Choline supplementation attenuates experimental sepsis-associated acute kidney injury

Serum and Urine Metabolites and Kidney Function

Key Points

Background

Metabolites represent a read-out of cellular processes underlying states of health and disease.

Methods

We evaluated cross-sectional and longitudinal associations between 1255 serum and 1398 urine known and unknown (denoted with “X” in name) metabolites (Metabolon HD4, 721 detected in both biofluids) and kidney function in 1612 participants of the Atherosclerosis Risk in Communities study. All analyses were adjusted for clinical and demographic covariates, including for baseline eGFR and urine albumin-creatinine ratio (UACR) in longitudinal analyses.

Results

At visit 5 of the Atherosclerosis Risk in Communities study, the mean age of participants was 76 years (SD 6); 56% were women, mean eGFR was 62 ml/min per 1.73 m2 (SD 20), and median UACR level was 13 mg/g (interquartile range, 25). In cross-sectional analysis, 675 serum and 542 urine metabolites were associated with eGFR (Bonferroni-corrected P < 4.0E-5 for serum analyses and P < 3.6E-5 for urine analyses), including 248 metabolites shared across biofluids. Fewer metabolites (75 serum and 91 urine metabolites, including seven metabolites shared across biofluids) were cross-sectionally associated with albuminuria. Guanidinosuccinate; N2,N2-dimethylguanosine; hydroxy-N6,N6,N6-trimethyllysine; X-13844; and X-25422 were significantly associated with both eGFR and albuminuria. Over a mean follow-up of 6.6 years, serum mannose (hazard ratio [HR], 2.3 [1.6–3.2], P = 2.7E-5) and urine X-12117 (HR, 1.7 [1.3–2.2], P = 1.9E-5) were risk factors of UACR doubling, whereas urine sebacate (HR, 0.86 [0.80–0.92], P = 1.9E-5) was inversely associated. Compared with clinical characteristics alone, including the top five endogenous metabolites in serum and urine associated with longitudinal outcomes improved the outcome prediction (area under the receiver operating characteristic curves for eGFR decline: clinical model=0.79, clinical+metabolites model=0.87, P = 8.1E-6; for UACR doubling: clinical model=0.66, clinical+metabolites model=0.73, P = 2.9E-5).

Conclusions

Metabolomic profiling in different biofluids provided distinct and potentially complementary insights into the biology and prognosis of kidney diseases.

Enhanced STAT3/PIK3R1/mTOR signaling triggers tubular cell inflammation and apoptosis in septic-induced acute kidney injury: implications for therapeutic intervention

Septic acute kidney injury (AKI) is a severe form of renal dysfunction associated with high morbidity and mortality rates. However, the pathophysiological mechanisms underlying septic AKI remain incompletely understood. Herein, we investigated the signaling pathways involved in septic AKI using the mouse models of lipopolysaccharide (LPS) treatment and cecal ligation and puncture (CLP). In these models, renal inflammation and tubular cell apoptosis were accompanied by the aberrant activation of the mechanistic target of rapamycin (mTOR) and the signal transducer and activator of transcription 3 (STAT3) signaling pathways. Pharmacological inhibition of either mTOR or STAT3 significantly improved renal function and reduced apoptosis and inflammation. Interestingly, inhibition of STAT3 with pharmacological inhibitors or small interfering RNA blocked LPS-induced mTOR activation in renal tubular cells, indicating a role of STAT3 in mTOR activation. Moreover, knockdown of STAT3 reduced the expression of the phosphoinositide-3-kinase regulatory subunit 1 (PIK3R1/p85α), a key subunit of the phosphatidylinositol 3-kinase for AKT and mTOR activation. Chromatin immunoprecipitation assay also proved the binding of STAT3 to PIK3R1 gene promoter in LPS-treated kidney tubular cells. In addition, knockdown of PIK3R1 suppressed mTOR activation during LPS treatment. These findings highlight the dysregulation of mTOR and STAT3 pathways as critical mechanisms underlying the inflammatory and apoptotic phenotypes observed in renal tubular cells during septic AKI, suggesting the STAT3/ PIK3R1/mTOR pathway as a therapeutic target of septic AKI.

SAH and SAM/SAH ratio associate with acute kidney injury in critically ill patients: A case-control study

BACKGROUND

Acute kidney injury (AKI) is a serious clinical emergency with an acute onset, rapid progression and poor prognosis, which has high morbidity and mortality in hospitalized patients. DNA methylation plays an important role in the occurrence and progression of kidney disease, and aberrant methylation and certain altered methylation-related metabolites have been reported in AKI patients. However, the specific alterations of methylation-related metabolites in the AKI patients were not investigated clearly.

