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.

Identification of Genes with Rare Loss of Function Variants Associated with Aggressive Prostate Cancer and Survival.

BACKGROUND: Prostate cancer (PrCa) is a substantial cause of mortality among men globally. Rare germline mutations in BRCA2 have been validated robustly as increasing risk of aggressive forms with a poorer prognosis; however, evidence remains less definitive for other genes. OBJECTIVE: To detect genes associated with PrCa aggressiveness, through a pooled analysis of rare variant sequencing data from six previously reported studies in the UK Genetic Prostate Cancer Study (UKGPCS). DESIGN, SETTING, AND PARTICIPANTS: We accumulated a cohort of 6805 PrCa cases, in which a set of ten candidate genes had been sequenced in all samples. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: We examined the association between rare putative loss of function (pLOF) variants in each gene and aggressive classification (defined as any of death from PrCa, metastatic disease, stage T4, or both stage T3 and Gleason score ≥8). Secondary analyses examined staging phenotypes individually. Cox proportional hazards modelling and Kaplan-Meier survival analyses were used to further examine the relationship between mutation status and survival. RESULTS AND LIMITATIONS: We observed associations between PrCa aggressiveness and pLOF mutations in ATM, BRCA2, MSH2, and NBN (odds ratio = 2.67-18.9). These four genes and MLH1 were additionally associated with one or more secondary analysis phenotype. Carriers of germline mutations in these genes experienced shorter PrCa-specific survival (hazard ratio = 2.15, 95% confidence interval 1.79-2.59, p = 4 × 10-16) than noncarriers. CONCLUSIONS: This study provides further support that rare pLOF variants in specific genes are likely to increase aggressive PrCa risk and may help define the panel of informative genes for screening and treatment considerations. PATIENT SUMMARY: By combining data from several previous studies, we have been able to enhance knowledge regarding genes in which inherited mutations would be expected to increase the risk of more aggressive PrCa. This may, in the future, aid in the identification of men at an elevated risk of dying from PrCa.

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.

An Integrative Pancreatic Cancer Risk Prediction Model in the UK Biobank.

Pancreatic cancer (PaCa) is a lethal cancer with an increasing incidence, highlighting the need for early prevention strategies. There is a lack of a comprehensive PaCa predictive model derived from large prospective cohorts. Therefore, we have developed an integrated PaCa risk prediction model for PaCa using data from the UK Biobank, incorporating lifestyle-related, genetic-related, and medical history-related variables for application in healthcare settings. We used a machine learning-based random forest approach and a traditional multivariable logistic regression method to develop a PaCa predictive model for different purposes. Additionally, we employed dynamic nomograms to visualize the probability of PaCa risk in the prediction model. The top five influential features in the random forest model were age, PRS, pancreatitis, DM, and smoking. The significant risk variables in the logistic regression model included male gender (OR = 1.17), age (OR = 1.10), non-O blood type (OR = 1.29), higher polygenic score (PRS) (Q5 vs. Q1, OR = 2.03), smoking (OR = 1.82), alcohol consumption (OR = 1.27), pancreatitis (OR = 3.99), diabetes (DM) (OR = 2.57), and gallbladder-related disease (OR = 2.07). The area under the receiver operating curve (AUC) of the logistic regression model is 0.78. Internal validation and calibration performed well in both models. Our integrative PaCa risk prediction model with the PRS effectively stratifies individuals at future risk of PaCa, aiding targeted prevention efforts and supporting community-based cancer prevention initiatives.

Characterizing prostate cancer risk through multi-ancestry genome-wide discovery of 187 novel risk variants.

The transferability and clinical value of genetic risk scores (GRSs) across populations remain limited due to an imbalance in genetic studies across ancestrally diverse populations. Here we conducted a multi-ancestry genome-wide association study of 156,319 prostate cancer cases and 788,443 controls of European, African, Asian and Hispanic men, reflecting a 57% increase in the number of non-European cases over previous prostate cancer genome-wide association studies. We identified 187 novel risk variants for prostate cancer, increasing the total number of risk variants to 451. An externally replicated multi-ancestry GRS was associated with risk that ranged from 1.8 (per standard deviation) in African ancestry men to 2.2 in European ancestry men. The GRS was associated with a greater risk of aggressive versus non-aggressive disease in men of African ancestry (P = 0.03). Our study presents novel prostate cancer susceptibility loci and a GRS with effective risk stratification across ancestry groups.

