Evaluating approaches for constructing polygenic risk scores for prostate cancer in men of African and European ancestry.

Genome-wide polygenic risk scores (GW-PRSs) have been reported to have better predictive ability than PRSs based on genome-wide significance thresholds across numerous traits. We compared the predictive ability of several GW-PRS approaches to a recently developed PRS of 269 established prostate cancer-risk variants from multi-ancestry GWASs and fine-mapping studies (PRS269). GW-PRS models were trained with a large and diverse prostate cancer GWAS of 107,247 cases and 127,006 controls that we previously used to develop the multi-ancestry PRS269. Resulting models were independently tested in 1,586 cases and 1,047 controls of African ancestry from the California Uganda Study and 8,046 cases and 191,825 controls of European ancestry from the UK Biobank and further validated in 13,643 cases and 210,214 controls of European ancestry and 6,353 cases and 53,362 controls of African ancestry from the Million Veteran Program. In the testing data, the best performing GW-PRS approach had AUCs of 0.656 (95% CI = 0.635-0.677) in African and 0.844 (95% CI = 0.840-0.848) in European ancestry men and corresponding prostate cancer ORs of 1.83 (95% CI = 1.67-2.00) and 2.19 (95% CI = 2.14-2.25), respectively, for each SD unit increase in the GW-PRS. Compared to the GW-PRS, in African and European ancestry men, the PRS269 had larger or similar AUCs (AUC = 0.679, 95% CI = 0.659-0.700 and AUC = 0.845, 95% CI = 0.841-0.849, respectively) and comparable prostate cancer ORs (OR = 2.05, 95% CI = 1.87-2.26 and OR = 2.21, 95% CI = 2.16-2.26, respectively). Findings were similar in the validation studies. This investigation suggests that current GW-PRS approaches may not improve the ability to predict prostate cancer risk compared to the PRS269 developed from multi-ancestry GWASs and fine-mapping.

Genome- and transcriptome-wide association studies of 386,000 Asian and European-ancestry women provide new insights into breast cancer genetics.

By combining data from 160,500 individuals with breast cancer and 226,196 controls of Asian and European ancestry, we conducted genome- and transcriptome-wide association studies of breast cancer. We identified 222 genetic risk loci and 137 genes that were associated with breast cancer risk at a p < 5.0 × 10-8 and a Bonferroni-corrected p < 4.6 × 10-6, respectively. Of them, 32 loci and 15 genes showed a significantly different association between ER-positive and ER-negative breast cancer after Bonferroni correction. Significant ancestral differences in risk variant allele frequencies and their association strengths with breast cancer risk were identified. Of the significant associations identified in this study, 17 loci and 14 genes are located 1Mb away from any of the previously reported breast cancer risk variants. Pathways analyses including 221 putative risk genes identified multiple signaling pathways that may play a significant role in the development of breast cancer. Our study provides a comprehensive understanding of and new biological insights into the genetics of this common malignancy.

Strengthening the Evidence for a Causal Link between Type 2 Diabetes Mellitus and Pancreatic Cancer: Insights from Two-Sample and Multivariable Mendelian Randomization.

This two-sample Mendelian randomization (MR) study was conducted to investigate the causal associations between type 2 diabetes mellitus (T2DM) and the risk of pancreatic cancer (PaCa), as this causal relationship remains inconclusive in existing MR studies. The selection of instrumental variables for T2DM was based on two genome-wide association study (GWAS) meta-analyses from European cohorts. Summary-level data for PaCa were extracted from the FinnGen and UK Biobank databases. Inverse variance weighted (IVW) and four other robust methods were employed in our MR analysis. Various sensitivity analyses and multivariable MR approaches were also performed to enhance the robustness of our findings. In the IVW and Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO) analyses, the odds ratios (ORs) for each 1-unit increase in genetically predicted log odds of T2DM were approximately 1.13 for PaCa. The sensitivity tests and multivariable MR supported the causal link between T2DM and PaCa without pleiotropic effects. Therefore, our analyses suggest a causal relationship between T2DM and PaCa, shedding light on the potential pathophysiological mechanisms of T2DM's impact on PaCa. This finding underscores the importance of T2DM prevention as a strategy to reduce the risk of PaCa.

Exploring the causal role of the immune response to varicella-zoster virus on multiple traits: a phenome-wide Mendelian randomization study.

