bioRxivPhysiologyPreprint
Blood mitochondrial health markers cf-mtDNA and GDF15 in human aging
Caroline TrumpffiD, Qiuhan HuangiD, Jeremy MichelsoniD, Cynthia C. LiuiD, David Shire, Christian Georg HabeckiD, Yaakov SterniD, Martin A. PicardiD
Abstract
Altered mitochondria biology can accelerate biological aging, but scalable biomarkers of mitochondrial health for population studies are lacking. We examined two potential candidates: 1) cell-free mitochondrial DNA (cf-mtDNA), a marker of mitochondrial signaling elevated with disease states accessible as distinct biological entities from plasma or serum; and 2) growth differentiation factor 15 (GDF15), an established biomarker of biological aging downstream of mitochondrial energy transformation defects and stress signaling. In a cohort of 430 participants aged 24-84 (54.2% women), we measured plasma and serum cf-mtDNA, and plasma GDF15 levels at two timepoints 5 years apart, then assessed their associations with age, BMI, diabetes, sex, health-related behaviors, and psychosocial factors. As expected, GDF15 showed a positive, exponential association with age (r=0.66, p<0.0001) and increased by 33% over five years. cf-mtDNA was not correlated with GDF15 or age. BMI and sex were also not related to cf-mtDNA nor GDF15. Type 2 diabetes was only positively associated with GDF15. Exploring potential drivers of systemic mitochondrial stress signaling, we report a novel association linking higher education to lower age-adjusted GDF15 (r=-0.14, p<0.0034), both at baseline and the 5-year follow up, highlighting a potential influence of psychosocial factors on mitochondrial health. Overall, our findings among adults spanning six decades of lifespan establish associations between age, diabetes and GDF15, an emerging marker of mitochondrial stress signaling. Further studies are needed to determine if the associations of blood GDF15 with age and metabolic stress can be moderated by psychosocial factors or health-related behaviors.
- organism: human
- assay: proteomics
- research focus: host-pathogen & immune response
- approach: statistical model
- Citations
- 13
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