Publications by authors named "Ruth C Travis"

313 Publications

Prospective analysis of circulating metabolites and endometrial cancer risk.

Gynecol Oncol 2021 Jun 5. Epub 2021 Jun 5.

Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands.

Background: Endometrial cancer is strongly associated with obesity and dysregulation of metabolic factors such as estrogen and insulin signaling are causal risk factors for this malignancy. To identify additional novel metabolic pathways associated with endometrial cancer we performed metabolomic analyses on pre-diagnostic plasma samples from 853 case-control pairs from the European Prospective Investigation into Cancer and Nutrition (EPIC).

Methods: A total of 129 metabolites (acylcarnitines, amino acids, biogenic amines, glycerophospholipids, hexoses, and sphingolipids) were measured by liquid chromatography-mass spectrometry. Conditional logistic regression estimated the associations of metabolites with endometrial cancer risk. An analysis focusing on clusters of metabolites using the bootstrap lasso method was also employed.

Results: After adjustment for body mass index, sphingomyelin [SM] C18:0 was positively (OR: 1.18, 95% CI: 1.05-1.33), and glycine, serine, and free carnitine (C0) were inversely (OR: 0.89, 95% CI: 0.80-0.99; OR: 0.89, 95% CI: 0.79-1.00 and OR: 0.91, 95% CI: 0.81-1.00, respectively) associated with endometrial cancer risk. Serine, C0 and two sphingomyelins were selected by the lasso method in >90% of the bootstrap samples. The ratio of esterified to free carnitine (OR: 1.14, 95% CI: 1.02-1.28) and that of short chain to free acylcarnitines (OR: 1.12, 95% CI: 1.00-1.25) were positively associated with endometrial cancer risk. Further adjustment for C-peptide or other endometrial cancer risk factors only minimally altered the results.

Conclusion: These findings suggest that variation in levels of glycine, serine, SM C18:0 and free carnitine may represent specific pathways linked to endometrial cancer development. If causal, these pathways may offer novel targets for endometrial cancer prevention.
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http://dx.doi.org/10.1016/j.ygyno.2021.06.001DOI Listing
June 2021

KLK3 SNP-SNP interactions for prediction of prostate cancer aggressiveness.

Sci Rep 2021 Apr 29;11(1):9264. Epub 2021 Apr 29.

Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California/Norris Comprehensive Cancer Center, Los Angeles, CA, 90015, USA.

Risk classification for prostate cancer (PCa) aggressiveness and underlying mechanisms remain inadequate. Interactions between single nucleotide polymorphisms (SNPs) may provide a solution to fill these gaps. To identify SNP-SNP interactions in the four pathways (the angiogenesis-, mitochondria-, miRNA-, and androgen metabolism-related pathways) associated with PCa aggressiveness, we tested 8587 SNPs for 20,729 cases from the PCa consortium. We identified 3 KLK3 SNPs, and 1083 (P < 3.5 × 10) and 3145 (P < 1 × 10) SNP-SNP interaction pairs significantly associated with PCa aggressiveness. These SNP pairs associated with PCa aggressiveness were more significant than each of their constituent SNP individual effects. The majority (98.6%) of the 3145 pairs involved KLK3. The 3 most common gene-gene interactions were KLK3-COL4A1:COL4A2, KLK3-CDH13, and KLK3-TGFBR3. Predictions from the SNP interaction-based polygenic risk score based on 24 SNP pairs are promising. The prevalence of PCa aggressiveness was 49.8%, 21.9%, and 7.0% for the PCa cases from our cohort with the top 1%, middle 50%, and bottom 1% risk profiles. Potential biological functions of the identified KLK3 SNP-SNP interactions were supported by gene expression and protein-protein interaction results. Our findings suggest KLK3 SNP interactions may play an important role in PCa aggressiveness.
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http://dx.doi.org/10.1038/s41598-021-85169-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8084951PMC
April 2021

Metabolic signatures of greater body size and their associations with risk of colorectal and endometrial cancers in the European Prospective Investigation into Cancer and Nutrition.

BMC Med 2021 Apr 30;19(1):101. Epub 2021 Apr 30.

International Agency for Research on Cancer, World Health Organization, Lyon, France.

Background: The mechanisms underlying the obesity-cancer relationship are incompletely understood. This study aimed to characterise metabolic signatures of greater body size and to investigate their association with two obesity-related malignancies, endometrial and colorectal cancers, and with weight loss within the context of an intervention study.

Methods: Targeted mass spectrometry metabolomics data from 4326 participants enrolled in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort and 17 individuals from a single-arm pilot weight loss intervention (Intercept) were used in this analysis. Metabolic signatures of body size were first determined in discovery (N = 3029) and replication (N = 1297) sets among EPIC participants by testing the associations between 129 metabolites and body mass index (BMI), waist circumference (WC), and waist-to-hip ratio (WHR) using linear regression models followed by partial least squares analyses. Conditional logistic regression models assessed the associations between the metabolic signatures with endometrial (N = 635 cases and 648 controls) and colorectal (N = 423 cases and 423 controls) cancer risk using nested case-control studies in EPIC. Pearson correlation between changes in the metabolic signatures and weight loss was tested among Intercept participants.

Results: After adjustment for multiple comparisons, greater BMI, WC, and WHR were associated with higher levels of valine, isoleucine, glutamate, PC aa C38:3, and PC aa C38:4 and with lower levels of asparagine, glutamine, glycine, serine, lysoPC C17:0, lysoPC C18:1, lysoPC C18:2, PC aa C42:0, PC ae C34:3, PC ae C40:5, and PC ae C42:5. The metabolic signature of BMI (OR 1.50, 95% CI 1.30-1.74), WC (OR 1.46, 95% CI 1.27-1.69), and WHR (OR 1.54, 95% CI 1.33-1.79) were each associated with endometrial cancer risk. Risk of colorectal cancer was positively associated with the metabolic signature of WHR (OR: 1.26, 95% CI 1.07-1.49). In the Intercept study, a positive correlation was observed between weight loss and changes in the metabolic signatures of BMI (r = 0.5, 95% CI 0.06-0.94, p = 0.03), WC (r = 0.5, 95% CI 0.05-0.94, p = 0.03), and WHR (r = 0.6, 95% CI 0.32-0.87, p = 0.01).

