements 35,36 , J. Margriet Collée 86 , Marcia Cruz Correa 87 , Fergus J. Couch 88 , Angela Cox 89 , Julie M. Cunningham 88 , Cezary Cybulski 90 , Kamila Czene 91 , Mary B. Daly 92 , Anna deFazio 93,94 , Peter Devilee 95,96 , Orland Diez 97 , Manuela Gago-Dominguez 98,99 , Jenny L. Donovan 100 , Thilo Dörk 49 , Eric J. Duell 101 , Alison M. Dunning 9 , Miriam Dwek 102 , Diana M. Eccles 103 , Christopher K. Edlund 104 , NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-018-08054-4 ARTICLE NATURE COMMUNICATIONS | (2019) 10:431 | https://doi.org/10.1038/s41467-018-08054-4 | www.nature.com/naturecommunications 17 Digna R Velez Edwards 105 , Carolina Ellberg 106 , D. Gareth Evans 107 , Peter A. Fasching 37,108 , Robert L. Ferris 109 , Triantafillos Liloglou 110 , Jane C. Figueiredo 111,112 , Olivia Fletcher 113 , Renée T. Fortner 76 , Florentia Fostira 114 , Silvia Franceschi 115 , Eitan Friedman 116,117 , Steven J. Gallinger 118,119,120 , Patricia A. Ganz 121 , Judy Garber 122 , José A. García-Sáenz 68 , Simon A. Gayther 123,124,125 , Graham G. Giles 126,127,128 , Andrew K. Godwin 129 , Mark S. Goldberg 130,131 , David E. Goldgar 132 , Ellen L. Goode 133 , Marc T. Goodman 134,135 , Gary Goodman 136 , Kjell Grankvist 137 , Mark H. Greene 138 , Henrik Gronberg 91 , Jacek Gronwald 90 , Pascal Guénel 139 , Niclas Håkansson 140 , Per Hall 91,141 , Ute Hamann 142 , Freddie C. Hamdy 143 , Robert J. Hamilton 144 , Jochen Hampe 145 , Aage Haugen 146 , Florian Heitz 147,148 , Rolando Herrero 149 , Peter Hillemanns 49 , Michael Hoffmeister 56 , Estrid Høgdall 150,151 , Yun-Chul Hong 152 , John L. Hopper 127 , Richard Houlston 153 , Peter J. Hulick 154,155 , David J. Hunter 1 , David G. Huntsman 156,157,158 , Gregory Idos 17 , Evgeny N. Imyanitov 159 , Sue Ann Ingles 17 , Claudine Isaacs 160 , Anna Jakubowska 90,161 , Paul James 71,162 , Mark A. Jenkins 62,127 , Mattias Johansson 14 , Mikael Johansson 163 , Esther M. John 164 , Amit D. Joshi 3,165 , Radka Kaneva 166 , Beth Y. Karlan 167 , Linda E. Kelemen 168 , Tabea Kühl 169 , Kay-Tee Khaw 170 , Elza Khusnutdinova 171,172 , Adam S. Kibel 173 , Lambertus A. Kiemeney 174 , Jeri Kim 175 , Susanne K. Kjaer 150,176 , Julia A. Knight 177,178 , Manolis Kogevinas 39,179,180,181 , Zsofia Kote-Jarai 40 , Stella Koutros 182 , Vessela N. Kristensen 183,184,185 , Jolanta Kupryjanczyk 186 , Martin Lacko 187 , Stephan Lam 188 , Diether Lambrechts 189,190 , Maria Teresa Landi 191 , Philip Lazarus 192 , Nhu D. Le 193 , Eunjung Lee 123 , Flavio Lejbkowicz 194 , Heinz-Josef Lenz 104 , Goska Leslie 11 , Davor Lessel 195 , Jenny Lester 167 , Douglas A. Levine 196,197 ,LiLi 198,199 , Christopher I. Li 200 , Annika Lindblom 201 , Noralane M. Lindor 202 , Geoffrey Liu 203 , Fotios Loupakis 204 , Jan Lubiński 90 , Lovise Maehle 205 , Christiane Maier 206 , Arto Mannermaa 207,208,209 , Loic Le Marchand 210 , Sara Margolin 211 , Taymaa May 212 , Lesley McGuffog 11 , Alfons Meindl 213 , Pooja Middha 76,214 , Austin Miller 215 , Roger L. Milne 126,127 , Robert J. MacInnis 126,127 , Francesmary Modugno 216,217 , Marco Montagna 218 , Victor Moreno 219 , Kirsten B. Moysich 220 , Lorelei Mucci 3 , Kenneth Muir 221,222 , Anna Marie Mulligan 223,224 , Katherine L. Nathanson 225 , David E. Neal 58,143,226 , Andrew R. Ness 227 , Susan L. Neuhausen 228 , Heli Nevanlinna 229 , Polly A. Newcomb 21,43 , Lisa F. Newcomb 21,230 , Finn Cilius Nielsen 231 , Liene Nikitina-Zake 232 , Børge G. Nordestgaard 50,51,52 , Robert L. Nussbaum 233 , Kenneth Offit 234,235 , Edith Olah 236 , Ali Amin Al Olama 11,237 , Olufunmilayo I. Olopade 238 , Andrew F. Olshan 239,240 , Håkan Olsson 106 , Ana Osorio 38,39 , Hardev Pandha 241 , Jong Y. Park 242 , Nora Pashayan 243,244 , Michael T. Parsons 245 , Tanja Pejovic 246,247 , Kathryn L. Penney 81 , Wilbert H M. Peters 248 , Catherine M. Phelan 242 , Amanda I. Phipps 21,249 , Dijana Plaseska-Karanfilska 250 , Miranda Pring 251 , Darya Prokofyeva 171 , Paolo Radice 252 , Kari Stefansson 253 , Susan J. Ramus 254,255 , Leon Raskin 256 , Gad Rennert 257 , Hedy S. Rennert 257 , Elizabeth J. van Rensburg 258 , Marjorie J. Riggan 41 , Harvey A. Risch 259 , Angela Risch 260,261,262 , Monique J. Roobol 263 , Barry S. Rosenstein 264,265 , Mary Anne Rossing 83,266 , Kim De Ruyck 267 , Emmanouil Saloustros 268 , Dale P. Sandler 269 , Elinor J. Sawyer 270 , Matthew B. Schabath 242 , Johanna Schleutker 271,272,273 , Marjanka K. Schmidt 274,275 , V. Wendy Setiawan 276 , Hongbing Shen 277 , Erin M. Siegel 7 , Weiva Sieh 278 , Christian F. Singer 279 , Martha L. Slattery 280 , Karina Dalsgaard Sorensen 281,282 , Melissa C. Southey 283,284 , Amanda B. Spurdle 245 , Janet L. Stanford 21,249 , Victoria L. Stevens 20 , Sebastian Stintzing 285 , Jennifer Stone 127,286 , Karin Sundfeldt 287 , Rebecca Sutphen 288 , Anthony J. Swerdlow 40,289 , Eloiza H. Tajara 290,291 , Catherine M. Tangen 292 , Adonina Tardon 293 , Jack A. Taylor 269,294 , M. Dawn Teare 295 , Manuel R. Teixeira 296,297 , Mary Beth Terry 298 , Kathryn L. Terry 299,300 , Stephen N. Thibodeau 88 , Mads Thomassen 301 , Line Bjørge 302,303 , Marc Tischkowitz 304,305 , Amanda E. Toland 306 , Diana Torres 142,307 , Paul A. Townsend 308 , Ruth C. Travis 309 , Nadine Tung 310 , Shelley S. Tworoger 3,242 , Cornelia M. Ulrich 21,311 , Nawaid Usmani 312,313 , Celine M. Vachon 133 , ARTICLE NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-018-08054-4 18 NATURE COMMUNICATIONS | (2019) 10:431 | https://doi.org/10.1038/s41467-018-08054-4 | www.nature.com/naturecommunications Els Van Nieuwenhuysen 314 , Ana Vega 39,315 , Miguel Elías Aguado-Barrera 315 , Qin Wang 11 , Penelope M. Webb 316 , Clarice R. Weinberg 317 , Stephanie Weinstein 22 , Mark C. Weissler 318 , Jeffrey N. Weitzel 319 , Catharine M.L. West 320 , Emily White 321,322 , Alice S. Whittemore 323,324 , H-Erich Wichmann 325,326,327 , Fredrik Wiklund 91 , Robert Winqvist 328,329 , Alicja Wolk 140,330 , Penella Woll 331 , Michael Woods 332 , Anna H. Wu 123 , Xifeng Wu 333 , Drakoulis Yannoukakos 114 , Wei Zheng 256 , Shanbeh Zienolddiny 146 , Argyrios Ziogas 27 , Kristin K. Zorn 334 , Jacqueline M. Lane 4,335 , Richa Saxena 4,335 , Duncan Thomas 123 , Rayjean J. Hung 177,178 , Brenda Diergaarde 336,337 , James McKay 338 , Ulrike Peters 249 , Li Hsu 21 , Montserrat García-Closas 22 , Rosalind A. Eeles 40,339 , Georgia Chenevix-Trench 245 , Paul J. Brennan 14 , Christopher A. Haiman 17 , Jacques Simard 340 , Douglas F. Easton 9,11 , Stephen B. Gruber 123 , Paul D.P. Pharoah 9,11 , Alkes L. Price 1,3,4 , Bogdan Pasaniuc 341 , Christopher I. Amos 342 , Peter Kraft 1,3 & Sara Lindström 21,249 1 Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Boston, MA 02115, USA. 2 Unit of Cardiovascular Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Nobels vagen 13, 17177 Stockholm, Sweden. 