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Search: WFRF:(Ljungberg Börje 1949 ) > Muller David C.

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1.
  • Clasen, Joanna L., et al. (author)
  • Reproductive and hormonal factors and risk of renal cell carcinoma among women in the european prospective investigation into cancer and nutrition
  • 2023
  • In: Cancer Medicine. - : John Wiley & Sons. - 2045-7634. ; 12:14, s. 15588-15600
  • Journal article (peer-reviewed)abstract
    • Background: Renal cell carcinoma (RCC) is twice as common among men compared with women, and hormonal factors have been suggested to partially explain this difference. There is currently little evidence on the roles of reproductive and hormonal risk factors in RCC aetiology.Materials & Methods: We investigated associations of age at menarche and age at menopause, pregnancy-related factors, hysterectomy and ovariectomy and exogenous hormone use with RCC risk among 298,042 women in the European Prospective Investigation into Cancer and Nutrition (EPIC) study.Results: During 15 years of follow-up, 438 RCC cases were identified. Parous women had higher rates of RCC compared with nulliparous women (HR = 1.71, 95% CI 1.18, 2.46), and women who were older at age of first pregnancy had lower rates of RCC (30 years + vs. <20 years HR = 0.53, 95% CI 0.34, 0.82). Additionally, we identified a positive association for hysterectomy (HR = 1.43 95% CI 1.09, 1.86) and bilateral ovariectomy (HR = 1.67, 95% CI 1.13, 2.47), but not unilateral ovariectomy (HR = 0.99, 95% CI 0.61, 1.62) with RCC risk. No clear associations were found for age at menarche, age at menopause or exogenous hormone use.Conclusion: Our results suggest that parity and reproductive organ surgeries may play a role in RCC aetiology.
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2.
  • Guida, Florence, et al. (author)
  • The blood metabolome of incident kidney cancer: A case-control study nested within the MetKid consortium
  • 2021
  • In: PLoS Medicine. - : Public Library of Science (PLOS). - 1549-1277 .- 1549-1676. ; 18:9
  • Journal article (peer-reviewed)abstract
    • Background: Excess bodyweight and related metabolic perturbations have been implicated in kidney cancer aetiology, but the specific molecular mechanisms underlying these relationships are poorly understood. In this study, we sought to identify circulating metabolites that predispose kidney cancer and to evaluate the extent to which they are influenced by body mass index (BMI).Methods and findings: We assessed the association between circulating levels of 1,416 metabolites and incident kidney cancer using pre-diagnostic blood samples from up to 1,305 kidney cancer case–control pairs from 5 prospective cohort studies. Cases were diagnosed on average 8 years after blood collection. We found 25 metabolites robustly associated with kidney cancer risk. In particular, 14 glycerophospholipids (GPLs) were inversely associated with risk, including 8 phosphatidylcholines (PCs) and 2 plasmalogens. The PC with the strongest association was PC ae C34:3 with an odds ratio (OR) for 1 standard deviation (SD) increment of 0.75 (95% confidence interval [CI]: 0.68 to 0.83, p = 2.6 × 10−8). In contrast, 4 amino acids, including glutamate (OR for 1 SD = 1.39, 95% CI: 1.20 to 1.60, p = 1.6 × 10−5), were positively associated with risk. Adjusting for BMI partly attenuated the risk association for some—but not all—metabolites, whereas other known risk factors of kidney cancer, such as smoking and alcohol consumption, had minimal impact on the observed associations. A mendelian randomisation (MR) analysis of the influence of BMI on the blood metabolome highlighted that some metabolites associated with kidney cancer risk are influenced by BMI. Specifically, elevated BMI appeared to decrease levels of several GPLs that were also found inversely associated with kidney cancer risk (e.g., −0.17 SD change [ßBMI] in 1-(1-enyl-palmitoyl)-2-linoleoyl-GPC (P-16:0/18:2) levels per SD change in BMI, p = 3.4 × 10−5). BMI was also associated with increased levels of glutamate (ßBMI: 0.12, p = 1.5 × 10−3). While our results were robust across the participating studies, they were limited to study participants of European descent, and it will, therefore, be important to evaluate if our findings can be generalised to populations with different genetic backgrounds.Conclusions: This study suggests a potentially important role of the blood metabolome in kidney cancer aetiology by highlighting a wide range of metabolites associated with the risk of developing kidney cancer and the extent to which changes in levels of these metabolites are driven by BMI - the principal modifiable risk factor of kidney cancer.
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3.
