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

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

Patterns in metabolite profile are associated with risk of more aggressive prostate cancer: a prospective study of 3057 matched case‐control sets from EPIC

Metabolomics may reveal novel insights into the etiology of prostate cancer, for which few risk factors are established. We investigated the association between patterns in baseline plasma metabolite profile and subsequent prostate cancer risk, using data from 3,057 matched case-control sets from the European Prospective Investigation into Cancer and Nutrition (EPIC). We measured 119 metabolite concentrations in plasma samples, collected on average 9.4 years before diagnosis, by mass spectrometry (AbsoluteIDQ p180 Kit, Biocrates Life Sciences AG). Metabolite patterns were identified using treelet transform, a statistical method for identification of groups of correlated metabolites. Associations of metabolite patterns with prostate cancer risk (OR1SD ) were estimated by conditional logistic regression. Supplementary analyses were conducted for metabolite patterns derived using principal component analysis and for individual metabolites. Men with metabolite profiles characterized by higher concentrations of either phosphatidylcholines or hydroxysphingomyelins (OR1SD = 0.77, 95% confidence interval 0.66-0.89), acylcarnitines C18:1 and C18:2, glutamate, ornithine and taurine (OR1SD = 0.72, 0.57-0.90), or lysophosphatidylcholines (OR1SD = 0.81, 0.69-0.95) had lower risk of advanced stage prostate cancer at diagnosis, with no evidence of heterogeneity by follow-up time. Similar associations were observed for the two former patterns with aggressive disease risk (the more aggressive subset of advanced stage), while the latter pattern was inversely related to risk of prostate cancer death (OR1SD = 0.77, 0.61-0.96). No associations were observed for prostate cancer overall or less aggressive tumor subtypes. In conclusion, metabolite patterns may be related to lower risk of more aggressive prostate tumors and prostate cancer death, and might be relevant to etiology of advanced stage prostate cancer

Pre-diagnostic metabolite concentrations and prostate cancer risk in 1077 cases and 1077 matched controls in the European Prospective Investigation into Cancer and Nutrition.

BACKGROUND: Little is known about how pre-diagnostic metabolites in blood relate to risk of prostate cancer. We aimed to investigate the prospective association between plasma metabolite concentrations and risk of prostate cancer overall, and by time to diagnosis and tumour characteristics, and risk of death from prostate cancer. METHODS: In a case-control study nested in the European Prospective Investigation into Cancer and Nutrition, pre-diagnostic plasma concentrations of 122 metabolites (including acylcarnitines, amino acids, biogenic amines, glycerophospholipids, hexose and sphingolipids) were measured using targeted mass spectrometry (AbsoluteIDQ p180 Kit) and compared between 1077 prostate cancer cases and 1077 matched controls. Risk of prostate cancer associated with metabolite concentrations was estimated by multi-variable conditional logistic regression, and multiple testing was accounted for by using a false discovery rate controlling procedure. RESULTS: Seven metabolite concentrations, i.e. acylcarnitine C18:1, amino acids citrulline and trans-4-hydroxyproline, glycerophospholipids PC aa C28:1, PC ae C30:0 and PC ae C30:2, and sphingolipid SM (OH) C14:1, were associated with prostate cancer (p < 0.05), but none of the associations were statistically significant after controlling for multiple testing. Citrulline was associated with a decreased risk of prostate cancer (odds ratio (OR1SD) = 0.73; 95% confidence interval (CI) 0.62-0.86; p trend = 0.0002) in the first 5 years of follow-up after taking multiple testing into account, but not after longer follow-up; results for other metabolites did not vary by time to diagnosis. After controlling for multiple testing, 12 glycerophospholipids were inversely associated with advanced stage disease, with risk reduction up to 46% per standard deviation increase in concentration (OR1SD = 0.54; 95% CI 0.40-0.72; p trend = 0.00004 for PC aa C40:3). Death from prostate cancer was associated with higher concentrations of acylcarnitine C3, amino acids methionine and trans-4-hydroxyproline, biogenic amine ADMA, hexose and sphingolipid SM (OH) C14:1 and lower concentration of glycerophospholipid PC aa C42:4. CONCLUSIONS: Several metabolites, i.e. C18:1, citrulline, trans-4-hydroxyproline, three glycerophospholipids and SM (OH) C14:1, might be related to prostate cancer. Analyses by time to diagnosis indicated that citrulline may be a marker of subclinical prostate cancer, while other metabolites might be related to aetiology. Several glycerophospholipids were inversely related to advanced stage disease. More prospective data are needed to confirm these associations

Prospective investigation of risk factors for prostate cancer in the UK Biobank cohort study

