Meat consumption and risk of ischemic heart disease: A systematic review and meta-analysis.

There is uncertainty regarding the association between unprocessed red and processed meat consumption and the risk of ischemic heart disease (IHD), and little is known regarding the association with poultry intake. The aim of this systematic review and meta-analysis was to quantitatively assess the associations of unprocessed red, processed meat, and poultry intake and risk of IHD in published prospective studies. We systematically searched CAB Abstract, MEDLINE, EMBASE, Web of Science, bioRxiv and medRxiv, and reference lists of selected studies and previous systematic reviews up to June 4, 2021. All prospective cohort studies that assessed associations between 1(+) meat types and IHD risk (incidence and/or death) were selected. The meta-analysis was conducted using fixed-effects models. Thirteen published articles were included (ntotal = 1,427,989; ncases = 32,630). Higher consumption of unprocessed red meat was associated with a 9% (relative risk (RR) per 50 g/day higher intake, 1.09; 95% confidence intervals (CI), 1.06 to 1.12; nstudies = 12) and processed meat intake with an 18% higher risk of IHD (1.18; 95% CI, 1.12 to 1.25; nstudies = 10). There was no association with poultry intake (nstudies = 10). This study provides substantial evidence that unprocessed red and processed meat, though not poultry, might be risk factors for IHD.

Pan-cancer analysis of pre-diagnostic blood metabolite concentrations in the European Prospective Investigation into Cancer and Nutrition.

BACKGROUND: Epidemiological studies of associations between metabolites and cancer risk have typically focused on specific cancer types separately. Here, we designed a multivariate pan-cancer analysis to identify metabolites potentially associated with multiple cancer types, while also allowing the investigation of cancer type-specific associations. METHODS: We analysed targeted metabolomics data available for 5828 matched case-control pairs from cancer-specific case-control studies on breast, colorectal, endometrial, gallbladder, kidney, localized and advanced prostate cancer, and hepatocellular carcinoma nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. From pre-diagnostic blood levels of an initial set of 117 metabolites, 33 cluster representatives of strongly correlated metabolites and 17 single metabolites were derived by hierarchical clustering. The mutually adjusted associations of the resulting 50 metabolites with cancer risk were examined in penalized conditional logistic regression models adjusted for body mass index, using the data-shared lasso penalty. RESULTS: Out of the 50 studied metabolites, (i) six were inversely associated with the risk of most cancer types: glutamine, butyrylcarnitine, lysophosphatidylcholine a C18:2, and three clusters of phosphatidylcholines (PCs); (ii) three were positively associated with most cancer types: proline, decanoylcarnitine, and one cluster of PCs; and (iii) 10 were specifically associated with particular cancer types, including histidine that was inversely associated with colorectal cancer risk and one cluster of sphingomyelins that was inversely associated with risk of hepatocellular carcinoma and positively with endometrial cancer risk. CONCLUSIONS: These results could provide novel insights for the identification of pathways for cancer development, in particular those shared across different cancer types.

Describing a new food group classification system for UK biobank: analysis of food groups and sources of macro- and micronutrients in 208,200 participants.

PURPOSE: The UK Biobank study collected detailed dietary data using a web-based self-administered 24 h assessment tool, the Oxford WebQ. We aimed to describe a comprehensive food grouping system for this questionnaire and to report dietary intakes and key sources of selected nutrients by sex and education. METHODS: Participants with at least one valid 24-h questionnaire were included (n = 208,200). Dietary data were grouped based on the presence of nutrients as well as culinary use, processing, and plant/animal origin. For each food group, we calculated the contribution to energy intake, key macronutrients, and micronutrients. We also identified the top contributors to energy intake, free sugars and saturated fat by sex and education. RESULTS: From the 93 food groups, the top five contributors to energy intake (in descending order) were: desserts/cakes/pastries; white bread; white pasta/rice; bananas/other fruit; semi-skimmed milk. Wine, beer, and fruit juices were the top beverage contributors to overall energy intake. Biscuits, and desserts/cakes/pastries were the highest contributors to free sugars, total fat, and saturated fat intakes, but also contributed to the calcium and iron intakes. Top contributors to energy, saturated fat, and free sugars were broadly similar by sex and education category, with small differences in average nutrient intakes across the population. CONCLUSION: This new food classification system will support the growing interest in the associations between food groups and health outcomes and the development of food-based dietary guidelines. Food group variables will be available to all users of the UK Biobank WebQ questionnaire.