BACKGROUND: The immune response to infections could be largely driven by the individual's genes, especially in the major histocompatibility complex (MHC) region. Varicella-zoster virus (VZV) is a highly communicable pathogen. In addition to infection, the reactivations of VZV can be a potential causal factor for multiple traits. Identification of VZV immune response-related health conditions can therefore help elucidate the aetiology of certain diseases. METHODS: A phenome-wide Mendelian randomization (MR) study of anti-VZV immunoglobulin G (IgG) levels with 1370 traits was conducted to explore the potential causal role of VZV-specific immune response on multiple traits using the UK Biobank cohort. For the robustness of the results, we performed MR analyses using five different methods. To investigate the impact of the MHC region on MR results, the analyses were conducted using instrumental variables (IVs) inside (IVmhc) and outside (IVno.mhc) the MHC region or all together (IVfull). RESULTS: Forty-nine single nucleotide polymorphisms (IVfull) were associated with anti-VZV IgG levels, of which five (IVmhc) were located in the MHC region and 44 (IVno.mhc) were not. Statistical evidence (false discovery rate < 0.05 in at least three of the five MR methods) for a causal effect of anti-VZV IgG levels was found on 22 traits using IVmhc, while no evidence was found when using IVno.mhc or IVfull. The reactivations of VZV increased the risk of Dupuytren disease, mononeuropathies of the upper limb, sarcoidosis, coeliac disease, teeth problems and earlier onset of allergic rhinitis, which evidence was concordant with the literature. Suggestive causal evidence (P < 0.05 in at least three of five MR methods) using IVfull, IVmhc and IVno.mhc was detected in 92, 194 and 56 traits, respectively. MR results from IVfull correlated with those from IVmhc or IVno.mhc. However, the results between IVmhc and IVno.mhc were noticeably different, as evidenced by causal associations in opposite directions between anti-VZV IgG and ten traits. CONCLUSIONS: In this exploratory study, anti-VZV IgG was causally associated with multiple traits. IVs in the MHC region might have a substantial impact on MR, and therefore, could be potentially considered in future MR studies.

Predicting risk of endometrial cancer in asymptomatic women (PRECISION): Model development and external validation.

OBJECTIVES: Develop an endometrial cancer risk prediction model and externally validate it for UK primary care use. DESIGN: Cohort study. SETTING: The UK Biobank was used for model development and a linked primary (Clinical Practice Research Datalink, CPRD) and secondary care (HES), mortality (ONS) and cancer register (NRCAS) dataset was used for external validation. POPULATION: Women aged 45-60 years with no history of endometrial cancer or hysterectomy. METHODS: Model development was performed using a flexible parametric survival model and stepwise backward selection aiming to minimise the Akaike information criterion. Model performance on external validation was assessed through flexible calibration plots, calculation of the expected to observed ratio and C-statistic and decision curve analysis. MAIN OUTCOME MEASURES: Endometrial cancer diagnosis within 1-10 years of the index date. RESULTS: Model development included 222 031 women (902 incident endometrial cancer cases) and external validation 3 094 371 women (8585 endometrial cancer cases). The final model (with equation provided) incorporated age, body mass index, waist circumference, age at menarche, menopause and last birth, hormone replacement, tamoxifen and oral contraceptive pill use, type 2 diabetes, smoking and family history of bowel cancer. It was well calibrated on external validation (calibration slope 1.14, 95% confidence interval [CI] 1.11-1.17, E/O 1.03, 95% CI 1.01-1.05), with moderate/good discrimination (C-statistic 0.70, 95% CI 0.69-0.70) and had improved net benefit compared with previously developed models. CONCLUSIONS: The Predicting risk of endometrial cancer in asymptomatic women model (PRECISION), using easily measurable anthropometric, reproductive, personal and family history, accurately quantifies a woman's 10-year risk of endometrial cancer. Its use could determine eligibility for primary endometrial cancer prevention trials and for targeted resource allocation in UK general practices.

The association of herpes zoster and influenza vaccinations with the risk of developing dementia: a population-based cohort study within the UK Clinical Practice Research Datalink.

