Mendelian randomisation analyses of UK Biobank and published data suggest that increased adiposity lowers risk of breast and prostate cancer

Association between visceral adiposity index and prostate cancer in men aged 40 years and older: a nationwide cross-sectional study

OBJECTIVES

This study aimed to elucidate the correlation of Visceral Adiposity Index (VAI) with prostate cancer (PCa) among men aged 40 years and older in the United States.

METHODS

Analysis included multivariate linear and logistic regression, smoothing curve fitting, and threshold effect evaluation using 2003-2010 National Health and Nutrition Examination Survey (NHANES) data. The stability of this relationship across demographic groups was assessed via subgroup analyses and interaction tests.

RESULTS

Among 2,768 participants, those with elevated VAI displayed lower total prostate-specific antigen (tPSA) levels and reduced PCa risk. Each VAI unit elevation corresponded to a 0.075 ng/mL tPSA reduction [-0.075 (-0.145, -0.005)] and 18.8% PCa risk reduction [0.812 (0.687, 0.960)]. Top-quartile VAI individuals exhibited 0.282 ng/mL reduced tPSA [-0.282 (-0.557, -0.007)] and 49.7% reduced PCa risk [0.503 (0.282, 0.896)] relative to bottom-quartile counterparts. This inverse relationship was more pronounced in men ≥70 years. Moreover, VAI-tPSA in other races demonstrated a U-shaped pattern, with a 2.09 inflection point. At the same time, a Mexican American subgroup exhibited an inverted U-shape for VAI and PCa risk, with a 1.42 inflection point.

CONCLUSION

In men aged ≥70, VAI indicates an inverse PCa relationship. However, PSA-based PCa screening may be influenced in visceral-obese individuals aged <70.

Obesity, Physical Activity, and Cancer Incidence in Two Geographically Distinct Populations; The Gulf Cooperation Council Countries and the United Kingdom-A Systematic Review and Meta-Analysis

BACKGROUND

The relationship between obesity, physical activity, and cancer has not been well studied across different countries. The age-standardized rate of cancer in the UK is double-triple that in the Gulf Cooperation Council Countries (GCCCs). Here, we study the association between obesity, physical activity, and cancer incidence with the aim to elucidate cancer epidemiology and risk factors in two geographically, ethnically, and climatically different parts of the world.

METHODS

Our systematic search (from 2016 to 2023) in PubMed, EMBASE, Scopus, and APA PsycINFO databases resulted in 64 studies totaling 13,609,578 participants. The Cochrane risk of bias tool, GRADE, R programming language, and the meta package were used.

RESULTS

Significant associations between obesity and cancer were found in both regions, with a stronger association in the UK (p ≤ 0.0001) than the GCCCs (p = 0.0042). While physical inactivity alone did not show a statistically significant association with cancer incidence, the pooled hazard ratio analysis revealed that the presence of both obesity and physical inactivity was associated with a significantly higher cancer incidence. The most common types of cancer were breast cancer in the UK and colorectal cancer across the GCCCs.

CONCLUSION

Although both regions share similarities, advanced healthcare systems, genetic characteristics, dietary habits, and cultural practices may influence cancer incidence and types.

Novel perspectives on the link between obesity and cancer risk: from mechanisms to clinical implications

Existing epidemiologic and clinical studies have demonstrated that obesity is associated with the risk of a variety of cancers. In recent years, an increasing number of experimental and clinical studies have unraveled the complex relationship between obesity and cancer risk and the underlying mechanisms. Obesity-induced abnormalities in immunity and biochemical metabolism, including chronic inflammation, hormonal disorders, dysregulation of adipokines, and microbial dysbiosis, may be important contributors to cancer development and progression. These contributors play different roles in cancer development and progression at different sites. Lifestyle changes, weight loss medications, and bariatric surgery are key approaches for weight-centered, obesity-related cancer prevention. Treatment of obesity-related inflammation and hormonal or metabolic dysregulation with medications has also shown promise in preventing obesity-related cancers. In this review, we summarize the mechanisms through which obesity affects the risk of cancer at different sites and explore intervention strategies for the prevention of obesity-associated cancers, concluding with unresolved questions and future directions regarding the link between obesity and cancer. The aim is to provide valuable theoretical foundations and insights for the in-depth exploration of the complex relationship between obesity and cancer risk and its clinical applications.