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.

Association between an inflammatory biomarker score and future dementia diagnosis in the population-based UK Biobank cohort of 500,000 people.

This study was designed to investigate the relationship between a systematic inflammatory biomarker measure, concurrent and later cognitive performance, and future dementia risk. The literature has reported the potential involvement of inflammation in cognitive performance as well as Alzheimer's Disease, but not consistently. We used a population-based cohort of 500,000 people in the UK and assessed the association between a composite inflammatory biomarker and cognitive performance measures across five domains measured concurrently and 4-13 years later, taking advantage of the large sample size. We also assessed the same biomarker's association with dementia diagnosis 3-11 years later in the initially dementia-free sample. We report small but significant associations between elevated biomarker levels and worsened cognitive performance at baseline for four cognitive tasks (OR = 1.204, p<0.001 for Prospective memory, ß = -0.366, p<0.001 for Fluid intelligence, ß = 8.819, p<0.001 for Reaction time, and ß = -0.224, p<0.001 for Numeric memory), comparing the highest quartile of the biomarker to the lowest. We also found that for one measure (Pairs matching) higher biomarker levels were associated with fewer errors, i.e. better performance (ß = -0.096, p<0.001). We also report that the 4th quartiles of the baseline biomarker levels were significantly associated with cognitive task scores assessed years later on the p< = 0.002 level, except for the Pair matching test, for which none of the quartiles remained a significant predictor. Finally, the highest biomarker quartile was significantly associated with increased dementia risk compared to the lowest quartile (HR = 1.349, p<0.001). A case-only analysis to assess disease subtype heterogeneity suggested probable differences in the association with the highest biomarker quartile between vascular dementia and Alzheimer disease subtypes (OR = 1.483, p = 0.055). Our results indicate that systemic inflammation may play a small but significant part in dementia pathophysiology, especially in vascular dementia.

Evaluating Approaches for Constructing Polygenic Risk Scores for Prostate Cancer in Men of African and European Ancestry.

Genome-wide polygenic risk scores (GW-PRS) have been reported to have better predictive ability than PRS 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 GWAS and fine-mapping studies (PRS 269 ). GW-PRS models were trained using a large and diverse prostate cancer GWAS of 107,247 cases and 127,006 controls used to develop the multi-ancestry PRS 269 . 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 OR 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. However, compared to the GW-PRS, in African and European ancestry men, the PRS 269 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 OR (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 data. This investigation suggests that current GW-PRS approaches may not improve the ability to predict prostate cancer risk compared to the multi-ancestry PRS 269 constructed with fine-mapping.

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.

Biochemical activity induced by a germline variation in KLK3 (PSA) associates with cellular function and clinical outcome in prostate cancer.

Genetic variation at the 19q13.3 KLK locus is linked with prostate cancer susceptibility. The non-synonymous KLK3 SNP, rs17632542 (c.536T>C; Ile163Thr-substitution in PSA) is associated with reduced prostate cancer risk, however, the functional relevance is unknown. Here, we identify that the SNP variant-induced change in PSA biochemical activity as a previously undescribed function mediating prostate cancer pathogenesis. The 'Thr' PSA variant led to small subcutaneous tumours, supporting reduced prostate cancer risk. However, 'Thr' PSA also displayed higher metastatic potential with pronounced osteolytic activity in an experimental metastasis in-vivo model. Biochemical characterization of this PSA variant demonstrated markedly reduced proteolytic activity that correlated with differences in in-vivo tumour burden. The SNP is associated with increased risk for aggressive disease and prostate cancer-specific mortality in three independent cohorts, highlighting its critical function in mediating metastasis. Carriers of this SNP allele had reduced serum total PSA and a higher free/total PSA ratio that could contribute to late biopsy decisions and delay in diagnosis. Our results provide a molecular explanation for the prominent 19q13.3 KLK locus, rs17632542 SNP, association with a spectrum of prostate cancer clinical outcomes.

