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).

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 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.

Vegans, vegetarians, fish-eaters and meat-eaters in the UK show discrepant environmental impacts.

Modelled dietary scenarios often fail to reflect true dietary practice and do not account for variation in the environmental burden of food due to sourcing and production methods. Here we link dietary data from a sample of 55,504 vegans, vegetarians, fish-eaters and meat-eaters with food-level data on greenhouse gas emissions, land use, water use, eutrophication risk and potential biodiversity loss from a review of 570 life-cycle assessments covering more than 38,000 farms in 119 countries. Our results include the variation in food production and sourcing that is observed in the review of life-cycle assessments. All environmental indicators showed a positive association with amounts of animal-based food consumed. Dietary impacts of vegans were 25.1% (95% uncertainty interval, 15.1-37.0%) of high meat-eaters (≥100 g total meat consumed per day) for greenhouse gas emissions, 25.1% (7.1-44.5%) for land use, 46.4% (21.0-81.0%) for water use, 27.0% (19.4-40.4%) for eutrophication and 34.3% (12.0-65.3%) for biodiversity. At least 30% differences were found between low and high meat-eaters for most indicators. Despite substantial variation due to where and how food is produced, the relationship between environmental impact and animal-based food consumption is clear and should prompt the reduction of the latter.

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.

DQA1*0102 DQB1*0602 haplotype distinguishes coeliac disease and its complications from gluten unrelated enteropathies.

BACKGROUND: Duodenal villous atrophy is due not only to coeliac disease and its complications but also to other rare enteropathies unrelated to gluten consumption, defined as noncoeliac enteropathies. The diagnosis of noncoeliac enteropathies remains challenging, and HLA typing has been widely used to exclude coeliac disease if DQ2 and DQ8 alleles are absent. However, the frequency of the various HLA alleles in noncoeliac enteropathies is still unknown. AIMS: To describe the HLA genetic profile of patients affected by noncoeliac enteropathies who have been evaluated at our centres between 2000 and 2021, and to investigate the diagnostic role of HLA typing. METHODS: Genomic DNA was collected from 44 Italian and 19 British adult patients with noncoeliac enteropathies. Patient genotypes were compared with those of healthy Italian and British populations obtained from HLA bone marrow donors' banks. In addition, genotypes were also compared with those of patients with coeliac disease and complicated coeliac disease. RESULTS: Both in the Italian and in the British group, the DQA1*0102 DQB1*0602 haplotype and related alleles occurred significantly more frequently in patients with noncoeliac enteropathies compared to coeliac disease and complicated coeliac disease. CONCLUSIONS: Together with negative HLA-DQ2 and DQ8 haplotypes, the DQA1*0102 DQB1*0602 haplotype can be used to guide the differential diagnosis between coeliac disease and noncoeliac enteropathies.

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.

Diet-wide association study of 92 foods and nutrients and lung cancer risk in the European Prospective Investigation into Cancer and Nutrition study and the Netherlands Cohort Study.

It is unclear whether diet, and in particular certain foods or nutrients, are associated with lung cancer risk. We assessed associations of 92 dietary factors with lung cancer risk in 327 790 participants in the European Prospective Investigation into Cancer and Nutrition (EPIC). Cox regression yielded adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) per SD higher intake/day of each food/nutrient. Correction for multiple comparisons was performed using the false discovery rate and identified associations were evaluated in the Netherlands Cohort Study (NLCS). In EPIC, 2420 incident lung cancer cases were identified during a median of 15 years of follow-up. Higher intakes of fibre (HR per 1 SD higher intake/day = 0.91, 95% CI 0.87-0.96), fruit (HR = 0.91, 95% CI 0.86-0.96) and vitamin C (HR = 0.91, 95% CI 0.86-0.96) were associated with a lower risk of lung cancer, whereas offal (HR = 1.08, 95% CI 1.03-1.14), retinol (HR = 1.06, 95% CI 1.03-1.10) and beer/cider (HR = 1.04, 95% CI 1.02-1.07) intakes were positively associated with lung cancer risk. Associations did not differ by sex and there was less evidence for associations among never smokers. None of the six associations with overall lung cancer risk identified in EPIC were replicated in the NLCS (2861 cases), however in analyses of histological subtypes, inverse associations of fruit and vitamin C with squamous cell carcinoma were replicated in the NLCS. Overall, there is little evidence that intakes of specific foods and nutrients play a major role in primary lung cancer risk, but fruit and vitamin C intakes seem to be inversely associated with squamous cell lung cancer.

Long-term weight change and risk of breast cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC) study.

