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

Sex-specific Mendelian randomization phenome-wide association study of basal metabolic rate

Observationally, higher basal metabolic rate (BMR) is associated with metabolism-related disorders, cancer, aging, and mortality. In this Mendelian randomization (MR) phenome-wide association study, using two-sample MR methods, we systematically and comprehensively investigated the health effects of genetically predicted BMR across the phenome sex-specifically. We obtained sex-specific genetic variants strongly (p < 5 × 10- 8) and independently (r2 < 0.001) predicting BMR from the UK Biobank and applied them to over 1,000 phenotypes within the same study. We combined genetic variant-specific Wald estimates using inverse-variance weighting, supplemented by sensitivity analysis. We used a false-discovery rate correction to allow for multiple comparisons as well as multivariable MR adjusted for body mass index and testosterone to investigate the independent effects of BMR on phenotypes with significant univariable associations. We obtained 217/219 genetic variants predicting BMR and applied them to 1,150/1,242 phenotypes in men/women, respectively. BMR was associated with 190/270 phenotypes in univariable analysis and 122/123 phenotypes in multivariable analysis in men/women. Examples of robust associations in multivariable analysis included those with neoplasms, diseases of the circulatory system, and growth and reproductive investment. In conclusion, BMR might affect a wide range of health-related outcomes. The underlying mechanisms and interactions between phenotypes warrant further study, as BMR is modifiable.

Basal metabolic rate by FAO/WHO/UNU as a prognostic factor for survival in patients with gastric cancer: A cohort study

The basal metabolic rate (BMR) is a crucial indicator of the body's energy expenditure at rest and is essential for understanding metabolic needs. This retrospective study evaluated the prognostic significance of BMR in 521 predominantly Asian patients with stage I-III gastric cancer who underwent curative-intent resection. BMR was calculated using the Food and Agriculture Organization/World Health Organization/United Nations University (FWU BMR) equation. Multivariate Cox regression analysis identified FWU BMR as a significant predictor of overall survival (OS) (P < .001). Fractional polynomial modeling revealed a linear relationship between FWU BMR and OS, with higher values correlating with lower mortality risk. The FWU model, which included FWU BMR along with other clinical variables, showed superior predictive performance (C-index: 0.815, iAUC: 0.775) compared to that of the same model lacking BMR. Additionally, although the differences were not statistically significant, the FWU model also outperformed those using the BMR derived from alternative equations, including the Harris-Benedict equation. The nomogram, based on the FWU model, demonstrated good calibration. These findings suggest that the FWU BMR is a valuable prognostic factor in patients with gastric cancer post-resection, enhancing predictive accuracy and aiding in personalized post-surgical care. However, further validation in diverse populations is required.

Genetic effect of basal metabolic rate on the benign neoplasm of bone and articular cartilage: a Mendelian randomization study

Background

Previous studies have found an association between basal metabolic rate (BMR) and various malignant neoplasms, including bone tumors. BMR is also associated with bone mineral density, but the causality between BMR and benign neoplasms of bone and articular cartilage remains uncertain.

Design

Single nucleotide polymorphisms (SNPs) associated with BMR (p < 5 × 10-8) were used as instrumental variables for Mendelian randomization analysis of neoplasm risk. The inverse variance weighted (IVW) method was the primary approach, with the weighted median and MR-Egger regression serving as supplements.

Results

In this MR analysis, the IVW method supported a causal relationship between BMR and benign neoplasms of bone and articular cartilage (OR = 1.417; 95% CI, 1.039 to 1.930; p = 0.027). No evidence of heterogeneity or pleiotropy in the selected SNPs was found in our study. Thus, based on these results, we discovered a possible causal relationship between BMR and benign neoplasms of bone and articular cartilage.

Conclusions

In this MR study, evidence suggested a genetic correlation between genetically predicted BMR and the risk of neoplasms in bone and articular cartilage.

Causal relationships between obesity-related anthropometric indicators and sepsis risk: a Mendelian-randomization study

Background

Previous studies have reported an association between obesity and risk of sepsis. However, the results have been inconsistent, and no causal inference can be drawn from them. Therefore, we conducted a Mendelian-randomization (MR) study to investigate causal relationships between available obesity-related anthropometric indicators and sepsis risk.