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.

Family History of Prostate Cancer and Survival Outcomes in the UK Genetic Prostate Cancer Study.

BACKGROUND: A family history (FH) of prostate cancer (PrCa) is associated with an increased likelihood of PrCa diagnosis. Conflicting evidence exists regarding familial PrCa and clinical outcomes among PrCa patients, including all-cause mortality/overall survival (OS), PrCa-specific survival (PCSS), aggressive histology, and stage at diagnosis. OBJECTIVE: To determine how the number, degree, and age of a PrCa patient's affected relatives are associated with OS and PCSS of those already diagnosed with PrCa. DESIGN, SETTING, AND PARTICIPANTS: The UK Genetic Prostate Cancer Study is a longitudinal, multi-institutional, observational study collecting baseline and follow-up clinical data since 1992. We examined OS and PCSS in 16340 men by degree and number of relatives with prostate and genetically related cancers (breast, ovarian, and colorectal). OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The primary outcome was all-cause mortality among PrCa patients. The risk of death with respect to FH was assessed by calculating hazard ratios from Cox proportional hazard regression models, adjusting for relevant factors. RESULTS AND LIMITATIONS: A stronger FH was inversely associated with the risk of all-cause and PrCa-specific mortality. This association was greater in those with an increasing number (p-trend < 0.001) and increasing closeness (p-trend < 0.001) of the diagnosed relatives. Patients with at least one first-degree relative were at a lower risk of all-cause mortality than those with no FH (hazard ratio = 0.82 [95% confidence interval 0.75-0.89]). The population is largely of European ancestry, and this may cause an issue with representation and generalisation. Data are missing on epidemiological risk factors for death such as smoking and on comorbidities. Recall of family members' diagnoses may affect the classification of FH in unconfirmed cases. CONCLUSIONS: Based on the investigation of the type and timing of relatives' cancers, it is likely that reductions in mortality are due almost completely to a greater awareness of the disease. This study provides information for clinicians guiding patients and their relatives based on their familial risk. It shows the importance of screening and awareness programmes, which are likely to improve survival among men with an FH. PATIENT SUMMARY: We were interested in how a family history of prostate cancer affects survival in prostate cancer patients. We studied 16340 patients, categorised them according to the strength of their family history, and found that the stronger their family history, the better they did in terms of overall survival. We looked at the type and timing of patients' diagnoses compared with those of their relatives and found that this effect is likely to be explained by awareness, which indicates the importance of screening and awareness programmes.

CanRisk-Prostate: A Comprehensive, Externally Validated Risk Model for the Prediction of Future Prostate Cancer.

PURPOSE: Prostate cancer (PCa) is highly heritable. No validated PCa risk model currently exists. We therefore sought to develop a genetic risk model that can provide personalized predicted PCa risks on the basis of known moderate- to high-risk pathogenic variants, low-risk common genetic variants, and explicit cancer family history, and to externally validate the model in an independent prospective cohort. MATERIALS AND METHODS: We developed a risk model using a kin-cohort comprising individuals from 16,633 PCa families ascertained in the United Kingdom from 1993 to 2017 from the UK Genetic Prostate Cancer Study, and complex segregation analysis adjusting for ascertainment. The model was externally validated in 170,850 unaffected men (7,624 incident PCas) recruited from 2006 to 2010 to the independent UK Biobank prospective cohort study. RESULTS: The most parsimonious model included the effects of pathogenic variants in BRCA2, HOXB13, and BRCA1, and a polygenic score on the basis of 268 common low-risk variants. Residual familial risk was modeled by a hypothetical recessively inherited variant and a polygenic component whose standard deviation decreased log-linearly with age. The model predicted familial risks that were consistent with those reported in previous observational studies. In the validation cohort, the model discriminated well between unaffected men and men with incident PCas within 5 years (C-index, 0.790; 95% CI, 0.783 to 0.797) and 10 years (C-index, 0.772; 95% CI, 0.768 to 0.777). The 50% of men with highest predicted risks captured 86.3% of PCa cases within 10 years. CONCLUSION: To our knowledge, this is the first validated risk model offering personalized PCa risks. The model will assist in counseling men concerned about their risk and can facilitate future risk-stratified population screening approaches.

