Sphingolipids and Kidney Disease: Possible Role of Preeclampsia and Intrauterine Growth Restriction (IUGR)

Untargeted Urinary Volatilomics Reveals Hexadecanal as a Potential Biomarker for Preeclampsia

Preeclampsia (PE) is a severe hypertensive pregnancy disorder characterized by endothelial dysfunction, placental ischemia and oxidative stress; however, reliable non-invasive biomarkers for early detection are limited. In this study, untargeted solid-phase microextraction with gas chromatography-mass spectrometry (SPME-GC-MS) was used to analyze volatile organic compounds in the urine of 45 women with PE and 46 healthy controls. Among the 29 metabolites identified, hexadecanal-a product of lipid peroxidation and sphingolipid metabolism-was found to be the most significant, with an area under the receiver operating characteristic (ROC) curve of 0.618, highlighting its diagnostic potential. This result emphasizes the role of hexadecanal in oxidative stress and placental dysfunction, which are central to the pathophysiology of PE. The results support hexadecanal as a potential non-invasive biomarker while demonstrating the efficacy of SPME-GC-MS in identifying metabolic disorders associated with PE, paving the way for further research to confirm its clinical utility for early diagnosis and risk assessment.

Machine learning models to identify lead compound and substitution optimization to have derived energetics and conformational stability through docking and MD simulations for sphingosine kinase 1

Sphingosine kinases (SphKs) are a group of important enzymes that circulate at low micromolar concentrations in mammals and have received considerable attention due to the roles they play in a broad array of biological processes including apoptosis, mutagenesis, lymphocyte migration, radio- and chemo-sensitization, and angiogenesis. In the present study, we constructed three classification models by four machine learning (ML) algorithms including naive bayes (NB), support vector machine (SVM), logistic regression, and random forest from 395 compounds. The generated ML models were validated by fivefold cross validation. Five different scaffold hit fragments resulted from SVM model-based virtual screening and docking results indicate that all the five fragments exhibit common hydrogen bond interaction a catalytic residue of SphK1. Further, molecular dynamics (MD) simulations and binding free energy calculation had been carried out with the identified five fragment leads and three cocrystal inhibitors. The best 15 fragments were selected. Molecular dynamics (MD) simulations showed that among these compounds, 7 compounds have favorable binding energy compared with cocrystal inhibitors. Hence, the study showed that the present lead fragments could act as potential inhibitors against therapeutic target of cancers and neurodegenerative disorders.

Sphingolipids and Chronic Kidney Disease

Sphingolipids (SLs) are bioactive signaling molecules essential for various cellular processes, including cell survival, proliferation, migration, and apoptosis. Key SLs such as ceramides, sphingosine, and their phosphorylated forms play critical roles in cellular integrity. Dysregulation of SL levels is implicated in numerous diseases, notably chronic kidney disease (CKD). This review focuses on the role of SLs in CKD, highlighting their potential as biomarkers for early detection and prognosis. SLs maintain renal function by modulating the glomerular filtration barrier, primarily through the activity of podocytes. An imbalance in SLs can lead to podocyte damage, contributing to CKD progression. SL metabolism involves complex enzyme-catalyzed pathways, with ceramide serving as a central molecule in de novo and salvage pathways. Ceramides induce apoptosis and are implicated in oxidative stress and inflammation, while sphingosine-1-phosphate (S1P) promotes cell survival and vascular health. Studies have shown that SL metabolism disorders are linked to CKD progression, diabetic kidney disease, and glomerular diseases. Targeting SL pathways could offer novel therapeutic approaches for CKD. This review synthesizes recent research on SL signaling regulation in kidney diseases, emphasizing the importance of maintaining SL balance for renal health and the potential therapeutic benefits of modulating SL pathways.

A multi-tissue metabolome atlas of primate pregnancy

Pregnancy induces dramatic metabolic changes in females; yet, the intricacies of this metabolic reprogramming remain poorly understood, especially in primates. Using cynomolgus monkeys, we constructed a comprehensive multi-tissue metabolome atlas, analyzing 273 samples from 23 maternal tissues during pregnancy. We discovered a decline in metabolic coupling between tissues as pregnancy progressed. Core metabolic pathways that were rewired during primate pregnancy included steroidogenesis, fatty acid metabolism, and arachidonic acid metabolism. Our atlas revealed 91 pregnancy-adaptive metabolites changing consistently across 23 tissues, whose roles we verified in human cell models and patient samples. Corticosterone and palmitoyl-carnitine regulated placental maturation and maternal tissue progenitors, respectively, with implications for maternal preeclampsia, diabetes, cardiac hypertrophy, and muscle and liver regeneration. Moreover, we found that corticosterone deficiency induced preeclampsia-like inflammation, indicating the atlas's potential clinical value. Overall, our multi-tissue metabolome atlas serves as a framework for elucidating the role of metabolic regulation in female health during pregnancy.