Methods

We performed MR analyses using genome-wide association study (GWAS) summary statistics on 14 anthropometric indicators [namely body mass index (BMI), waist and hip circumferences (WC, HC), basal metabolic rate (BMR), whole-body fat mass (WBFM), trunk fat mass (TFM), leg fat mass (LFM), arm fat mass (AFM), body fat percentage (BFP), whole-body fat-free mass (WBFFM), trunk fat-free mass (TFFM), leg fat-free mass (LFFM), arm fat-free mass (AFFM), and whole-body water mass (WBWM)], sepsis, critical care sepsis, and 28-day death due to sepsis from the UK Biobank and FinnGen cohort. The primary method of MR analysis was inverse variance-weighted average method. Sensitivity analyses, including heterogeneity and horizontal-pleiotropy tests, were conducted to assess the stability of the MR results. Additionally, we applied multiple-variable MR (MVMR) to evaluate the effect of BMI on the relationship between each anthropometric indicator and sepsis risk.

Results

Our MR analysis demonstrated causal relationships between 14 anthropometric indicators and sepsis of different severities. After we adjusted for BMI, MVMR analyses indicated that WC, BMR, LFM, WBFFM, TFFM, AFFM, and WBWM remained significantly associated with the presence of sepsis (all p < 0.05). A sensitivity analysis confirmed the reliability of our MR results, and no significant horizontal pleiotropy was detected.

Conclusion

This MR study revealed that increases in obesity-related anthropometric indicators had causal associations with a higher risk of sepsis, which might provide important insights for the identification of individuals at risk for sepsis in community and hospital settings.

Anthropometric indicators may explain the high incidence of follicular lymphoma in Europeans: Results from a bidirectional two-sample two-step Mendelian randomisation

BACKGROUND

Non-Hodgkin's lymphoma incidence rates vary between European and Asian populations. The reasons remain unclear. This two-sample two-step Mendelian randomisation (MR) study aimed to investigate the causal relationship between anthropometric indicators (AIs) and diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma (FL) and the possible mediating role of basal metabolic rate (BMR) in Europe.

METHODS

We used the following AIs as exposures: body mass index (BMI), whole-body fat mass (WBFM), whole-body fat-free mass (WBFFM), waist circumference(WC), hip circumference(HC), standing height (SH), and weight(Wt). DLBCL and FL represented the outcomes, and BMR was a mediator. A two-sample MR analysis was performed to examine the association between AIs and DLBCL and FL onset. We performed reverse-MR analysis to determine whether DLBCL and FL interfered with the AIs. A two-step MR analysis was performed to determine whether BMR mediated the causality.

FINDINGS

WBFFM and SH had causal relationships with FL. A causal association between AIs and DLBCL was not observed. Reverse-MR analysis indicated the causal relationships were not bidirectional. Two-step MR suggested BMR may mediate the causal effect of WBFFM and SH on FL.

CONCLUSIONS

We observed a causal relationship between WBFFM and SH and the onset of FL in Europeans, Which may explain the high incidence of follicular lymphoma in Europeans.

Association between basal metabolic rate and cardio-metabolic risk factors: Evidence from a Mendelian Randomization study

BACKGROUND

Cardio-metabolic risk factors play a crucial role in the development of cardiovascular and metabolic diseases. Basal metabolic rate (BMR) is a fundamental physiological parameter that affects energy expenditure and might contribute to variations in these risk factors. However, the exact relationship between BMR and cardio-metabolic risk factors has remained unclear.

METHODS

We employed Mendelian Randomization (MR) analysis to explore the association between BMR (N: 534,045) and various cardio-metabolic risk factors, including body mass index (BMI, N: 681,275), fasting glucose (N: 200,622), high-density lipoprotein (HDL) cholesterol (N = 403,943), low-density lipoprotein (LDL) cholesterol (N = 431,167), total cholesterol (N: 344,278), and triglycerides (N: 441,016), C-reactive protein (N: 436,939), waist circumference (N: 232,101), systolic blood pressure (N: 810,865), diastolic blood pressure (N: 810,865), glycated haemoglobin (N: 389,889), and N-terminal prohormone brain natriuretic peptide (N: 21,758). We leveraged genetic variants strongly associated with BMR as instrumental variables to investigate potential causal relationships, with the primary analysis using the Inverse Variance Weighted (IVW) method.