3 Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Boston, MA 02115, USA. 4 Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, 75 Ames St, Cambridge, MA 02142, USA. 5 Department of Population and Quantitative Health Sciences, Case Western Reserve University, 10900 Eucid Avenue, Cleveland, OH 44106, USA. 6 Seidman Cancer Center, University Hospitals, Cleveland, OH 44106, USA. 7 Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center and Research Institute, 12902 Magnolia Dr. MRC-CANCONT, Tampa, FL 33612, USA. 8 Department of Gastrointestinal Oncology, H. Lee Moffitt Cancer Center and Research Institute, 12902 Magnolia Dr. MRC-CANCONT, Tampa, FL 33612, USA. 9 Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, 2 Worts’Causeway, Cambridge CB1 8RN, UK. 10 Department of Biomedical Data Science, The Geisel School of Medicine at Dartmouth, 1 Medical Center Drive, Lebanon, NH 03756, USA. 11 Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, 2 Worts’Causeway, Cambridge CB1 8RN, UK. 12 Department of Electron Microscopy/Molecular Pathology, The Cyprus Institute of Neurology and Genetics, 1683 Nicosia, Cyprus. 13 Genetic Epidemiology Group, International Agency for Research on Cancer, 150 Cours Albert Thomas, 69008 Lyon, France. 14 Section of Genetics, International Agency for Research on Cancer, 150 cours Albert Thomas, 69008 Lyon, France. 15 Division of Psychiatry, University College London, Maple House, 149 Tottenham Court Road, London W1T 7NF, UK. 16 UCL Genetics Institute, University College London, Gower Street, London WC1E 6BT, UK. 17 Department of Preventive Medicine, Keck School of Medicine, University of Southern California Norris Comprehensive Cancer Center, Los Angeles, CA 48109, USA. 18 Public Health Sciences, University of Virginia, P.O. Box 800717 Charlottesville, VI 22908, USA. 19 Center for Public Health Genomics, University of Virginia, P.O. Box 800717 Charlottesville, VI 22908, USA. 20 Epidemiology Research Program, American Cancer Society, 250 Williams Street NW, Atlanta, GA 30303, USA. 21 Public Health Sciences Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave. N., Seattle, WA 98109-1024, USA. 22 Division of Cancer Epidemiology and Genetics, National Cancer Institute, 9609 Medical Center Dr, Rockville, MD 20850, USA. 23 Department of Thoracic Surgery, Division of Epidemiology, Vanderbilt University Medical Center, 609 Oxford House, Nashville, TN 37232, USA. 24 Department of Neurology, Dartmouth-Hitchcock Medical Center, 7927 Rubin Building, Room 860, One Medical Center Drive, Lebanon, NH 3756, USA. 25 Fred ALitwin Center for Cancer Genetics, Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, 600 University Avenue, Toronto, ON M5G1X5, Canada. 26 Department of Molecular Genetics, University of Toronto, 1 King’s College Circle, Toronto, ON M5S1A8, Canada. 27 Department of Epidemiology, Genetic Epidemiology Research Institute, University of California Irvine, 224 Irvine Hall, Irvine, CA 92617, USA. 28 NNAlexandrov Research Institute of Oncology and Medical Radiology, Settlement of Lesnoy-2, 223040 Minsk, Belarus. 29 Markey Cancer Center, University of Kentucky, 800 Rose Street, cc445, Lexington, KY 40508, USA. 30 Department of Public Health Sciences, and Cancer Research Institute, Queen’s University, 10 Stuart Street, Kingston, ON K7L 3N6, Canada. 31 Department of Breast Medical Oncology, University of Texas MD Anderson Cancer Center, 1155 Pressler St, Houston, TX 77030, USA. 32 Cancer Prevention and Control Program, Rutgers Cancer Institute of New Jersey, 195 Little Albany Street, Room 5568, New Brunswick, NJ 08903, USA. 33 Department of Pathology, Landspitali University Hospital, Hringbraut, Reykjavik 101, Iceland. 34 BMC (Biomedical Centre), Faculty of Medicine, University of Iceland, Vatnsmyrarvegi 16, Reykjavik 101, Iceland. 35 Australian Prostate Cancer Research Centre-Qld, Translational Research Institute, 37 Kent St, Woolloongabba, QLD 4102, Australia. 36 Institute of Health and Biomedical Innovation and School of Biomedical Science, Queensland University of Technology, 60 Musk Ave, Kelvin Grove, QLD 4059, Australia. 37 Department of Gynecology and Obstetrics, Comprehensive Cancer Center Erlangen Nuremberg, University Hospital Erlangen, FriedrichAlexander-University Erlangen-Nuremberg, Universitaetsstrasse 21-23, 91054 Erlangen, Germany. 38 Human Cancer Genetics Programme, Spanish National Cancer Research Centre (CNIO), Calle de Melchor Fernández Almagro, 3, 28029 Madrid, Spain. 39 Biomedical Network on Rare Diseases (CIBERER), AvMonforte de Lemos, 3-5Pabellón 11Planta 0, 28029 Madrid, Spain. 40 Division of Genetics and Epidemiology, The Institute of Cancer Research, 15 Cotswold Road, London SM2 5NG, UK. 41 Department of Obstetrics and Gynecology, Duke University Medical Center, 25171 Morris Bldg, Durham, NC 27710, USA. 42 Department of Genetic Epidemiology, University Medical Center Goettingen, Humboldtallee 32, 37073 Goettingen, Germany. 43 School of Public Health, University of Washington, 1959 NE Pacific Street, Health Science Buidling, F-350, Seattle, WA 98195, USA. 44 Department of Oncology, Helsinki University Hospital, University of Helsinki, Haartmaninkatu 4, 00290 Helsinki, Finland. 45 Department of Oncology, Örebro University Hospital, 70185 Örebro, Sweden. 46 Fondazione Policlinico Universitario AGemelli IRCCS, 00168 Roma, Italy. 47 Università Cattolica del Sacro Cuore, 00168 Roma, Italy. 48 Department of Radiation Oncology, Hannover Medical School, CarlNeuberg-Straße 1, 30625 Hannover, Germany. 49 Gynaecology Research Unit, Hannover Medical School, Carl-Neuberg-Straße 1, 30625 Hannover, Germany. 