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans.

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same region.

Fine-mapping the HOXB region detects common variants tagging a rare coding allele: evidence for synthetic association in prostate cancer.

The HOXB13 gene has been implicated in prostate cancer (PrCa) susceptibility. We performed a high resolution fine-mapping analysis to comprehensively evaluate the association between common genetic variation across the HOXB genetic locus at 17q21 and PrCa risk. This involved genotyping 700 SNPs using a custom Illumina iSelect array (iCOGS) followed by imputation of 3195 SNPs in 20,440 PrCa cases and 21,469 controls in The PRACTICAL consortium. We identified a cluster of highly correlated common variants situated within or closely upstream of HOXB13 that were significantly associated with PrCa risk, described by rs117576373 (OR 1.30, P = 2.62×10(-14)). Additional genotyping, conditional regression and haplotype analyses indicated that the newly identified common variants tag a rare, partially correlated coding variant in the HOXB13 gene (G84E, rs138213197), which has been identified recently as a moderate penetrance PrCa susceptibility allele. The potential for GWAS associations detected through common SNPs to be driven by rare causal variants with higher relative risks has long been proposed; however, to our knowledge this is the first experimental evidence for this phenomenon of synthetic association contributing to cancer susceptibility.

Main nutrient patterns are associated with prospective weight change in adults from 10 European countries.

PURPOSE: Various food patterns have been associated with weight change in adults, but it is unknown which combinations of nutrients may account for such observations. We investigated associations between main nutrient patterns and prospective weight change in adults. METHODS: This study includes 235,880 participants, 25-70 years old, recruited between 1992 and 2000 in 10 European countries. Intakes of 23 nutrients were estimated from country-specific validated dietary questionnaires using the harmonized EPIC Nutrient DataBase. Four nutrient patterns, explaining 67 % of the total variance of nutrient intakes, were previously identified from principal component analysis. Body weight was measured at recruitment and self-reported 5 years later. The relationship between nutrient patterns and annual weight change was examined separately for men and women using linear mixed models with random effect according to center controlling for confounders. RESULTS: Mean weight gain was 460 g/year (SD 950) and 420 g/year (SD 940) for men and women, respectively. The annual differences in weight gain per one SD increase in the pattern scores were as follows: principal component (PC) 1, characterized by nutrients from plant food sources, was inversely associated with weight gain in men (-22 g/year; 95 % CI -33 to -10) and women (-18 g/year; 95 % CI -26 to -11). In contrast, PC4, characterized by protein, vitamin B2, phosphorus, and calcium, was associated with a weight gain of +41 g/year (95 % CI +2 to +80) and +88 g/year (95 % CI +36 to +140) in men and women, respectively. Associations with PC2, a pattern driven by many micro-nutrients, and with PC3, a pattern driven by vitamin D, were less consistent and/or non-significant. CONCLUSIONS: We identified two main nutrient patterns that are associated with moderate but significant long-term differences in weight gain in adults.

Healthy lifestyle and risk of breast cancer among postmenopausal women in the European Prospective Investigation into Cancer and Nutrition cohort study.

Breast cancer is the most common cancer among women and prevention strategies are needed to reduce incidence worldwide. A healthy lifestyle index score (HLIS) was generated to investigate the joint effect of modifiable lifestyle factors on postmenopausal breast cancer risk. The study included 242,918 postmenopausal women from the multinational European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, with detailed information on diet and lifestyle assessed at baseline. The HLIS was constructed from five factors (diet, physical activity, smoking, alcohol consumption and anthropometry) by assigning scores of 0-4 to categories of each component, for which higher values indicate healthier behaviours. Hazard ratios (HR) were estimated by Cox proportional regression models. During 10.9 years of median follow-up, 7,756 incident breast cancer cases were identified. There was a 3% lower risk of breast cancer per point increase of the HLIS. Breast cancer risk was inversely associated with a high HLIS when fourth versus second (reference) categories were compared [adjusted HR = 0.74; 95% confidence interval (CI): 0.66-0.83]. The fourth versus the second category of the HLIS was associated with a lower risk for hormone receptor double positive (adjusted HR = 0.81, 95% CI: 0.67-0.98) and hormone receptor double negative breast cancer (adjusted HR = 0.60, 95% CI: 0.40-0.90). Findings suggest having a high score on an index of combined healthy behaviours reduces the risk of developing breast cancer among postmenopausal women. Programmes which engage women in long term health behaviours should be supported.