RESULTS

Our MR analysis revealed compelling evidence of a causal link between BMR and specific cardio-metabolic risk factors. Specifically, genetically determined higher BMR was associated with an increased BMI (β = 0.7538, 95% confidence interval [CI]: 0.6418 to 0.8659, p < 0.001), lower levels of HDL cholesterol (β = -0.3293, 95% CI: 0.4474 to -0.2111, p < 0.001), higher levels of triglycerides (β = 0.1472, 95% CI: 0.0370 to 0.2574, p = 0.0088), waist circumference (β = 0.4416, 95% CI: 0.2949 to 0.5883, p < 0.001), and glycated haemoglobin (β = 0.1037, 95% CI: 0.0080 to 0.1995, p = 0.0377). However, we did not observe any significant association between BMR and fasting glucose, LDL cholesterol, total cholesterol, C-reactive protein, systolic blood pressure, diastolic blood pressure, or N-terminal prohormone brain natriuretic peptide (all p-values>0.05).

CONCLUSION

This MR study provides valuable insights into the relationship between BMR and cardio-metabolic risk factors. Understanding the causal links between BMR and these factors could have important implications for the development of targeted interventions and therapies.

Insights into modifiable risk factors of erectile dysfunction, a wide-angled Mendelian Randomization study

INTRODUCTION

The causal association between modifiable risk factors and erectile dysfunction (ED) remains unclear, which hinders the early identification and intervention of patients with ED. The present study aimed to clarify the causal association between 42 predominant risk factors and ED.

METHODS

Univariate Mendelian Randomization (MR), multivariate MR, and mediation MR analyses were used to investigate the causal association between 42 modifiable risk factors and ED. Combined results were pooled from two independent ED genome-wide association studies to verify the findings.

RESULTS

Genetically predicted body mass index (BMI), waist circumference, trunk fat mass, whole body fat mass, poor overall health rating, type 2 diabetes, basal metabolic rate, adiponectin, cigarette consumption, insomnia, snoring, hypertension, stroke, ischemic stroke, coronary heart disease, myocardial infarction, heart failure, and major depressive disorder were found to increase the risk of ED (all P < 0.05). Additionally, genetic liability to higher body fat percentage and alcohol consumption were suggestively associated with an increased risk of ED (P < 0.05 and adjusted P > 0.05). Genetic predisposition to higher sex hormone-binding globulin (SHBG) levels could decrease the risk of ED (P < 0.05). No significant association was detected between lipid levels and ED. Multivariate MR identified type 2 diabetes, basal metabolic rate, cigarette consumption, hypertension, and coronary heart disease as risk factors for ED. The combined results confirmed that waist circumference, whole body fat mass, poor overall health rating, type 2 diabetes, basal metabolic rate, adiponectin, cigarette consumption, snoring, hypertension, ischemic stroke, coronary heart disease, myocardial infarction, heart failure, and major depressive disorder could increase the risk of ED (all P < 0.05), while higher SHBG decreased the risk of ED (P = 0.004). There were suggestive significances of BMI, insomnia, and stroke on ED (P < 0.05 and adjusted P > 0.05).

CONCLUSION

This comprehensive MR study supported the causal role of obesity, type 2 diabetes, basal metabolic rate, poor self-health rating, cigarette and alcohol consumption, insomnia and snoring, depression, hypertension, stroke, ischemic stroke, coronary heart disease, myocardial infarction, heart failure, SHBG, and adiponectin in the onset and development of ED.