Conclusions: Obesity is associated with a distinct metabolic signature comprising changes in levels of specific amino acids and lipids which is positively associated with both colorectal and endometrial cancer and is potentially reversible following weight loss.
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http://dx.doi.org/10.1186/s12916-021-01970-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8086283PMC
April 2021

Association of Pre-diagnostic Antibody Responses to Escherichia coli and Bacteroides fragilis Toxin Proteins with Colorectal Cancer in a European Cohort.

Gut Microbes 2021 Jan-Dec;13(1):1-14

Department of Medical Biosciences, Pathology, Umeå University, Ireland.

Experimental evidence has implicated genotoxic () and enterotoxigenic (ETBF) in the development of colorectal cancer (CRC). However, evidence from epidemiological studies is sparse. We therefore assessed the association of serological markers of and ETBF exposure with odds of developing CRC in the European Prospective Investigation into Nutrition and Cancer (EPIC) study.Serum samples of incident CRC cases and matched controls (n = 442 pairs) were analyzed for immunoglobulin (Ig) A and G antibody responses to seven proteins and two isoforms of the ETBF toxin via multiplex serology. Multivariable-adjusted conditional logistic regression analyses were used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for the association of sero-positivity to and ETBF with CRC.The IgA-positivity of any of the tested antigens was associated with higher odds of developing CRC (OR: 1.42; 95% CI: 1.05-1.91). Dual-positivity for both IgA and IgG to and ETBF was associated with >1.7-fold higher odds of developing CRC, with a significant association only for IgG (OR: 1.75; 95% CI: 1.04, 2.94). This association was more pronounced when restricted to the proximal colon cancers (OR: 2.62; 95% CI: 1.09, 6.29) compared to those of the distal colon (OR: 1.24; 95% CI: 0.51, 3.00) (= 0.095). Sero-positivity to and ETBF was associated with CRC development, suggesting that co-infection of these bacterial species may contribute to colorectal carcinogenesis. These findings warrant further exploration in larger prospective studies and within different population groups.
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http://dx.doi.org/10.1080/19490976.2021.1903825DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8078709PMC
April 2021

Comparative performance of lung cancer risk models to define lung screening eligibility in the United Kingdom.

Br J Cancer 2021 Jun 12;124(12):2026-2034. Epub 2021 Apr 12.

International Agency for Research on Cancer, Lyon, France.

Background: The National Health Service England (NHS) classifies individuals as eligible for lung cancer screening using two risk prediction models, PLCOm2012 and Liverpool Lung Project-v2 (LLPv2). However, no study has compared the performance of lung cancer risk models in the UK.

Methods: We analysed current and former smokers aged 40-80 years in the UK Biobank (N = 217,199), EPIC-UK (N = 30,813), and Generations Study (N = 25,777). We quantified model calibration (ratio of expected to observed cases, E/O) and discrimination (AUC).

Results: Risk discrimination in UK Biobank was best for the Lung Cancer Death Risk Assessment Tool (LCDRAT, AUC = 0.82, 95% CI = 0.81-0.84), followed by the LCRAT (AUC = 0.81, 95% CI = 0.79-0.82) and the Bach model (AUC = 0.80, 95% CI = 0.79-0.81). Results were similar in EPIC-UK and the Generations Study. All models overestimated risk in all cohorts, with E/O in UK Biobank ranging from 1.20 for LLPv3 (95% CI = 1.14-1.27) to 2.16 for LLPv2 (95% CI = 2.05-2.28). Overestimation increased with area-level socioeconomic status. In the combined cohorts, USPSTF 2013 criteria classified 50.7% of future cases as screening eligible. The LCDRAT and LCRAT identified 60.9%, followed by PLCOm2012 (58.3%), Bach (58.0%), LLPv3 (56.6%), and LLPv2 (53.7%).

Conclusion: In UK cohorts, the ability of risk prediction models to classify future lung cancer cases as eligible for screening was best for LCDRAT/LCRAT, very good for PLCOm2012, and lowest for LLPv2. Our results highlight the importance of validating prediction tools in specific countries.
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http://dx.doi.org/10.1038/s41416-021-01278-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8184952PMC
June 2021

Genetically predicted circulating concentrations of micronutrients and risk of colorectal cancer among individuals of European descent: a Mendelian randomization study.

Am J Clin Nutr 2021 06;113(6):1490-1502

Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.

Background: The literature on associations of circulating concentrations of minerals and vitamins with risk of colorectal cancer is limited and inconsistent. Evidence from randomized controlled trials (RCTs) to support the efficacy of dietary modification or nutrient supplementation for colorectal cancer prevention is also limited.

Objectives: To complement observational and RCT findings, we investigated associations of genetically predicted concentrations of 11 micronutrients (β-carotene, calcium, copper, folate, iron, magnesium, phosphorus, selenium, vitamin B-6, vitamin B-12, and zinc) with colorectal cancer risk using Mendelian randomization (MR).

Methods: Two-sample MR was conducted using 58,221 individuals with colorectal cancer and 67,694 controls from the Genetics and Epidemiology of Colorectal Cancer Consortium, Colorectal Cancer Transdisciplinary Study, and Colon Cancer Family Registry. Inverse variance-weighted MR analyses were performed with sensitivity analyses to assess the impact of potential violations of MR assumptions.

Results: Nominally significant associations were noted for genetically predicted iron concentration and higher risk of colon cancer [ORs per SD (ORSD): 1.08; 95% CI: 1.00, 1.17; P value = 0.05] and similarly for proximal colon cancer, and for vitamin B-12 concentration and higher risk of colorectal cancer (ORSD: 1.12; 95% CI: 1.03, 1.21; P value = 0.01) and similarly for colon cancer. A nominally significant association was also noted for genetically predicted selenium concentration and lower risk of colon cancer (ORSD: 0.98; 95% CI: 0.96, 1.00; P value = 0.05) and similarly for distal colon cancer. These associations were robust to sensitivity analyses. Nominally significant inverse associations were observed for zinc and risk of colorectal and distal colon cancers, but sensitivity analyses could not be performed. None of these findings survived correction for multiple testing. Genetically predicted concentrations of β-carotene, calcium, copper, folate, magnesium, phosphorus, and vitamin B-6 were not associated with disease risk.