Causal Relationship Between Kidney Function and Cancer Risk: A Mendelian Randomization Study

RATIONALE & OBJECTIVE

Patients treated with kidney replacement therapy experience a 1.5- to 2-fold increased risk of cancer and cancer mortality compared with the general population. Whether this excess risk extends to people with earlier stage chronic kidney disease and whether reduced kidney function is causally related to cancer is unclear.

STUDY DESIGN

Two-sample Mendelian randomization (MR).

SETTING & PARTICIPANTS

Genome-wide association study (GWAS) summary statistics for estimated glomerular filtration rate (eGFR) (n=567,460) and urinary albumin-creatine ratio (UACR) (n=127,865) from the CKDGen consortium and cancer outcomes from the UK Biobank (n = 407,329).

EXPOSURE

eGFR and UACR.

OUTCOME

Overall cancer incidence, cancer-related mortality and site-specific colorectal, lung, and urinary tract cancer incidence.

ANALYTICAL APPROACH

Univariable and multivariable MR conducted for all outcomes.

RESULTS

The mean eGFR and median UACR were 91.4mL/min/1.73m2 and 9.32mg/g, respectively, in the CKDGen, and 90.4mL/min/1.73m2 and 9.29mg/g, respectively, in the UK Biobank. There were 98,093 cases of cancer, 15,850 cases of cancer-related death, 6,664 colorectal, 3584 lung, and 3,271 urinary tract cancer cases, respectively. The genetic instruments for eGFR and UACR comprised 34 and 38 variants, respectively. Genetically predicted kidney function (eGFR and UACR) was not associated with overall cancer risk or cancer death. The association between genetically predicted eGFR and UACR and overall cancer incidence had an odds ratio of 0.88 ([95% CI, 0.40-1.97], P=0.8) and 0.90 ([95% CI, 0.78-1.04], P=0.2) respectively, using the inverse-variance weighted method. An adjusted generalized additive model for eGFR and cancer demonstrated evidence of nonlinearity. However, there was no evidence of a causal association between eGFR and cancer in a stratified MR.

LIMITATIONS

To avoid overlapping samples a smaller GWAS for UACR was used, which reduced the strength of the instrument and may introduce population stratification.

CONCLUSIONS

Our study did not show a causal association between kidney function, overall cancer incidence, and cancer-related death.

PLAIN-LANGUAGE SUMMARY

Does reduced kidney function cause cancer? Patients with chronic kidney disease have been shown to have an increased risk of cancer and cancer-related death. However, it is not clear whether kidney disease is causally related to cancer or the association is due to other factors such as immune suppression and inflammation or a result of distortion of the analyses from unidentified variables (confounding). We used large, published genetic studies as well a database including 407,329 people in the United Kingdom in a series of Mendelian randomization analysis. Mendelian randomization uses the random assignment of genetic variants at birth to investigate causal relationships without confounding from measured and unmeasured confounders. We found that there is no evidence of a causal relationship between reduced kidney function and cancer.

Disentangling the relationships of body mass index and circulating sex hormone concentrations in mammographic density using Mendelian randomization

PURPOSE

Mammographic density phenotypes, adjusted for age and body mass index (BMI), are strong predictors of breast cancer risk. BMI is associated with mammographic density measures, but the role of circulating sex hormone concentrations is less clear. We investigated the relationship between BMI, circulating sex hormone concentrations, and mammographic density phenotypes using Mendelian randomization (MR).

METHODS

We applied two-sample MR approaches to assess the association between genetically predicted circulating concentrations of sex hormones [estradiol, testosterone, sex hormone-binding globulin (SHBG)], BMI, and mammographic density phenotypes (dense and non-dense area). We created instrumental variables from large European ancestry-based genome-wide association studies and applied estimates to mammographic density phenotypes in up to 14,000 women of European ancestry. We performed analyses overall and by menopausal status.