BACKGROUND: The role of obesity and weight change in breast-cancer development is complex and incompletely understood. We investigated long-term weight change and breast-cancer risk by body mass index (BMI) at age 20 years, menopausal status, hormone replacement therapy (HRT) and hormone-receptor status. METHODS: Using data on weight collected at three different time points from women who participated in the European Prospective Investigation into Cancer and Nutrition (EPIC) study, we investigated the association between weight change from age 20 years until middle adulthood and risk of breast cancer. RESULTS: In total, 150 257 women with a median age of 51 years at cohort entry were followed for an average of 14 years (standard deviation = 3.9) during which 6532 breast-cancer cases occurred. Compared with women with stable weight (±2.5 kg), long-term weight gain >10 kg was positively associated with postmenopausal breast-cancer risk in women who were lean at age 20 [hazard ratio (HR) = 1.42; 95% confidence interval 1.22-1.65] in ever HRT users (HR = 1.23; 1.04-1.44), in never HRT users (HR = 1.40; 1.16-1.68) and in oestrogen-and-progesterone-receptor-positive (ER+PR+) breast cancer (HR = 1.46; 1.15-1.85). CONCLUSION: Long-term weight gain was positively associated with postmenopausal breast cancer in women who were lean at age 20, both in HRT ever users and non-users, and hormone-receptor-positive breast cancer.

Circulating inflammatory cytokines and risk of five cancers: a Mendelian randomization analysis.

BACKGROUND: Epidemiological and experimental evidence has linked chronic inflammation to cancer aetiology. It is unclear whether associations for specific inflammatory biomarkers are causal or due to bias. In order to examine whether altered genetically predicted concentration of circulating cytokines are associated with cancer development, we performed a two-sample Mendelian randomisation (MR) analysis. METHODS: Up to 31,112 individuals of European descent were included in genome-wide association study (GWAS) meta-analyses of 47 circulating cytokines. Single nucleotide polymorphisms (SNPs) robustly associated with the cytokines, located in or close to their coding gene (cis), were used as instrumental variables. Inverse-variance weighted MR was used as the primary analysis, and the MR assumptions were evaluated in sensitivity and colocalization analyses and a false discovery rate (FDR) correction for multiple comparisons was applied. Corresponding germline GWAS summary data for five cancer outcomes (breast, endometrial, lung, ovarian, and prostate), and their subtypes were selected from the largest cancer-specific GWASs available (cases ranging from 12,906 for endometrial to 133,384 for breast cancer). RESULTS: There was evidence of inverse associations of macrophage migration inhibitory factor with breast cancer (OR per SD = 0.88, 95% CI 0.83 to 0.94), interleukin-1 receptor antagonist with endometrial cancer (0.86, 0.80 to 0.93), interleukin-18 with lung cancer (0.87, 0.81 to 0.93), and beta-chemokine-RANTES with ovarian cancer (0.70, 0.57 to 0.85) and positive associations of monokine induced by gamma interferon with endometrial cancer (3.73, 1.86 to 7.47) and cutaneous T-cell attracting chemokine with lung cancer (1.51, 1.22 to 1.87). These associations were similar in sensitivity analyses and supported in colocalization analyses. CONCLUSIONS: Our study adds to current knowledge on the role of specific inflammatory biomarker pathways in cancer aetiology. Further validation is needed to assess the potential of these cytokines as pharmacological or lifestyle targets for cancer prevention.

Plasma concentrations of persistent organic pollutants and pancreatic cancer risk.

BACKGROUND: Findings and limitations of previous studies on persistent organic pollutants (POPs) and pancreatic cancer risk support conducting further research in prospective cohorts. METHODS: We conducted a prospective case-control study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Participants were 513 pancreatic cancer cases and 1020 matched controls. Concentrations of 22 POPs were measured in plasma collected at baseline. RESULTS: Some associations were observed at higher concentrations of p, p'-DDT, trans-nonachlor, ß-hexachlorocyclohexane and the sum of six organochlorine pesticides and of 16 POPs. The odds ratio (OR) for the upper quartile of trans-nonachlor was 1.55 (95% confidence interval 1.06-2.26; P for trend = 0.025). Associations were stronger in the groups predefined as most valid (participants having fasted >6 h, with microscopic diagnostic confirmation, normal weight, and never smokers), and as most relevant (follow-up ≥10 years). Among participants having fasted >6 h, the ORs were relevant for 10 of 11 exposures. Higher ORs were also observed among cases with microscopic confirmation than in cases with a clinical diagnosis, and among normal-weight participants than in the rest of participants. Among participants with a follow-up ≥10 years, estimates were higher than in participants with a shorter follow-up (for trans-nonachlor: OR = 2.14, 1.01 to 4.53, P for trend = 0.035). Overall, trans-nonachlor, three PCBs and the two sums of POPs were the exposures most clearly associated with pancreatic cancer risk. CONCLUSIONS: Individually or in combination, most of the 22 POPs analysed did not or only moderately increased the risk of pancreatic cancer.