Conclusions: These results suggest possible causal associations of circulating iron and vitamin B-12 (positively) and selenium (inversely) with risk of colon cancer.
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http://dx.doi.org/10.1093/ajcn/nqab003DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8168352PMC
June 2021

Prospective analyses of testosterone and sex hormone-binding globulin with the risk of 19 types of cancer in men and postmenopausal women in UK Biobank.

Int J Cancer 2021 Aug 31;149(3):573-584. Epub 2021 Mar 31.

Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.

We investigated the associations of estimated free and total circulating testosterone and sex hormone-binding globulin (SHBG) with cancer risk in men and postmenopausal women, using a pan-cancer approach, including 19 cancers in UK Biobank. Risk was estimated using multivariable-adjusted Cox regression in up to 182 608 men and 122 112 postmenopausal women who were cancer-free at baseline. Participants diagnosed with cancer within 2 years of baseline were excluded. Hazard ratios (HRs) and confidence intervals (CIs) were corrected for regression dilution bias using repeat measurements. We accounted for multiple testing using the false discovery rate. In men, higher free testosterone was associated with higher risks of melanoma and prostate cancer (HR per 50 pmol/L increase = 1.35, 95% CI 1.14-1.61 and 1.10, 1.04-1.18, respectively). Higher total testosterone was associated with an elevated risk of liver cancer (HR per 5 nmol/L = 2.45, 1.56-3.84), and higher SHBG was associated with a higher risk of liver cancer (HR per 10 nmol/L = 1.56, 1.31-1.87) and a lower risk of prostate cancer (0.93, 0.91-0.96); the associations with liver cancer were partially attenuated after excluding men diagnosed within 4.7 years from baseline. In postmenopausal women, free and total testosterone and SHBG were associated with risks of endometrial (HR per 10 pmol/L = 1.59, 1.32-1.90; HR per 0.5 nmol/L = 1.34, 1.18-1.52 and HR per 25 nmol/L = 0.78, 0.67-0.91, respectively) and breast cancer (1.32, 1.22-1.43; 1.24, 1.17-1.31 and 0.88, 0.83-0.94, respectively). We report a novel association of free testosterone with malignant melanoma in men, and confirm known associations between testosterone and risks for prostate, breast and endometrial cancers. The association with liver cancer in men may be attributable to reverse causation.
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http://dx.doi.org/10.1002/ijc.33555DOI Listing
August 2021

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

Metabolites 2021 Feb 20;11(2). Epub 2021 Feb 20.

Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK.

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.
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http://dx.doi.org/10.3390/metabo11020121DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7923783PMC
February 2021

Meat consumption and risk of 25 common conditions: outcome-wide analyses in 475,000 men and women in the UK Biobank study.

BMC Med 2021 03 2;19(1):53. Epub 2021 Mar 2.

Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Richard Doll Building, Old Road Campus, Oxford, OX3 7LF, UK.

Background: There is limited prospective evidence on the association between meat consumption and many common, non-cancerous health outcomes. We examined associations of meat intake with risk of 25 common conditions (other than cancer).

Methods: We used data from 474,985 middle-aged adults recruited into the UK Biobank study between 2006 and 2010 and followed up until 2017 (mean follow-up 8.0 years) with available information on meat intake at baseline (collected via touchscreen questionnaire), and linked hospital admissions and mortality data. For a large sub-sample (~ 69,000), dietary intakes were re-measured three or more times using an online, 24-h recall questionnaire.

Results: On average, participants who reported consuming meat regularly (three or more times per week) had more adverse health behaviours and characteristics than participants who consumed meat less regularly, and most of the positive associations observed for meat consumption and health risks were substantially attenuated after adjustment for body mass index (BMI). In multi-variable adjusted (including BMI) Cox regression models corrected for multiple testing, higher consumption of unprocessed red and processed meat combined was associated with higher risks of ischaemic heart disease (hazard ratio (HRs) per 70 g/day higher intake 1.15, 95% confidence intervals (CIs) 1.07-1.23), pneumonia (1.31, 1.18-1.44), diverticular disease (1.19, 1.11-1.28), colon polyps (1.10, 1.06-1.15), and diabetes (1.30, 1.20-1.42); results were similar for unprocessed red meat and processed meat intakes separately. Higher consumption of unprocessed red meat alone was associated with a lower risk of iron deficiency anaemia (IDA: HR per 50 g/day higher intake 0.80, 95% CIs 0.72-0.90). Higher poultry meat intake was associated with higher risks of gastro-oesophageal reflux disease (HR per 30 g/day higher intake 1.17, 95% CIs 1.09-1.26), gastritis and duodenitis (1.12, 1.05-1.18), diverticular disease (1.10, 1.04-1.17), gallbladder disease (1.11, 1.04-1.19), and diabetes (1.14, 1.07-1.21), and a lower IDA risk (0.83, 0.76-0.90).

Conclusions: Higher unprocessed red meat, processed meat, and poultry meat consumption was associated with higher risks of several common conditions; higher BMI accounted for a substantial proportion of these increased risks suggesting that residual confounding or mediation by adiposity might account for some of these remaining associations. Higher unprocessed red meat and poultry meat consumption was associated with lower IDA risk.
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http://dx.doi.org/10.1186/s12916-021-01922-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7923515PMC
March 2021

Polygenic hazard score is associated with prostate cancer in multi-ethnic populations.

Nat Commun 2021 02 23;12(1):1236. Epub 2021 Feb 23.

Division of Cancer Sciences, University of Manchester, Manchester Academic Health Science Centre, Radiotherapy Related Research, The Christie Hospital NHS Foundation Trust, Manchester, UK.

