Recent heritability analyses have indicated that genome-wide association studies (GWAS) have the potential to improve genetic risk prediction for complex diseases based on polygenic risk score (PRS), a simple modelling technique that can be implemented using summary-level data from the discovery samples. We herein propose modifications to improve the performance of PRS. We introduce threshold-dependent winner's-curse adjustments for marginal association coefficients that are used to weight the single-nucleotide polymorphisms (SNPs) in PRS. Further, as a way to incorporate external functional/annotation knowledge that could identify subsets of SNPs highly enriched for associations, we propose variable thresholds for SNPs selection. We applied our methods to GWAS summary-level data of 14 complex diseases. Across all diseases, a simple winner's curse correction uniformly led to enhancement of performance of the models, whereas incorporation of functional SNPs was beneficial only for selected diseases. Compared to the standard PRS algorithm, the proposed methods in combination led to notable gain in efficiency (25-50% increase in the prediction R2) for 5 of 14 diseases. As an example, for GWAS of type 2 diabetes, winner's curse correction improved prediction R2 from 2.29% based on the standard PRS to 3.10% (P = 0.0017) and incorporating functional annotation data further improved R2 to 3.53% (P = 2×10-5). Our simulation studies illustrate why differential treatment of certain categories of functional SNPs, even when shown to be highly enriched for GWAS-heritability, does not lead to proportionate improvement in genetic risk-prediction because of non-uniform linkage disequilibrium structure.

Pathway analysis of genome-wide association studies (GWAS) offer a unique opportunity to collectively evaluate genetic variants with effects that are too small to be detected individually. We applied a pathway analysis to a bladder cancer GWAS containing data from 3,532 cases and 5,120 controls of European background (n = 5 studies). Thirteen hundred and ninety-nine pathways were drawn from five publicly available resources (Biocarta, Kegg, NCI-PID, HumanCyc, and Reactome), and we constructed 22 additional candidate pathways previously hypothesized to be related to bladder cancer. In total, 1421 pathways, 5647 genes and ∼90,000 SNPs were included in our study. Logistic regression model adjusting for age, sex, study, DNA source, and smoking status was used to assess the marginal trend effect of SNPs on bladder cancer risk. Two complementary pathway-based methods (gene-set enrichment analysis [GSEA], and adapted rank-truncated product [ARTP]) were used to assess the enrichment of association signals within each pathway. Eighteen pathways were detected by either GSEA or ARTP at P≤0.01. To minimize false positives, we used the I(2) statistic to identify SNPs displaying heterogeneous effects across the five studies. After removing these SNPs, seven pathways ('Aromatic amine metabolism' [P(GSEA) = 0.0100, P(ARTP) = 0.0020], 'NAD biosynthesis' [P(GSEA) = 0.0018, P(ARTP) = 0.0086], 'NAD salvage' [P(ARTP) = 0.0068], 'Clathrin derived vesicle budding' [P(ARTP) = 0.0018], 'Lysosome vesicle biogenesis' [P(GSEA) = 0.0023, P(ARTP)<0.00012], 'Retrograde neurotrophin signaling' [P(GSEA) = 0.00840], and 'Mitotic metaphase/anaphase transition' [P(GSEA) = 0.0040]) remained. These pathways seem to belong to three fundamental cellular processes (metabolic detoxification, mitosis, and clathrin-mediated vesicles). Identification of the aromatic amine metabolism pathway provides support for the ability of this approach to identify pathways with established relevance to bladder carcinogenesis.

Tobacco smoking is responsible for over 90% of lung cancer cases, and yet the precise molecular alterations induced by smoking in lung that develop into cancer and impact survival have remained obscure.