General and abdominal obesity and risk of esophageal and gastric adenocarcinoma in the European Prospective Investigation into Cancer and Nutrition.

General obesity, as reflected by BMI, is an established risk factor for esophageal adenocarcinoma (EAC), a suspected risk factor for gastric cardia adenocarcinoma (GCC) and appears unrelated to gastric non-cardia adenocarcinoma (GNCC). How abdominal obesity, as commonly measured by waist circumference (WC), relates to these cancers remains largely unexplored. Using measured anthropometric data from 391,456 individuals from the European Prospective Investigation into Cancer and Nutrition (EPIC) study and 11 years of follow-up, we comprehensively assessed the association of anthropometric measures with risk of EAC, GCC and GNCC using multivariable proportional hazards regression. One hundred twenty-four incident EAC, 193 GCC and 224 GNCC were accrued. After mutual adjustment, BMI was unrelated to EAC, while WC showed a strong positive association (highest vs. lowest quintile HR = 1.19; 95% CI, 0.63-2.22 and HR = 3.76; 1.72-8.22, respectively). Hip circumference (HC) was inversely related to EAC after controlling for WC, while WC remained positively associated (HR = 0.35; 0.18-0.68, and HR=4.10; 1.94-8.63, respectively). BMI was not associated with GCC or GNCC. WC was related to higher risks of GCC after adjustment for BMI and more strongly after adjustment for HC (highest vs. lowest quintile HR = 1.91; 1.09-3.37, and HR = 2.23; 1.28-3.90, respectively). Our study demonstrates that abdominal, rather than general, obesity is an indisputable risk factor for EAC and also provides evidence for a protective effect of gluteofemoral (subcutaneous) adipose tissue in EAC. Our study further shows that general obesity is not a risk factor for GCC and GNCC, while the role of abdominal obesity in GCC needs further investigation.

Fine-mapping identifies multiple prostate cancer risk loci at 5p15, one of which associates with TERT expression.

Associations between single nucleotide polymorphisms (SNPs) at 5p15 and multiple cancer types have been reported. We have previously shown evidence for a strong association between prostate cancer (PrCa) risk and rs2242652 at 5p15, intronic in the telomerase reverse transcriptase (TERT) gene that encodes TERT. To comprehensively evaluate the association between genetic variation across this region and PrCa, we performed a fine-mapping analysis by genotyping 134 SNPs using a custom Illumina iSelect array or Sequenom MassArray iPlex, followed by imputation of 1094 SNPs in 22 301 PrCa cases and 22 320 controls in The PRACTICAL consortium. Multiple stepwise logistic regression analysis identified four signals in the promoter or intronic regions of TERT that independently associated with PrCa risk. Gene expression analysis of normal prostate tissue showed evidence that SNPs within one of these regions also associated with TERT expression, providing a potential mechanism for predisposition to disease.

Prediction of individual genetic risk to prostate cancer using a polygenic score.

BACKGROUND: Polygenic risk scores comprising established susceptibility variants have shown to be informative classifiers for several complex diseases including prostate cancer. For prostate cancer it is unknown if inclusion of genetic markers that have so far not been associated with prostate cancer risk at a genome-wide significant level will improve disease prediction. METHODS: We built polygenic risk scores in a large training set comprising over 25,000 individuals. Initially 65 established prostate cancer susceptibility variants were selected. After LD pruning additional variants were prioritized based on their association with prostate cancer. Six-fold cross validation was performed to assess genetic risk scores and optimize the number of additional variants to be included. The final model was evaluated in an independent study population including 1,370 cases and 1,239 controls. RESULTS: The polygenic risk score with 65 established susceptibility variants provided an area under the curve (AUC) of 0.67. Adding an additional 68 novel variants significantly increased the AUC to 0.68 (P = 0.0012) and the net reclassification index with 0.21 (P = 8.5E-08). All novel variants were located in genomic regions established as associated with prostate cancer risk. CONCLUSIONS: Inclusion of additional genetic variants from established prostate cancer susceptibility regions improves disease prediction.