Coffee Intake, Caffeine Metabolism Genotype, and Survival Among Men with Prostate Cancer.

BACKGROUND: Coffee intake may lower prostate cancer risk and progression, but postdiagnosis outcomes by caffeine metabolism genotype are not well characterized. OBJECTIVE: To evaluate associations between coffee intake, caffeine metabolism genotype, and survival in a large, multicenter study of men with prostate cancer. DESIGN, SETTING, AND PARTICIPANTS: Data from The PRACTICAL Consortium database for 5727 men with prostate cancer from seven US, Australian, and European studies were included. The cases included had data available for the CYP1A2 -163C>A rs762551 single-nucleotide variant associated with caffeine metabolism, coffee intake, and >6 mo of follow-up. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Multivariable-adjusted Cox proportional hazards models across pooled patient-level data were used to compare the effect of coffee intake (categorized as low [reference], high, or none/very low) in relation to overall survival (OS) and prostate cancer-specific survival (PCSS), with stratified analyses conducted by clinical disease risk and genotype. RESULTS AND LIMITATIONS: High coffee intake appeared to be associated with longer PCSS (hazard ratio [HR] 0.85, 95% confidence interval [CI] 0.68-1.08; p = 0.18) and OS (HR 0.90, 95% CI 0.77-1.07; p = 0.24), although results were not statistically significant. In the group with clinically localized disease, high coffee intake was associated with longer PCSS (HR 0.66, 95% CI 0.44-0.98; p = 0.040), with comparable results for the group with advanced disease (HR 0.92, 95% CI 0.69-1.23; p = 0.6). High coffee intake was associated with longer PCSS among men with the CYP1A2 AA (HR 0.67, 95% CI 0.49-0.93; p = 0.017) but not the AC/CC genotype (p = 0.8); an interaction was detected (p = 0.042). No associations with OS were observed in subgroup analyses (p > 0.05). Limitations include the nominal statistical significance and residual confounding. CONCLUSIONS: Coffee intake was associated with longer PCSS among men with a CYP1A2 -163AA (*1F/*1F) genotype, a finding that will require further replication. PATIENT SUMMARY: It is likely that coffee intake is associated with longer prostate cancer-specific survival in certain groups, but more research is needed to fully understand which men may benefit and why.

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.

Risk Factors Associated with Pancreatic Cancer in the UK Biobank Cohort.

Evidence on pancreatic cancer (PaCa) risk factors from large population-based cohort studies is limited. This study investigated the PaCa risk factors and the population attributable fraction (PAF) of modifiable risk factors in the UK Biobank cohort. The UK Biobank is a prospective cohort consisting of 502,413 participants with a mean follow-up time of 8.2 years. A binomial generalized linear regression model was used to calculate relative risks for PaCa risk factors. PAF was calculated to estimate the proportional reduction in PaCa if modifiable risk factors were to be eliminated. A total of 728 (0.14%) PaCa incident cases and 412,922 (82.19%) non-PaCa controls were analyzed. The non-modifiable risk factors included age and gender. The modifiable risk factors were cigarette smoking, overweight and obesity, increased waist circumstance, abdominal obesity, Diabetic Mellitus (DM), and pancreatitis history. The PAF suggested that eliminating smoking and obesity can contribute around a 16% reduction in PaCa cases while avoiding abdominal obesity can eliminate PaCa cases by 22%. Preventing pancreatitis and DM could potentially reduce PaCa cases by 1% and 6%, respectively. This study has identified modifiable and non-modifiable PaCa risk factors in the UK population. The PAF of modifiable risk factors can be applied to inform PaCa prevention programs.

Investigation of the association between the antibody responses to neurotropic viruses and dementia outcomes in the UK Biobank.