50 Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev Ringvej 75, 2730 Herlev, Denmark. 51 Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev Ringvej 75, 2730 Herlev, Denmark. 52 Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3B, 2200 Copenhagen, Denmark. 53 DrMargarete Fischer-Bosch-Institute of Clinical Pharmacology, Auerbachstr112, 70376 Stuttgart, Germany. 54 University of Tübingen, Geschwister-Scholl-Platz, 72074 Tübingen, Germany. 55 German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany. 56 Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-018-08054-4 ARTICLE NATURE COMMUNICATIONS | (2019) 10:431 | https://doi.org/10.1038/s41467-018-08054-4 | www.nature.com/naturecommunications 19 69120 Heidelberg, Germany. 57 Division of Preventive Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany. 58 Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, CB2 0RE Cambridge, UK. 59 Genetic Counseling Unit, Hereditary Cancer Program, IDIBGI (Institut d’Investigació Biomèdica de Girona), Catalan Institute of Oncology, CIBERONC, AvFrança s/n, 17007 Girona, Spain. 60 Clinical Sciences, Lund University, Box 117, 221 00 Lund, Sweden. 61 Department of Genetics and Pathology, Division of Laboratory Medicine, 221 85 Lund, Sweden. 62 University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Parkville, VIC 3010, Australia. 63 Colorectal Oncogenomics Group, Department of Clinical Pathology, The University of Melbourne, Parkville, VIC 3010, Australia. 64 Genomic Medicine and Family Cancer Clinic, Royal Melbourne Hospital, Parkville, VIC 3010, Australia. 65 Department of Obstetrics and Gynecology, University of Heidelberg, Im Neuenheimer Feld 440, 69120 Heidelberg, Germany. 66 Molecular Epidemiology Group, C080, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany. 67 Department of Pathology, University of Helsinki and Helsinki University Hospital, Biomedicum Helsinki 4th floor, Haartmaninkatu 8, 00029 Helsinki, Finland. 68 Medical Oncology Department, Hospital Clínico San Carlos, Instituto de Investigación Sanitaria San Carlos (IdISSC), Centro Investigación Biomédica en Red de Cáncer (CIBERONC), Calle del Prof Martín Lagos, 28040 Madrid, Spain. 69 Section of Genetic Oncology, Department of Laboratory Medicine, University and University Hospital of Pisa, via Roma 67, 56126 Pisa, Italy. 70 Peter MacCallum Cancer Center, 305 Grattan Street, Melbourne, VIC 3000, Australia. 71 Sir Peter MacCallum Department of Oncology, The University of Melbourne, 305 Grattan Street, Melbourne, VIC 3000, Australia. 72 Sorbonne Université, GRC N°5 ONCOTYPE-URO, Tenon Hospital, 75020 Paris, France. 73 CeRePP, Tenon Hospital, 75020 Paris, France. 74 Division of Genetic Epidemiology, Department of Medicine, University of Utah School of Medicine, Salt Lake City, UT 84112, USA. 75 George EWahlen Department of Veterans Affairs Medical Center, Salt Lake City, UT 84112, USA. 76 Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany. 77 Department of Biology, University of Pisa, 56126 Pisa, Italy. 78 Molecular Oncology Research Center, Barretos Cancer Hospital, Rua Antenor Duarte Villela, 1331, Barretos, SP 784-400, Brazil. 79 Head and Neck Surgery Department, Barretos Cancer Hospital, Pio XII, 1331, Antenor Duarte Villela St, Barretos, SP 14784-400, Brazil. 80 Division of Gastroenterology, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA. 81 Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, 181 Longwood Avenue, Boston, MA 02115, USA. 82 Cancer Epidemiology Group, University Cancer Center Hamburg (UCCH), University Medical Center HamburgEppendorf, Martinistraße 52, 20246 Hamburg, Germany. 83 Program in Epidemiology, Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, WA 98109, USA. 84 Centre for Medical Genetics, Ghent University, De Pintelaan 185, 9000 Gent, Belgium. 85 Molecular Endocrinology Laboratory, Department of Cellular and Molecular Medicine, KU Leuven, Leuven 3000, Belgium. 86 Department of Clinical Genetics, Erasmus University Medical Center, Wytemaweg 80, 3015 Rotterdam, CN, The Netherlands. 87 University of Puerto Rico Medical Sciences Campus and Comprehensive Cancer Center, San Juan, PR 00936, USA. 88 Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 First StSW, Rochester, MN 55905, USA. 89 Sheffield Institute for Nucleic Acids (SInFoNiA), Department of Oncology and Metabolism, University of Sheffield, Western Bank, Sheffield S10 2TN, UK. 90 International Hereditary Cancer Center, Department of Genetics and Pathology, Pomeranian Medical University, ulUnii Lubelskiej 1, 71-252 Szczecin, Poland. 91 Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Karolinska Univ Hospital, 171 76 Stockholm, Sweden. 92 Department of Clinical Genetics, Fox Chase Cancer Center, 333 Cottman Ave, Philadelphia, PA 19111, USA. 93 Centre for Cancer Research, The Westmead Institute for Medical Research, The University of Sydney, 176 Hawkesbury Rd, Sydney, NSW 2145, Australia. 94 Department of Gynaecological Oncology, Westmead Hospital, Hawkesbury Rd & Darcy Rd, Sydney, NSW 2145, Australia. 95 Department of Pathology, Leiden University Medical Center, Albinusdreef 2, 2333 ZA Leiden, The Netherlands. 96 Department of Human Genetics, Leiden University Medical Center, Albinusdreef 2, 2333 ZA Leiden, The Netherlands. 97 Oncogenetics Group, Clinical and Molecular Genetics Area, Vall d’Hebron Institute of Oncology (VHIO), University Hospital, Vall d’Hebron, Passeig de la Vall d’Hebron 119-129, 08035 Barcelona, Spain. 98 Genomic Medicine Group, Galician Foundation of Genomic Medicine, Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), Complejo Hospitalario Universitario de Santiago, SERGAS, Travesía da Choupana S/N, 15706 Santiago de Compostela, Spain. 99 Moores Cancer Center, University of California, San Diego, 3855 Health Sciences Drive, La Jolla, CA 92037, USA. 100 School of Social and Community Medicine, University of Bristol, Bristol BS8 1TH, UK. 101 Unit of Nutrition and Cancer, Cancer Epidemiology Research Program, Catalan Institute of Oncology (ICO-IDIBELL), AvGran Via 199-203, L’Hospitalet de Llobregat, 08908 Barcelona, Spain. 