scholarly journals Effect of Basal Metabolic Rate on Cancer: A Mendelian Randomization Study

2021 ◽  
Vol 12 ◽  
Author(s):  
Jack C. M. Ng ◽  
C. Mary Schooling
Keyword(s):  
Growth Factor ◽  
Cancer Risk ◽  
Confidence Interval ◽  
Metabolic Rate ◽  
Basal Metabolic Rate ◽  
Odds Ratio ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Sensitivity Analyses ◽  
Insulin Like Growth Factor

Background: Basal metabolic rate is associated with cancer, but these observations are open to confounding. Limited evidence from Mendelian randomization studies exists, with inconclusive results. Moreover, whether basal metabolic rate has a similar role in cancer for men and women independent of insulin-like growth factor 1 increasing cancer risk has not been investigated.Methods: We conducted a two-sample Mendelian randomization study using summary data from the UK Biobank to estimate the causal effect of basal metabolic rate on cancer. Overall and sex-specific analysis and multiple sensitivity analyses were performed including multivariable Mendelian randomization to control for insulin-like growth factor 1.Results: We obtained 782 genetic variants strongly (p-value < 5 × 10–8) and independently (r2 < 0.01) predicting basal metabolic rate. Genetically predicted higher basal metabolic rate was associated with an increase in cancer risk overall (odds ratio, 1.06; 95% confidence interval, 1.02–1.10) with similar estimates by sex (odds ratio for men, 1.07; 95% confidence interval, 1.002–1.14; odds ratio for women, 1.06; 95% confidence interval, 0.995–1.12). Sensitivity analyses including adjustment for insulin-like growth factor 1 showed directionally consistent results.Conclusion: Higher basal metabolic rate might increase cancer risk. Basal metabolic rate as a potential modifiable target of cancer prevention warrants further study.

scholarly journals Circulating Insulin-Like Growth Factor-1 Level and Ovarian Cancer Risk

2016 ◽  
Vol 38 (2) ◽  
pp. 589-597 ◽  
Author(s):  
Yiyang Li ◽  
Yang Li ◽  
Jialing Zhang ◽  
Changjun Zheng ◽  
He Zhu ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Growth Factor ◽  
Cancer Risk ◽  
Confidence Interval ◽  
Odds Ratio ◽  
Meta Analysis ◽  
Epidemiological Studies ◽  
Ovarian Cancer Risk ◽  
Insulin Like Growth Factor ◽  
Summary Odds Ratio

Background/Aims: Insulin-like growth factor-1 (IGF-1) has an important role in cells' proliferation, differentiation and apoptosis, and it may be involved in carcinogenesis. Several epidemiological studies assessed the association between circulating IGF-1 level and ovarian cancer risk, but there was still no conclusive finding. Methods: A meta-analysis of published studies was performed to assess the association between circulating IGF-1 level and ovarian cancer risk. The summary odds ratio (OR) with 95% confidence interval (95%CI) was calculated through meta-analysis to evaluate the strength of the association. Results: Five eligible studies were included into the meta-analysis, which involved a total of 2,028 cases of ovarian cancer and 4,625 controls. Meta-analysis of total 5 studies showed that high circulating IGF-1 level was correlated with decreased risk of ovarian cancer (OR = 0.84, 95%CI 0.74-0.97, P = 0.013). After adjusting for heterogeneity, high circulating IGF-1 level was still correlated with decreased risk of ovarian cancer (OR = 0.83, 95%CI 0.72-0.95, P = 0.007). Subgroup analysis by age showed that circulating IGF-1 level was not correlated with ovarian cancer risk in women both less than 55 years and more than 55 years. However, after adjusting for heterogeneity, high circulating IGF-1 level was correlated with decreased ovarian cancer risk in women less than 55 years (OR = 0.82, 95%CI 0.72-0.94, P = 0.004). Conclusion: Our meta-analysis suggests that high circulating IGF-1 level may be correlated with decreased ovarian cancer risk, especially in women less than 55 years. More studies are needed to further assess the association between circulating IGF-1 level and ovarian cancer risk in the future.

scholarly journals Causal Relationship Between Parathyroid Hormone and the Risk of Osteoarthritis: A Mendelian Randomization Study