BACKGROUND: Dementia affects ability to remember, think, or make decisions that interfere with doing everyday activities. There is no cure, therefore any prevention or delay of the onset is of importance. This study aims to investigate the association between zoster and influenza vaccinations and the risk of developing dementia. METHODS: We conducted a retrospective population-based cohort study using electronic health records from 1469 general practices contributing to the Clinical Practice Research Datalink (CPRD) Aurum database with linked hospital episode statistics (HES) and Office for National Statistics (ONS) mortality records. We built two 'matched cohorts': zoster vaccine (854,745 exposed individuals) matched with 8.8 million comparators without a history of zoster vaccination, and influenza vaccine (742,487 exposed individuals) matched with 7.12 million comparators without a history of vaccination as another comparator group. The cohorts were then followed to assess the association of exposure (vaccine) with outcome (dementia diagnosis). RESULTS: Zoster vaccination was associated with a lower risk of dementia diagnosis (adjusted hazard ratio (HR) 0.78 with 95% CI: 0.77-0.79), Alzheimer's diagnosis (adjusted HR 0.91 with 95% CI: 0.89-0.92 and other types of dementia (adjusted HR 0.71 with 95% CI: 0.69-0.72). Influenza vaccination also was associated with a slightly reduced hazard of dementia risk (adjusted HR 0.96 with 95% CI: 0.94-0.97). CONCLUSION: Both zoster vaccine for prevention of shingles / herpes zoster and influenza vaccine to prevent influenza were associated with diminished risk of dementia, with the zoster association appearing more pronounced.

Polygenic risk scores for prediction of breast cancer risk in Asian populations.

PURPOSE: Non-European populations are under-represented in genetics studies, hindering clinical implementation of breast cancer polygenic risk scores (PRSs). We aimed to develop PRSs using the largest available studies of Asian ancestry and to assess the transferability of PRS across ethnic subgroups. METHODS: The development data set comprised 138,309 women from 17 case-control studies. PRSs were generated using a clumping and thresholding method, lasso penalized regression, an Empirical Bayes approach, a Bayesian polygenic prediction approach, or linear combinations of multiple PRSs. These PRSs were evaluated in 89,898 women from 3 prospective studies (1592 incident cases). RESULTS: The best performing PRS (genome-wide set of single-nucleotide variations [formerly single-nucleotide polymorphism]) had a hazard ratio per unit SD of 1.62 (95% CI = 1.46-1.80) and an area under the receiver operating curve of 0.635 (95% CI = 0.622-0.649). Combined Asian and European PRSs (333 single-nucleotide variations) had a hazard ratio per SD of 1.53 (95% CI = 1.37-1.71) and an area under the receiver operating curve of 0.621 (95% CI = 0.608-0.635). The distribution of the latter PRS was different across ethnic subgroups, confirming the importance of population-specific calibration for valid estimation of breast cancer risk. CONCLUSION: PRSs developed in this study, from association data from multiple ancestries, can enhance risk stratification for women of Asian ancestry.

Assessing the impact of MRI based diagnostics on pre-treatment disease classification and prognostic model performance in men diagnosed with new prostate cancer from an unscreened population.

INTRODUCTION: Pre-treatment risk and prognostic groups are the cornerstone for deciding management in non-metastatic prostate cancer. All however, were developed in the pre-MRI era. Here we compared categorisation of cancers using either only clinical parameters or with MRI enhanced information in men referred for suspected prostate cancer from an unscreened population. PATIENT AND METHODS: Data from men referred from primary care to our diagnostic service and with both clinical (digital rectal examination [DRE] and systematic biopsies) and MRI enhanced attributes (MRI stage and combined systematic/targeted biopsies) were used for this study. Clinical vs MRI data were contrasted for clinico-pathological and risk group re-distribution using the European Association of Urology (EAU), American Urological Association (AUA) and UK National Institute for Health Care Excellence (NICE) Cambridge Prognostic Group (CPG) models. Differences were retrofitted to a population cohort with long-term prostate cancer mortality (PCM) outcomes to simulate impact on model performance. We further contrasted individualised overall survival (OS) predictions using the Predict Prostate algorithm. RESULTS: Data from 370 men were included (median age 66y). Pre-biopsy MRI stage reassignments occurred in 7.8% (versus DRE). Image-guided biopsies increased Grade Group 2 and ≥ Grade Group 3 assignments in 2.7% and 2.9% respectively. The main change in risk groups was more high-risk cancers (6.2% increase in the EAU and AUA system, 4.3% increase in CPG4 and 1.9% CPG5). When extrapolated to a historical population-based cohort (n = 10,139) the redistribution resulted in generally lower concordance indices for PCM. The 5-tier NICE-CPG system outperformed the 4-tier AUA and 3-tier EAU models (C Index 0.70 versus 0.65 and 0.64). Using an individualised prognostic model, changes in predicted OS were small (median difference 1% and 2% at 10- and 15-years' respectively). Similarly, estimated treatment survival benefit changes were minimal (1% at both 10- and 15-years' time frame). CONCLUSION: MRI guided diagnostics does change pre-treatment risk groups assignments but the overall prognostic impact appears modest in men referred from unscreened populations. Particularly, when using more granular tiers or individualised prognostic models. Existing risk and prognostic models can continue to be used to counsel men about treatment option until long term survival outcomes are available.

