Description of the updated nutrition calculation of the Oxford WebQ questionnaire and comparison with the previous version among 207,144 participants in UK Biobank.

PURPOSE: The Oxford WebQ is a web-based 24-h dietary assessment method which has been used in UK Biobank and other large prospective studies. The food composition table used to calculate nutrient intakes has recently been replaced with the UK Nutrient Databank, which has food composition data closer in time to when participants completed the questionnaire, and new dietary variables were incorporated. Here we describe the updated version of the Oxford WebQ questionnaire nutrient calculation, and compare nutrient intakes with the previous version used. METHODS: 207,144 UK Biobank participants completed ≥ 1 Oxford WebQs, and means and standard deviations of nutrient intakes were averaged for all completed 24-h dietary assessments. Spearman correlations and weighted kappa statistics were used to compare the re-classification and agreement of nutrient intakes between the two versions. RESULTS: 35 new nutrients were incorporated in the updated version. Compared to the previous version, most nutrients were very similar in the updated version except for a few nutrients which showed a difference of > 10%: lower with the new version for trans-fat (- 20%), and vitamin C (- 15%), but higher for retinol (+ 42%), vitamin D (+ 26%) and vitamin E (+ 20%). Most participants were in the same (> 60%) or adjacent (> 90%) quintile of intake for the two versions. Except for trans-fat (r = 0.58, κ = 0.42), very high correlations were found between the nutrients calculated using the two versions (r > 0.79 and κ > 0.60). CONCLUSION: Small absolute differences in nutrient intakes were observed between the two versions, and the ranking of individuals was minimally affected, except for trans-fat

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

Circulating free testosterone and risk of aggressive prostate cancer : Prospective and Mendelian randomisation analyses in international consortia

Publisher Copyright: © 2022 The Authors. International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC.Previous studies had limited power to assess the associations of testosterone with aggressive disease as a primary endpoint. Further, the association of genetically predicted testosterone with aggressive disease is not known. We investigated the associations of calculated free and measured total testosterone and sex hormone-binding globulin (SHBG) with aggressive, overall and early-onset prostate cancer. In blood-based analyses, odds ratios (OR) and 95% confidence intervals (CI) for prostate cancer were estimated using conditional logistic regression from prospective analysis of biomarker concentrations in the Endogenous Hormones, Nutritional Biomarkers and Prostate Cancer Collaborative Group (up to 25 studies, 14 944 cases and 36 752 controls, including 1870 aggressive prostate cancers). In Mendelian randomisation (MR) analyses, using instruments identified using UK Biobank (up to 194 453 men) and outcome data from PRACTICAL (up to 79 148 cases and 61 106 controls, including 15 167 aggressive cancers), ORs were estimated using the inverse-variance weighted method. Free testosterone was associated with aggressive disease in MR analyses (OR per 1 SD = 1.23, 95% CI = 1.08-1.40). In blood-based analyses there was no association with aggressive disease overall, but there was heterogeneity by age at blood collection (OR for men aged <60 years 1.14, CI = 1.02-1.28; Phet =.0003: inverse association for older ages). Associations for free testosterone were positive for overall prostate cancer (MR: 1.20, 1.08-1.34; blood-based: 1.03, 1.01-1.05) and early-onset prostate cancer (MR: 1.37, 1.09-1.73; blood-based: 1.08, 0.98-1.19). SHBG and total testosterone were inversely associated with overall prostate cancer in blood-based analyses, with null associations in MR analysis. Our results support free testosterone, rather than total testosterone, in the development of prostate cancer, including aggressive subgroups.Peer reviewe

The relationship between lipoprotein A and other lipids with prostate cancer risk:A multivariable Mendelian randomisation study