Clinical classification and long-term outcomes of seronegative coeliac disease: a 20-year multicentre follow-up study.

BACKGROUND: Seronegative coeliac disease is poorly defined. AIMS: To study clinical phenotypes and long-term outcomes of seronegative coeliac disease in a multicentre cohort over 20 years. METHODS: Seronegative coeliac disease was diagnosed in HLA-DQ2/DQ8-positive patients with villous atrophy (VA), negative IgA endomysial (EmA), tissue transglutaminase (tTG) and deamidated-gliadin antibodies (DGP), clinical and histological response to a gluten-free diet (GFD), and no alternative causes for VA. In patients with IgA deficiency, coeliac disease was diagnosed through VA, positive IgG EmA/tTG/DGP and clinical/histological response to a GFD (coeliac disease+IgAd). Patients with seropositive coeliac disease served as controls. RESULTS: Of 227 patients previously diagnosed with seronegative coeliac disease, true seronegative coeliac disease was confirmed in 84, coeliac disease+IgAd in 48, and excluded in 55. Lack of follow-up duodenal biopsy precluded diagnosing seronegative coeliac disease in 40 patients. 2084 patients with seropositive coeliac disease served as controls. True seronegative coeliac disease had more severe symptoms at diagnosis and a higher risk of complications (HR 10.87, 95% CI 6.11-19.33, P < 0.001) and mortality (HR 2.18, 95% CI 1.12-4.26, P < 0.01) than seropositive coeliac disease. There were no differences between true seronegative coeliac disease and coeliac disease+IgAd. On multivariate analysis, age at diagnosis, lack of clinical response to a GFD, true seronegative coeliac disease, coeliac disease+IgAd, and classical presentation predicted complications. Age at diagnosis, complications and absence of clinical response to a GFD predicted mortality. CONCLUSIONS: Seronegative coeliac disease has a more aggressive disease phenotype than seropositive coeliac disease. These data argue against over-reliance on serology for the diagnosis of coeliac disease and support a strict clinical and histologic follow-up in seronegative coeliac disease.

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.

Development and validation of a lifestyle-based model for colorectal cancer risk prediction: the LiFeCRC score.

BACKGROUND: Nutrition and lifestyle have been long established as risk factors for colorectal cancer (CRC). Modifiable lifestyle behaviours bear potential to minimize long-term CRC risk; however, translation of lifestyle information into individualized CRC risk assessment has not been implemented. Lifestyle-based risk models may aid the identification of high-risk individuals, guide referral to screening and motivate behaviour change. We therefore developed and validated a lifestyle-based CRC risk prediction algorithm in an asymptomatic European population. METHODS: The model was based on data from 255,482 participants in the European Prospective Investigation into Cancer and Nutrition (EPIC) study aged 19 to 70 years who were free of cancer at study baseline (1992-2000) and were followed up to 31 September 2010. The model was validated in a sample comprising 74,403 participants selected among five EPIC centres. Over a median follow-up time of 15 years, there were 3645 and 981 colorectal cancer cases in the derivation and validation samples, respectively. Variable selection algorithms in Cox proportional hazard regression and random survival forest (RSF) were used to identify the best predictors among plausible predictor variables. Measures of discrimination and calibration were calculated in derivation and validation samples. To facilitate model communication, a nomogram and a web-based application were developed. RESULTS: The final selection model included age, waist circumference, height, smoking, alcohol consumption, physical activity, vegetables, dairy products, processed meat, and sugar and confectionary. The risk score demonstrated good discrimination overall and in sex-specific models. Harrell's C-index was 0.710 in the derivation cohort and 0.714 in the validation cohort. The model was well calibrated and showed strong agreement between predicted and observed risk. Random survival forest analysis suggested high model robustness. Beyond age, lifestyle data led to improved model performance overall (continuous net reclassification improvement = 0.307 (95% CI 0.264-0.352)), and especially for young individuals below 45 years (continuous net reclassification improvement = 0.364 (95% CI 0.084-0.575)). CONCLUSIONS: LiFeCRC score based on age and lifestyle data accurately identifies individuals at risk for incident colorectal cancer in European populations and could contribute to improved prevention through motivating lifestyle change at an individual level.