Little is known whether genetic variants identified in genome-wide association studies interact to increase bladder cancer risk. Recently, we identified two- and three-variant combinations associated with a particular increase of bladder cancer risk in a urinary bladder cancer case-control series (Leibniz Research Centre for Working Environment and Human Factors at TU Dortmund (IfADo), 1501 cases, 1565 controls). In an independent case-control series (Nijmegen Bladder Cancer Study, NBCS, 1468 cases, 1720 controls) we confirmed these two- and three-variant combinations. Pooled analysis of the two studies as discovery group (IfADo-NBCS) resulted in sufficient statistical power to test up to four-variant combinations by a logistic regression approach. The New England and Spanish Bladder Cancer Studies (2080 cases and 2167 controls) were used as a replication series. Twelve previously identified risk variants were considered. The strongest four-variant combination was obtained in never smokers. The combination of rs1014971[AA] near apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like 3A (APOBEC3A) and chromobox homolog 6 (CBX6), solute carrier family 1s4 (urea transporter), member 1 (Kidd blood group) (SLC14A1) exon single nucleotide polymorphism (SNP) rs1058396[AG, GG], UDP glucuronosyltransferase 1 family, polypeptide A complex locus (UGT1A) intron SNP rs11892031[AA] and rs8102137[CC, CT] near cyclin E1 (CCNE1) resulted in an unadjusted odds ratio (OR) of 2.59 (95% CI = 1.93-3.47; P = 1.87 × 10-10), while the individual variant ORs ranged only between 1.11 and 1.30. The combination replicated in the New England and Spanish Bladder Cancer Studies (ORunadjusted = 1.60, 95% CI = 1.10-2.33; P = 0.013). The four-variant combination is relatively frequent, with 25% in never smoking cases and 11% in never smoking controls (total study group: 19% cases, 14% controls). In conclusion, we show that four high-risk variants can statistically interact to confer increased bladder cancer risk particularly in never smokers.

High-throughput transcriptomics has matured into a very well established and widely utilised research tool over the last two decades. Clinical datasets generated on a range of different platforms continue to be deposited in public repositories provide an ever-growing, valuable resource for reanalysis. Cost and tissue availability normally preclude processing samples across multiple technologies, making it challenging to directly evaluate performance and whether data from different platforms can be reliably compared or integrated.

Bladder cancer has been linked with long-term exposure to disinfection by-products (DBPs) in drinking water.

The length of female reproductive lifespan is associated with multiple adverse outcomes, including breast cancer, cardiovascular disease and infertility. The biological processes that govern the timing of the beginning and end of reproductive life are not well understood. Genetic variants are known to contribute to ∼50% of the variation in both age at menarche and menopause, but to date the known genes explain <15% of the genetic component. We have used genome-wide association in a bivariate meta-analysis of both traits to identify genes involved in determining reproductive lifespan. We observed significant genetic correlation between the two traits using genome-wide complex trait analysis. However, we found no robust statistical evidence for individual variants with an effect on both traits. A novel association with age at menopause was detected for a variant rs1800932 in the mismatch repair gene MSH6 (P = 1.9 × 10(-9)), which was also associated with altered expression levels of MSH6 mRNA in multiple tissues. This study contributes to the growing evidence that DNA repair processes play a key role in ovarian ageing and could be an important therapeutic target for infertility.

Analyses of genome-wide association study (GWAS) data have revealed that detectable genetic mosaicism involving large (>2 Mb) structural autosomal alterations occurs in a fraction of individuals. We present results for a set of 24,849 genotyped individuals (total GWAS set II [TGSII]) in whom 341 large autosomal abnormalities were observed in 168 (0.68%) individuals. Merging data from the new TGSII set with data from two prior reports (the Gene-Environment Association Studies and the total GWAS set I) generated a large dataset of 127,179 individuals; we then conducted a meta-analysis to investigate the patterns of detectable autosomal mosaicism (n = 1,315 events in 925 [0.73%] individuals). Restricting to events >2 Mb in size, we observed an increase in event frequency as event size decreased. The combined results underscore that the rate of detectable mosaicism increases with age (p value = 5.5 × 10(-31)) and is higher in men (p value = 0.002) but lower in participants of African ancestry (p value = 0.003). In a subset of 47 individuals from whom serial samples were collected up to 6 years apart, complex changes were noted over time and showed an overall increase in the proportion of mosaic cells as age increased. Our large combined sample allowed for a unique ability to characterize detectable genetic mosaicism involving large structural events and strengthens the emerging evidence of non-random erosion of the genome in the aging population.

Breast cancer is the most common cancer among women. To date, 22 common breast cancer susceptibility loci have been identified accounting for ∼8% of the heritability of the disease. We attempted to replicate 72 promising associations from two independent genome-wide association studies (GWAS) in ∼70,000 cases and ∼68,000 controls from 41 case-control studies and 9 breast cancer GWAS. We identified three new breast cancer risk loci at 12p11 (rs10771399; P = 2.7 × 10(-35)), 12q24 (rs1292011; P = 4.3 × 10(-19)) and 21q21 (rs2823093; P = 1.1 × 10(-12)). rs10771399 was associated with similar relative risks for both estrogen receptor (ER)-negative and ER-positive breast cancer, whereas the other two loci were associated only with ER-positive disease. Two of the loci lie in regions that contain strong plausible candidate genes: PTHLH (12p11) has a crucial role in mammary gland development and the establishment of bone metastasis in breast cancer, and NRIP1 (21q21) encodes an ER cofactor and has a role in the regulation of breast cancer cell growth.