102 Department of Biomedical Sciences, Faculty of Science and Technology, University of Westminster, 309 Regent Street, London W1B 2HW, UK. 103 Cancer Sciences Academic Unit, Faculty of Medicine, University of Southampton, Tremona Road, Southampton SO16 6YD, UK. 104 Department of Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA. 105 Vanderbilt Epidemiology Center, Vanderbilt Genetics Institute, Department of Obstetrics and Gynecology, Vanderbilt University Medical Center, 2525 West End Avenue, Suite 600, Nashville, TN 37203, USA. 106 Department of Cancer Epidemiology, Clinical Sciences, Lund University, Barngatan 4, Skånes universitetssjukhus, 222 42 Lund, Sweden. 107 Manchester Centre for Genomic Medicine, Division of Evolution and Genomic Sciences, University of Manchester, St Mary’s Hospital, Central Manchester University Hospitals NHS Foundation Trust, Oxford Road, Manchester M13 9WL, UK. 108 David Geffen School of Medicine, Department of Medicine Division of Hematology and Oncology, University of California at Los Angeles, 10833 Le Conte Ave, Los Angeles, CA 90095, USA. 109 Department of Otolaryngology, UPMC Hillman Cancer Center, Cancer Pavilion, University of Pittsburgh, Suite 500, 5150 Centre Avenue, Pittsburgh, PA 15232, USA. 110 Molecular and Clinical Cancer Medicine, Roy Castle Lung Cancer Research Programme, The University of Liverpool Institute of Translational Medicine, The Wiliam Duncan Building, 6 West Derby Street, Liverpool L69 3BX, UK. 111 Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Los Angeles, CA 90048, USA. 112 Keck School of Medicine, University of Southern California, 1450 Biggy Street, Los Angeles, CA 90033, USA. 113 The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, 123 Old Brompton Road, London SW7 3RP, UK. 114 Molecular Diagnostics Laboratory, INRASTES, National Centre for Scientific Research ‘Demokritos’, Neapoleos 10, AgParaskevi, Athens 15310, Greece. 115 Section of Infections, International Agency for Research on Cancer, 150 cours Albert Thomas, 69008 Lyon, France. 116 The Susanne Levy Gertner Oncogenetics Unit, Chaim Sheba Medical Center, Emek HaEla St 1, 52621 Ramat Gan, Israel. 117 Sackler Faculty of Medicine, Tel Aviv University, Haim Levanon 30, 69978 Ramat Aviv, Israel. 118 Department of Surgery, Mount Sinai Hospital, 600 University Avenue, Toronto, ON M5G 1X5, Canada. 119 Samuel Lunenfeld Research Institute, 600 University Avenue, Toronto, ON M5G 1X5, Canada. 120 University Health Network Toronto General Hospital, 200 Elizabeth St, Toronto, ON M5G 2C4, Canada. 121 Schools of Medicine and Public Health, Division of Cancer Prevention & Control Research, Jonsson Comprehensive Cancer Centre, UCLA, 650 Charles Young Drive South, Los Angeles, CA 90095-6900, USA. 122 Cancer Risk and Prevention Clinic, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA 02215, USA. 123 Department of Preventive Medicine, Keck School of Medicine, University of Southern California, 1975 Zonal Ave, Los Angeles, CA 90033, USA. 124 Center for Cancer Prevention and Translational Genomics, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Spielberg Building, 8725 Alden Dr, Los Angeles, CA 90048, USA. 125 Department of Biomedical Sciences, Cedars-Sinai Medical Center, Spielberg Building, 8725 Alden Dr, Los Angeles, CA 90048, USA. 126 Cancer Epidemiology & Intelligence Division, Cancer Council Victoria, 615 St Kilda Road, Melbourne, VIC 3004, Australia. 127 Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Level 1, 723 Swanston Street, Melbourne, VIC 3010, Australia. 128 Department ARTICLE NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-018-08054-4 20 NATURE COMMUNICATIONS | (2019) 10:431 | https://doi.org/10.1038/s41467-018-08054-4 | www.nature.com/naturecommunications of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC, Australia. 129 Department of Pathology and Laboratory Medicine, University of Kansas Medical Center, 3901 Rainbow Blvd, Kansas City, KS 66160, USA. 130 Department of Medicine, McGill University, 1001 Decarie Boulevard, Montréal, QC H4A3J1, Canada. 131 Division of Clinical Epidemiology, Royal Victoria Hospital, McGill University, 1001 Decarie Boulevard, Montréal, QC H4A3J1, Canada. 132 Department of Dermatology, Huntsman Cancer Institute, University of Utah School of Medicine, 2000 Circle of Hope, Salt Lake City, UT 84112, USA. 133 Department of Health Sciences Research, Mayo Clinic, 200 First StSW, Rochester, MN 55905, USA. 134 Cancer Prevention and Control, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, 8700 Beverly Blvd, Room 1S37, Los Angeles, CA 90048, USA. 135 Community and Population Health Research Institute, Department of Biomedical Sciences, Cedars-Sinai Medical Center, 8700 Beverly Blvd, Room 1S37, Los Angeles, CA 90048, USA. 136 Public Health Sciences Division, Swedish Cancer Institute, 1221 Madison StSte 300, Seattle, WA 98109, USA. 137 Unit of Clinical Chemistry, Department of Medical Biosciences, Umeå University, By 6M van 2, Sjukhusomradet, Umea universitet, 901 85 Umea, Sweden. 138 Clinical Genetics Branch, National Cancer Institute, DCEG, 9609 Medical Center Dr, Bethesda, MD 20850-9772, USA. 139 Cancer & Environment Group, Center for Research in Epidemiology and Population Health (CESP), INSERM, University Paris-Sud, University Paris-Saclay, 94805 Villejuif, France. 140 Department of Environmental Medicine, Division of Nutritional Epidemiology, Karolinska Institutet, Nobels väg 13, SE-171 77, SE-171 Stockholm, Sweden. 141 Department of Oncology, Södersjukhuset, Sjukhusbacken 10, 118 83 Stockholm, Sweden. 142 Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 580, 69120 Heidelberg, Germany. 143 Nuffield Department of Surgical Sciences, Faculty of Medical Science, John Radcliffe Hospital, University of Oxford, Oxford OX1 2JD, UK. 144 Department of Surgical Oncology, Princess Margaret Cancer Centre, 610 University Avenue, Toronto, Ontario M5G2M9, Canada. 145 Department of Internal Medicine 1, University Hospital Dresden, Technische Universität Dresden (TU Dresden), 01307 Dresden, Germany. 146 National Institute of Occupational Health (STAMI), Gydas vei 8, 0033 Oslo, Norway. 147 Department of Gynecology and Gynecologic Oncology, DrHorst Schmidt Kliniken Wiesbaden, Ludwig-Erhard-Straße 100, 65199 Wiesbaden, Germany. 