Recommended Definitions of Aggressive Prostate Cancer for Etiologic Epidemiologic Research.

BACKGROUND: In the era of widespread prostate-specific antigen testing, it is important to focus etiologic research on the outcome of aggressive prostate cancer, but studies have defined this outcome differently. We aimed to develop an evidence-based consensus definition of aggressive prostate cancer using clinical features at diagnosis for etiologic epidemiologic research. METHODS: Among prostate cancer cases diagnosed in 2007 in the National Cancer Institute's Surveillance, Epidemiology, and End Results-18 database with follow-up through 2017, we compared the performance of categorizations of aggressive prostate cancer in discriminating fatal prostate cancer within 10 years of diagnosis, placing the most emphasis on sensitivity and positive predictive value (PPV). RESULTS: In our case population (n = 55 900), 3073 men died of prostate cancer within 10 years. Among 12 definitions that included TNM staging and Gleason score, sensitivities ranged from 0.64 to 0.89 and PPVs ranged from 0.09 to 0.23. We propose defining aggressive prostate cancer as diagnosis of category T4 or N1 or M1 or Gleason score of 8 or greater prostate cancer, because this definition had one of the higher PPVs (0.23, 95% confidence interval = 0.22 to 0.24) and reasonable sensitivity (0.66, 95% confidence interval = 0.64 to 0.67) for prostate cancer death within 10 years. Results were similar across sensitivity analyses. CONCLUSIONS: We recommend that etiologic epidemiologic studies of prostate cancer report results for this definition of aggressive prostate cancer. We also recommend that studies separately report results for advanced category (T4 or N1 or M1), high-grade (Gleason score ≥8), and fatal prostate cancer. Use of this comprehensive set of endpoints will facilitate comparison of results from different studies and help elucidate prostate cancer etiology.

The effect of sample size on polygenic hazard models for prostate cancer.

We determined the effect of sample size on performance of polygenic hazard score (PHS) models in prostate cancer. Age and genotypes were obtained for 40,861 men from the PRACTICAL consortium. The dataset included 201,590 SNPs per subject, and was split into training and testing sets. Established-SNP models considered 65 SNPs that had been previously associated with prostate cancer. Discovery-SNP models used stepwise selection to identify new SNPs. The performance of each PHS model was calculated for random sizes of the training set. The performance of a representative Established-SNP model was estimated for random sizes of the testing set. Mean HR98/50 (hazard ratio of top 2% to average in test set) of the Established-SNP model increased from 1.73 [95% CI: 1.69-1.77] to 2.41 [2.40-2.43] when the number of training samples was increased from 1 thousand to 30 thousand. Corresponding HR98/50 of the Discovery-SNP model increased from 1.05 [0.93-1.18] to 2.19 [2.16-2.23]. HR98/50 of a representative Established-SNP model using testing set sample sizes of 0.6 thousand and 6 thousand observations were 1.78 [1.70-1.85] and 1.73 [1.71-1.76], respectively. We estimate that a study population of 20 thousand men is required to develop Discovery-SNP PHS models while 10 thousand men should be sufficient for Established-SNP models.

Clinical phenotype and mortality in patients with idiopathic small bowel villous atrophy: a dual-centre international study.

OBJECTIVE: Causes of small-bowel villous atrophy (VA) include coeliac disease (CD), its complications and other rare non-coeliac enteropathies. However, forms of VA of unknown aetiology may also exist. We defined them as idiopathic VA (IVA). To retrospectively classify the largest cohort of IVA patients and compare their natural history with CD. METHODS: Notes of 76 IVA patients attending two tertiary centres between January 2000 and March 2019 were retrospectively reviewed. CD, its complications and all the known causes of VA were excluded in all of them. Persistence of VA during follow-up and lymphoproliferative features were used to retrospectively classify IVA, as follows. Group 1: IVA with spontaneous histological recovery (50 patients). Group 2: persistent IVA without lymphoproliferative features (14 patients). Group 3: persistent IVA with lymphoproliferative features (12 patients). Survival was compared between IVA groups and 1114 coeliac patients. HLA was compared between IVA patients, coeliac patients and appropriate controls. RESULTS: Five-year survival was 96% in IVA group 1, 100% in IVA group 2, 27% in IVA group 3 and 97% in CD. On a multivariate analysis hypoalbuminemia (P = 0.002) and age at diagnosis (P = 0.04) predicted mortality in IVA. Group 2 showed association with HLA DQB1*0301 and DQB1*06. CONCLUSION: IVA consists of three groups of enteropathies with distinct clinical phenotypes and prognoses. Mortality in IVA is higher than in CD and mainly due to lymphoproliferative conditions necessitating more aggressive therapies.