African-specific improvement of a polygenic hazard score for age at diagnosis of prostate cancer.

Polygenic hazard score (PHS) models are associated with age at diagnosis of prostate cancer. Our model developed in Europeans (PHS46) showed reduced performance in men with African genetic ancestry. We used a cross-validated search to identify single nucleotide polymorphisms (SNPs) that might improve performance in this population. Anonymized genotypic data were obtained from the PRACTICAL consortium for 6253 men with African genetic ancestry. Ten iterations of a 10-fold cross-validation search were conducted to select SNPs that would be included in the final PHS46+African model. The coefficients of PHS46+African were estimated in a Cox proportional hazards framework using age at diagnosis as the dependent variable and PHS46, and selected SNPs as predictors. The performance of PHS46 and PHS46+African was compared using the same cross-validated approach. Three SNPs (rs76229939, rs74421890 and rs5013678) were selected for inclusion in PHS46+African. All three SNPs are located on chromosome 8q24. PHS46+African showed substantial improvements in all performance metrics measured, including a 75% increase in the relative hazard of those in the upper 20% compared to the bottom 20% (2.47-4.34) and a 20% reduction in the relative hazard of those in the bottom 20% compared to the middle 40% (0.65-0.53). In conclusion, we identified three SNPs that substantially improved the association of PHS46 with age at diagnosis of prostate cancer in men with African genetic ancestry to levels comparable to Europeans.

Constitutional morphological features and risk of hip osteoarthritis: a case-control study using standard radiographs.

OBJECTIVES: To evaluate the risk of association with hip osteoarthritis (OA) of 14 morphological features measured on standard antero-posterior pelvis radiographs. METHODS: A case-control study of 566 symptomatic unilateral hip OA cases and 1108 controls without hip OA, using the Genetics of OA and Lifestyle database. Unaffected hips of cases were assumed to reflect pre-OA morphology of the contralateral affected hip. ORs with 95% CI adjusted for confounding factors were calculated using logistic regression. Hierarchical clustering on principal component method was used to identify clusters of morphological features. Proportional risk contribution (PRC) of these morphological features in the context of other risk factors of hip OA was estimated using receiver operating characteristic analysis. RESULTS: All morphological features showed right-left symmetry in controls. Each feature was associated with hip OA after adjusting for age, gender and body mass index. Increased sourcil angle had the strongest association (OR: 6.93, 95% CI 5.16 to 9.32). Three clusters were identified. The PRC varied between individual features, as well as between clusters. It was 35% (95% CI 31% to 40%) for all 14 morphological features, compared to 21% (95% CI 19% to 24%) for all other well-established risk factors. CONCLUSIONS: Constitutional morphological variation strongly associates with hip OA development and may explain much of its heritability. Relevant morphological measures can be assessed readily on standard radiographs to help predict risk of hip OA. Prospective studies are required to provide further support for causality.

Marital status and prostate cancer incidence: a pooled analysis of 12 case-control studies from the PRACTICAL consortium.

While being in a committed relationship is associated with a better prostate cancer prognosis, little is known about how marital status relates to its incidence. Social support provided by marriage/relationship could promote a healthy lifestyle and an increased healthcare seeking behavior. We investigated the association between marital status and prostate cancer risk using data from the PRACTICAL Consortium. Pooled analyses were conducted combining 12 case-control studies based on histologically-confirmed incident prostate cancers and controls with information on marital status prior to diagnosis/interview. Marital status was categorized as married/partner, separated/divorced, single, or widowed. Tumours with Gleason scores ≥ 8 defined high-grade cancers, and low-grade otherwise. NCI-SEER's summary stages (local, regional, distant) indicated the extent of the cancer. Logistic regression was used to derive odds ratios (ORs) and 95% confidence intervals (CI) for the association between marital status and prostate cancer risk, adjusting for potential confounders. Overall, 14,760 cases and 12,019 controls contributed to analyses. Compared to men who were married/with a partner, widowed men had an OR of 1.19 (95% CI 1.03-1.35) of prostate cancer, with little difference between low- and high-grade tumours. Risk estimates among widowers were 1.14 (95% CI 0.97-1.34) for local, 1.53 (95% CI 1.22-1.92) for regional, and 1.56 (95% CI 1.05-2.32) for distant stage tumours. Single men had elevated risks of high-grade cancers. Our findings highlight elevated risks of incident prostate cancer among widowers, more often characterized by tumours that had spread beyond the prostate at the time of diagnosis. Social support interventions and closer medical follow-up in this sub-population are warranted.