Effect of basal metabolic rate on rheumatoid arthritis: a Mendelian randomization study

PURPOSE

Basal metabolic rate (BMR) as one of the most basic and significant indicators of metabolism has been associated with human health. Previous studies showed that the development of rheumatoid arthritis (RA) is linked to BMR; however, the causal relationship between BMR and RA is unknown. Thus, we aimed to explore the causal relationship between BMR and RA as well as RA-related factors.

METHODS

Mendelian randomization (MR) analysis was performed on collected genome-wide association studies information. The effect of horizontal pleiotropy was detected by MR-PRESSO and MR-Radial. Five MR analysis methods were applied, including inverse variance weighted, MR-Egger, weighted median, weighted mode, and simple mode. Four sensitivity analysis methods were used for the validation of the significant MR analysis results. A two-component mixture of regressions method was additionally used to validate single nucleotide polymorphisms and to verify results.

RESULTS

Genetically, there is a causal effect of BMR on overall RA (odds ratio = 1.25, 95% confidence interval: 1.07-1.47, PIVW = .006), seropositive RA (odds ratio = 1.20, 95% confidence interval: 1.01-1.44, PIVW = .035), and seronegative RA (odds ratio = 1.36, 95% confidence interval: 1.04-1.78, PIVW = .023). Sensitivity analyses validated the robustness of the above associations. No evidence supported the effect of RA on BMR. Moreover, BMR showed no causal relationship with rheumatoid factor, C-reactive protein, erythrocyte sedimentation rate, interleukin-1β, tumor necrosis factor-α, and matrix metallopeptidase 3.

CONCLUSION

MR results implied the causal effect of BMR on RA and raised our attention to the importance of BMR in RA's pathology.

Genetically predicted thyroid function and risk of colorectal cancer: a bidirectional Mendelian randomization study

BACKGROUND

Observational studies have reported an association between thyroid function and colorectal cancer (CRC), with conflicting results. Elucidating the causal relationship between thyroid function and CRC facilitates the development of new preventive strategies to reduce CRC incidence.

METHOD

We applied a two-sample Mendelian randomization (MR) method to evaluate the causal relationship between five thyroid-related indexes, including hyperthyroidism, hypothyroidism, thyroid stimulating hormone (TSH), free thyroxine (FT4) and basal metabolic rate (BMR), and CRC. Genome-wide association study statistics for thyroid-related phenotypes were obtained from the ThyroidOmics consortium, and summary statistics for genetic associations with CRC were obtained from the FinnGen consortium. We set a series of criteria to screen single nucleotide polymorphisms (SNPs) as instrumental variables and then performed bidirectional MR analysis, stratified analysis and extensive sensitivity analysis. Multiplicative random-effects inverse variance weighted was the primary analysis method, supplemented by weighted median and MR-Egger.

RESULT

We identified 12 SNPs for hyperthyroidism, 10 SNPs for hypothyroidism, 41 SNPs for TSH, 18 SNPs for FT4, and 556 SNPs for BMR. Genetically predicted hyperthyroidism, hypothyroidism, TSH, and FT4 were not associated with CRC risk (all P > 0.05). Sensitivity analysis revealed no heterogeneity or pleiotropy. Genetically predicted BMR was significantly associated with increased CRC risk after removing outlier (OR = 1.30, P = 0.0029). Stratified analysis showed that BMR was significantly associated with colon cancer (OR = 1.33, P = 0.0074) but not rectal cancer. In the reverse analysis, there was no evidence of an effect of CRC on thyroid function (all P > 0.05).

CONCLUSION

Our bidirectional MR analysis provides new insights into the relationship between thyroid function and CRC. CRC prevention may benefit from enhanced screening of high BMR populations.

Hypothesis-free discovery of novel cancer predictors using machine learning

BACKGROUND

Cancer is a leading cause of morbidity and mortality worldwide, and better understanding of the risk factors could enhance prevention.

METHODS

We conducted a hypothesis-free analysis combining machine learning and statistical approaches to identify cancer risk factors from 2828 potential predictors captured at baseline. There were 459,169 UK Biobank participants free from cancer at baseline and 48,671 new cancer cases during the 10-year follow-up. Logistic regression models adjusted for age, sex, ethnicity, education, material deprivation, smoking, alcohol intake, body mass index and skin colour (as a proxy for sun sensitivity) were used for obtaining adjusted odds ratios, with continuous predictors presented using quintiles (Q).