Red meat, poultry and fish consumption and risk of diabetes: a 9 year prospective cohort study of the China Kadoorie Biobank.

AIMS/HYPOTHESIS: Previous evidence linking red meat consumption with diabetes risk mainly came from western countries, with little evidence from China, where patterns of meat consumption are different. Moreover, global evidence remains inconclusive about the associations of poultry and fish consumption with diabetes. Therefore we investigated the associations of red meat, poultry and fish intake with incidence of diabetes in a Chinese population. METHODS: The prospective China Kadoorie Biobank recruited ~512,000 adults (59% women, mean age 51 years) from ten rural and urban areas across China in 2004-2008. At the baseline survey, a validated interviewer-administered laptop-based questionnaire was used to collect information on the consumption frequency of major food groups including red meat, poultry, fish, fresh fruit and several others. During ~9 years of follow-up, 14,931 incidences of new-onset diabetes were recorded among 461,036 participants who had no prior diabetes, cardiovascular diseases or cancer at baseline. Cox regression analyses were performed to calculate adjusted HRs for incident diabetes associated with red meat, poultry and fish intake. RESULTS: At baseline, 47.0%, 1.3% and 8.9% of participants reported a regular consumption (i.e. ≥4 days/week) of red meat, poultry and fish, respectively. After adjusting for adiposity and other potential confounders, each 50 g/day increase in red meat and fish intake was associated with 11% (HR 1.11 [95% CI 1.04, 1.20]) and 6% (HR 1.06 [95% CI 1.00, 1.13]) higher risk of incident diabetes, respectively. For both, the associations were more pronounced among men and women from urban areas, with an HR (95% CI) of 1.42 (1.15, 1.74) and 1.18 (1.03, 1.36), respectively, per 50 g/day red meat intake and 1.15 (1.02, 1.30) and 1.11 (1.01, 1.23), respectively, per 50 g/day fish intake. There was no significant association between diabetes and poultry intake, either overall (HR 0.96 [95% CI 0.83, 1.12] per 50 g/day intake) or in specific population subgroups. CONCLUSIONS/INTERPRETATION: In Chinese adults, both red meat and fish, but not poultry, intake were positively associated with diabetes risk, particularly among urban participants. Our findings add new evidence linking red meat and fish intake with cardiometabolic diseases. DATA AVAILABILITY: Details of how to access the China Kadoorie Biobank data and rules of China Kadoorie Biobank data release are available from www.ckbiobank.org/site/Data+Access.

Nutrient-wide association study of 92 foods and nutrients and breast cancer risk.

BACKGROUND: Several dietary factors have been reported to be associated with risk of breast cancer, but to date, unequivocal evidence only exists for alcohol consumption. We sought to systematically assess the association between intake of 92 foods and nutrients and breast cancer risk using a nutrient-wide association study. METHODS: Using data from 272,098 women participating in the European Prospective Investigation into Cancer and Nutrition (EPIC) study, we assessed dietary intake of 92 foods and nutrients estimated by dietary questionnaires. Cox regression was used to quantify the association between each food/nutrient and risk of breast cancer. A false discovery rate (FDR) of 0.05 was used to select the set of foods and nutrients to be replicated in the independent Netherlands Cohort Study (NLCS). RESULTS: Six foods and nutrients were identified as associated with risk of breast cancer in the EPIC study (10,979 cases). Higher intake of alcohol overall was associated with a higher risk of breast cancer (hazard ratio (HR) for a 1 SD increment in intake = 1.05, 95% CI 1.03-1.07), as was beer/cider intake and wine intake (HRs per 1 SD increment = 1.05, 95% CI 1.03-1.06 and 1.04, 95% CI 1.02-1.06, respectively), whereas higher intakes of fibre, apple/pear, and carbohydrates were associated with a lower risk of breast cancer (HRs per 1 SD increment = 0.96, 95% CI 0.94-0.98; 0.96, 95% CI 0.94-0.99; and 0.96, 95% CI 0.95-0.98, respectively). When evaluated in the NLCS (2368 cases), estimates for each of these foods and nutrients were similar in magnitude and direction, with the exception of beer/cider intake, which was not associated with risk in the NLCS. CONCLUSIONS: Our findings confirm a positive association of alcohol consumption and suggest an inverse association of dietary fibre and possibly fruit intake with breast cancer risk.