METHOD

In this study, 61 AKI and 61 matched non-AKI inpatients were recruited after propensity score matching the age and hypertension. And 11 methylation-related metabolites in the plasma and urine of the two groups were quantified by using UHPLC-MS/MS method.

RESULTS

Certain methylation-relate intermediates were up-regulated in the plasma (choline, trimethylamine N-oxide (TMAO), trimethyl lysine (TML), S-adenosylmethionine (SAM) and S-adenosylhomocysteine (SAH)) and down-regulated in the urine of AKI inpatients (choline, betaine, TMAO, dimethylglycine (DMG), SAM and taurine). The correlation analysis revealed a relatively strong correlation between plasma SAH, SAM/SAH ratio and renal function index (serum creatinine (SCr) and estimated glomerular filtration rate (eGFR), r = 0.523-0.616), and the correlation of urinary intermediates with renal function index was weaker than that in the plasma. Furthermore, receiver operating characteristic (ROC) analysis showed that plasma SAH and urinary SAM/SAH ratio represented the best distinguishing efficiency with AUC 0.844 and 0.794, respectively. Moreover, the findings of binary regression analysis demonstrated plasma choline, TMAO, TML, SAM and SAH were the risk markers of AKI (up-regulation in plasma, OR > 1), urinary choline, betaine, TMAO, DMG and SAM were protective markers of AKI (down-regulation in urine, OR < 1), and SAM/SAH ratio was a protective marker in plasma and urine (down-regulation in both two biofluids, OR = 0.510, 0.383-0.678 in plasma, OR = 0.904, 0.854-0.968 in urine), indicating the increased risk of AKI when combined with the alteration of plasma and urinary levels.

CONCLUSION

The comprehensive analysis of plasma and urine samples from AKI inpatients offers a more extensive assessment of methylated metabolic alterations, suggesting a close relationship between AKI stress and altered methylation ability. The plasma level of SAH and SAM/SAH ratio and urinary SAM/SAH ratio both showed a strong correlation with renal function (SCr and eGFR) and good accuracy for distinguishing AKI in the two biomatrices, which exhibited promising prospects in predicting renal function decline and providing further information for the pathogenesis of AKI.

Targets and Mechanisms of Xuebijing in the Treatment of Acute Kidney Injury Associated with Sepsis: A Network Pharmacology-based Study

INTRODUCTION

Sepsis is a state of the systemic inflammatory response of the host induced by infection, frequently affecting numerous organs and producing varied degrees of damage. The most typical consequence of sepsis is sepsis-associated acute kidney injury(SA-AKI). Xuebijing is developed based on XueFuZhuYu Decoction. Five Chinese herbal extracts, including Carthami Flos, Radix Paeoniae Rubra, Chuanxiong Rhizoma, Radix Salviae, and Angelicae Sinensis Radix, make up the majority of the mixture. It has properties that are anti-inflammatory and anti-oxidative stress. Xuebijing is an effective medication for the treatment of SA-AKI, according to clinical research. But its pharmacological mechanism is still not completely understood.

METHODS

First, the composition and target information of Carthami Flos, Radix Paeoniae Rubra, Chuanxiong Rhizoma, Radix Salviae, and Angelicae Sinensis Radix were collected from the TCMSP database, while the therapeutic targets of SA-AKI were exported from the gene card database. To do a GO and KEGG enrichment analysis, we first screened the key targets using a Venn diagram and Cytoscape 3.9.1. To assess the binding activity between the active component and the target, we lastly used molecular docking.

RESULTS

For Xuebijing, a total of 59 active components and 267 corresponding targets were discovered, while for SA-AKI, a total of 1,276 targets were connected. There were 117 targets in all that was shared by goals for active ingredients and objectives for diseases. The TNF signaling pathway and the AGE-RAGE pathway were later found to be significant pathways for the therapeutic effects of Xuebijing by GO analysis and KEGG pathway analysis. Quercetin, luteolin, and kaempferol were shown to target and modulate CXCL8, CASP3, and TNF, respectively, according to molecular docking results.

CONCLUSION

This study predicts the mechanism of action of the active ingredients of Xuebijing in the treatment of SA-AKI, which provides a basis for future applications of Xuebijing and studies targeting the mechanism.