148 Department of Gynecology and Gynecologic Oncology, Kliniken Essen-Mitte/ EvangHuyssens-Stiftung/ Knappschaft GmbH, Henricistrasse 92, 45136 Essen, Germany. 149 Early Detection and Prevention Section, International Agency for Research on Cancer, 150 cours Albert Thomas, 69008 Lyon, France. 150 Department of Virus, Lifestyle and Genes, Danish Cancer Society Research Center, Strandboulevarden 49, DK-2100 Copenhagen, Denmark. 151 Molecular Unit, Department of Pathology, Herlev Hospital, University of Copenhagen, Herlev Ringvej 75, DK-2730 Herlev, Denmark. 152 Preventive Medicine, Seoul National University College of Medicine, 1 Gwanak-ro, Gwanak-gu, Seoul 151 742, Korea. 153 German Research Center for Environmental Health, Institute for Cancer Research, Ingolstadter Landstr1, London SM2 5NG, UK. 154 Center for Medical Genetics, NorthShore University HealthSystem, 1000 Central St, Evanston, IL 60201, USA. 155 The University of Chicago Pritzker School of Medicine, 924 E 57th St, Chicago, IL 60637, USA. 156 British Columbia’s Ovarian Cancer Research (OVCARE) Program, Vancouver General Hospital, BC Cancer Agency and University of British Columbia, #3427-600 West 10th Avenue, Vancouver, BC V5Z 4E6, Canada. 157 Department of Molecular Oncology, BC Cancer Agency Research Centre, #3427-600 West 10th Avenue, Vancouver, BC V5Z 4E6, Canada. 158 Department of Pathology and Laboratory Medicine, University of British Columbia, #3427-600 West 10th Avenue, Vancouver, BC V5Z 4E6, Canada. 159 NNPetrov Institute of Oncology, Leningradskaya ul, 68, StPetersburg, Russia 197758. 160 Lombardi Comprehensive Cancer Center, Georgetown University, 3800 Reservoir Road, Washington, DC 20007, USA. 161 Independent Laboratory of Molecular Biology and Genetic Diagnostics, Pomeranian Medical University, Rybacka 1, 70-204 Szczecin, Poland. 162 Parkville Familial Cancer Centre, Peter MacCallum Cancer Center, 305 Grattan Street, Melbourne, VIC 3000, Australia. 163 Department of Radiation Sciences, Umeå University, By 6M van 2, Sjukhusomradet, Umea universitet, 901 85 Umea, Sweden. 164 Department of Medicine, Division of Oncology and Stanford Cancer Institute, Stanford University School of Medicine, 780 Welch Rd, Stanford, CA 94304, USA. 165 Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, 02114 Boston, MA, USA. 166 Molecular Medicine Center, Department of Medical Chemistry and Biochemistry, Medical Faculty, Medical University of Sofia, Sofia 1504, Bulgaria. 167 Women’s Cancer Program at the Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Los Angeles, CA 90048, USA. 168 Hollings Cancer Center and Department of Public Health Sciences, Medical University of South Carolina, 68 President Street Bioengineering Building, MSC955, Charleston, SC 29425, USA. 169 Cancer Epidemiology, University Cancer Center Hamburg (UCCH), University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany. 170 Clinical Gerontology, Department of Public Health and Primary Care, University of Cambridge, 2 Worts’Causeway, Cambridge CB1 8RN, UK. 171 Department of Genetics and Fundamental Medicine, Bashkir State University, ulZaki Validi 32, Ufa, Russia 450076. 172 Institute of Biochemistry and Genetics, Ufa Scientific Center of Russian Academy of Sciences, 71 prosp Oktyabrya, Ufa, Russia 450054. 173 Division of Urologic Surgery, Brigham and Womens Hospital, Boston, Massachusettes 02115, USA. 174 Radboud Institute for Health Sciences, Radboud University Medical Center, Geert Grooteplein 21, 6525 EZ Nijmegen, The Netherlands. 175 Department of Genitourinary Medical Oncology, University of Texas MD Anderson Cancer Center, 1155 Pressler St, Houston, TX 77030, USA. 176 Department of Gynaecology, Rigshospitalet, University of Copenhagen, Blegdamsvej 9, DK-2100 Copenhagen, Denmark. 177 Prosserman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health System, 60 Murray Street, Toronto, Ontario M5T 3L9, Canada. 178 Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, 155 College Street, Toronto, ON M5T3M7, Canada. 179 Centre for Research in Environmental Epidemiology (CREAL), ISGlobal, 08036 Barcelona, Spain. 180 IMIM (Hospital del Mar Research Institute), Barcelona 08003, Spain. 181 Universitat Pompeu Fabra (UPF), Barcelona 08002, Spain. 182 Division of Cancer Epidemiology and Genetics, National Cancer Institute, Department of Health and Human Services, National Institutes of Health, 9609 Medical Center Dr, Bethesda, MD 20892, USA. 183 Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, Ullernchausseen 70, 0379 Oslo, Norway. 184 Faculty of Medicine, Institute of Clinical Medicine, University of Oslo, Kirkeveien 166, 0450 Oslo, Norway. 185 Department of Clinical Molecular Biology, Oslo University Hospital, University of Oslo, Kirkeveien 166, 0450 Oslo, Norway. 186 Department of Pathology and Laboratory Diagnostics, the Maria Sklodowska-Curie Institute - Oncology Center, Roentgena 5, 02-781 Warsaw, Poland. 187 Head and Neck Surgery, Department of Otorhinolaryngology, Maastricht University Medical Center, PDebyelaan 25, POBox 5800, 6202 AZ Maastricht, The Netherlands. 188 Department of Integrative Oncology, British Columbia Cancer Agency, Room 10-111 675 West 10th Avenue, Vancouver, BC V5Z1L3, Canada. 189 VIB Center for Cancer Biology, VIB, Herestraat 49, 3001 Leuven, Belgium. 190 Laboratory for Translational Genetics, Department of Human Genetics, University of Leuven, Oude Markt 13, 3000 Leuven, Belgium. 191 Integrative Tumor Epidemiology Branch, DCEG, National Cancer Institute, 9609 Medical Center Drive, Room SG/7E106, Rockville, MD 20850, USA. 192 College of Pharmacy, Washington State University, PBS 431 PO Box 1495, Spokane, WA 99210-1495, USA. 193 Cancer Control Research, BC Cancer Agency, 675 West 10th Avenue, Vancouver, BC V5Z 1L3, Canada. 194 Clalit Health Services, Clalit National Israeli Cancer Control Center, Carmel Medical Center, 2 Horev Street, 3436212 Haifa, Israel. 195 Institute of Human Genetics, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany. 196 Gynecology Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA. 197 Gynecologic Oncology, Laura and Isaac Pearlmutter Cancer Center, NYU Langone Medical Center, 240 East 38th Street 19th Floor, New York, NY 10016, USA. 198 Department of Family Medicine and Community Health, Mary Ann Swetland Center for Environmental Health, Case Western Reserve University, Cleveland, OH 44106, USA. 199 Servicio Galego de Saude (SERGAS), Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), 15706 Santiago De Compostela, Spain. 