Active and passive cigarette smoking and breast cancer risk: results from the EPIC cohort.

Recent cohort studies suggest that increased breast cancer risks were associated with longer smoking duration, higher pack-years and a dose-response relationship with increasing pack-years of smoking between menarche and first full-term pregnancy (FFTP). Studies with comprehensive quantitative life-time measures of passive smoking suggest an association between passive smoking dose and breast cancer risk. We conducted a study within the European Prospective Investigation into Cancer and Nutrition to examine the association between passive and active smoking and risk of invasive breast cancer and possible effect modification by known breast cancer risk factors. Among the 322,988 women eligible for the study, 9,822 developed breast cancer (183,608 women with passive smoking information including 6,264 cases). When compared to women who never smoked and were not being exposed to passive smoking at home or work at the time of study registration, current, former and currently exposed passive smokers were at increased risk of breast cancer (hazard ratios (HR) [95% confidence interval (CI)] 1.16 [1.05-1.28], 1.14 [1.04-1.25] and 1.10 [1.01-1.20], respectively). Analyses exploring associations in different periods of life showed the most important increase in risk with pack-years from menarche to FFTP (1.73 [1.29-2.32] for every increase of 20 pack-years) while pack-years smoked after menopause were associated with a significant decrease in breast cancer risk (HR = 0.53, 95% CI: 0.34-0.82 for every increase of 20 pack-years). Our results provide an important replication, in the largest cohort to date, that smoking (passively or actively) increases breast cancer risk and that smoking between menarche and FFTP is particularly deleterious.

Identifying proteomic risk factors for cancer using prospective and exome analyses of 1463 circulating proteins and risk of 19 cancers in the UK Biobank.

The availability of protein measurements and whole exome sequence data in the UK Biobank enables investigation of potential observational and genetic protein-cancer risk associations. We investigated associations of 1463 plasma proteins with incidence of 19 cancers and 9 cancer subsites in UK Biobank participants (average 12 years follow-up). Emerging protein-cancer associations were further explored using two genetic approaches, cis-pQTL and exome-wide protein genetic scores (exGS). We identify 618 protein-cancer associations, of which 107 persist for cases diagnosed more than seven years after blood draw, 29 of 618 were associated in genetic analyses, and four had support from long time-to-diagnosis ( > 7 years) and both cis-pQTL and exGS analyses: CD74 and TNFRSF1B with NHL, ADAM8 with leukemia, and SFTPA2 with lung cancer. We present multiple blood protein-cancer risk associations, including many detectable more than seven years before cancer diagnosis and that had concordant evidence from genetic analyses, suggesting a possible role in cancer development.

Identifying proteomic risk factors for overall, aggressive, and early onset prostate cancer using Mendelian Randomisation and tumour spatial transcriptomics.

