Metabolic profile changes of kidney aging and protective effects of Polygonatum sibiricum polysaccharides on D-galactose-induced aging mice

Objective

To investigate the metabolic trajectory of kidney aging and the effects of Polygonatum sibiricum polysaccharides (PSP) against kidney aging in D-galactose (D-gal)-induced aging mice, based on ultra-performance liquid chromatography/Q-Exactive Orbitrap mass spectrometry (UPLC-Q-Exactive MS/MS).

Methods

A total of 36 C57 BL/6J mice were randomly allocated to six groups: control (CON), model (MOD), PSP low-dose (PSP-L), PSP medium-dose (PSP-M), PSP high-dose (PSP-H), and positive drug ascorbic acid (VC) groups. To create models of aging mice, D-gal was intraperitoneally administered to all other groups of mice except the CON group. After modeling, the appropriate Chinese medicine [PSP-L: 150 mg/(kg·d), PSP-M: 300 mg/(kg·d), PSP-H: 600 mg/(kg·d)] or positive drug [ascorbic acid, 300 mg/(kg·d)] was administered for intervention. Key markers of renal function in urine and serum of mice in each group, such as creatinine (Crea), urea nitrogen (BUN), and uric acid (UA) levels, as well as key indicators of oxidative stress in serum and kidney, including superoxide dismutase (SOD), catalase (CAT), malondialdehyde (MDA), and glutathione peroxidase (GSH-Px) were determined to validate the successful establishment of kidney aging models and to estimate the effects of PSP. Hematoxylin and eosin (HE), periodic acid Schiff (PAS), and β-galactosidase staining were used to assess the renal pathological changes. The metabolic profiles of serum, kidney, and urine samples from CON, MOD, and PSP-H groups were analyzed by UPLC-Q-Exactive MS/MS, and pattern recognition methods were used to outline the metabolic trajectory of kidney aging and to identify the characteristic metabolites.

Results

Age-related alterations in renal histopathology and impaired renal function in mice were also associated with oxidative stress indicators. Following the injection of PSP [PSP-H: 600 mg/(kg·d)], the pathological indices associated with aging were adjusted to normal levels, renal function and oxidative stress were improved in aging mice, and renal pathological damage was markedly improved. Meanwhile, the potential biomarkers were identified by UPLC-Q-Exactive MS/MS analysis and were further analyzed to form related metabolic pathways, with P < 0.05 as a threshold. The results showed that purine, sphingolipid, glycerophospholipid, tryptophan, and riboflavin metabolisms were the main metabolic pathways associated with aging. After administration of PSP, these pathological indices returned to normal levels, and biomarkers related to the aging process, such as adenosine monophosphate (AMP), tryptophan, and 5-hydroxytryptophan, also demonstrated, to some degree, reverse regulation (promoting synthesis).

Conclusion

Metabolomics methods based on UPLC-Q-Exactive MS/MS and multivariate statistical analysis can be adopted to establish metabolic profiles in aging mice. PSP has been shown to protect against kidney aging by interfering with the purine, sphingolipid, glycerophospholipid, tryptophan, and riboflavin metabolisms in the kidney.