Mammographic breast density (MD) reflects breast fibroglandular content. Its decline following adjuvant tamoxifen treated, estrogen receptor (ER)-positive breast cancer has been associated with improved outcomes. Breast cancers arise from structures termed lobules, and lower MD is associated with increased age-related lobule involution. We assessed whether pre-treatment involution influenced associations between MD decline and risk of breast cancer-specific death. ER-positive tamoxifen treated patients diagnosed at Kaiser Permanente Northwest (1990-2008) were defined as cases who died of breast cancer (n = 54) and matched controls (remained alive over similar follow-up; n = 180). Lobule involution was assessed by examining terminal duct lobular units (TDLUs) in benign tissues surrounding cancers as TDLU count/mm2, median span and acini count/TDLU. MD (%) was measured in the unaffected breast at baseline (median 6-months before) and follow-up (median 12-months after tamoxifen initiation). TDLU measures and baseline MD were positively associated among controls (p < 0.05). In multivariable regression models, MD decline (≥10%) was associated with reduced risk of breast cancer-specific death before (odds ratio (OR): 0.41, 95% CI: 0.18-0.92) and after (OR: 0.41, 95% CI: 0.18-0.94) adjustment for TDLU count/mm2, TDLU span (OR: 0.34, 95% CI: 0.14-0.84), and acini count/TDLU (OR: 0.33, 95% CI: 0.13-0.81). MD decline following adjuvant tamoxifen is associated with reduced risk of breast cancer-specific death, irrespective of pre-treatment lobule involution.

Publicly available tumor gene expression datasets are widely reanalyzed, but it is unclear how representative they are of clinical populations. Estimations of molecular subtype classification and prognostic gene signatures were calculated for 16,130 patients from 70 breast cancer datasets. Collated patient demographics and clinical characteristics were sparse for many studies. Considerable variations were observed in dataset size, patient/tumor characteristics, and molecular composition. Results were compared with Surveillance, Epidemiology, and End Results Program (SEER) figures. The proportion of basal subtype tumors ranged from 4 to 59%. Date of diagnosis ranged from 1977 to 2013, originating from 20 countries across five continents although European ancestry dominated. Publicly available breast cancer gene expression datasets are a great resource, but caution is required as they tend to be enriched for high grade, ER-negative tumors from European-ancestry patients. These results emphasize the need to derive more representative and annotated molecular datasets from diverse populations.

Evidence from literature, including the BRIDGES study, indicates that germline protein truncating variants (PTVs) in FANCM confer moderately increased risk of ER-negative and triple-negative breast cancer (TNBC), especially for women with a family history of the disease. Association between FANCM missense variants (MVs) and breast cancer risk has been postulated. In this study, we further used the BRIDGES study to test 689 FANCM MVs for association with breast cancer risk, overall and in ER-negative and TNBC subtypes, in 39,885 cases (7566 selected for family history) and 35,271 controls of European ancestry. Sixteen common MVs were tested individually; the remaining rare 673 MVs were tested by burden analyses considering their position and pathogenicity score. We also conducted a meta-analysis of our results and those from published studies. We did not find evidence for association for any of the 16 variants individually tested. The rare MVs were significantly associated with increased risk of ER-negative breast cancer by burden analysis comparing familial cases to controls (OR = 1.48; 95% CI 1.07-2.04; P = 0.017). Higher ORs were found for the subgroup of MVs located in functional domains or predicted to be pathogenic. The meta-analysis indicated that FANCM MVs overall are associated with breast cancer risk (OR = 1.22; 95% CI 1.08-1.38; P = 0.002). Our results support the definition from previous analyses of FANCM as a moderate-risk breast cancer gene and provide evidence that FANCM MVs could be low/moderate risk factors for ER-negative and TNBC subtypes. Further genetic and functional analyses are necessary to clarify better the increased risks due to FANCM MVs.