BACKGROUND: Understanding the role of circulating proteins in prostate cancer risk can reveal key biological pathways and identify novel targets for cancer prevention. METHODS: We investigated the association of 2002 genetically predicted circulating protein levels with risk of prostate cancer overall, and of aggressive and early onset disease, using cis-pQTL Mendelian randomisation (MR) and colocalisation. Findings for proteins with support from both MR, after correction for multiple-testing, and colocalisation were replicated using two independent cancer GWAS, one of European and one of African ancestry. Proteins with evidence of prostate-specific tissue expression were additionally investigated using spatial transcriptomic data in prostate tumour tissue to assess their role in tumour aggressiveness. Finally, we mapped risk proteins to drug and ongoing clinical trials targets. FINDINGS: We identified 20 proteins genetically linked to prostate cancer risk (14 for overall [8 specific], 7 for aggressive [3 specific], and 8 for early onset disease [2 specific]), of which the majority replicated where data were available. Among these were proteins associated with aggressive disease, such as PPA2 [Odds Ratio (OR) per 1 SD increment = 2.13, 95% CI: 1.54-2.93], PYY [OR = 1.87, 95% CI: 1.43-2.44] and PRSS3 [OR = 0.80, 95% CI: 0.73-0.89], and those associated with early onset disease, including EHPB1 [OR = 2.89, 95% CI: 1.99-4.21], POGLUT3 [OR = 0.76, 95% CI: 0.67-0.86] and TPM3 [OR = 0.47, 95% CI: 0.34-0.64]. We confirmed an inverse association of MSMB with prostate cancer overall [OR = 0.81, 95% CI: 0.80-0.82], and also found an inverse association with both aggressive [OR = 0.84, 95% CI: 0.82-0.86] and early onset disease [OR = 0.71, 95% CI: 0.68-0.74]. Using spatial transcriptomics data, we identified MSMB as the genome-wide top-most predictive gene to distinguish benign regions from high grade cancer regions that comparatively had five-fold lower MSMB expression. Additionally, ten proteins that were associated with prostate cancer risk also mapped to existing therapeutic interventions. INTERPRETATION: Our findings emphasise the importance of proteomics for improving our understanding of prostate cancer aetiology and of opportunities for novel therapeutic interventions. Additionally, we demonstrate the added benefit of in-depth functional analyses to triangulate the role of risk proteins in the clinical aggressiveness of prostate tumours. Using these integrated methods, we identify a subset of risk proteins associated with aggressive and early onset disease as priorities for investigation for the future prevention and treatment of prostate cancer. FUNDING: This work was supported by Cancer Research UK (grant no. C8221/A29017).

Physical activity and risk of breast cancer overall and by hormone receptor status: the European prospective investigation into cancer and nutrition.

Physical activity is associated with reduced risks of invasive breast cancer. However, whether this holds true for breast cancer subtypes defined by the estrogen receptor (ER) and the progesterone receptor (PR) status is controversial. The study included 257,805 women from the multinational EPIC-cohort study with detailed information on occupational, recreational and household physical activity and important cofactors assessed at baseline. During 11.6 years of median follow-up, 8,034 incident invasive breast cancer cases were identified. Data on ER, PR and combined ER/PR expression were available for 6,007 (67.6%), 4,814 (54.2%) and 4,798 (53.9%) cases, respectively. Adjusted hazard ratios (HR) were estimated by proportional hazards models. Breast cancer risk was inversely associated with moderate and high levels of total physical activity (HR = 0.92, 95% confidence interval (CI): 0.86-0.99, HR = 0.87, 95%-CI: 0.79-0.97, respectively; p-trend = 0.002), compared to the lowest quartile. Among women diagnosed with breast cancer after age 50, the largest risk reduction was found with highest activity (HR = 0.86, 95%-CI: 0.77-0.97), whereas for cancers diagnosed before age 50 strongest associations were found for moderate total physical activity (HR = 0.78, 95%-CI: 0.64-0.94). Analyses by hormone receptor status suggested differential associations for total physical activity (p-heterogeneity = 0.04), with a somewhat stronger inverse relationship for ER+/PR+ breast tumors, primarily driven by PR+ tumors (p-heterogeneity < 0.01). Household physical activity was inversely associated with ER-/PR- tumors. The results of this largest prospective study on the protective effects of physical activity indicate that moderate and high physical activity are associated with modest decreased breast cancer risk. Heterogeneities by receptor status indicate hormone-related mechanisms.

Fine mapping of a region of chromosome 11q13 reveals multiple independent loci associated with risk of prostate cancer.