200 Translational Research Program, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA. 201 Department of NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-018-08054-4 ARTICLE NATURE COMMUNICATIONS | (2019) 10:431 | https://doi.org/10.1038/s41467-018-08054-4 | www.nature.com/naturecommunications 21 Molecular Medicine and Surgery, Karolinska Institutet, Karolinska Univ Hospital, 171 76 Stockholm, Sweden. 202 Health Sciences Research, Mayo Clinic Arizona, 13400 EShea Blvd, Scottsdale, AZ 85259, USA. 203 Epidemiology Division, Princess Margaret Cancer Centre, 610 University Avenue, Toronto, ON M5G2M9, Canada. 204 Unit of Oncology 1, Department of Clinical and Experimental Oncology, Istituto Oncologico Veneto IRCCS, 35122 Padua, Italy. 205 Department of Medical Genetics, Oslo University Hospital, Kirkeveien 166, 0450 Oslo, Norway. 206 Institute of Human Genetics, University Hospital Ulm, Prittwitzstrasse 43, 89075 Ulm, Germany. 207 Translational Cancer Research Area, University of Eastern Finland, Yliopistonranta 1, 70210 Kuopio, Finland. 208 Institute of Clinical Medicine, Pathology and Forensic Medicine, University of Eastern Finland, KuopioYliopistonranta 1, 70210, Finland. 209 Imaging Center, Department of Clinical Pathology, Kuopio University Hospital, Puijonlaaksontie 2, 70210 Kuopio, Finland. 210 Epidemiology Program, University of Hawaii Cancer Center, 701 Ilalo St, Honolulu, HI 96813, USA. 211 Department of Clinical Science and Education, Södersjukhuset, Karolinska Institutet, Stockholm 17177, Sweden. 212 Division of Gynecologic Oncology, University Health Network, Princess Margaret Hospital, 610 University Avenue, OPG Wing, 6-811, Toronto, ON M5G 2M9, Canada. 213 Division of Gynaecology and Obstetrics, , Technische Universität München, Arcisstraße 21, 80333 Munich, Germany. 214 Faculty of Medicine, University of Heidelberg, In Neuenheimer Feld 672, 69120 Heidelberg, Germany. 215 NRG Oncology, Statistics and Data Management Center, Roswell Park Cancer Institute, Elm & Carlton Streets, Buffalo, NY 14263, USA. 216 Womens Cancer Research Center, Magee-Womens Research Institute and Hillman Cancer Center, Pittsburgh, PA 15213, USA. 217 Division of Gynecologic Oncology, Department of Obstetrics, Gynecology and Reproductive Sciences, University of Pittsburgh School of Medicine, 300 Halket Street, Pittsburgh, PA 15213, USA. 218 Immunology and Molecular Oncology Unit, Veneto Institute of Oncology IOV - IRCCS, Via Gattamelata 64, Padua 35128, Italy. 219 Catalan Institute of Oncology, Bellvitge Biomedical Research Institute (IDIBELL), Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP) and University of Barcelona, Barcelona 08908, Spain. 220 Division of Cancer Prevention and Control, Roswell Park Cancer Institute, Elm & Carlton Streets, Buffalo, NY 14263, USA. 221 Division of Population Health, Health Services Research and Primary Care, University of Manchester, Oxford Road, Manchester M13 9PL, UK. 222 Division of Health Sciences, Warwick Medical School, University of Warwick, Coventry CV4 7AL, UK. 223 Department of Laboratory Medicine and Pathobiology, University of Toronto, 1 King’s College Circle, Toronto, ON M5S1A8, Canada. 224 Laboratory Medicine Program, University Health Network, 200 Elizabeth Street, Toronto, ON M5G2C4, Canada. 225 Department of Medicine, Abramson Cancer Center, Perelman School of Medicine at the University of Pennsylvania, 3400 Civic Center Boulevard, Philadelphia, PA 19104, USA. 226 Department of Oncology, Addenbrooke’s Hospital, University of Cambridge, Cambridge CB1 8RN, UK. 227 NIHR Bristol Biomedical Research Centre Nutrition Theme, University of Bristol, Upper Maudlin Street, Bristol BS2 8AE, UK. 228 Department of Population Sciences, Beckman Research Institute of City of Hope, 1500 E Duarte, Duarte, CA 91010, USA. 229 Department of Obstetrics and Gynecology, Helsinki University Hospital, University of Helsinki, Haartmaninkatu 8, 00290 Helsinki, Finland. 230 Department of Urology, University of Washington, Seattle, Washington 98195, USA. 231 Center for Genomic Medicine, Rigshospitalet, Copenhagen University Hospital, Blegdamsvej 9, DK-2100 Copenhagen, Denmark. 232 Latvian Biomedical Research and Study Centre, Ratsupites str 1, Riga LV-1067, Latvia. 233 Cancer Genetics and Prevention Program, University of California San Francisco, 1600 Divisadero St, San Francisco, CA 94143-1714, USA. 234 Clinical Genetics Research Lab, Department of Cancer Biology and Genetics, Memorial Sloan-Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA. 235 Clinical Genetics Service, Department of Medicine, Memorial Sloan-Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA. 236 Department of Molecular Genetics, National Institute of Oncology, Ráth György u7-9, 1122 Budapest, Hungary. 237 Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 0QQ, UK. 238 Center for Clinical Cancer Genetics, The University of Chicago, 5841S Maryland Ave, Chicago, IL 60637, USA. 239 Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, 135 Dauer Dr, Chapel Hill, NC 27599-7435, USA. 240 UNC Lineberger Comprehensive Cancer Center, 450 West Dr, Chapell Hill, NC 27599, USA. 241 The University of Surrey, Guildford, Surrey GU2 7XH, UK. 242 Department of Cancer Epidemiology, HLee Moffitt Cancer Center and Research Institute, 12902 Magnolia Drive, Tampa, FL 33612, USA. 243 Department of Applied Health Research, University College London, 1-19 Torrington Place, London WC1E 6BT, UK. 244 Centre for Cancer Genetic Epidemiology, Department of Oncology, Strangeways Laboratory, University of Cambridge, Cambridge CB1 8RN, UK. 245 Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, 300 Herston Road, Brisbane, QLD 4006, Australia. 246 Department of Obstetrics and Gynecology, Oregon Health & Science University, 3181 SW Sam Jackson Park Road, L-466, Portland, OR 97239, USA. 247 Knight Cancer Institute, Oregon Health & Science University, 3181 SW Sam Jackson Park Road, L-466, Portland, OR 97239, USA. 248 Department of Gastroenterology, Radboud University Nijmegen Medical Center, Geert Grooteplein Zuid 10, Internal BOBox 433, 6525 GA Nijmegen, The Netherlands. 