Prostate cancer is the most common cancer in British men but its aetiology is not well understood. We aimed to identify risk factors for prostate cancer in British males.We studied 219 335 men from the UK Biobank study who were free from cancer at baseline. Exposure data were collected at recruitment. Prostate cancer risk by the different exposures was estimated using multivariable-adjusted Cox proportional hazards models.In all, 4575 incident cases of prostate cancer occurred during 5.6 years of follow-up. Prostate cancer risk was positively associated with the following: black ethnicity (hazard ratio black vs white=2.61, 95% confidence interval=2.10-3.24); having ever had a prostate-specific antigen test (1.31, 1.23-1.40); being diagnosed with an enlarged prostate (1.54, 1.38-1.71); and having a family history of prostate cancer (1.94, 1.77-2.13). Conversely, Asian ethnicity (Asian vs white hazard ratio=0.62, 0.47-0.83), excess adiposity (body mass index (⩾35 vs &lt;25 kg m-2=0.75, 0.64-0.88) and body fat (⩾30.1 vs &lt;20.5%=0.81, 0.73-0.89)), cigarette smoking (current vs never smokers=0.85, 0.77-0.95), having diabetes (0.70, 0.62-0.80), and never having had children (0.89, 0.81-0.97) or sexual intercourse (0.53, 0.33-0.84) were related to a lower risk.In this new large British prospective study, we identified associations with already-established, putative and possible novel risk factors for being diagnosed with prostate cancer. Future research will examine associations by tumour characteristics

Physical activity and breast cancer risk: results from the UK Biobank prospective cohort

Background Previous studies suggest a protective role of physical activity in breast cancer risk, largely based on self-reported activity. We aimed to clarify this association by examining breast cancer risk in relation to self-reported physical activity, informed by accelerometer-based measures in a large subset of participants. Methods We analysed data from 47,456 premenopausal and 126,704 postmenopausal women in UK Biobank followed from 2006 to 2014. Physical activity was self-reported at baseline, and at resurvey in a subsample of 6443 participants. Accelerometer data, measured from 2013 to 2015, were available in 20,785 women. Relative risks (RRs) and 95% confidence intervals (CIs) were calculated by using multivariable-adjusted Cox regression. Results A total of 3189 cases were diagnosed during follow-up (mean = 5.7 years). Women in the top compared with the bottom quartile of self-reported physical activity had a reduced risk of both premenopausal (RR 0.75; 95% CI 0.60–0.93) and postmenopausal breast cancer (RR 0.87; 95% CI 0.78–0.98), after adjusting for adiposity. In analyses utilising physical activity values assigned from accelerometer measurements, an increase of 5 milli-gravity was associated with a 21% (RR 0.79; 95% CI 0.66–0.95) reduction in premenopausal and a 16% (RR 0.84; 95% CI 0.73–0.96) reduction in postmenopausal breast cancer risk. Conclusions Greater physical activity is associated with a reduction in breast cancer risk, which appears to be independent of any association it may have on risk through its effects on adiposity

NMR Metabolite Profiles in Male Meat-Eaters, Fish-Eaters, Vegetarians and Vegans, and Comparison with MS Metabolite Profiles

Metabolomics may help to elucidate mechanisms underlying diet-disease relationships and identify novel risk factors for disease. To inform the design and interpretation of such research, evidence on diet-metabolite associations and cross-assay comparisons is needed. We aimed to compare nuclear magnetic resonance (NMR) metabolite profiles between meat-eaters, fish-eaters, vegetarians and vegans, and to compare NMR measurements to those from mass spectrometry (MS), clinical chemistry and capillary gas-liquid chromatography (GC). We quantified 207 serum NMR metabolite measures in 286 male participants of the European Prospective Investigation into Cancer and Nutrition (EPIC)-Oxford cohort. Using univariate and multivariate analyses, we found that metabolite profiles varied by diet group, especially for vegans; the main differences compared to meat-eaters were lower levels of docosahexaenoic acid, total n-3 and saturated fatty acids, cholesterol and triglycerides in very-low-density lipoproteins, various lipid factions in high-density lipoprotein, sphingomyelins, tyrosine and creatinine, and higher levels of linoleic acid, total n-6, polyunsaturated fatty acids and alanine. Levels in fish-eaters and vegetarians differed by metabolite measure. Concentrations of 13 metabolites measured using both NMR and MS, clinical chemistry or GC were mostly similar. In summary, vegans’ metabolite profiles were markedly different to those of men consuming animal products. The studied metabolomics platforms are complementary, with limited overlap between metabolite classes

Comparison of Major Protein-Source Foods and Other Food Groups in Meat-Eaters and Non-Meat-Eaters in the EPIC-Oxford Cohort

Differences in health outcomes between meat-eaters and non-meat-eaters might relate to differences in dietary intakes between these diet groups. We assessed intakes of major protein-source foods and other food groups in six groups of meat-eaters and non-meat-eaters participating in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Oxford study. The data were from 30,239 participants who answered questions regarding their consumption of meat, fish, dairy or eggs and completed a food frequency questionnaire (FFQ) in 2010. Participants were categorized as regular meat-eaters, low meat-eaters, poultry-eaters, fish-eaters, vegetarians and vegans. FFQ foods were categorized into 45 food groups and analysis of variance was used to test for differences between age-adjusted mean intakes of each food group by diet group. Regular meat-eaters, vegetarians and vegans, respectively, consumed about a third, quarter and a fifth of their total energy intake from high protein-source foods. Compared with regular meat-eaters, low and non-meat-eaters consumed higher amounts of high-protein meat alternatives (soy, legumes, pulses, nuts, seeds) and other plant-based foods (whole grains, vegetables, fruits) and lower amounts of refined grains, fried foods, alcohol and sugar-sweetened beverages. These findings provide insight into potential nutritional explanations for differences in health outcomes between diet groups