Genome-wide association studies have identified prostate cancer susceptibility alleles on chromosome 11q13. As part of the Cancer Genetic Markers of Susceptibility (CGEMS) Initiative, the region flanking the most significant marker, rs10896449, was fine mapped in 10 272 cases and 9123 controls of European origin (10 studies) using 120 common single nucleotide polymorphisms (SNPs) selected by a two-staged tagging strategy using HapMap SNPs. Single-locus analysis identified 18 SNPs below genome-wide significance (P< 10(-8)) with rs10896449 the most significant (P= 7.94 × 10(-19)). Multi-locus models that included significant SNPs sequentially identified a second association at rs12793759 [odds ratio (OR) = 1.14, P= 4.76 × 10(-5), adjusted P= 0.004] that is independent of rs10896449 and remained significant after adjustment for multiple testing within the region. rs10896438, a proxy of previously reported rs12418451 (r(2)= 0.96), independent of both rs10896449 and rs12793759 was detected (OR = 1.07, P= 5.92 × 10(-3), adjusted P= 0.054). Our observation of a recombination hotspot that separates rs10896438 from rs10896449 and rs12793759, and low linkage disequilibrium (rs10896449-rs12793759, r(2)= 0.17; rs10896449-rs10896438, r(2)= 0.10; rs12793759-rs10896438, r(2)= 0.12) corroborate our finding of three independent signals. By analysis of tagged SNPs across ∼123 kb using next generation sequencing of 63 controls of European origin, 1000 Genome and HapMap data, we observed multiple surrogates for the three independent signals marked by rs10896449 (n= 31), rs10896438 (n= 24) and rs12793759 (n= 8). Our results indicate that a complex architecture underlying the common variants contributing to prostate cancer risk at 11q13. We estimate that at least 63 common variants should be considered in future studies designed to investigate the biological basis of the multiple association signals.

Lifestyle, dietary factors, and antibody levels to oral bacteria in cancer-free participants of a European cohort study.

BACKGROUND: Increasing evidence suggests that oral microbiota play a pivotal role in chronic diseases, in addition to the well-established role in periodontal disease. Moreover, recent studies suggest that oral bacteria may also be involved in carcinogenesis; periodontal disease has been linked to several cancers. In this study, we examined whether lifestyle factors have an impact on antibody levels to oral bacteria. METHODS: Data on demographic characteristics, lifestyle factors, and medical conditions were obtained at the time of blood sample collection. For the current analysis, we measured antibody levels to 25 oral bacteria in 395 cancer-free individuals using an immunoblot array. Combined total immunoglobin G (IgG) levels were obtained by summing concentrations for all oral bacteria measured. RESULTS: IgG antibody levels were substantially lower among current and former smokers (1,697 and 1,677 ng/mL, respectively) than never smokers (1,960 ng/mL; p trend = 0.01), but did not vary by other factors, including body mass index, diabetes, physical activity, or by dietary factors, after adjusting for age, sex, education, country, and smoking status. The highest levels of total IgG were found among individuals with low education (2,419 ng/mL). CONCLUSIONS: Our findings on smoking are consistent with previous studies and support the notion that smokers have a compromised humoral immune response. Moreover, other major factors known to be associated with inflammatory markers, including obesity, were not associated with antibody levels to a large number of oral bacteria.

Identifying proteomic risk factors for overall, aggressive and early onset prostate cancer using Mendelian randomization and tumor spatial transcriptomics.