RESULTS

Genetically predicted BMI was positively associated with non-dense area (IVW: β = 1.79; 95% CI = 1.58, 2.00; p = 9.57 × 10-63) and inversely associated with dense area (IVW: β = - 0.37; 95% CI = - 0.51,- 0.23; p = 4.7 × 10-7). We observed weak evidence for an association of circulating sex hormone concentrations with mammographic density phenotypes, specifically inverse associations between genetically predicted testosterone concentration and dense area (β = - 0.22; 95% CI = - 0.38, - 0.053; p = 0.009) and between genetically predicted estradiol concentration and non-dense area (β =  - 3.32; 95% CI = - 5.83, - 0.82; p = 0.009), although results were not consistent across a range of MR approaches.

CONCLUSION

Our findings support a positive causal association between BMI and mammographic non-dense area and an inverse association between BMI and dense area. Evidence was weaker and inconsistent for a causal effect of circulating sex hormone concentrations on mammographic density phenotypes. Based on our findings, associations between circulating sex hormone concentrations and mammographic density phenotypes are weak at best.

Predicted body fat percentage, fat mass and lean body mass in relation to risk of prostate cancer: Results from the NHANES 1999 to 2010

The purpose of this study is to examine the relationship between fat mass (FM), body fat percentage (BF%), lean body mass (LM), and prostate cancer (PCa), and evaluate their potential impact on the risk of PCa. Data from the National Health and Nutrition Examination Survey (NHANES) of the United States were utilized. Adult male participants from 6 survey cycles between 1999 and 2010 were selected as the study sample. Multivariable logistic regression analysis was conducted to explore the association between BF%, LM, and PCa, while controlling for potential confounding variables. Among the 8440 participants, 359 cases of PCa were diagnosed. The relationship between BF%, LM, and PCa was nonlinear. In the multivariable logistic regression analysis, there was an independent association between BF% and PCa risk (OR: 1.04, 95% CI: 1.02-1.06), suggesting that higher BF% levels are associated with an increased risk of PCa. Conversely, higher LM levels were associated with a decreased risk of PCa (OR: 0.96, 95% CI: 0.95-0.98). The findings of this study demonstrate a correlation between BF% and LM with PCa, but do not provide direct evidence of a causal relationship. Higher BF% levels are associated with an increased risk of PCa, while higher LM levels are associated with a decreased risk. These results provide valuable insights for understanding and potentially preventing PCa, although further research is needed to fully comprehend the underlying mechanisms.

A Mendelian randomization-based approach to explore the relationship between leukocyte counts and breast cancer risk in European ethnic groups

Exploring the potential association between peripheral blood leukocyte counts and breast cancer risk by Mendelian randomization (MR) analysis methods. Genetic data related to peripheral blood sorting counts of leukocytes were collected from a genome-wide association study by Blood Cell Consortium (BCX). Single nucleotide polymorphic loci predicting peripheral blood sorting counts of these leukocytes were selected as instrumental variables according to the correlation assumption, independence assumption and exclusivity assumption of MR. The data on breast cancer and its subtypes were obtained from Breast Cancer Association Consortium (BCAC) and FinnGen Consortium. In this study, the Inverse-Variance Weighted (IVW), Weighted Median, MR-Egger, Maximum Likelihood (ML), MR-PRESSO and Constrained Maximum Likelihood and Model Averaging (cML-MA) methods of random effects models were used for MR analysis. Cochran's Q analysis, and MR-Egger intercept analysis were applied for sensitivity analysis. IVW and cML-MA were considered the primary analytical tools, and the results of the other 4 MRs were used as complementary and validation. The results suggest that there is no significant causal relationship between leukocyte count and breast cancer risk (IVW OR = 0.98 [95% CI: 0.93-1.03], p-value = 0.35; CML-MA OR = 1.01 [95% CI: 0.98-1.05], p-value = 0.51). In addition, we analyzed whether there was a potential correlation between the five main types of categorized leukocyte counts and different breast cancer subtypes. We did not find significant evidence to support a significant correlation between leukocyte counts and breast cancer subtypes.