RESULTS

In addition to smoking, older age and male sex, positively associating features included several anthropometric characteristics, whole body water mass, pulse, hypertension and biomarkers such as urinary microalbumin (Q5 vs. Q1 OR 1.16, 95% CI = 1.13-1.19), C-reactive protein (Q5 vs. Q1 OR 1.20, 95% CI = 1.16-1.24) and red blood cell distribution width (Q5 vs. Q1 OR 1.18, 95% CI = 1.14-1.21), among others. High-density lipoprotein cholesterol (Q5 vs. Q1 OR 0.84, 95% CI = 0.81-0.87) and albumin (Q5 vs. Q1 OR 0.84, 95% CI = 0.81-0.87) were inversely associated with cancer. In sex-stratified analyses, higher testosterone increased the risk in females but not in males (Q5 vs. Q1 ORfemales 1.23, 95% CI = 1.17-1.30). Phosphate was associated with a lower risk in females but a higher risk in males (Q5 vs. Q1 ORfemales 0.94, 95% CI = 0.90-0.99 vs. ORmales 1.09, 95% CI 1.04-1.15).

CONCLUSIONS

This hypothesis-free analysis suggests personal characteristics, metabolic biomarkers, physical measures and smoking as important predictors of cancer risk, with further studies needed to confirm causality and clinical relevance.

Combining machine learning with Cox models to identify predictors for incident post-menopausal breast cancer in the UK Biobank

We aimed to identify potential novel predictors for breast cancer among post-menopausal women, with pre-specified interest in the role of polygenic risk scores (PRS) for risk prediction. We utilised an analysis pipeline where machine learning was used for feature selection, prior to risk prediction by classical statistical models. An "extreme gradient boosting" (XGBoost) machine with Shapley feature-importance measures were used for feature selection among [Formula: see text] 1.7 k features in 104,313 post-menopausal women from the UK Biobank. We constructed and compared the "augmented" Cox model (incorporating the two PRS, known and novel predictors) with a "baseline" Cox model (incorporating the two PRS and known predictors) for risk prediction. Both of the two PRS were significant in the augmented Cox model ([Formula: see text]). XGBoost identified 10 novel features, among which five showed significant associations with post-menopausal breast cancer: plasma urea (HR = 0.95, 95% CI 0.92-0.98, [Formula: see text]), plasma phosphate (HR = 0.68, 95% CI 0.53-0.88, [Formula: see text]), basal metabolic rate (HR = 1.17, 95% CI 1.11-1.24, [Formula: see text]), red blood cell count (HR = 1.21, 95% CI 1.08-1.35, [Formula: see text]), and creatinine in urine (HR = 1.05, 95% CI 1.01-1.09, [Formula: see text]). Risk discrimination was maintained in the augmented Cox model, yielding C-index 0.673 vs 0.667 (baseline Cox model) with the training data and 0.665 vs 0.664 with the test data. We identified blood/urine biomarkers as potential novel predictors for post-menopausal breast cancer. Our findings provide new insights to breast cancer risk. Future research should validate novel predictors, investigate using multiple PRS and more precise anthropometry measures for better breast cancer risk prediction.

Effect of basal metabolic rate on lifespan: a sex-specific Mendelian randomization study

Observationally, the association of basal metabolic rate (BMR) with mortality is mixed, although some ageing theories suggest that higher BMR should reduce lifespan. It remains unclear whether a causal association exists. In this one-sample Mendelian randomization study, we aimed to estimate the casual effect of BMR on parental attained age, a proxy for lifespan, using two-sample Mendelian randomization methods. We obtained genetic variants strongly (p-value < 5 × 10^-8) and independently (r² < 0.001) predicting BMR from the UK Biobank and applied them to a genome-wide association study of parental attained age based on the UK Biobank. We meta-analyzed genetic variant-specific Wald ratios using inverse-variance weighting with multiplicative random effects by sex, supplemented by sensitivity analysis. A total of 178 and 180 genetic variants predicting BMR in men and women were available for father's and mother's attained age, respectively. Genetically predicted BMR was inversely associated with father's and mother's attained age (years of life lost per unit increase in effect size of genetically predicted BMR, 0.46 and 1.36; 95% confidence interval 0.07-0.85 and 0.89-1.82), with a stronger association in women than men. In conclusion, higher BMR might reduce lifespan. The underlying pathways linking to major causes of death and relevant interventions warrant further investigation.

