Mitochondrial respiration variability and simulations in human skeletal muscle: The Gene SMART study. Issue 2 (9th January 2020)

• Record Type: Journal Article
• Authors: Jacques, Macsue; Kuang, Jujiao; Bishop, David J.; Yan, Xu; Alvarez‐Romero, Javier; Munson, Fiona; Garnham, Andrew; Papadimitriou, Ioannis; Voisin, Sarah; Eynon, Nir
• Is Part Of: FASEB journal. Volume 34:Issue 2(2020)
• Page Start: 2978
• Page End: 2986
• Publication Date: 2020-01-09
• Subjects: exercise -- intervention -- mitochondria -- OXPHOS -- oxygen consumption; Biology -- Periodicals; Biology, Experimental -- Periodicals; 570
• DOI: 10.1096/fj.201901997RR
• Languages: English
• ISSNs: 0892-6638

Abstract

Abstract: Mitochondrial respiration using the oxygraph‐2k respirometer (Oroboros) is widely used to estimate mitochondrial capacity in human skeletal muscle. Here, we measured mitochondrial respiration variability, in a relatively large sample, and for the first time, using statistical simulations, we provide the sample size required to detect meaningful respiration changes following lifestyle intervention. Muscle biopsies were taken from healthy, young men from the Gene SMART cohort, at multiple time points. We utilized samples for each measurement with two technical repeats using two respirometer chambers (n = 160 pairs of same muscle after removal of low‐quality samples). We measured the Technical Error of measurement (TEM ) and the coefficient of variation (CV) for each mitochondrial complex. There was a high correlation between measurements from the two chambers ( R > 0.7 P < .001) for all complexes, but the TEM was large (7.9‐27 pmol s −1 mg −1 ; complex dependent), and the CV was >15% for all complexes. We performed statistical simulations of a range of effect sizes at 80% power and found that 75 participants (with duplicate measurements) are required to detect a 6% change in mitochondrial respiration after an intervention, while for interventions with 11% effect size, ~24 participants are sufficient. The high variability in respiration suggests that the typical sample sizes in exercise studies may not be sufficient to capture exercise‐induced changes.