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

Limeng Ning; Changjing He; Chunliu Lu; Wanzhong Huang; Ting Zeng; Qiang Su

doi:10.1016/j.heliyon.2024.e28154

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

Heliyon. 2024 Mar 23;10(7):e28154. doi: 10.1016/j.heliyon.2024.e28154. eCollection 2024 Apr 15.

Authors

Limeng Ning¹, Changjing He^{2

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20}, Chunliu Lu³, Wanzhong Huang¹, Ting Zeng²¹, Qiang Su¹

Affiliations

¹ Department of Cardiology, Jiangbin Hospital of Guangxi Zhuang Autonomous Region, No. 85 Hedi Road, Nanning, Guangxi, 530021, China.
² Pediatric surgery, Affiliated Hospital of Youjiang Medical University for Nationalities, Youjiang Medical University for Nationalities, Baise, China.
³ Health Management Service Center, Jiangbin Hospital of Guangxi Zhuang Autonomous Region, No.85 Hedi Road, Nanning, Guangxi, 530021, China.
⁴ Guangxi Clinical Medical Research Center for Hepatobiliary Diseases, China.
⁵ Guangxi Zhuang Autonomous Region Engineering Research Center for Biomaterials in Bone and Joint Degenerative Diseases, China.
⁶ Guangxi Key Laboratory for Preclinica1 and Translational Research on Bone and Joint Degenerative Diseases, China.
⁷ Guangxi Key Laboratory of Molecular Pathology in Hepatobiliary Diseases, China.
⁸ Guangxi Key Laboratory of Clinical Cohort Research on Bone and Joint Degenerative Disease, China.
⁹ Guangxi Key Laboratory of Medical Research Basic Guarantee for Immune-Related Disease Research, China.
¹⁰ Guangxi Key Laboratory for Biomedical Material Research, China.
¹¹ Key Laboratory of Research on Prevention and Control of High Incidence Diseases in Western Guangxi, China.
¹² Key Laboratory of Molecular Pathology in Tumors of Guangxi, China.
¹³ Key Laboratory of Research on Clinical Molecular Diagnosis for High Incidence Diseases in Western Guangxi, China.
¹⁴ Baise Key Laboratory of Mo1ecular Pathology in Tumors, China.
¹⁵ Baise Key Laboratory for Metabolic Diseases, China.
¹⁶ Baise Key Laboratory for Research and Deve1opment on Clinical Mo1ecular Diagnosis for High-Incidence Diseases, China.
¹⁷ Key Laboratory of the Bone and Joint Degenerative Diseases, China.
¹⁸ Laboratory of the Atherosclerosis and Ischemic Cardiovascular Diseases, China.
¹⁹ Life Science and C1inical Medicine Research Center, China.
²⁰ Key Laboratory of Clinical Diagnosis and Treatment Research of High Incidence Diseases in Guangxi, China.
²¹ Health Management Service Center, Jiangbin Hospital of Guangxi Zhuang Autonomous Region, No. 85 Hedi Road, Nanning, Guangxi, 530021, China.

Abstract

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.

Keywords: Basal metabolic rate; Cardio-metabolic risk factors; Evidence; Mendelian randomization.