Background: Understanding the role of circulating proteins in prostate cancer risk can reveal key biological pathways and identify novel targets for cancer prevention. Methods: We investigated the association of 2,002 genetically predicted circulating protein levels with risk of prostate cancer overall, and of aggressive and early onset disease, using cis-pQTL Mendelian randomization (MR) and colocalization. Findings for proteins with support from both MR, after correction for multiple-testing, and colocalization were replicated using two independent cancer GWAS, one of European and one of African ancestry. Proteins with evidence of prostate-specific tissue expression were additionally investigated using spatial transcriptomic data in prostate tumor tissue to assess their role in tumor aggressiveness. Finally, we mapped risk proteins to drug and ongoing clinical trials targets. Results: We identified 20 proteins genetically linked to prostate cancer risk (14 for overall [8 specific], 7 for aggressive [3 specific], and 8 for early onset disease [2 specific]), of which a majority were novel and replicated. Among these were proteins associated with aggressive disease, such as PPA2 [Odds Ratio (OR) per 1 SD increment = 2.13, 95% CI: 1.54-2.93], PYY [OR = 1.87, 95% CI: 1.43-2.44] and PRSS3 [OR = 0.80, 95% CI: 0.73-0.89], and those associated with early onset disease, including EHPB1 [OR = 2.89, 95% CI: 1.99-4.21], POGLUT3 [OR = 0.76, 95% CI: 0.67-0.86] and TPM3 [OR = 0.47, 95% CI: 0.34-0.64]. We confirm an inverse association of MSMB with prostate cancer overall [OR = 0.81, 95% CI: 0.80-0.82], and also find an inverse association with both aggressive [OR = 0.84, 95% CI: 0.82-0.86] and early onset disease [OR = 0.71, 95% CI: 0.68-0.74]. Using spatial transcriptomics data, we identified MSMB as the genome-wide top-most predictive gene to distinguish benign regions from high grade cancer regions that had five-fold lower MSMB expression. Additionally, ten proteins that were associated with prostate cancer risk mapped to existing therapeutic interventions. Conclusion: Our findings emphasize the importance of proteomics for improving our understanding of prostate cancer etiology and of opportunities for novel therapeutic interventions. Additionally, we demonstrate the added benefit of in-depth functional analyses to triangulate the role of risk proteins in the clinical aggressiveness of prostate tumors. Using these integrated methods, we identify a subset of risk proteins associated with aggressive and early onset disease as priorities for investigation for the future prevention and treatment of prostate cancer.

Longitudinal changes in weight in relation to smoking cessation in participants of the EPIC-PANACEA study.

PURPOSE: We assessed the association between smoking cessation and prospective weight change in the European population of the European Prospective Investigation into Cancer and Nutrition-Physical Activity, Nutrition, Alcohol, Cessation of smoking, Eating out of home And obesity (EPIC-PANACEA) project. METHODS: The study involved more than 300,000 healthy volunteers, recruited between 1992 and 2000 in 9 European countries, who provided data on anthropometry and smoking habits at baseline and after a follow-up of 5 years on average. Adjusted mixed-effects linear regression models were used to obtain sex-specific summary estimates of the association between the change in smoking status and the annual change in weight. RESULTS: Smoking cessation tends to be followed by weight gain; when compared to stable smokers, annual weight gain was higher in men (0.44 kg (95%CI: 0.36; 0.52)) and women (0.46 kg (95%CI: 0.41; 0.52)) who stopped smoking during follow-up. When smokers who stopped smoking at least 1 year before recruitment were compared to never smokers, no major differences in annual weight gain were observed. The excess weight gain following smoking cessation appears to mainly occur in the first years following the cessation. CONCLUSIONS: When considering the benefits of smoking cessation, such findings strengthen the need for promoting cessation offering information on weight gain control and support to weight-concerned smokers in order to remove a barrier to quitting.

Variety in vegetable and fruit consumption and risk of bladder cancer in the European Prospective Investigation into Cancer and Nutrition.

Recent research does not show an association between fruit and vegetable consumption and bladder cancer risk. None of these studies investigated variety in fruit and vegetable consumption, which may capture different aspects of consumption. We investigated whether a varied consumption of vegetables and fruits is associated with bladder cancer risk in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Detailed data on food consumption and complete follow-up for cancer incidence were available for 452,185 participants, who were recruited from ten European countries. After a mean follow-up of 8.7 years, 874 participants were diagnosed with bladder cancer. Diet diversity scores (DDSs) were used to quantify the variety in fruit and vegetable consumption. Multivariable Cox proportional hazard models were used to assess the effect of the DDSs on bladder cancer risk. There was no evidence of a statistically significant association between bladder cancer risk and any of the DDSs when these scores were considered as continuous covariates. However, the hazard ratio (HR) for the highest tertile of the DDS for combined fruit and vegetable consumption was marginally significant compared to the lowest (HR = 1.30, 95% confidence interval: 1.00-1.69, p-trend = 0.05). In EPIC, there is no clear association between a varied fruit and vegetable consumption and bladder cancer risk. This finding provides further evidence for the absence of any strong association between fruit and vegetable consumption as measured by a food frequency questionnaire and bladder cancer risk.