Genetic models for cancer have been evaluated using almost exclusively European data, which could exacerbate health disparities. A polygenic hazard score (PHS) is associated with age at prostate cancer diagnosis and improves screening accuracy in Europeans. Here, we evaluate performance of PHS (PHS, adapted for OncoArray) in a multi-ethnic dataset of 80,491 men (49,916 cases, 30,575 controls). PHS is associated with age at diagnosis of any and aggressive (Gleason score ≥ 7, stage T3-T4, PSA ≥ 10 ng/mL, or nodal/distant metastasis) cancer and prostate-cancer-specific death. Associations with cancer are significant within European (n = 71,856), Asian (n = 2,382), and African (n = 6,253) genetic ancestries (p < 10). Comparing the 80/20 PHS percentiles, hazard ratios for prostate cancer, aggressive cancer, and prostate-cancer-specific death are 5.32, 5.88, and 5.68, respectively. Within European, Asian, and African ancestries, hazard ratios for prostate cancer are: 5.54, 4.49, and 2.54, respectively. PHS risk-stratifies men for any, aggressive, and fatal prostate cancer in a multi-ethnic dataset.
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http://dx.doi.org/10.1038/s41467-021-21287-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7902617PMC
February 2021

Additional SNPs improve risk stratification of a polygenic hazard score for prostate cancer.

Prostate Cancer Prostatic Dis 2021 Jun 8;24(2):532-541. Epub 2021 Jan 8.

Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, 02115, USA.

Background: Polygenic hazard scores (PHS) can identify individuals with increased risk of prostate cancer. We estimated the benefit of additional SNPs on performance of a previously validated PHS (PHS46).

Materials And Method: 180 SNPs, shown to be previously associated with prostate cancer, were used to develop a PHS model in men with European ancestry. A machine-learning approach, LASSO-regularized Cox regression, was used to select SNPs and to estimate their coefficients in the training set (75,596 men). Performance of the resulting model was evaluated in the testing/validation set (6,411 men) with two metrics: (1) hazard ratios (HRs) and (2) positive predictive value (PPV) of prostate-specific antigen (PSA) testing. HRs were estimated between individuals with PHS in the top 5% to those in the middle 40% (HR95/50), top 20% to bottom 20% (HR80/20), and bottom 20% to middle 40% (HR20/50). PPV was calculated for the top 20% (PPV80) and top 5% (PPV95) of PHS as the fraction of individuals with elevated PSA that were diagnosed with clinically significant prostate cancer on biopsy.

Results: 166 SNPs had non-zero coefficients in the Cox model (PHS166). All HR metrics showed significant improvements for PHS166 compared to PHS46: HR95/50 increased from 3.72 to 5.09, HR80/20 increased from 6.12 to 9.45, and HR20/50 decreased from 0.41 to 0.34. By contrast, no significant differences were observed in PPV of PSA testing for clinically significant prostate cancer.

Conclusions: Incorporating 120 additional SNPs (PHS166 vs PHS46) significantly improved HRs for prostate cancer, while PPV of PSA testing remained the same.
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http://dx.doi.org/10.1038/s41391-020-00311-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8157993PMC
June 2021

Metabolic syndrome biomarkers and prostate cancer risk in the UK Biobank.

Int J Cancer 2021 Feb 11;148(4):825-834. Epub 2020 Sep 11.

Translational Oncology and Urology Research (TOUR), School of Cancer and Pharmaceutical Sciences, King's College London, London, UK.

We investigated the association between metabolic syndrome (MetS) and its components and risk of prostate cancer (PCa) in a cohort of men enrolled in the UK Biobank. Our study cohort included 220 622 PCa-free men with baseline measurements of triglycerides (TGs), HDL-cholesterol (HDL), glycated hemoglobin (HbA1c), blood pressure (BP), and waist circumference (WC). Multivariable Cox proportional hazards regression was used to analyze associations with PCa for: individual metabolic components (TG, HDL, HbA1c, BP, WC), combinations of two and three components, and MetS overall (three or more components). We conducted mediation analyses to examine potential hormonal and inflammatory pathways (total testosterone [TT], C-reactive protein [CRP], insulin-like growth factor 1 [IGF-1]) through which MetS components may influence PCa risk. A total of 5409 men in the study developed PCa during a median follow-up of 6.9 years. We found no significant association between MetS and PCa risk (hazard ratio [HR] = 0.99, 95% confidence interval [CI] = 0.92-1.06). No associations were found with PCa risk and individual measurements of TG, HDL, BP, or WC. However, an inverse association was observed with elevated HbA1c (≥42 mmol/mol) (HR = 0.89, 95% CI = 0.79-0.98). Consistent inverse associations were observed between HbA1c and risk of PCa. Mediation analysis revealed TT, CRP, and IGF-1 as potential mediating factors for this association contributing 10.2%, 7.1%, and 7.9% to the total effect, respectively. Overall MetS had no association with PCa risk. However, a consistent inverse association with PCa risk was found for HbA1c. This association may be explained in part through hormonal and inflammatory pathways.
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http://dx.doi.org/10.1002/ijc.33255DOI Listing
February 2021

Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction.

Nat Genet 2021 01 4;53(1):65-75. Epub 2021 Jan 4.

Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia.

Prostate cancer is a highly heritable disease with large disparities in incidence rates across ancestry populations. We conducted a multiancestry meta-analysis of prostate cancer genome-wide association studies (107,247 cases and 127,006 controls) and identified 86 new genetic risk variants independently associated with prostate cancer risk, bringing the total to 269 known risk variants. The top genetic risk score (GRS) decile was associated with odds ratios that ranged from 5.06 (95% confidence interval (CI), 4.84-5.29) for men of European ancestry to 3.74 (95% CI, 3.36-4.17) for men of African ancestry. Men of African ancestry were estimated to have a mean GRS that was 2.18-times higher (95% CI, 2.14-2.22), and men of East Asian ancestry 0.73-times lower (95% CI, 0.71-0.76), than men of European ancestry. These findings support the role of germline variation contributing to population differences in prostate cancer risk, with the GRS offering an approach for personalized risk prediction.
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http://dx.doi.org/10.1038/s41588-020-00748-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8148035PMC
January 2021

Risk Prediction for Renal Cell Carcinoma: Results from the European Prospective Investigation into Cancer and Nutrition (EPIC) Prospective Cohort Study.