Women of African descent have the highest breast cancer mortality in the United States and are more likely than women from other population groups to develop an aggressive disease. It remains uncertain to what extent breast cancer in Africa is reminiscent of breast cancer in African American or European American patients. Here, we performed whole-exome sequencing of genomic DNA from 191 breast tumor and non-cancerous adjacent tissue pairs obtained from 97 African American, 69 European American, 2 Asian American, and 23 Kenyan patients. Our analysis of the sequencing data revealed an elevated tumor mutational burden in both Kenyan and African American patients, when compared with European American patients. TP53 mutations were most prevalent, particularly in African American patients, followed by PIK3CA mutations, which showed similar frequencies in European American, African American, and the Kenyan patients. Mutations targeting TBX3 were confined to European Americans and those targeting the FBXW7 tumor suppressor to African American patients whereas mutations in the ARID1A gene that are known to confer resistance to endocrine therapy were distinctively enriched among Kenyan patients. A Kyoto Encyclopedia of Genes and Genomes pathway analysis could link FBXW7 mutations to an increased mitochondrial oxidative phosphorylation capacity in tumors carrying these mutations. Finally, Catalogue of Somatic Mutations in Cancer (COSMIC) mutational signatures in tumors correlated with the occurrence of driver mutations, immune cell profiles, and neighborhood deprivation with associations ranging from being mostly modest to occasionally robust. To conclude, we found mutational profiles that were different between these patient groups. The differences concentrated among genes with low mutation frequencies in breast cancer.

Genome-wide association studies (GWAS) are designed to identify individual regions associated with cancer risk, but only explain a small fraction of the inherited variability. Alternative approach analyzing genetic variants within biological pathways has been proposed to discover networks of susceptibility genes with additional effects. The gene set enrichment analysis (GSEA) may complement and expand traditional GWAS analysis to identify novel genes and pathways associated with bladder cancer risk. We selected three GSEA methods: Gen-Gen, Aligator, and the SNP Ratio Test to evaluate cellular signaling pathways involved in bladder cancer susceptibility in a Texas GWAS population. The candidate genetic polymorphisms from the significant pathway selected by GSEA were validated in an independent NCI GWAS. We identified 18 novel pathways (P < 0.05) significantly associated with bladder cancer risk. Five of the most promising pathways (P ≤ 0.001 in any of the three GSEA methods) among the 18 pathways included two cell cycle pathways and neural cell adhesion molecule (NCAM), platelet-derived growth factor (PDGF), and unfolded protein response pathways. We validated the candidate polymorphisms in the NCI GWAS and found variants of RAPGEF1, SKP1, HERPUD1, CACNB2, CACNA1C, CACNA1S, COL4A2, SRC, and CACNA1C were associated with bladder cancer risk. Two CCNE1 variants, rs8102137 and rs997669, from cell cycle pathways showed the strongest associations; the CCNE1 signal at 19q12 has already been reported in previous GWAS. These findings offer additional etiologic insights highlighting the specific genes and pathways associated with bladder cancer development. GSEA may be a complementary tool to GWAS to identify additional loci of cancer susceptibility.

Postmenopausal obesity is associated with increased circulating levels of androgens and estrogens and elevated breast cancer risk. Crown-like structures (CLS; microscopic foci of dying adipocytes surrounded by macrophages) are proposed to represent sites of increased aromatization of androgens to estrogens. Accordingly, we examined relationships between CLS and sex-steroid hormones in breast adipose tissue and serum from postmenopausal breast cancer patients.

We conducted a multi-stage, genome-wide association study of bladder cancer with a primary scan of 591,637 SNPs in 3,532 affected individuals (cases) and 5,120 controls of European descent from five studies followed by a replication strategy, which included 8,382 cases and 48,275 controls from 16 studies. In a combined analysis, we identified three new regions associated with bladder cancer on chromosomes 22q13.1, 19q12 and 2q37.1: rs1014971, (P = 8 × 10⁻¹²) maps to a non-genic region of chromosome 22q13.1, rs8102137 (P = 2 × 10⁻¹¹) on 19q12 maps to CCNE1 and rs11892031 (P = 1 × 10⁻⁷) maps to the UGT1A cluster on 2q37.1. We confirmed four previously identified genome-wide associations on chromosomes 3q28, 4p16.3, 8q24.21 and 8q24.3, validated previous candidate associations for the GSTM1 deletion (P = 4 × 10⁻¹¹) and a tag SNP for NAT2 acetylation status (P = 4 × 10⁻¹¹), and found interactions with smoking in both regions. Our findings on common variants associated with bladder cancer risk should provide new insights into the mechanisms of carcinogenesis.