BACKGROUND: Numerous epidemiological studies have investigated the role of blood lipids in prostate cancer (PCa) risk, though findings remain inconclusive to date. The ongoing research has mainly involved observational studies, which are often prone to confounding. This study aimed to identify the relationship between genetically predicted blood lipid concentrations and PCa. METHODS AND FINDINGS: Data for low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides (TG), apolipoprotein A (apoA) and B (apoB), lipoprotein A (Lp(a)), and PCa were acquired from genome-wide association studies in UK Biobank and the PRACTICAL consortium, respectively. We used a two-sample summary-level Mendelian randomisation (MR) approach with both univariable and multivariable (MVMR) models and utilised a variety of robust methods and sensitivity analyses to assess the possibility of MR assumptions violation. No association was observed between genetically predicted concentrations of HDL, TG, apoA and apoB, and PCa risk. Genetically predicted LDL concentration was positively associated with total PCa in the univariable analysis, but adjustment for HDL, TG, and Lp(a) led to a null association. Genetically predicted concentration of Lp(a) was associated with higher total PCa risk in the univariable (OR(weighted median) per standard deviation (SD) = 1.091; 95% CI 1.028 to 1.157; P = 0.004) and MVMR analyses after adjustment for the other lipid traits (OR(IVW) per SD = 1.068; 95% CI 1.005 to 1.134; P = 0.034). Genetically predicted Lp(a) was also associated with advanced (MVMR OR(IVW) per SD = 1.078; 95% CI 0.999 to 1.163; P = 0.055) and early age onset PCa (MVMR OR(IVW) per SD = 1.150; 95% CI 1.015,1.303; P = 0.028). Although multiple estimation methods were utilised to minimise the effect of pleiotropy, the presence of any unmeasured pleiotropy cannot be excluded and may limit our findings. CONCLUSIONS: We observed that genetically predicted Lp(a) concentrations were associated with an increased PCa risk. Future studies are required to understand the underlying biological pathways of this finding, as it may inform PCa prevention through Lp(a)-lowering strategies

DNA hypermethylation of the serotonin receptor type-2A gene is associated with a worse response to a weight loss intervention in subjects with metabolic syndrome

Understanding the regulation of gene activities depending on DNA methylation has been the subject of much recent study. However, although polymorphisms of the HTR2A gene have been associated with both obesity and psychiatric disorders, the role of HTR2A gene methylation in these illnesses remains uncertain. The aim of this study was to evaluate the association of HTR2A gene promoter methylation levels in white blood cells (WBC) with obesity traits and depressive symptoms in individuals with metabolic syndrome (MetS) enrolled in a behavioural weight loss programme. Analyses were based on 41 volunteers (mean age 49 ± 1 year) recruited within the RESMENA study. Depressive symptoms (as determined using the Beck Depression Inventory), anthropometric and biochemical measurements were analysed at the beginning and after six months of weight loss treatment. At baseline, DNA from WBC was isolated and cytosine methylation in the HTR2A gene promoter was quantified by a microarray approach. In the whole-study sample, a positive association of HTR2A gene methylation with waist circumference and insulin levels was detected at baseline. Obesity measures significantly improved after six months of dietary treatment, where a lower mean HTR2A gene methylation at baseline was associated with major reductions in body weight, BMI and fat mass after the treatment. Moreover, mean HTR2A gene methylation at baseline significantly predicted the decrease in depressive symptoms after the weight loss treatment. In conclusion, this study provides newer evidence that hypermethylation of the HTR2A gene in WBC at baseline is significantly associated with a worse response to a weight-loss intervention and with a lower decrease in depressive symptoms after the dietary treatment in subjects with MetS

Examination of potential novel biochemical factors in relation to prostate cancer incidence and mortality in UK Biobank