Evaluation of associations between genetically predicted circulating protein biomarkers and breast cancer risk.

A small number of circulating proteins have been reported to be associated with breast cancer risk, with inconsistent results. Herein, we attempted to identify novel protein biomarkers for breast cancer via the integration of genomics and proteomics data. In the Breast Cancer Association Consortium (BCAC), with 122,977 cases and 105,974 controls of European descendants, we evaluated the associations of the genetically predicted concentrations of >1,400 circulating proteins with breast cancer risk. We used data from a large-scale protein quantitative trait loci (pQTL) analysis as our study instrument. Summary statistics for these pQTL variants related to breast cancer risk were obtained from the BCAC and used to estimate odds ratios (OR) for each protein using the inverse-variance weighted method. We identified 56 proteins significantly associated with breast cancer risk by instrumental analysis (false discovery rate <0.05). Of these, the concentrations of 32 were influenced by variants close to a breast cancer susceptibility locus (ABO, 9q34.2). Many of these proteins, such as insulin receptor, insulin-like growth factor receptor 1 and other membrane receptors (OR: 0.82-1.18, p values: 6.96 × 10-4 -3.28 × 10-8 ), are linked to insulin resistance and estrogen receptor signaling pathways. Proteins identified at other loci include those involved in biological processes such as alcohol and lipid metabolism, proteolysis, apoptosis, immune regulation and cell motility and proliferation. Consistent associations were observed for 22 proteins in the UK Biobank data (p < 0.05). The study identifies potential novel biomarkers for breast cancer, but further investigation is needed to replicate our findings.

Genome-wide association study implicates immune dysfunction in the development of Hodgkin lymphoma.

To further our understanding of inherited susceptibility to Hodgkin lymphoma (HL), we performed a meta-analysis of 7 genome-wide association studies totaling 5325 HL cases and 22 423 control patients. We identify 5 new HL risk loci at 6p21.31 (rs649775; P = 2.11 × 10-10), 6q23.3 (rs1002658; P = 2.97 × 10-8), 11q23.1 (rs7111520; P = 1.44 × 10-11), 16p11.2 (rs6565176; P = 4.00 × 10-8), and 20q13.12 (rs2425752; P = 2.01 × 10-8). Integration of gene expression, histone modification, and in situ promoter capture Hi-C data at the 5 new and 13 known risk loci implicates dysfunction of the germinal center reaction, disrupted T-cell differentiation and function, and constitutive NF-κB activation as mechanisms of predisposition. These data provide further insights into the genetic susceptibility and biology of HL.

Appraising the role of previously reported risk factors in epithelial ovarian cancer risk: A Mendelian randomization analysis.