2021 ◽  
Vol 12 ◽  
Author(s):  
Guiwu Huang ◽  
Yanlin Zhong ◽  
Wenchang Li ◽  
Weiming Liao ◽  
Peihui Wu
Keyword(s):  
Parathyroid Hormone ◽  
Confidence Interval ◽  
Odds Ratio ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Sensitivity Analyses ◽  
Inverse Association ◽  
Genome Wide ◽  
Inverse Variance ◽  
Weighted Median

BackgroundPrevious studies have demonstrated an inverse association between parathyroid hormone (PTH) and the risk of osteoarthritis (OA). However, it remains unknown whether such association reflects causality. We aimed to apply a Mendelian randomization (MR) approach to investigate the causal association between PTH and OA.Materials and MethodsWe performed a two-sample MR analysis using summary statistics from 13 cohorts (PTH, N = 29,155) and a recent genome-wide association study meta-analysis (OA, N = 455,221) by the UK Biobank and Arthritis Research UK OA Genetics (arcOGEN). MR analyses were carried out mainly using the inverse-variance-weighted method. Sensitivity analyses were performed to test the robustness of the associations using the weighted median method, the MR–Egger method, and “leave-one-out” analysis. Analyses were performed again to test whether the associations remained statistically significant after excluding any outlier variants that were detected using the MR-PRESSO (Mendelian Randomization Pleiotropy RESidual Sum and Outlier) test.ResultsFive single-nucleotide polymorphisms (SNPs) were selected as instrumental variables at the genome-wide significance threshold (p < 5 × 10–8). The causal effect between PTH and OA was genetically predicted using the inverse-variance-weighted method (odds ratio = 0.67, 95% confidence interval: 0.50–0.90; p = 0.008). This result was borne out using the weighted median method (odds ratio = 0.73, 95% confidence interval: 0.60–0.90; p = 0.004). The causality remained robust after discarding the outlier variants as well as SNPs associated with confounding factors.ConclusionMR analysis supported a potential causative relationship between decreased serum circulating PTH and a higher risk of hip and knee OA.

scholarly journals Assessment of Bidirectional Relationships Between Polycystic Ovary Syndrome and Periodontitis: Insights From a Mendelian Randomization Analysis

2021 ◽  
Vol 12 ◽  
Author(s):  
Pengfei Wu ◽  
Xinghao Zhang ◽  
Ping Zhou ◽  
Wan Zhang ◽  
Danyang Li ◽  
...  
Keyword(s):  
Polycystic Ovary Syndrome ◽  
Odds Ratio ◽  
Mendelian Randomization ◽  
Polycystic Ovary ◽  
Causal Effect ◽  
Sensitivity Analyses ◽  
Ovary Syndrome ◽  
Unit Increase ◽  
Log Odds ◽  
Mr Study

BackgroundObservational studies have indicated an association between polycystic ovary syndrome (PCOS) and periodontitis, but it is unclear whether the association is cofounded or causal. We conducted a two-sample Mendelian randomization (MR) study to investigate the bidirectional relationship between genetically predicted PCOS and periodontitis.MethodsFrom two genome-wide association studies we selected 13 and 7 single nucleotide polymorphisms associated with PCOS and periodontitis, respectively, as instrumental variables. We utilized publicly shared summary-level statistics from European-ancestry cohorts. To explore the causal effect of PCOS on periodontitis, 12,289 cases of periodontitis and 22,326 controls were incorporated, while 4,890 cases of PCOS and 20,405 controls in the reverse MR. Inverse-variance weighted method was employed in the primary MR analysis and multiple sensitivity analyses were implemented.ResultsGenetically determined PCOS was not causally associated with risk of periodontitis (odds ratio 0.97; 95% confidence interval 0.88–1.06; P = 0.50) per one-unit increase in the log-odds ratio of periodontitis. Similarly, no causal effect of periodontitis on PCOS was shown with the odds ratio for PCOS was 1.17 (95% confidence interval 0.91–1.49; P = 0.21) per one-unit increase in the log-odds ratio of periodontitis. Consistent results were yielded via additional MR methods. Sensitivity analyses demonstrated no presence of horizontal pleiotropy or heterogeneity.ConclusionThe bidirectional MR study couldn’t provide convincing evidence for the causal relationship between genetic liability to PCOS and periodontitis in the Europeans. Triangulating evidence across further observational and genetic-epidemiological studies is necessary.