Candidate variant association studies have been largely unsuccessful in identifying common breast cancer susceptibility variants, although most studies have been underpowered to detect associations of a realistic magnitude. We assessed 41 common non-synonymous single-nucleotide polymorphisms (nsSNPs) for which evidence of association with breast cancer risk had been previously reported. Case-control data were combined from 38 studies of white European women (46 450 cases and 42 600 controls) and analyzed using unconditional logistic regression. Strong evidence of association was observed for three nsSNPs: ATXN7-K264R at 3p21 [rs1053338, per allele OR = 1.07, 95% confidence interval (CI) = 1.04-1.10, P = 2.9 × 10(-6)], AKAP9-M463I at 7q21 (rs6964587, OR = 1.05, 95% CI = 1.03-1.07, P = 1.7 × 10(-6)) and NEK10-L513S at 3p24 (rs10510592, OR = 1.10, 95% CI = 1.07-1.12, P = 5.1 × 10(-17)). The first two associations reached genome-wide statistical significance in a combined analysis of available data, including independent data from nine genome-wide association studies (GWASs): for ATXN7-K264R, OR = 1.07 (95% CI = 1.05-1.10, P = 1.0 × 10(-8)); for AKAP9-M463I, OR = 1.05 (95% CI = 1.04-1.07, P = 2.0 × 10(-10)). Further analysis of other common variants in these two regions suggested that intronic SNPs nearby are more strongly associated with disease risk. We have thus identified a novel susceptibility locus at 3p21, and confirmed previous suggestive evidence that rs6964587 at 7q21 is associated with risk. The third locus, rs10510592, is located in an established breast cancer susceptibility region; the association was substantially attenuated after adjustment for the known GWAS hit. Thus, each of the associated nsSNPs is likely to be a marker for another, non-coding, variant causally related to breast cancer risk. Further fine-mapping and functional studies are required to identify the underlying risk-modifying variants and the genes through which they act.

We describe temporal trends in breast cancer incidence by molecular subtypes in Scotland because public health prevention programmes, diagnostic and therapeutic services are shaped by differences in tumour biology.

Predict Breast (www.predict.nhs.uk) is an online prognostication and treatment benefit tool for early invasive breast cancer. The aim of this study was to incorporate the prognostic effect of progesterone receptor (PR) status into a new version of PREDICT and to compare its performance to the current version (2.2).

The human fecal and oral microbiome may play a role in the etiology of breast cancer through modulation of endogenous estrogen metabolism. This study aimed to investigate associations of circulating estrogens and estrogen metabolites with the fecal and oral microbiome in postmenopausal African women. A total of 117 women with fecal (N = 110) and oral (N = 114) microbiome data measured by 16S rRNA gene sequencing, and estrogens and estrogen metabolites data measured by liquid chromatography tandem mass spectrometry were included. The outcomes were measures of the microbiome and the independent variables were the estrogens and estrogen metabolites. Estrogens and estrogen metabolites were associated with the fecal microbial Shannon index (global P < 0.01). In particular, higher levels of estrone (β = 0.36, P = 0.03), 2-hydroxyestradiol (β = 0.30, P = 0.02), 4-methoxyestrone (β = 0.51, P = 0.01), and estriol (β = 0.36, P = 0.04) were associated with higher levels of the Shannon index, while 16alpha-hydroxyestrone (β = -0.57, P < 0.01) was inversely associated with the Shannon index as indicated by linear regression. Conjugated 2-methoxyestrone was associated with oral microbial unweighted UniFrac as indicated by MiRKAT (P < 0.01) and PERMANOVA, where conjugated 2-methoxyestrone explained 2.67% of the oral microbial variability, but no other estrogens or estrogen metabolites were associated with any other beta diversity measures. The presence and abundance of multiple fecal and oral genera, such as fecal genera from families Lachnospiraceae and Ruminococcaceae, were associated with several estrogens and estrogen metabolites as indicated by zero-inflated negative binomial regression. Overall, we found several associations of specific estrogens and estrogen metabolites and the fecal and oral microbiome. IMPORTANCE Several epidemiologic studies have found associations of urinary estrogens and estrogen metabolites with the fecal microbiome. However, urinary estrogen concentrations are not strongly correlated with serum estrogens, a known risk factor for breast cancer. To better understand whether the human fecal and oral microbiome were associated with breast cancer risk via the regulation of estrogen metabolism, we conducted this study to investigate the associations of circulating estrogens and estrogen metabolites with the fecal and oral microbiome in postmenopausal African women. We found several associations of parent estrogens and several estrogen metabolites with the microbial communities, and multiple individual associations of estrogens and estrogen metabolites with the presence and abundance of multiple fecal and oral genera, such as fecal genera from families Lachnospiraceae and Ruminococcaceae, which have estrogen metabolizing properties. Future large, longitudinal studies to investigate the dynamic changes of the fecal and oral microbiome and estrogen relationship are needed.