Cancer Epidemiol Biomarkers Prev 2021 Mar 17;30(3):507-512. Epub 2020 Dec 17.

School of Public Health, Imperial College London, London, United Kingdom.

Background: Early detection of renal cell carcinoma (RCC) has the potential to improve disease outcomes. No screening program for sporadic RCC is in place. Given relatively low incidence, screening would need to focus on people at high risk of clinically meaningful disease so as to limit overdiagnosis and screen-detected false positives.

Methods: Among 192,172 participants from the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort (including 588 incident RCC cases), we evaluated a published RCC risk prediction model (including age, sex, BMI, and smoking status) in terms of discrimination (C-statistic) and calibration (observed probability as a function of predicted probability). We used a flexible parametric survival model to develop an expanded model including age, sex, BMI, and smoking status, with the addition of self-reported history of hypertension and measured blood pressure.

Results: The previously published model yielded well-calibrated probabilities and good discrimination (C-statistic [95% CI]: 0.699 [0.679-0.721]). Our model had slightly improved discrimination (0.714 [0.694-0.735], bootstrap optimism-corrected C-statistic: 0.709). Despite this good performance, predicted risk was low for the vast majority of participants, with 70% of participants having 10-year risk less than 0.0025.

Conclusions: Although the models performed well for the prediction of incident RCC, they are currently insufficiently powerful to identify individuals at substantial risk of RCC in a general population.

Impact: Despite the promising performance of the EPIC RCC risk prediction model, further development of the model, possibly including biomarkers of risk, is required to enable risk stratification of RCC.
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http://dx.doi.org/10.1158/1055-9965.EPI-20-1438DOI Listing
March 2021

Circulating insulin-like growth factor-I, total and free testosterone concentrations and prostate cancer risk in 200 000 men in UK Biobank.

Int J Cancer 2021 May 11;148(9):2274-2288. Epub 2020 Dec 11.

Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.

Insulin-like growth factor-I (IGF-I) and testosterone have been implicated in prostate cancer aetiology. Using data from a large prospective full-cohort with standardised assays and repeat blood measurements, and genetic data from an international consortium, we investigated the associations of circulating IGF-I, sex hormone-binding globulin (SHBG), and total and calculated free testosterone concentrations with prostate cancer incidence and mortality. For prospective analyses, risk was estimated using multivariable-adjusted Cox regression in 199 698 male UK Biobank participants. Hazard ratios (HRs) were corrected for regression dilution bias using repeat hormone measurements from a subsample. Two-sample Mendelian randomisation (MR) analysis of IGF-I and risk used genetic instruments identified from UK Biobank men and genetic outcome data from the PRACTICAL consortium (79 148 cases and 61 106 controls). We used cis- and all (cis and trans) SNP MR approaches. A total of 5402 men were diagnosed with and 295 died from prostate cancer (mean follow-up 6.9 years). Higher circulating IGF-I was associated with elevated prostate cancer diagnosis (HR per 5 nmol/L increment = 1.09, 95% CI 1.05-1.12) and mortality (HR per 5 nmol/L increment = 1.15, 1.02-1.29). MR analyses also supported the role of IGF-I in prostate cancer diagnosis (cis-MR odds ratio per 5 nmol/L increment = 1.34, 1.07-1.68). In observational analyses, higher free testosterone was associated with a higher risk of prostate cancer (HR per 50 pmol/L increment = 1.10, 1.05-1.15). Higher SHBG was associated with a lower risk (HR per 10 nmol/L increment = 0.95, 0.94-0.97), neither was associated with prostate cancer mortality. Total testosterone was not associated with prostate cancer. These findings implicate IGF-I and free testosterone in prostate cancer development and/or progression.
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http://dx.doi.org/10.1002/ijc.33416DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8048461PMC
May 2021

Vegetarian and vegan diets and risks of total and site-specific fractures: results from the prospective EPIC-Oxford study.

BMC Med 2020 11 23;18(1):353. Epub 2020 Nov 23.

Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Richard Doll Building, Old Road Campus, Oxford, OX3 7LF, UK.

Background: There is limited prospective evidence on possible differences in fracture risks between vegetarians, vegans, and non-vegetarians. We aimed to study this in a prospective cohort with a large proportion of non-meat eaters.

Methods: In EPIC-Oxford, dietary information was collected at baseline (1993-2001) and at follow-up (≈ 2010). Participants were categorised into four diet groups at both time points (with 29,380 meat eaters, 8037 fish eaters, 15,499 vegetarians, and 1982 vegans at baseline in analyses of total fractures). Outcomes were identified through linkage to hospital records or death certificates until mid-2016. Using multivariable Cox regression, we estimated the risks of total (n = 3941) and site-specific fractures (arm, n = 566; wrist, n = 889; hip, n = 945; leg, n = 366; ankle, n = 520; other main sites, i.e. clavicle, rib, and vertebra, n = 467) by diet group over an average of 17.6 years of follow-up.

Results: Compared with meat eaters and after adjustment for socio-economic factors, lifestyle confounders, and body mass index (BMI), the risks of hip fracture were higher in fish eaters (hazard ratio 1.26; 95% CI 1.02-1.54), vegetarians (1.25; 1.04-1.50), and vegans (2.31; 1.66-3.22), equivalent to rate differences of 2.9 (0.6-5.7), 2.9 (0.9-5.2), and 14.9 (7.9-24.5) more cases for every 1000 people over 10 years, respectively. The vegans also had higher risks of total (1.43; 1.20-1.70), leg (2.05; 1.23-3.41), and other main site fractures (1.59; 1.02-2.50) than meat eaters. Overall, the significant associations appeared to be stronger without adjustment for BMI and were slightly attenuated but remained significant with additional adjustment for dietary calcium and/or total protein. No significant differences were observed in risks of wrist or ankle fractures by diet group with or without BMI adjustment, nor for arm fractures after BMI adjustment.