Death receptor 3 is involved in preeclampsia through regulating placental trophoblast cell physiology by inactivating the PI3K/AKT pathway

BACKGROUND

Preeclampsia (PE) is a pregnancy related disease that affects about 5% of pregnancies. Death receptor 3 (DR3) expression is significantly elevated in both placental tissue and plasma of PE patients. However, whether DR3 was involved in trophoblasts in pathogenesis of PE are not well elucidated.

OBJECTIVE

Our research was designed to illustrate the biological roles of DR3 in placental trophoblasts, as well as explain its relevant mechanisms.

METHODS

HTR-8/SVneo cells viability, migration, invasion, and apoptosis were assessed using MTT, Transwell assay, and flow cytometry analysis, respectively. Levels of DR3, PI3K, and AKT in HTR-8/SVneo cells were analyzed via reverse transcription-quantitative polymerase chain reaction assay. Western blot analysis was utilized to assess DR3, p-PI3K, p-AKT, PI3K, and AKT protein expression.

RESULTS

Upregulation of DR3 obviously inhibited HTR-8/SVneo cells viability, migration, and invasion, as well as promoted HTR-8/SVneo cells apoptosis, as opposed to the control-plasmid group. We also found that DR3-plasmid enhanced cleaved-caspase3 expression, reduced p-PI3K and p-AKT protein expression, and p-PI3K/PI3K or p-AKT/AKT ratio in HTR-8/SVneo cells. Importantly, IGF-1, a PI3K/AKT signaling pathway agonist, partially reversed the effects of DR3-plasmid on the cell viability, migration, invasion, apoptosis, and PI3K/AKT signal pathway in HTR-8/SVneo cells.

CONCLUSION

DR3 was involved in PE through regulating placental trophoblast cell physiology via PI3K/AKT pathway, which might be a promising therapeutic target for PE therapy.

Sphingosine 1-Phosphate Activates S1PR3 to Induce a Proinflammatory Phenotype in Human Myometrial Cells

One of the common mechanisms responsible for obstetric complications, affecting millions of women every year, is abnormal uterine contractility. Despite the critical importance of this process for women's health, the mechanisms of uterine contraction regulation remain poorly understood. The initiation of uterine smooth muscle (myometrial) contraction is an inflammatory process, accompanied by upregulation of proinflammatory genes and cytokine release. In this study, we show that sphingolipid metabolism is activated during human labor and that sphingosine 1-phosphate (S1P), the main bioactive sphingolipid, may modify the myometrial proinflammatory phenotype. Our data in both primary and immortalized human myometrial cells show that exogenous S1P induces a proinflammatory gene signature and upregulates the expression of known inflammatory markers of parturition, such as IL8 and COX2. Using expression of IL8 as a readout for S1P activity in myometrial cells, we established that these S1P effects are mediated through the activation of S1P receptor 3 (S1PR3) and downstream activation of ERK1/2 pathways. Inhibition of S1PR3 in human myometrial cells attenuates upregulation of IL8, COX2, and JUNB both at the mRNA and protein levels. Furthermore, activation of S1PR3 with a receptor-specific agonist recapitulated the effects seen after treatment with exogenous S1P. Collectively, these results suggest a signaling pathway activated by S1P in human myometrium during parturition and propose new targets for development of novel therapeutics to alter uterine contractility during management of preterm labor or labor dystocia.

Diagnostic Value of IGFBP-2 in Predicting Preeclampsia before 20 Weeks of Pregnancy: A Prospective Nested Case-Control Study

Purpose

To identify novel biomarker insulin-like growth factor binding protein-2 (IGFBP-2) associated with preeclampsia (PE) before 20 weeks of gestation and to explore the predictive value of plasma IGFBP-2 in PE.

Methods

A prospective nested case-control investigation involving 122 PE patients and 122 normal controls (NC) that were matched 1 : 1 in terms of age and week of pregnancy was carried out in Guangzhou Women and Children's Medical Center (Guangzhou, China, 2018030306) from April 2016 to December 2019. At 8 to 20 weeks, blood samples from the mother were taken. To calculate the correlations, univariate conditional logistic regression was employed.

