Fecal microbiota composition is related to brown adipose tissue 18F-fluorodeoxyglucose uptake in young adults.

OBJECTIVE: Human brown adipose tissue (BAT) has gained considerable attention as a potential therapeutic target for obesity and its related cardiometabolic diseases; however, whether the gut microbiota might be an efficient stimulus to activate BAT metabolism remains to be ascertained. We aimed to investigate the association of fecal microbiota composition with BAT volume and activity and mean radiodensity in young adults. METHODS: 82 young adults (58 women, 21.8 ± 2.2 years old) participated in this cross-sectional study. DNA was extracted from fecal samples and 16S rRNA sequencing was performed to analyse the fecal microbiota composition. BAT was determined via a static 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography-computed tomography scan (PET/CT) after a 2 h personalized cooling protocol. 18F-FDG uptake was also quantified in white adipose tissue (WAT) and skeletal muscles. RESULTS: The relative abundance of Akkermansia, Lachnospiraceae sp. and Ruminococcus genera was negatively correlated with BAT volume, BAT SUVmean and BAT SUVpeak (all rho ≤ - 0.232, P ≤ 0.027), whereas the relative abundance of Bifidobacterium genus was positively correlated with BAT SUVmean and BAT SUVpeak (all rho ≥ 0.262, P ≤ 0.012). On the other hand, the relative abundance of Sutterellaceae and Bifidobacteriaceae families was positively correlated with 18F-FDG uptake by WAT and skeletal muscles (all rho ≥ 0.213, P ≤ 0.042). All the analyses were adjusted for the PET/CT scan date as a proxy of seasonality. CONCLUSION: Our results suggest that fecal microbiota composition is involved in the regulation of BAT and glucose uptake by other tissues in young adults. Further studies are needed to confirm these findings. CLINICAL TRIAL INFORMATION: ClinicalTrials.gov no. NCT02365129 (registered 18 February 2015).

Inter- and intra-researcher reproducibility of heart rate variability parameters in three human cohorts.

Heart rate variability (HRV) is a valid and non-invasive indicator of cardiac autonomic nervous system functioning. Short-term HRV recordings (e.g., 10 min long) produce data that usually is manually processed. Researcher subjective decision-making on data processing could produce inter- or intra-researcher differences whose magnitude has not been previously quantified in three independent human cohorts. This study examines the inter- and intra-researcher reproducibility of HRV parameters (i.e., the influence of R-R interval selection by different researchers and by the same researcher in different moments on the quantification of HRV parameters, respectively) derived from short-term recordings in a cohort of children with overweight/obesity, young adults and middle-age adults. Participants were recruited from 3 different studies: 107 children (10.03 ± 1.13 years, 58% male), 132 young adults (22.22 ± 2.20 years, 33% males) and 73 middle-aged adults (53.62 ± 5.18 years, 48% males). HRV was measured using a Polar RS800CX heart rate monitor. The intraclass correlation coefficient (ICC) ranged from 0.703 to 0.989 and from 0.950 to 0.998 for inter-and intra-researcher reproducibility, respectively. Limits of agreement for HRV parameters were higher for the inter-researcher processing compared with the intra-researcher processing. On average, the intra-researcher differences were 31%, 62%, and 80% smaller than the inter-researchers differences based on Coefficient of Variation in children, young and middle-aged adults, respectively. Our study provides the quantification of the inter-researcher and intra-researcher differences in three independent human cohorts, which could elicit some clinical relevant differences for HRV parameters. Based on our findings, we recommend the HRV data signal processing to be performed always by the same trained researcher and we postulate a development of algorithms for an automatic ECG selection.