The global population over 60 years old is projected to reach 1.5 billion by 2050. Understanding age-related disorders and gender-specificities is crucial for a healthy aging. Reliable age-related biomarkers are needed, preferentially obtained through non-invasive methods. Urine-derived stem cells (UDSCs) can be easily obtained, although a detailed bioenergetic characterization, according to the donor aging, remain unexplored. UDSCs were isolated from young and elderly adult women (22-35 and 70-94 years old, respectively). Surprisingly, UDSCs from elderly subjects exhibited significantly higher maximal oxygen consumption and bioenergetic health index than those from younger individuals, evaluated through oxygen consumption rate. Exploratory data analysis methods were applied to engineer a minimal subset of features for the classification and stratification of UDSCs. Additionally, RNAseq of UDSCs was performed to identify age-related transcriptional changes. Transcriptional analysis revealed downregulation of genes related to glucuronidation and estrogen metabolism, and upregulation of inflammation-related genes in UDSCs from elderly individuals. This study demonstrates unexpected differences in the UDSCs' OCR between young and elderly individuals, revealing improved bioenergetics in concurrent with an aged-like transcriptome signature. UDSCs offer a non-invasive model for studying age-related changes, holding promise for aging research and therapeutic studies.
Keywords: Aging; Machine learning; Metabolism; Mitochondria; Transcriptome; Urine-derived stem cells; Women.
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