Conclusions: Non-meat eaters, especially vegans, had higher risks of either total or some site-specific fractures, particularly hip fractures. This is the first prospective study of diet group with both total and multiple specific fracture sites in vegetarians and vegans, and the findings suggest that bone health in vegans requires further research.
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http://dx.doi.org/10.1186/s12916-020-01815-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7682057PMC
November 2020

The Variant C.349A>G Is Associated with Prostate Cancer Risk and Carriers Share a Common Ancestor.

Cancers (Basel) 2020 Nov 4;12(11). Epub 2020 Nov 4.

Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark.

The identification of recurrent founder variants in cancer predisposing genes may have important implications for implementing cost-effective targeted genetic screening strategies. In this study, we evaluated the prevalence and relative risk of the recurrent variant c.349A>G in a series of 462 Portuguese patients with early-onset and/or familial/hereditary prostate cancer (PrCa), as well as in the large multicentre PRACTICAL case-control study comprising 55,162 prostate cancer cases and 36,147 controls. Additionally, we investigated the potential shared ancestry of the carriers by performing identity-by-descent, haplotype and age estimation analyses using high-density SNP data from 70 variant carriers belonging to 11 different populations included in the PRACTICAL consortium. The missense variant c.349A>G was found significantly associated with an increased risk for PrCa (OR 1.9; 95% CI: 1.1-3.2). A shared haplotype flanking the variant in all carriers was identified, strongly suggesting a common founder of European origin. Additionally, using two independent statistical algorithms, implemented by DMLE+2.3 and ESTIAGE, we were able to estimate the age of the variant between 2300 and 3125 years. By extending the haplotype analysis to 14 additional carrier families, a shared core haplotype was revealed among all carriers matching the conserved region previously identified in the high-density SNP analysis. These findings are consistent with c.349A>G being a founder variant associated with increased PrCa risk, suggesting its potential usefulness for cost-effective targeted genetic screening in PrCa families.
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http://dx.doi.org/10.3390/cancers12113254DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7694218PMC
November 2020

Urinary Melatonin in Relation to Breast Cancer Risk: Nested Case-Control Analysis in the DOM Study and Meta-analysis of Prospective Studies.

Cancer Epidemiol Biomarkers Prev 2021 01 3;30(1):97-103. Epub 2020 Nov 3.

Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, England, United Kingdom.

Background: Exposure to higher levels of melatonin may be associated with lower breast cancer risk, but epidemiologic evidence has been limited. We examined the relationship in a case-control study nested within the Diagnostisch Onderzoek Mammacarcinoom (DOM) study and conducted a meta-analysis of prospective studies.

Methods: Concentrations of 6-sulfatoxymelatonin (aMT6s) in prediagnostic first morning urine voids were measured in 274 postmenopausal women diagnosed with breast cancer and 274 matched controls from the DOM study. Conditional logistic regression models were used to estimate multivariable adjusted ORs of breast cancer for thirds of aMT6s. Meta-analysis of this and previous prospective studies of urinary melatonin with breast cancer risk estimated the inverse-variance weighted averages of study-specific log RRs of breast cancer for the highest versus lowest levels of aMT6s.

Results: In the DOM study, the ORs of breast cancer for the middle and highest versus lowest thirds of aMT6s were 0.70 [95% confidence interval (CI), 0.45-1.09] and 0.72 (95% CI, 0.44-1.19), respectively. In the meta-analysis of the DOM study with six previous studies (2,296 cases), RR of breast cancer for the highest versus lowest levels of aMT6s was 0.87 (95% CI, 0.76-1.01).

Conclusions: Results from the DOM study, together with the published prospective data, do not support a strong association of melatonin with breast cancer risk.

Impact: This study adds to the relatively scarce prospective data on melatonin in relation to breast cancer risk. The totality of the prospective evidence does not clearly show an association between melatonin and breast cancer risk, but further data are needed to be able to exclude a modest association.
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http://dx.doi.org/10.1158/1055-9965.EPI-20-0822DOI Listing
January 2021

Blood Metal Levels and Amyotrophic Lateral Sclerosis Risk: A Prospective Cohort.

Ann Neurol 2021 01 6;89(1):125-133. Epub 2020 Nov 6.

Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands.

Objective: Metals have been suggested as a risk factor for amyotrophic lateral sclerosis (ALS), but only retrospective studies are available to date. We compared metal levels in prospectively collected blood samples from ALS patients and controls, to explore whether metals are associated with ALS mortality.

Methods: A nested ALS case-control study was conducted within the prospective EPIC (European Prospective Investigation into Cancer and Nutrition) cohort. Cases were identified through death certificates. We analyzed metal levels in erythrocyte samples obtained at recruitment, as a biomarker for metal exposure from any source. Arsenic, cadmium, copper, lead, manganese, mercury, selenium, and zinc concentrations were measured by inductively coupled plasma-mass spectrometry. To estimate ALS risk, we applied conditional logistic regression models.

Results: The study population comprised 107 cases (65% female) and 319 controls matched for age, sex, and study center. Median time between blood collection and ALS death was 8 years (range = 1-15). Comparing the highest with the lowest tertile, cadmium (odds ratio [OR] = 2.04, 95% confidence interval [CI] = 1.08-3.87) and lead (OR = 1.89, 95% CI = 0.97-3.67) concentrations suggest associations with increased ALS risk. Zinc was associated with a decreased risk (OR = 0.50, 95% CI = 0.27-0.94). Associations for cadmium and lead remained when limiting analyses to noncurrent smokers.

Interpretation: This is the first study to compare metal levels before disease onset, minimizing reverse causation. The observed associations suggest that cadmium, lead, and zinc may play a role in ALS etiology. Cadmium and lead possibly act as intermediates on the pathway from smoking to ALS. ANN NEUROL 20209999:n/a-n/a.
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http://dx.doi.org/10.1002/ana.25932DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7756568PMC
January 2021

Recommended Definitions of Aggressive Prostate Cancer for Etiologic Epidemiologic Research.