The causes that trigger the onset of dementia are still unknown. Recently there has been an increasing interest in the possible role of infectious agents in the brain in the pathogenesis of this condition. Amongst the viruses, members of the Herpesviridae family, namely herpes simplex virus-1 (HSV1), cytomegalovirus (CMV), human herpesvirus-6 (HHV6), human herpesvirus-7 (HHV7) and varicella zoster virus (VZV) have been suggested as potential causes of the disease. However, the relative importance of these and other viruses in contributing to dementia remains unclear. We evaluated the association between seropositivity status of all viruses available in a large, population-based dataset (the UK Biobank) and dementia risk in an unbiased way. Of the 15 viruses investigated, our results showed a statistically significant increase of dementia risk associated only with HSV1 seropositivity (OR 2.14, 95% C.I. 1.21-3.81). However, by combining the data we found that seropositivity for 4 viruses (HSV1, HHV6, HHV7 and VZV) also significantly increases the risk of dementia (OR = 2.37, 95% C.I. 1.43-3.92). These four viruses have been described previously as neurotropic viruses. Our results provide support for a role for neurotropic viruses in the pathology of dementia.

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.

Quantifying the Effect of Physical Activity on Endometrial Cancer Risk.

Endometrial cancer incidence is rising, with 435,000 global cases in 2019. An effective, low-cost primary prevention strategy is required to reduce disease burden. Obesity, insulin resistance, and inflammation contribute to endometrial carcinogenesis and physical activity targets these pathways. This study sought to quantify the amount of physical activity required to impact upon endometrial cancer risk. Physical activity data from 222,031 female participants with an intact uterus in the UK Biobank study were analyzed using a multivariable Cox proportional hazards model. A systematic review of the literature was performed, searching CENTRAL, Embase, and MEDLINE databases up to April 19, 2021. Studies including participants with and without endometrial cancer investigating the effect of physical activity measured in MET-hours/week (MET-h/week) on disease risk were included. Two reviewers independently selected studies, extracted data, and evaluated the risk of bias. Within the UK Biobank, each 1 MET-h/week increase in total physical activity was associated with a 0.2% [95% confidence interval (CI), 0.1-0.4; P = 0.020] reduction in endometrial cancer risk, equating to a 10.4% reduction if performing 50 MET-h/week or 7 hours of jogging per week. Eleven cohort and 12 case-control studies were identified in the systematic review, including 821,599 participants. One study reported a nonsignificant effect of 1 MET-h/week increases in physical activity on endometrial cancer risk (OR, 1.00; 95% CI, 0.99-1.00). Eight studies found significant reductions in disease risk of 15%-53%, but only in the most physically active individuals. Physical activity reduces endometrial cancer risk, but the effect size appears small. Regular vigorous activity should be encouraged to maximize the health benefit observed. PREVENTION RELEVANCE: Effective, low-cost primary prevention strategies are urgently needed to tackle the rapid global increase in endometrial cancer. We sought to quantify the effect of physical activity on endometrial cancer risk, noting a linear inverse relationship influenced by body mass index. The most beneficial type and amount of activity remain unclear.

A suggested shared aetiology of dementia - a colocalization study.

Identification of shared causal genes between dementia and its related clinical outcomes can help understand shared aetiology and multimorbidity surrounding dementia. We performed the HyPrColoc colocalization analysis to detect possible shared causal genes between dementia or Alzheimer's disease (AD) and 5 selected traits: stroke, diabetes, atherosclerosis, cholesterol level, and alcohol consumption within 601 dementia or AD associated genetic regions using summary results of the UK Biobank genome-wide association studies. Functional analysis was performed on the candidate causal genes to explore potential biological pathways. Rs150562240 in the LPIN3 gene was identified as a candidate shared causal variant across dementia, AD and atherosclerosis. Evidence for pairwise colocalization between dementia and stroke, dementia (or AD) and atherosclerosis, and dementia (or AD) and diabetes was found in 2, 6 and 2 genetic regions respectively. Colocalization signals between diabetes and the other 3 non-dementia/AD traits were detected in 5 regions. The colocalization evidence shown in our study suggested shared aetiology between dementia and related diseases such as stroke, atherosclerosis, and diabetes.