Results

Herein, 12 clinical indices were significantly different between the PE and NC groups (uric acid (UA), cystatin C (Cys C), aspartate aminotransferase (AST), glutamyl transpeptidase (γ-GT), total bilirubin (TB), prothrombin time (PT), red blood cell (RBC), hematocrit (HCT), red cell distribution width (RDW), platelets (PLT), mean platelet volume (MPV), and thrombocytocrit (PCT)). Compared with the NC group (36.79 ± 19.91 pg/mL), the expression level of IGFBP2 in the PE group (19.76 ± 19.40 pg/mL) before 20 weeks of pregnancy was significantly decreased (P < 0.01). Two high-risk factors were found to be significantly associated with PE independently of confounders: anemia 4.35 (2.20-8.45) (P < 0.01) and cesarean section history 8.25 (2.67-26.67) (P < 0.01). As a result of the univariate logistic regression analysis, the following three variables were included in the final logistic regression model.: Y = −18.841 − 0.085 × (IGFBP‐2) + 0.630 × (RDW) + 0.165 × (AST) + 0.863 × (MPV). In comparison to IGFBP-2 alone as an independent predictor of PE (AUC = 0.897, 95% CI 0.830–0.964), the model's discriminatory power was considerably higher (AUC = 0.953, 95% CI 0.911–0.995).

Conclusion

Plasma IGFBP-2 before 20 weeks of pregnancy combined with high-risk factors and routine blood indexes has a high early predictive value for PE.

Nephrotoxicity in cancer treatment: An update

It has been estimated that nearly 80% of anticancer drug-treated patients receive potentially nephrotoxic drugs, while the kidneys play a central role in the excretion of anticancer drugs. Nephrotoxicity has long been a serious complication that hampers the effectiveness of cancer treatment and continues to influence both mortality and length of hospitalization among cancer patients exposed to either conventional cytotoxic agents or targeted therapies. Kidney injury arising from anticancer drugs tends to be associated with preexisting comorbidities, advanced cancer stage, and the use of concomitant non-chemotherapeutic nephrotoxic drugs. Despite the prevalence and impact of kidney injury on therapeutic outcomes, the field is sorely lacking in an understanding of the mechanisms driving cancer drug-induced renal pathophysiology, resulting in quite limited and largely ineffective management of anticancer drug-induced nephrotoxicity. Consequently, there is a clear imperative for understanding the basis for nephrotoxic manifestations of anticancer agents for the successful management of kidney injury by these drugs. This article provides an overview of current preclinical research on the nephrotoxicity of cancer treatments and highlights prospective approaches to mitigate cancer therapy-related renal toxicity.

Using Machine Learning to Identify Metabolomic Signatures of Pediatric Chronic Kidney Disease Etiology

BACKGROUND

Untargeted plasma metabolomic profiling combined with machine learning (ML) may lead to discovery of metabolic profiles that inform our understanding of pediatric CKD causes. We sought to identify metabolomic signatures in pediatric CKD based on diagnosis: FSGS, obstructive uropathy (OU), aplasia/dysplasia/hypoplasia (A/D/H), and reflux nephropathy (RN).

METHODS

Untargeted metabolomic quantification (GC-MS/LC-MS, Metabolon) was performed on plasma from 702 Chronic Kidney Disease in Children study participants (n: FSGS=63, OU=122, A/D/H=109, and RN=86). Lasso regression was used for feature selection, adjusting for clinical covariates. Four methods were then applied to stratify significance: logistic regression, support vector machine, random forest, and extreme gradient boosting. ML training was performed on 80% total cohort subsets and validated on 20% holdout subsets. Important features were selected based on being significant in at least two of the four modeling approaches. We additionally performed pathway enrichment analysis to identify metabolic subpathways associated with CKD cause.

RESULTS

ML models were evaluated on holdout subsets with receiver-operator and precision-recall area-under-the-curve, F1 score, and Matthews correlation coefficient. ML models outperformed no-skill prediction. Metabolomic profiles were identified based on cause. FSGS was associated with the sphingomyelin-ceramide axis. FSGS was also associated with individual plasmalogen metabolites and the subpathway. OU was associated with gut microbiome-derived histidine metabolites.

CONCLUSION

ML models identified metabolomic signatures based on CKD cause. Using ML techniques in conjunction with traditional biostatistics, we demonstrated that sphingomyelin-ceramide and plasmalogen dysmetabolism are associated with FSGS and that gut microbiome-derived histidine metabolites are associated with OU.