BACKGROUND: Various risk factors have been associated with epithelial ovarian cancer risk in observational epidemiological studies. However, the causal nature of the risk factors reported, and thus their suitability as effective intervention targets, is unclear given the susceptibility of conventional observational designs to residual confounding and reverse causation. Mendelian randomization (MR) uses genetic variants as proxies for risk factors to strengthen causal inference in observational studies. We used MR to evaluate the association of 12 previously reported risk factors (reproductive, anthropometric, clinical, lifestyle, and molecular factors) with risk of invasive epithelial ovarian cancer, invasive epithelial ovarian cancer histotypes, and low malignant potential tumours. METHODS AND FINDINGS: Genetic instruments to proxy 12 risk factors were constructed by identifying single nucleotide polymorphisms (SNPs) that were robustly (P < 5 × 10-8) and independently associated with each respective risk factor in previously reported genome-wide association studies. These risk factors included genetic liability to 3 factors (endometriosis, polycystic ovary syndrome, type 2 diabetes) scaled to reflect a 50% higher odds liability to disease. We obtained summary statistics for the association of these SNPs with risk of overall and histotype-specific invasive epithelial ovarian cancer (22,406 cases; 40,941 controls) and low malignant potential tumours (3,103 cases; 40,941 controls) from the Ovarian Cancer Association Consortium (OCAC). The OCAC dataset comprises 63 genotyping project/case-control sets with participants of European ancestry recruited from 14 countries (US, Australia, Belarus, Germany, Belgium, Denmark, Finland, Norway, Canada, Poland, UK, Spain, Netherlands, and Sweden). SNPs were combined into multi-allelic inverse-variance-weighted fixed or random effects models to generate effect estimates and 95% confidence intervals (CIs). Three complementary sensitivity analyses were performed to examine violations of MR assumptions: MR-Egger regression and weighted median and mode estimators. A Bonferroni-corrected P value threshold was used to establish strong evidence (P < 0.0042) and suggestive evidence (0.0042 < P < 0.05) for associations. In MR analyses, there was strong or suggestive evidence that 2 of the 12 risk factors were associated with invasive epithelial ovarian cancer and 8 of the 12 were associated with 1 or more invasive epithelial ovarian cancer histotypes. There was strong evidence that genetic liability to endometriosis was associated with an increased risk of invasive epithelial ovarian cancer (odds ratio [OR] per 50% higher odds liability: 1.10, 95% CI 1.06-1.15; P = 6.94 × 10-7) and suggestive evidence that lifetime smoking exposure was associated with an increased risk of invasive epithelial ovarian cancer (OR per unit increase in smoking score: 1.36, 95% CI 1.04-1.78; P = 0.02). In analyses examining histotypes and low malignant potential tumours, the strongest associations found were between height and clear cell carcinoma (OR per SD increase: 1.36, 95% CI 1.15-1.61; P = 0.0003); age at natural menopause and endometrioid carcinoma (OR per year later onset: 1.09, 95% CI 1.02-1.16; P = 0.007); and genetic liability to polycystic ovary syndrome and endometrioid carcinoma (OR per 50% higher odds liability: 0.89, 95% CI 0.82-0.96; P = 0.002). There was little evidence for an association of genetic liability to type 2 diabetes, parity, or circulating levels of 25-hydroxyvitamin D and sex hormone binding globulin with ovarian cancer or its subtypes. The primary limitations of this analysis include the modest statistical power for analyses of risk factors in relation to some less common ovarian cancer histotypes (low grade serous, mucinous, and clear cell carcinomas), the inability to directly examine the association of some ovarian cancer risk factors that did not have robust genetic variants available to serve as proxies (e.g., oral contraceptive use, hormone replacement therapy), and the assumption of linear relationships between risk factors and ovarian cancer risk. CONCLUSIONS: Our comprehensive examination of possible aetiological drivers of ovarian carcinogenesis using germline genetic variants to proxy risk factors supports a role for few of these factors in invasive epithelial ovarian cancer overall and suggests distinct aetiologies across histotypes. The identification of novel risk factors remains an important priority for the prevention of epithelial ovarian cancer.

Evidence that the 5p12 Variant rs10941679 Confers Susceptibility to Estrogen-Receptor-Positive Breast Cancer through FGF10 and MRPS30 Regulation.

Genome-wide association studies (GWASs) have revealed increased breast cancer risk associated with multiple genetic variants at 5p12. Here, we report the fine mapping of this locus using data from 104,660 subjects from 50 case-control studies in the Breast Cancer Association Consortium (BCAC). With data for 3,365 genotyped and imputed SNPs across a 1 Mb region (positions 44,394,495-45,364,167; NCBI build 37), we found evidence for at least three independent signals: the strongest signal, consisting of a single SNP rs10941679, was associated with risk of estrogen-receptor-positive (ER+) breast cancer (per-g allele OR ER+ = 1.15; 95% CI 1.13-1.18; p = 8.35 × 10-30). After adjustment for rs10941679, we detected signal 2, consisting of 38 SNPs more strongly associated with ER-negative (ER-) breast cancer (lead SNP rs6864776: per-a allele OR ER- = 1.10; 95% CI 1.05-1.14; p conditional = 1.44 × 10-12), and a single signal 3 SNP (rs200229088: per-t allele OR ER+ = 1.12; 95% CI 1.09-1.15; p conditional = 1.12 × 10-05). Expression quantitative trait locus analysis in normal breast tissues and breast tumors showed that the g (risk) allele of rs10941679 was associated with increased expression of FGF10 and MRPS30. Functional assays demonstrated that SNP rs10941679 maps to an enhancer element that physically interacts with the FGF10 and MRPS30 promoter regions in breast cancer cell lines. FGF10 is an oncogene that binds to FGFR2 and is overexpressed in ∼10% of human breast cancers, whereas MRPS30 plays a key role in apoptosis. These data suggest that the strongest signal of association at 5p12 is mediated through coordinated activation of FGF10 and MRPS30, two candidate genes for breast cancer pathogenesis.