Insight into the causality between basal metabolic rate and endometrial and ovarian cancers: Analysis utilizing systematic Mendelian randomization and genetic association data from over 331,000 UK biobank participants

BACKGROUND

Observational studies have demonstrated that basal metabolic rate (BMR) is associated with the risk of endometrial cancer (EC) and ovarian cancer (OC). However, it is unclear whether these associations reflect a causal relationship.

OBJECTIVE

To reveal the causality between BMR and EC and OC, we performed the first comprehensive two-sample Mendelian randomization (MR) analyses.

METHODS

Genetic variants were used as proxies of BMR. GWAS summary statistics of BMR, EC and OC were obtained from the UK Biobank Consortium, Endometrial Cancer Association Consortium and Ovarian Cancer Association Consortium respectively. The inverse variance weighted method was employed as the main approach for MR analysis. A series of sensitivity analyses were implemented to validate the robustness and reliability of the results.

RESULTS

BMR was significantly related to an increased risk of EC (OR_SD  = 1.49; 95% CI: 1.29-1.72; p-Value < .001) and OC (OR_SD  = 1.21; 95% CI: 1.08-1.35; p-Value < .001). Furthermore, the stratified analysis indicated that BMR was positively associated with endometrioid endometrial cancer (EEC) (OR_SD  = 1.45; 95% CI, 1.23-1.70; p-Value < .001), clear cell ovarian cancer(CCOC) (OR_SD  = 1.89; 95% CI:1.35-2.64; p-Value < .001) and endometrioid ovarian cancer risk (EOC) (OR_SD  = 1.45; 95% CI: 1.12-1.88; p-Value = .005). However, there were no significant associations of BMR with invasive mucinous ovarian cancer (IMOC), high-grade serous ovarian cancer (HGSOC) and low-grade serous ovarian cancer (LGSOC). The robustness of the above results was further verified in sensitivity analyses.

CONCLUSION

The MR study provided etiological evidence for the positive association of BMR with the risk of EC, EEC, OC, CCOC and EOC. But this study did not provide enough evidence suggesting the causal associations of BMR with IMOC, HGSOC and LGSOC.

A bidirectional Mendelian randomization study supports the causal effects of a high basal metabolic rate on colorectal cancer risk

Purpose

We conducted a bidirectional two-sample Mendelian randomization (MR) study to determine whether genetically predicted basal metabolic rate (BMR) was a causal risk factor for colorectal cancer (CRC) or whether a genetically predicted CRC risk can influence the BMR level (i.e., reverse causation).

Methods

We employed 1,040 genetic variants as proxies for BMR to obtain effect estimates on CRC risk. Another 58 CRC-associated variants were used to estimate effects on BMR levels. Stratified analysis by tumor site was used to examine the causal associations between BMR and colon/rectal cancer risk.

Results

The inverse variance weighted (IVW) method indicated a significant causal effect of genetically determined BMR on CRC risk (OR_SD = 1.27, 95% CI = 1.07–1.51). No significant reverse causal association was identified between genetically increased CRC risk and BMR levels [IVW (β = 0, 95% CI = -0.01 to 0)]. The results of MR-Egger and the weighted median method were consistent with the IVW method. Stratified analysis by CRC sites identified significant causal associations between BMR and colon cancer [IVW (OR_SD = 1.45, 95% CI = 1.16-1-80)], and null evidence of a causal association between BMR and rectal cancer risk was found (p > 0.05).

Conclusion

Our findings add to the current literature by validating a positive relationship between high BMR levels and CRC risk instead of reverse causality. The genetically predicted BMR level was causally associated with colon cancer risk but not rectal cancer risk.