Assessment of the bi-directional relationship between blood mitochondrial DNA copy number and type 2 diabetes mellitus: a multivariable-adjusted regression and Mendelian randomisation study.

AIMS/HYPOTHESIS: Mitochondrial dysfunction, which can be approximated by blood mitochondrial DNA copy number (mtDNA-CN), has been implicated in the pathogenesis of type 2 diabetes mellitus. Thus far, however, insights from prospective cohort studies and Mendelian randomisation (MR) analyses on this relationship are limited. We assessed the association between blood mtDNA-CN and incident type 2 diabetes using multivariable-adjusted regression analyses, and the associations between blood mtDNA-CN and type 2 diabetes and BMI using bi-directional MR. METHODS: Multivariable-adjusted Cox proportional hazard models were used to estimate the association between blood mtDNA-CN and incident type 2 diabetes in 285,967 unrelated European individuals from UK Biobank free of type 2 diabetes at baseline. Additionally, a cross-sectional analysis was performed to investigate the association between blood mtDNA-CN and BMI. We also assessed the potentially causal relationship between blood mtDNA-CN and type 2 diabetes (N=898,130 from DIAGRAM, N=215,654 from FinnGen) and BMI (N=681,275 from GIANT) using bi-directional two-sample MR. RESULTS: During a median follow-up of 11.87 years, 15,111 participants developed type 2 diabetes. Participants with a higher level of blood mtDNA-CN are at lower risk of developing type 2 diabetes (HR 0.90 [95% CI 0.89, 0.92]). After additional adjustment for BMI and other confounders, these results attenuated moderately and remained present. The multivariable-adjusted cross-sectional analyses showed that higher blood mtDNA-CN was associated with lower BMI (-0.12 [95% CI -0.14, -0.10]) kg/m2. In the bi-directional MR analyses, we found no evidence for causal associations between blood mtDNA-CN and type 2 diabetes, and blood mtDNA-CN and BMI in either direction. CONCLUSIONS/INTERPRETATION: The results from the present study indicate that the observed association between low blood mtDNA-CN and higher risk of type 2 diabetes is likely not causal.

Assessment of reproducibility and biological variability of fasting and postprandial plasma metabolite concentrations using 1H NMR spectroscopy.

INTRODUCTION: It is crucial to understand the factors that introduce variability before applying metabolomics to clinical and biomarker research. OBJECTIVES: We quantified technical and biological variability of both fasting and postprandial metabolite concentrations measured using 1H NMR spectroscopy in plasma samples. METHODS: In the Netherlands Epidemiology of Obesity study (n = 6,671), 148 metabolite concentrations (101 metabolites belonging to lipoprotein subclasses) were measured under fasting and postprandial states (150 minutes after a mixed liquid meal). Technical variability was evaluated among 265 fasting and 851 postprandial samples, with the identical blood plasma sample being measured twice by the same laboratory protocol. Biological reproducibility was assessed by measuring 165 individuals twice across time for evaluation of short- (<6 months) and long-term (>3 years) biological variability. Intra-class coefficients (ICCs) were used to assess variability. The ICCs of the fasting metabolites were compared with the postprandial metabolites using two-sided paired Wilcoxon test separately for short- and long-term measurements. RESULTS: Both fasting and postprandial metabolite concentrations showed high technical reproducibility using 1H NMR spectroscopy (median ICC = 0.99). Postprandial metabolite concentrations revealed slightly higher ICC scores than fasting ones in short-term repeat measures (median ICC in postprandial and fasting metabolite concentrations 0.72 versus 0.67, Wilcoxon p-value = 8.0×10-14). Variability did not increase further in a long-term repeat measure, with median ICC in postprandial of 0.64 and in fasting metabolite concentrations 0.66. CONCLUSION: Technical reproducibility is excellent. Biological reproducibility of postprandial metabolite concentrations showed a less or equal variability than fasting metabolite concentrations over time.

Estimation of activity related energy expenditure and resting metabolic rate in freely moving mice from indirect calorimetry data.

Physical activity (PA) is a main determinant of total energy expenditure (TEE) and has been suggested to play a key role in body weight regulation. However, thus far it has been challenging to determine what part of the expended energy is due to activity in freely moving subjects. We developed a computational method to estimate activity related energy expenditure (AEE) and resting metabolic rate (RMR) in mice from activity and indirect calorimetry data. The method is based on penalised spline regression and takes the time dependency of the RMR into account. In addition, estimates of AEE and RMR are corrected for the regression dilution bias that results from inaccurate PA measurements. We evaluated the performance of our method based on 500 simulated metabolic chamber datasets and compared it to that of conventional methods. It was found that for a sample time of 10 minutes the penalised spline model estimated the time-dependent RMR with 1.7 times higher accuracy than the Kalman filter and with 2.7 times higher accuracy than linear regression. We assessed the applicability of our method on experimental data in a case study involving high fat diet fed male and female C57Bl/6J mice. We found that TEE in male mice was higher due to a difference in RMR while AEE levels were similar in both groups, even though female mice were more active. Interestingly, the higher activity did not result in a difference in AEE because female mice had a lower caloric cost of activity, which was likely due to their lower body weight. In conclusion, TEE decomposition by means of penalised spline regression provides robust estimates of the time-dependent AEE and RMR and can be applied to data generated with generic metabolic chamber and indirect calorimetry set-ups.

Skeletal muscle mitochondrial uncoupling, adaptive thermogenesis and energy expenditure.

PURPOSE OF REVIEW: The prevalence of obesity is still increasing, despite obesity treatment strategies that aim at reducing energy intake. In addition to this, exercise programmes designed to increase energy expenditure have only a low efficiency and have generated mixed results. Therefore, strategies based on increasing energy expenditure via nonexercise means are currently under investigation. One novel strategy is the modulation of adaptive thermogenesis. RECENT FINDINGS: Among others, adaptive thermogenesis can be modulated by changing dietary composition, treatment with hormone mimetics as well as by cold exposure. In humans, a large part of the adaptive thermogenic response is, in addition to a putative role of brown adipose tissue, determined by the skeletal muscle mass via the process of mitochondrial uncoupling. Here, we describe the molecular processes involved in mitochondrial uncoupling, state-of-the-art techniques to measure mitochondrial uncoupling in vitro and in vivo, as well as the current strategies to mitochondrial uncoupling. SUMMARY: Data generated in rodents and humans implicate that increasing adaptive thermogenesis by increasing skeletal muscle mitochondrial uncoupling indeed elevates total energy expenditure and thus may provide a promising target for the treatment of obesity.