J Natl Cancer Inst 2021 Jun;113(6):727-734

Behavioral and Epidemiology Research Group, American Cancer Society, Atlanta, GA, USA.

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.
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http://dx.doi.org/10.1093/jnci/djaa154DOI Listing
June 2021

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

Br J Cancer 2020 12 23;123(12):1808-1817. Epub 2020 Sep 23.

Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.

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.
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http://dx.doi.org/10.1038/s41416-020-01081-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7722733PMC
December 2020

Sleep duration and breast cancer incidence: results from the Million Women Study and meta-analysis of published prospective studies.

Sleep 2021 02;44(2)

Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.

Study Objectives: To investigate the association between sleep duration and breast cancer incidence, we examined the association in a large UK prospective study and conducted a meta-analysis of prospective studies.

Methods: In the Million Women Study, usual sleep duration over a 24-h period was collected in 2001 for 713,150 participants without prior cancer, heart problems, stroke, or diabetes (mean age = 60 years). Follow-up for breast cancer was by record linkage to national cancer registry data for 14.3 years on average from the 3-year resurvey. Cox regression models yielded multivariable-adjusted breast cancer relative risks (RR) and 95% confidence intervals (CIs) for sleep duration categories. Published prospective studies of sleep duration and breast cancer risk were included in a meta-analysis, which estimated the inverse-variance weighted average of study-specific log RRs for short and for long versus average duration sleep.

Results: After excluding the first 5 years to minimize reverse causation bias in the Million Women Study, 24,476 women developed breast cancer. Compared with 7-8 h of sleep, the RRs for <6, 6, 9, and >9 h of sleep were 1.01 (95% CI, 0.95-1.07), 0.99 (0.96-1.03), 1.01 (0.96-1.06), and 1.03 (0.95-1.12), respectively. In a meta-analysis of 14 prospective studies plus the Million Women Study, including 65,410 breast cancer cases, neither short (RR < 7 h = 0.99 [0.98-1.01]) nor long (RR > 8 h = 1.01 [0.98-1.04]) versus average duration sleep was associated with breast cancer risk.

Conclusions: The totality of the prospective evidence does not support an association between sleep duration and breast cancer risk.
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http://dx.doi.org/10.1093/sleep/zsaa166DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7879408PMC
February 2021

Meat intake and cancer risk: prospective analyses in UK Biobank.

Int J Epidemiol 2020 10;49(5):1540-1552

Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.

Background: Red and processed meat have been consistently associated with colorectal cancer risk, but evidence for other cancer sites and for poultry intake is limited. We therefore examined associations between total, red and processed meat and poultry intake and incidence for 20 common cancers.

Methods: We analyzed data from 474 996 participants (54% women) in UK Biobank. Participants were aged 37-73 years and cancer-free at baseline (2006-10). Multivariable-adjusted Cox proportional hazards models were used to determine associations between baseline meat intake and cancer incidence. Trends in risk across the baseline categories were calculated, assigning re-measured intakes from a subsample.

Results: During a mean follow-up of 6.9 years, 28 955 participants were diagnosed with malignant cancer. After correction for multiple testing, red and processed meat combined, and processed meat, were each positively associated with colorectal cancer risk [hazard ratio (HR) per 70 g/day higher intake of red and processed meat 1.32, 95% confidence interval 1.14-1.53; HR per 20 g/day higher intake of processed meat 1.18, 1.03-1.31] and red meat was associated with colon cancer risk (HR per 50 g/day higher intake of red meat 1.36, 1.13-1.64). Positive associations of red meat intake with colorectal and prostate cancer, processed meat intake with rectal cancer and poultry intake with cancers of the lymphatic and haematopoietic tissues did not survive multiple testing.

Conclusions: Higher intake of red and processed meat was specifically associated with a higher risk of colorectal cancer; there was little evidence that meat intake was associated with risk of other cancers.
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http://dx.doi.org/10.1093/ije/dyaa142DOI Listing
October 2020

Circulating Insulin-like Growth Factor-I Concentrations and Risk of 30 Cancers: Prospective Analyses in UK Biobank.

Cancer Res 2020 09 24;80(18):4014-4021. Epub 2020 Jul 24.

Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom.

Circulating insulin-like growth factor I (IGF-I) is positively associated with the risks of colorectal, breast, and prostate cancer, but evidence for other less common cancers is limited. In this study, we investigated associations between serum IGF-I concentrations and incidence of less common cancers in the UK Biobank study. To enable comparison of effect estimates, and as positive controls, both common and less common cancer sites (total 30) were included in an outcome-wide analysis. Data from 394,388 cancer-free participants in the UK Biobank study were analyzed. Multivariable adjusted Cox proportional hazards models were used to determine associations between baseline serum IGF-I concentrations and cancer incidence, using repeated IGF-I measurements from up to 14,149 participants to correct for regression dilution bias. Higher IGF-I concentration was associated with increased risks of thyroid cancer [HR per 5 nmol/L higher concentration 1.18; 95% confidence interval (CI), 1.01-1.37] in addition to colorectal (HR, 1.08; 95% CI, 1.03-1.13), breast (HR, 1.11; 95% CI, 1.07-1.15), and prostate cancer (HR, 1.08; 95% CI, 1.05-1.12), and reduced risks of ovarian and liver cancer. Mean follow-up was 6.9 years and the possibility that the observed associations may be influenced by reverse causality bias cannot be excluded. Additional nominally significant associations with malignant melanoma, multiple myeloma, oral cancer, and esophageal squamous cell carcinoma did not survive correction for multiple testing. Studies with longer follow-up and pooled analyses are needed to further assess how broad the role of IGF-I is in cancer development. SIGNIFICANCE: The results from this outcome-wide analysis are consistent with a positive association of IGF-I with cancers at several sites.
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http://dx.doi.org/10.1158/0008-5472.CAN-20-1281DOI Listing
September 2020

A Genetic Risk Score to Personalize Prostate Cancer Screening, Applied to Population Data.