AA9int: SNP interaction pattern search using non-hierarchical additive model set.

Motivation: The use of single nucleotide polymorphism (SNP) interactions to predict complex diseases is getting more attention during the past decade, but related statistical methods are still immature. We previously proposed the SNP Interaction Pattern Identifier (SIPI) approach to evaluate 45 SNP interaction patterns/patterns. SIPI is statistically powerful but suffers from a large computation burden. For large-scale studies, it is necessary to use a powerful and computation-efficient method. The objective of this study is to develop an evidence-based mini-version of SIPI as the screening tool or solitary use and to evaluate the impact of inheritance mode and model structure on detecting SNP-SNP interactions. Results: We tested two candidate approaches: the 'Five-Full' and 'AA9int' method. The Five-Full approach is composed of the five full interaction models considering three inheritance modes (additive, dominant and recessive). The AA9int approach is composed of nine interaction models by considering non-hierarchical model structure and the additive mode. Our simulation results show that AA9int has similar statistical power compared to SIPI and is superior to the Five-Full approach, and the impact of the non-hierarchical model structure is greater than that of the inheritance mode in detecting SNP-SNP interactions. In summary, it is recommended that AA9int is a powerful tool to be used either alone or as the screening stage of a two-stage approach (AA9int+SIPI) for detecting SNP-SNP interactions in large-scale studies. Availability and implementation: The 'AA9int' and 'parAA9int' functions (standard and parallel computing version) are added in the SIPI R package, which is freely available at https://linhuiyi.github.io/LinHY_Software/. Supplementary information: Supplementary data are available at Bioinformatics online.

Using prognosis to guide inclusion criteria, define standardised endpoints and stratify follow-up in active surveillance for prostate cancer.

OBJECTIVES: To test whether using disease prognosis can inform a rational approach to active surveillance (AS) for early prostate cancer. PATIENTS AND METHODS: We previously developed the Cambridge Prognostics Groups (CPG) classification, a five-tiered model that uses prostate-specific antigen (PSA), Grade Group and Stage to predict cancer survival outcomes. We applied the CPG model to a UK and a Swedish prostate cancer cohort to test differences in prostate cancer mortality (PCM) in men managed conservatively or by upfront treatment in CPG2 and 3 (which subdivides the intermediate-risk classification) vs CPG1 (low-risk). We then applied the CPG model to a contemporary UK AS cohort, which was optimally characterised at baseline for disease burden, to identify predictors of true prognostic progression. Results were re-tested in an external AS cohort from Spain. RESULTS: In a UK cohort (n = 3659) the 10-year PCM was 2.3% in CPG1, 1.5%/3.5% in treated/untreated CPG2, and 1.9%/8.6% in treated/untreated CPG3. In the Swedish cohort (n = 27 942) the10-year PCM was 1.0% in CPG1, 2.2%/2.7% in treated/untreated CPG2, and 6.1%/12.5% in treated/untreated CPG3. We then tested using progression to CPG3 as a hard endpoint in a modern AS cohort (n = 133). During follow-up (median 3.5 years) only 6% (eight of 133) progressed to CPG3. Predictors of progression were a PSA density ≥0.15 ng/mL/mL and CPG2 at diagnosis. Progression occurred in 1%, 8% and 21% of men with neither factor, only one, or both, respectively. In an independent Spanish AS cohort (n = 143) the corresponding rates were 3%, 10% and 14%, respectively. CONCLUSION: Using disease prognosis allows a rational approach to inclusion criteria, discontinuation triggers and risk-stratified management in AS.