Background: Although prostate cancer is a leading cause of cancer death, its aetiology is not well understood. We aimed to identify novel biochemical factors for prostate cancer incidence and mortality in UK Biobank. Methods: A range of cardiovascular, bone, joint, diabetes, renal and liver-related biomarkers were measured in baseline blood samples collected from up to 211,754 men at recruitment and in a subsample 5 years later. Participants were followed-up via linkage to health administrative datasets to identify prostate cancer cases. Hazard ratios (HRs) and 95% confidence intervals were calculated using multivariable-adjusted Cox regression corrected for regression dilution bias. Multiple testing was accounted for by using a false discovery rate controlling procedure. Results: After an average follow-up of 6.9 years, 5763 prostate cancer cases and 331 prostate cancer deaths were ascertained. Prostate cancer incidence was positively associated with circulating vitamin D, urea and phosphate concentrations and inversely associated with glucose, total protein and aspartate aminotransferase. Phosphate and cystatin-C were the only biomarkers positively and inversely, respectively, associated with risk in analyses excluding the first 4 years of follow-up. There was little evidence of associations with prostate cancer death. Conclusion: We found novel associations of several biomarkers with prostate cancer incidence. Future research will examine associations by tumour characteristics.</p

Genetic predisposition to metabolically unfavourable adiposity and prostate cancer risk:A Mendelian randomization analysis

BACKGROUND The associations of adiposity with aggressive prostate cancer risk are unclear. Using two-sample Mendelian randomization, we assessed the association of metabolically unfavourable adiposity (UFA), favourable adiposity (FA) and for comparison body mass index (BMI), with prostate cancer, including aggressive prostate cancer. METHODS We examined the association of these genetically predicted adiposity-related traits with risk of prostate cancer overall, aggressive and early onset disease using outcome summary statistics from the PRACTICAL consortium (including 15,167 aggressive cases). RESULTS In inverse-variance weighted models, there was little evidence that genetically predicted one standard deviation higher UFA, FA and BMI were associated with aggressive prostate cancer [OR: 0.85 (95% CI:0.61-1.19), 0.80 (0.53-1.23) and 0.97 (0.88-1.08), respectively]; these associations were largely consistent in sensitivity analyses accounting for horizontal pleiotropy. There was no strong evidence that genetically determined UFA, FA or BMI were associated with overall prostate cancer or early age of onset prostate cancer. CONCLUSIONS We did not find differences in the associations of UFA and FA with prostate cancer risk, which suggest that adiposity is unlikely to influence prostate cancer via the metabolic factors assessed; however, these did not cover some aspects related to metabolic health that may link obesity with aggressive prostate cancer, which should be explored in future studies

Intakes of major food groups in China and UK: results from 100,000 adults in the China Kadoorie biobank and UK biobank

PURPOSE: Different populations may exhibit differences in dietary intakes, which may result in heterogeneities in diet-disease associations. We compared intakes of major food groups overall, by sex, and by socio-economic status (SES) (defined as both education and income), between participants in the China Kadoorie Biobank (CKB) and the UK Biobank (UKB). METHODS: Data were from ~ 25,000 CKB participants who completed a validated interviewer-administered computer-based questionnaire (2013-2014) and ~ 74,000 UKB participants who completed ≥ 3 web-based 24-h dietary assessments (2009-2012). Intakes of 12 major food groups and five beverages were harmonized and compared between the cohorts overall, by sex and by SES. Multivariable-adjusted linear regression examined the associations between dietary intakes and body mass index (BMI) in each cohort. RESULTS: CKB participants reported consuming more rice, eggs, vegetables, soya products, and less wheat, other staple foods (other than rice and wheat), fish, poultry, all dairy products, fruit, and beverages compared to UKB participants. Red meat intake was similar in both cohorts. Having a higher SES was generally associated with a higher consumption of foods and beverages in CKB, whereas in UKB dietary intakes differed more by education and income, with a positive association observed for meat and income in both UKB and CKB but an inverse association observed for education in UKB. Associations of dietary intakes with BMI varied between the two cohorts. CONCLUSION: The large differences in dietary intakes and their associations with SES and BMI could provide insight into the interpretation of potentially different diet-disease associations between CKB and UKB