Cancer Epidemiol Biomarkers Prev 2020 09 24;29(9):1731-1738. Epub 2020 Jun 24.

Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota.

Background: A polygenic hazard score (PHS), the weighted sum of 54 SNP genotypes, was previously validated for association with clinically significant prostate cancer and for improved prostate cancer screening accuracy. Here, we assess the potential impact of PHS-informed screening.

Methods: United Kingdom population incidence data (Cancer Research United Kingdom) and data from the Cluster Randomized Trial of PSA Testing for Prostate Cancer were combined to estimate age-specific clinically significant prostate cancer incidence (Gleason score ≥7, stage T3-T4, PSA ≥10, or nodal/distant metastases). Using HRs estimated from the ProtecT prostate cancer trial, age-specific incidence rates were calculated for various PHS risk percentiles. Risk-equivalent age, when someone with a given PHS percentile has prostate cancer risk equivalent to an average 50-year-old man (50-year-standard risk), was derived from PHS and incidence data. Positive predictive value (PPV) of PSA testing for clinically significant prostate cancer was calculated using PHS-adjusted age groups.

Results: The expected age at diagnosis of clinically significant prostate cancer differs by 19 years between the 1st and 99th PHS percentiles: men with PHS in the 1st and 99th percentiles reach the 50-year-standard risk level at ages 60 and 41, respectively. PPV of PSA was higher for men with higher PHS-adjusted age.

Conclusions: PHS provides individualized estimates of risk-equivalent age for clinically significant prostate cancer. Screening initiation could be adjusted by a man's PHS.

Impact: Personalized genetic risk assessments could inform prostate cancer screening decisions.
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http://dx.doi.org/10.1158/1055-9965.EPI-19-1527DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7483627PMC
September 2020

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

Eur J Hum Genet 2020 10 8;28(10):1467-1475. Epub 2020 Jun 8.

Humangenetik Tuebingen, Paul-Ehrlich-Str 23, D-72076, Tuebingen, Germany.

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 HR (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 HR of the Discovery-SNP model increased from 1.05 [0.93-1.18] to 2.19 [2.16-2.23]. HR 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.
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http://dx.doi.org/10.1038/s41431-020-0664-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7608255PMC
October 2020

Hematologic Markers and Prostate Cancer Risk: A Prospective Analysis in UK Biobank.

Cancer Epidemiol Biomarkers Prev 2020 08 26;29(8):1615-1626. Epub 2020 May 26.

Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom.

Background: Risk factors for prostate cancer are not well understood. Red blood cell, platelet, and white blood cell indices may be markers of a range of exposures that might be related to prostate cancer risk. Therefore, we examined the associations of hematologic parameters with prostate cancer risk.

Methods: Complete blood count data from 209,686 male UK Biobank participants who were free from cancer at study baseline were analyzed. Participants were followed up via data linkage. After a mean follow-up of 6.8 years, 5,723 men were diagnosed with prostate cancer and 323 men died from prostate cancer. Multivariable-adjusted Cox regression was used to estimate adjusted HRs and 95% confidence intervals (CI) for prostate cancer incidence and mortality by hematologic parameters, and corrected for regression dilution bias.

Results: Higher red blood cell (HR per 1 SD increase = 1.09, 95% CI, 1.05-1.13) and platelet counts (HR = 1.07, 1.04-1.11) were associated with an increased risk of prostate cancer. Higher mean corpuscular volume (HR = 0.90, 0.87-0.93), mean corpuscular hemoglobin (HR = 0.90, 0.87-0.93), mean corpuscular hemoglobin concentration (HR = 0.87, 0.77-0.97), and mean sphered cell volume (HR = 0.91, 0.87-0.94) were associated with a lower prostate cancer risk. Higher white blood cell (HR = 1.14, 1.05-1.24) and neutrophil count (HR = 1.27, 1.09-1.48) were associated with prostate cancer mortality.

Conclusions: These associations of blood indices of prostate cancer risk and mortality may implicate shared common causes, including testosterone, nutrition, and inflammation/infection among several others in prostate cancer development and/or progression.

Impact: These associations provide insights into prostate cancer development and progression.
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http://dx.doi.org/10.1158/1055-9965.EPI-19-1525DOI Listing
August 2020

Genetically Determined Height and Risk of Non-hodgkin Lymphoma.

Front Oncol 2019 28;9:1539. Epub 2020 Jan 28.

Interdisciplinary Department of Medicine, University of Bari, Bari, Italy.

Although the evidence is not consistent, epidemiologic studies have suggested that taller adult height may be associated with an increased risk of some non-Hodgkin lymphoma (NHL) subtypes. Height is largely determined by genetic factors, but how these genetic factors may contribute to NHL risk is unknown. We investigated the relationship between genetic determinants of height and NHL risk using data from eight genome-wide association studies (GWAS) comprising 10,629 NHL cases, including 3,857 diffuse large B-cell lymphoma (DLBCL), 2,847 follicular lymphoma (FL), 3,100 chronic lymphocytic leukemia (CLL), and 825 marginal zone lymphoma (MZL) cases, and 9,505 controls of European ancestry. We evaluated genetically predicted height by constructing polygenic risk scores using 833 height-associated SNPs. We used logistic regression to estimate odds ratios (OR) and 95% confidence intervals (CI) for association between genetically determined height and the risk of four NHL subtypes in each GWAS and then used fixed-effect meta-analysis to combine subtype results across studies. We found suggestive evidence between taller genetically determined height and increased CLL risk (OR = 1.08, 95% CI = 1.00-1.17, = 0.049), which was slightly stronger among women (OR = 1.15, 95% CI: 1.01-1.31, = 0.036). No significant associations were observed with DLBCL, FL, or MZL. Our findings suggest that there may be some shared genetic factors between CLL and height, but other endogenous or environmental factors may underlie reported epidemiologic height associations with other subtypes.
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http://dx.doi.org/10.3389/fonc.2019.01539DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6999122PMC
January 2020