  • Heath, Alicia K, et al. (author)
  • Soft Drink and Juice Consumption and Renal Cell Carcinoma Incidence and Mortality in the European Prospective Investigation into Cancer and Nutrition
  • 2021
  • In: Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology. - : American Association for Cancer Research. - 1538-7755 .- 1055-9965. ; 30:6, s. 1270-1274
  • Journal article (peer-reviewed)abstract
    • BACKGROUND: Renal cell carcinoma (RCC) accounts for more than 80% of kidney cancers in adults, and obesity is a known risk factor. Regular consumption of sweetened beverages has been linked to obesity and several chronic diseases, including some types of cancer. It is uncertain whether soft drink and juice consumption is associated with risk of RCC. We investigated the associations of soft drink and juice consumption with RCC incidence and mortality in the European Prospective Investigation into Cancer and Nutrition (EPIC).METHODS: A total of 389,220 EPIC participants with median age of 52 years at recruitment (1991-2000) were included. Cox regression yielded adjusted HRs and 95% confidence intervals (CI) for RCC incidence and mortality in relation to intakes of juices and total, sugar-sweetened, and artificially sweetened soft drinks.RESULTS: A total of 888 incident RCCs and 356 RCC deaths were identified. In models including adjustment for body mass index and energy intake, there was no higher risk of incident RCC associated with consumption of juices (HR per 100 g/day increment = 1.03; 95% CI, 0.97-1.09), total soft drinks (HR = 1.01; 95% CI, 0.98-1.05), sugar-sweetened soft drinks (HR = 0.99; 95% CI, 0.94-1.05), or artificially sweetened soft drinks (HR = 1.02; 95% CI, 0.96-1.08). In these fully adjusted models, none of the beverages was associated with RCC mortality (HR, 95% CI per 100 g/day increment 1.06, 0.97-1.16; 1.03, 0.98-1.09; 0.97, 0.89-1.07; and 1.06, 0.99-1.14, respectively).CONCLUSIONS: Consumption of juices or soft drinks was not associated with RCC incidence or mortality after adjusting for obesity.IMPACT: Soft drink and juice intakes are unlikely to play an independent role in RCC development or mortality.
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4.
  • Johansson, Mattias, et al. (author)
  • The influence of obesity-related factors in the etiology of renal cell carcinoma—A mendelian randomization study
  • 2019
  • In: PLoS Medicine. - : Public Library of Science (PLoS). - 1549-1277 .- 1549-1676. ; 16:1
  • Journal article (peer-reviewed)abstract
    • Background: Several obesity-related factors have been associated with renal cell carcinoma (RCC), but it is unclear which individual factors directly influence risk. We addressed this question using genetic markers as proxies for putative risk factors and evaluated their relation to RCC risk in a mendelian randomization (MR) framework. This methodology limits bias due to confounding and is not affected by reverse causation.Methods and findings: Genetic markers associated with obesity measures, blood pressure, lipids, type 2 diabetes, insulin, and glucose were initially identified as instrumental variables, and their association with RCC risk was subsequently evaluated in a genome-wide association study (GWAS) of 10,784 RCC patients and 20,406 control participants in a 2-sample MR framework. The effect on RCC risk was estimated by calculating odds ratios (ORSD) for a standard deviation (SD) increment in each risk factor. The MR analysis indicated that higher body mass index increases the risk of RCC (ORSD: 1.56, 95% confidence interval [CI] 1.44–1.70), with comparable results for waist-to-hip ratio (ORSD: 1.63, 95% CI 1.40–1.90) and body fat percentage (ORSD: 1.66, 95% CI 1.44–1.90). This analysis further indicated that higher fasting insulin (ORSD: 1.82, 95% CI 1.30–2.55) and diastolic blood pressure (DBP; ORSD: 1.28, 95% CI 1.11–1.47), but not systolic blood pressure (ORSD: 0.98, 95% CI 0.84–1.14), increase the risk for RCC. No association with RCC risk was seen for lipids, overall type 2 diabetes, or fasting glucose.Conclusions: This study provides novel evidence for an etiological role of insulin in RCC, as well as confirmatory evidence that obesity and DBP influence RCC risk.
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5.
  • Laskar, Ruhina S, et al. (author)
  • Sex specific associations in genome wide association analysis of renal cell carcinoma.
  • 2019
  • In: European Journal of Human Genetics. - : Springer Science and Business Media LLC. - 1018-4813 .- 1476-5438. ; 27:10, s. 1589-1598
  • Journal article (peer-reviewed)abstract
    • Renal cell carcinoma (RCC) has an undisputed genetic component and a stable 2:1 male to female sex ratio in its incidence across populations, suggesting possible sexual dimorphism in its genetic susceptibility. We conducted the first sex-specific genome-wide association analysis of RCC for men (3227 cases, 4916 controls) and women (1992 cases, 3095 controls) of European ancestry from two RCC genome-wide scans and replicated the top findings using an additional series of men (2261 cases, 5852 controls) and women (1399 cases, 1575 controls) from two independent cohorts of European origin. Our study confirmed sex-specific associations for two known RCC risk loci at 14q24.2 (DPF3) and 2p21(EPAS1). We also identified two additional suggestive male-specific loci at 6q24.3 (SAMD5, male odds ratio (ORmale) = 0.83 [95% CI = 0.78-0.89], Pmale = 1.71 × 10-8 compared with female odds ratio (ORfemale) = 0.98 [95% CI = 0.90-1.07], Pfemale = 0.68) and 12q23.3 (intergenic, ORmale = 0.75 [95% CI = 0.68-0.83], Pmale = 1.59 × 10-8 compared with ORfemale = 0.93 [95% CI = 0.82-1.06], Pfemale = 0.21) that attained genome-wide significance in the joint meta-analysis. Herein, we provide evidence of sex-specific associations in RCC genetic susceptibility and advocate the necessity of larger genetic and genomic studies to unravel the endogenous causes of sex bias in sexually dimorphic traits and diseases like RCC.
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6.
  • Singleton, Rosie K., et al. (author)
  • Risk prediction for renal cell Carcinoma : Results from the European Prospective Investigation into Cancer and nutrition (EPIC) prospective cohort study
  • 2021
  • In: Cancer Epidemiology Biomarkers and Prevention. - : AACR. - 1055-9965 .- 1538-7755. ; 30:3, s. 507-512
  • Journal article (peer-reviewed)abstract
    • 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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