scholarly journals Insulin-like Growth Factor-1, Bone Mineral Density, and Fracture: A Mendelian Randomization Study

2021 ◽  
Author(s):  
Shuai Yuan ◽  
Zi-Hao Wan ◽  
Shi-Le Cheng ◽  
Karl Michaëlsson ◽  
Susanna C Larsson
Keyword(s):  
Bone Mineral Density ◽  
Growth Factor ◽  
Bone Mineral ◽  
Odds Ratio ◽  
Mendelian Randomization ◽  
European Ancestry ◽  
Insulin Like Growth Factor ◽  
Mineral Density ◽  
Genome Wide ◽  
Genetic Instruments

Abstract Context The associations of circulating insulin-like growth factor-1 (IGF-1) levels with bone mineral density and fracture risk are inconclusive in observational studies. Objective We conducted a mendelian randomization study to assess the associations of serum IGF-1 levels with estimated bone mineral density (eBMD) and fracture. Methods Genetic instruments for IGF-1 were selected at the genome-wide significance level (P < 5 × 10–8) from a genome-wide association study including 358 072 individuals of European ancestry. Summary-level data for eBMD (426 824 individuals) and fracture (53 184 fracture cases and 373 611 noncases) were obtained from the UK Biobank study. Univariable and multivariable mendelian randomization analyses methods were used to estimate the associations of IGF-1 with eBMD and fracture. The main outcome measure included the change of eBMD and odds ratio of fracture per genetically predicted 1-SD increase of serum IGF-1 levels. Results For 1-SD increase in IGF-1, the change of eBMD levels was 0.04 g/cm2 (95% CI, 0.01-0.07; P = .011) and the odds ratio of fracture was 0.94 (95% CI, 0.91-0.98; P = .003). The associations persisted with similar magnitude after adjustment for height. The association was consistent for fracture but not for eBMD after excluding genetic instruments that might directly influence these outcomes. The association between IGF-1 and fracture was somewhat attenuated after adjustment for eBMD (odds ratio 0.96; 95% CI, 0.92-0.99; P = .012). Conclusion The present study supports a role for IGF-1 in preventing fracture, possibly and partly mediated by greater bone mineral density.

scholarly journals Bias in two-sample Mendelian randomization when using heritable covariable-adjusted summary associations

2021 ◽  
Author(s):  
Fernando Pires Hartwig ◽  
Kate Tilling ◽  
George Davey Smith ◽  
Deborah A Lawlor ◽  
Maria Carolina Borges
Keyword(s):  
Waist Circumference ◽  
Genetic Variants ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Association Studies ◽  
Real Data ◽  
Sensitivity Analyses ◽  
Effect Estimate ◽  
Genome Wide Association Studies ◽  
Residual Confounding

Abstract Background Two-sample Mendelian randomization (MR) allows the use of freely accessible summary association results from genome-wide association studies (GWAS) to estimate causal effects of modifiable exposures on outcomes. Some GWAS adjust for heritable covariables in an attempt to estimate direct effects of genetic variants on the trait of interest. One, both or neither of the exposure GWAS and outcome GWAS may have been adjusted for covariables. Methods We performed a simulation study comprising different scenarios that could motivate covariable adjustment in a GWAS and analysed real data to assess the influence of using covariable-adjusted summary association results in two-sample MR. Results In the absence of residual confounding between exposure and covariable, between exposure and outcome, and between covariable and outcome, using covariable-adjusted summary associations for two-sample MR eliminated bias due to horizontal pleiotropy. However, covariable adjustment led to bias in the presence of residual confounding (especially between the covariable and the outcome), even in the absence of horizontal pleiotropy (when the genetic variants would be valid instruments without covariable adjustment). In an analysis using real data from the Genetic Investigation of ANthropometric Traits (GIANT) consortium and UK Biobank, the causal effect estimate of waist circumference on blood pressure changed direction upon adjustment of waist circumference for body mass index. Conclusions Our findings indicate that using covariable-adjusted summary associations in MR should generally be avoided. When that is not possible, careful consideration of the causal relationships underlying the data (including potentially unmeasured confounders) is required to direct sensitivity analyses and interpret results with appropriate caution.

Sign in / Sign up

Export Citation Format

Share Document