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

Observational studies suggest that higher birth weight (BW) is associated with increased risk of breast cancer in adult life. We conducted a two-sample Mendelian randomisation (MR) study to assess whether this association is causal. Sixty independent single nucleotide polymorphisms (SNPs) known to be associated at P < 5 × 10-8 with BW were used to construct (1) a 41-SNP instrumental variable (IV) for univariable MR after removing SNPs with pleiotropic associations with other breast cancer risk factors and (2) a 49-SNP IV for multivariable MR after filtering SNPs for data availability. BW predicted by the 41-SNP IV was not associated with overall breast cancer risk in inverse-variance weighted (IVW) univariable MR analysis of genetic association data from 122,977 breast cancer cases and 105,974 controls (odds ratio = 0.86 per 500 g higher BW; 95% confidence interval 0.73-1.01). Sensitivity analyses using four alternative methods and three alternative IVs, including an IV with 59 of the 60 BW-associated SNPs, yielded similar results. Multivariable MR adjusting for the effects of the 49-SNP IV on birth length, adult height, adult body mass index, age at menarche, and age at menopause using IVW and MR-Egger methods provided estimates consistent with univariable analyses. Results were also similar when all analyses were repeated after restricting to estrogen receptor-positive or -negative breast cancer cases. Point estimates of the odds ratios from most analyses performed indicated an inverse relationship between genetically-predicted BW and breast cancer, but we are unable to rule out an association between the non-genetically-determined component of BW and breast cancer. Thus, genetically-predicted higher BW was not associated with an increased risk of breast cancer in adult life in our MR study.

Novel Genetic Variants for Cartilage Thickness and Hip Osteoarthritis.

Osteoarthritis is one of the most frequent and disabling diseases of the elderly. Only few genetic variants have been identified for osteoarthritis, which is partly due to large phenotype heterogeneity. To reduce heterogeneity, we here examined cartilage thickness, one of the structural components of joint health. We conducted a genome-wide association study of minimal joint space width (mJSW), a proxy for cartilage thickness, in a discovery set of 13,013 participants from five different cohorts and replication in 8,227 individuals from seven independent cohorts. We identified five genome-wide significant (GWS, P≤5·0×10-8) SNPs annotated to four distinct loci. In addition, we found two additional loci that were significantly replicated, but results of combined meta-analysis fell just below the genome wide significance threshold. The four novel associated genetic loci were located in/near TGFA (rs2862851), PIK3R1 (rs10471753), SLBP/FGFR3 (rs2236995), and TREH/DDX6 (rs496547), while the other two (DOT1L and SUPT3H/RUNX2) were previously identified. A systematic prioritization for underlying causal genes was performed using diverse lines of evidence. Exome sequencing data (n = 2,050 individuals) indicated that there were no rare exonic variants that could explain the identified associations. In addition, TGFA, FGFR3 and PIK3R1 were differentially expressed in OA cartilage lesions versus non-lesioned cartilage in the same individuals. In conclusion, we identified four novel loci (TGFA, PIK3R1, FGFR3 and TREH) and confirmed two loci known to be associated with cartilage thickness.The identified associations were not caused by rare exonic variants. This is the first report linking TGFA to human OA, which may serve as a new target for future therapies.

An intergenic risk locus containing an enhancer deletion in 2q35 modulates breast cancer risk by deregulating IGFBP5 expression.

Breast cancer is the most diagnosed malignancy and the second leading cause of cancer mortality in females. Previous association studies have identified variants on 2q35 associated with the risk of breast cancer. To identify functional susceptibility loci for breast cancer, we interrogated the 2q35 gene desert for chromatin architecture and functional variation correlated with gene expression. We report a novel intergenic breast cancer risk locus containing an enhancer copy number variation (enCNV; deletion) located approximately 400Kb upstream to IGFBP5, which overlaps an intergenic ERα-bound enhancer that loops to the IGFBP5 promoter. The enCNV is correlated with modified ERα binding and monoallelic-repression of IGFBP5 following oestrogen treatment. We investigated the association of enCNV genotype with breast cancer in 1,182 cases and 1,362 controls, and replicate our findings in an independent set of 62,533 cases and 60,966 controls from 41 case control studies and 11 GWAS. We report a dose-dependent inverse association of 2q35 enCNV genotype (percopy OR = 0.68 95%CI 0.55-0.83, P = 0.0002; replication OR = 0.77 95% CI 0.73-0.82, P = 2.1 × 10-19) and identify 13 additional linked variants (r2 > 0.8) in the 20Kb linkage block containing the enCNV (P = 3.2 × 10-15 - 5.6 × 10-17). These associations were independent of previously reported 2q35 variants, rs13387042/rs4442975 and rs16857609, and were stronger for ER-positive than ER-negative disease. Together, these results suggest that 2q35 breast cancer risk loci may be mediating their effect through IGFBP5.