249 Department of Epidemiology, University of Washington School of Public Health, 1959 NE Pacific St, Seattle, WA 98195, USA. 250 Research Centre for Genetic Engineering and Biotechnology ‘Georgi DEfremov’, Macedonian Academy of Sciences and Arts, Boulevard Krste Petkov Misirkov, 1000 Skopje, Republic of Macedonia. 251 Bristol Dental School, University of Bristol, Lower Maudlin Street, Bristol BS1 2LY, UK. 252 Unit of Molecular Bases of Genetic Risk and Genetic Testing, Department of Research, Fondazione IRCCS (Istituto Di Ricovero e Cura a Carattere Scientifico) Istituto Nazionale dei Tumori (INT), Via Giacomo Venezian 1, 20133 Milan, Italy. 253 Decode genetics, Sturlugata 8, IS-101 ReykjavikReykjavikIceland, Iceland. 254 School of Women’s and Children’s Health, Faculty of Medicine, University of NSW Sydney, 18 High St, Sydney, NSW 2052, Australia. 255 The Kinghorn Cancer Centre, Garvan Institute of Medical Research, 384 Victoria Street, Sydney, NSW 2010, Australia. 256 Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, 1161 21st Ave S # D3300, Nashville, TN 37232, USA. 257 Clalit National Cancer Control Center, Carmel Medical Center and Technion Faculty of Medicine, 7 Michal Street, 34362 Haifa, Israel. 258 Department of Genetics, University of Pretoria, Private Bag X323, Arcadia 0007, South Africa. 259 Department of Chronic Disease Epidemiology, Yale School of Public Health, 60 College St, New Haven, CT 06510, USA. 260 Cancer Center Cluster Salzburg at PLUS, Department of Molecular Biology, University of Salzburg, Billrothstr11, 5020 Salzburg, Austria. 261 Division of Epigenomics and Cancer Risk Factors, DKFZ –German Cancer Research Center, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany. 262 Member of the German Center for Lung Research (DZL), Translational Lung Research Center Heidelberg (TLRC-H), 69120 Heidelberg, Germany. 263 Department of Urology, Erasmus University Medical Center, Wytemaweg 80, 3015 CN Rotterdam, The Netherlands. 264 Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY 10029, USA. 265 Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY 10029, USA. 266 Department of Epidemiology, University of Washington, M4 C308, 1100 Fairview Ave N, Seattle, WA 98109, USA. 267 Faculty of Medicine and Health Sciences, Basic Medical Sciences, Ghent University, De Pintelaan 185, 9000 Gent, Belgium. 268 Hereditary Cancer Clinic, University Hospital of Heraklion, Voutes, 711 10 Heraklion, Greece. 269 Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, 111TWAlexander Drive, Research Triangle Park, NC 27709, USA. 270 Research Oncology, Guy’s Hospital, King’s College London, Guy’s Hospital Great Maze Pond, London SE1 9RT, UK. 271 Institute of Biomedicine, University of Turku, 20014 Turku, Finland. 272 Division of Laboratory, Department of Medical Genetics, Turku University Hospital, 20014 Turku, Finland. 273 Prostate Cancer Research Center, Faculty of Medicine and Life Sciences and BioMediTech Institute, University of Tampere, 33014 Tampere, Finland. 274 Division of Molecular Pathology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands. 275 Division of Psychosocial Research and Epidemiology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek hospital, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands. 276 Department of Preventive Medicine, Keck School of Medicine, University of Southern ARTICLE NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-018-08054-4 22 NATURE COMMUNICATIONS | (2019) 10:431 | https://doi.org/10.1038/s41467-018-08054-4 | www.nature.com/naturecommunications California, 1450 Biggy Street, Los Angeles, CA 90033, USA. 277 Department of Epidemiology and Biostatistics, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, 101 Longmian Ave, Jiangning District, 211166 Nanjing, People’s Republic of China. 278 Department of Genetics and Genomic Sciences, Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, 2nd floor, New York, NY 10029, USA. 279 Dept of OB/GYN and Comprehensive Cancer Center, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria. 280 Department of Internal Medicine, University of Utah Health Sciences Center, 295 Chipeta Way, Salt Lake City, UT 84132, USA. 281 Department of Molecular Medicine, Aarhus University Hospital, DK-8200 Aarhus, Denmark. 282 Department of Clinical Medicine, Aarhus University, DK-8200 Aarhus, Denmark. 283 Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, 246 Clayton Road, Clayton, VIC 3168, Australia. 284 Department of Clinical Pathology, The University of Melbourne, Cnr Grattan Street and Royal Parade, Melbourne, VIC 3010, Australia. 285 Department of Medicine III, University Hospital, LMU Munich, Marchioninistr15, 81377 Munich, Germany. 286 The Curtin UWA Centre for Genetic Origins of Health and Disease, Curtin University and University of Western Australia, 35 Stirling Hwy, Perth, WA 6000, Australia. 287 Department of Obstetrics and Gynecology, Sahlgrenska Cancer Center, Inst Clinical Scienses, University of Gothenburg, Blå stråket 6, 41345 Gothenburg, Sweden. 288 Epidemiology Center, College of Medicine, University of South Florida, 3650 Spectrum Blvd, Suite 100, Tampa, FL 33612, USA. 289 Division of Breast Cancer Research, The Institute of Cancer Research, London SW7 3RP, UK. 290 Department of Molecular Biology, School of Medicine of São José do Rio Preto, Av Brig Faria Lima 5416 Vila São Pedro, São José do Rio Preto, SP 15090-000, Brazil. 291 Department of Genetics and Evolutive Biology, Institute of Biosciences, University of São Paulo, Rua do Matão, 321, São Paulo, SP 05508090, Brazil. 292 SWOG Statistical Center, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, USA. 293 Faculty of Medicine, University of Oviedo and CIBERESP, Campus del Cristo s/n, 33006 Oviedo, Spain. 294 Epigenetic and Stem Cell Biology Laboratory, National Institute of Environmental Health Sciences, NIH, 111TWAlexander Drive, Research Triangle Park, NC 27709, USA. 295 Medical Statistics Group, School of Health and Related Research (ScHARR), University of Sheffield, Regent Court, 30 Regent Street, Sheffield S1 4DA, UK. 296 Department of Genetics, Portuguese Oncology Institute, Rua DrAntónio Bernardino de Almeida 62, 4220-072 Porto, Portugal. 