Cardiometabolic risk factors are associated with immune cell mitochondrial respiration in humans

Abstract

Modifiable cardiometabolic risk factors induce the release of pro-inflammatory cytokines and reactive oxygen species from circulating peripheral blood mononuclear cells (PBMCs) resulting in increased cardiovascular disease risk and compromised immune health. These changes may be driven by metabolic reprogramming of PBMCs resulting in impaired mitochondrial respiration; however, this has not been fully tested. We aimed to determine the independent associations between cardiometabolic risk factors, such as blood pressure, BMI, and plasma lipids with impaired mitochondrial respiration in PBMCs isolated from generally healthy individuals (n=21) across the adult lifespan (12 M/ 9 F; age: 56 ± 21 years; age-range: 22-78 year; blood pressure: 123 ± 16 / 72 ± 10 mmHg; low-density lipoprotein cholesterol, LDL-C: 111 ± 22 mg/dL; and high-density lipoprotein cholesterol, HDL-C: 62 ± 16 mg/dL). PBMCs were isolated from whole blood by density dependent centrifugation and used to assess mitochondrial function by respirometry. Primary outcomes included baseline and maximal oxygen consumption rate (OCR) which were subsequently used to determine spare respiratory capacity and OCR metabolic potential. After correcting for HDL-C, SBP, and age, LDL-C was negatively associated with maximal respiration (r=-0.61, P=0.0073), spare respiratory capacity (r=-0.65, P=0.0038) and OCR metabolic potential (r=-0.59, P=0.010), respectively. In addition, there was a strong, but non-significant positive association between HDL-C and maximal respiration (r=0.46, P=0.057) and spare respiratory capacity (r=0.43, P=0.075), after correcting for other covariates. These data suggest a link between blood cholesterol and mitochondrial health that may provide insight into how cardiometabolic risk factors contribute to impaired immune cell function.

Protein Supplementation Does Not Maximize Adaptations to Low-Volume High-Intensity Interval Training in Sedentary, Healthy Adults: A Placebo-Controlled Double-Blind Randomized Study

“…These suggestions are mainly derived from a small number of studies, showing that post-endurance-exercise protein ingestion may increase myofibrillar synthesis and/or activators of mitochondrial biogenesis such as peroxisome proliferator-activated receptor gamma coactivator-1 alpha (PGC-1α) [ 54 , 55 , 56 ]. Given that mitochondrial function and capacity are closely related to CRF [ 57 ] and cardiometabolic health [ 58 , 59 ], the potential beneficial impact of post-exercise protein ingestion on maximizing the training-related adaptations of the mitochondria, as detected in previous studies, is encouraging. However, it has also been pointed out that the evidence of the role of protein supplementation on endurance-training adaptations is still rather inconclusive.…”

Understanding Long COVID; Mitochondrial Health and Adaptation—Old Pathways, New Problems

“…In fact, is has been suggested that the link between cardiometabolic risk factors and altered immune cell function is via reduced respiratory capacity, and a recent study did show this in apparently healthy individuals with some risk markers—hinting at immune cell reprogramming towards glycolysis [ 234 ]. Platelets can also be used to measure mitochondrial function, are easier to isolate than PBMCs, and they do seem to reflect overall systemic mitochondrial function; initial studies in runners before and after an event do seem to support this [ 144 , 235 ].…”

Novel standardized method for extracellular flux analysis of oxidative and glycolytic metabolism in peripheral blood mononuclear cells

“…A standardized XF assay protocol ensures reliable and comparable results across different PBMC donors, which increases the applicability of human PBMCs in experimental studies. Over the past decade, several clinical studies tested the applicability of metabolic PBMC responses as marker in the context of multiple disease pathologies such as diabetes 19 , 20 , 34 , 54 , 55 , cardiovascular disease 35 , 56 , obesity 21 , inherited metabolic diseases 22 , 57 , neurodegenerative diseases 23 , 58 , autoimmune disease 24 and schizophrenia 59 , as well as in the context of altered physiological conditions such as pregnancy 25 or responses to changed micronutrient status 33 . Future use of brightfield image analysis in such studies will standardize the XF assay workflow and improve data interpretation and comparison across studies.…”

“…Normalization of XF assay results is critical for accurate and consistent data interpretation and comparison. Multiple parameters for XF assay data normalization in PBMCs have been used, of which normalization to the number of plated cells via pre-XF assay cell counting has been mostly applied 20 , 21 , 24 , 33 – 35 . However, cell number and cell layer distribution are affected by daily and operator variation in counting, plating and handling, which can lead to inaccurate normalization.…”