297 Biomedical Sciences Institute (ICBAS), University of Porto, RJorge de Viterbo Ferreira 228, 4050-013 Porto, Portugal. 298 Department of Epidemiology, Mailman School of Public Health, Columbia University, 722 West 168th Street, New York, NY 10032, USA. 299 Obstetrics and Gynecology Epidemiology Center, Brigham and Women’s Hospital, 221 Longwood Avenue RFB 368, Boston, MA 02115, USA. 300 Harvard THChan School of Public Health, 221 Longwood Avenue RFB 368, Boston, MA 02115, USA. 301 Department of Clinical Genetics, Odense University Hospital, Sonder Boulevard 29, 5000 Odence C, Denmark. 302 Department of Gynecology and Obstetrics, Haukeland University Hospital, 5021 Bergen, Norway. 303 Centre for Cancer Biomarkers CCBIO, Department of Clinical Science, University of Bergen, 5021 Bergen, Norway. 304 Program in Cancer Genetics, Departments of Human Genetics and Oncology, McGill University, 1001 Decarie Boulevard, Montréal, QC H4A3J1, Canada. 305 Department of Medical Genetics, Cambridge University, Hills Road, Cambridge CB2 0QQ, UK. 306 Department of Cancer Biology and Genetics, The Ohio State University, 460W12th Avenue, Columbus, OH 43210, USA. 307 Institute of Human Genetics, Pontificia Universidad Javeriana, Carrera 7 No40-90, Bogota, Colombia. 308 Division of Cancer Sciences, Manchester Cancer Research Centre, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, NIHR Manchester Biomedical Research Centre, Health Innovation Manchester, University of Manchester, Manchester M20 4GJ, UK. 309 Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK. 310 Department of Medical Oncology, Beth Israel Deaconess Medical Center, 330 Brookline Avenue, Boston, MA 02215, USA. 311 Huntsman Cancer Institute and Department of Population Health Sciences, University of Utah, 2000 Circle of Hope, Rm 4125, Salt Lake City, UT 84112, USA. 312 Department of Oncology, Cross Cancer Institute, University of Alberta, 116 St & 85 Ave, Edmonton AB T6G 2R3, Canada. 313 Division of Radiation Oncology, Cross Cancer Institute, University of Alberta, 116 St & 85 Ave, Edmonton AB T6G 2R3, Canada. 314 Division of Gynecologic Oncology, Department of Obstetrics and Gynaecology and Leuven Cancer Institute, University Hospitals Leuven, Herestraat 49, 3000 Leuven, Belgium. 315 Fundación Pública Galega Medicina Xenómica & Instituto de Investigación Sanitaria de Santiago de Compostela, calle Choupana s/n, 15706 Santiago De Compostela, Spain. 316 Population Health Department, QIMR Berghofer Medical Research Institute, 300 Herston Road, Brisbane, QLD 4006, Australia. 317 Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, NIH, 111TWAlexander Drive, Research Triangle Park, NC 27709, USA. 318 Department of Otolaryngology/Head and Neck Surgery, University of North Carolina at Chapel Hill, Chapel Hill 27514 NC, USA. 319 City of Hope Clinical Cancer Genomics Community Research Network, 1500 East Duarte Road, Duarte, CA 91010, USA. 320 Division of Cancer Sciences, University of Manchester, Manchester Cancer Research Centre, Manchester Academic Health Science Centre,, The Christie Hospital NHS Foundation Trust, Manchester M13 9PL, UK. 321 Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, WA 98109, USA. 322 Department of Epidemiology, University of Washington, 1100 Fairview Ave N, Seattle, WA 98109, USA. 323 Department of Health Research and Policy - Epidemiology, Stanford University School of Medicine, 259 Campus Drive, Stanford, CA 94305, USA. 324 Department of Biomedical Data Science, Stanford University School of Medicine, 259 Campus Drive, Stanford, CA 94305, USA. 325 Institute of Medical Informatics, Biometry and Epidemiology, Chair of Epidemiology, Ludwig Maximilians University, Neuherberg D-85764, Munich 803539 Bavaria, Germany. 326 Helmholtz Zentrum Munchen, German Research Center for Environmental Health (GmbH), Institute of Epidemiology, Ingolstadter Landstr1, 85764 Neuherberg, Germany. 327 Institute of Medical Statistics and Epidemiology, Technical University Munich, Munich 80333, Germany. 328 Laboratory of Cancer Genetics and Tumor Biology, Cancer and Translational Medicine Research Unit, Biocenter Oulu, University of Oulu, Aapistie 5A, 90220 Oulu, Finland. 329 Laboratory of Cancer Genetics and Tumor Biology, Northern Finland Laboratory Centre Oulu, Aapistie 5A, 90220 Oulu, Finland. 330 Department of Surgical Sciences, Uppsala University, 751 85 Uppsala, Sweden. 331 Academic Unit of Clinical Oncology, University of Sheffield, Weston Park Hospital, Whitham Road, Sheffield S10 2SJ, UK. 332 Discipline of Genetics, Memorial University of Newfoundland, StJohn’s, NL A1C 5S7, Canada. 333 Department of Epidemiology, Division of Cancer Prevention and Population Science, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030, USA. 334 Magee-Womens Hospital, University of Pittsburgh School of Medicine, 300 Halket St, Pittsburgh, PA 15213, USA. 335 Center for Genomic Medicine and Department of Anasthesia, Massachusetts General Hospital, Boston, MA 02114, USA. 336 Human Genetics, Graduate School of Public Health, University of Pittsburgh, UPMC Cancer Pavilion, Suite 4C, Office # 467, 5150 Centre Avenue, Pittsburgh, PA 15232, USA. 337 UPMC Hillman Cancer Center, Pittsburgh 15232 PA, USA. 338 Genetic Cancer Susceptibility Group, International Agency for Research on Cancer, 150 cours Albert Thomas, 69008 Lyon, France. 339 Oncogenetics Team, The Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Downs Road, Sutton SM2 5NG, UK. 340 Genomics Center, Centre Hospitalier Universitaire de Québec - Université Laval Research Center, 2705 Laurier Boulevard, Québec City, QC G1V4G2, Canada. 341 UCLA Path and Lab Med, University of California, 10833 Le Conte Ave, Los Angeles, CA 190095, USA. 342 Department of Medicine, Epidemiology Section, Institute for Clinical and Translational Research, Baylor Medical College, One Baylor Plaza, MS: BCM451, Suite 100D, Houston, TX 77030-3411, USA NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-018-08054-4 ARTICLE NATURE COMMUNICATIONS | (2019) 10:431 | https://doi.org/10.1038/s41467-018-08054-4 | www.nature.com/naturecommunications 23