Identification of Novel Key Molecular Signatures in the Pathogenesis of Experimental Diabetic Kidney Disease

Overview of M-LP/MPV17L, a novel atypical PDE and possible target for drug development

M-LP/Mpv17L (Mpv17-like protein) was initially identified as a novel protein during screening of age-dependently expressed genes in mouse kidney. Previous findings suggested that human Mpv17-like protein (M-LP/MPV17L) is involved in the maintenance of mitochondrial DNA (mtDNA), thus playing a role in cell defense against mitochondrial dysfunction, although its molecular mechanism of action has remained unknown. Recently, generation of M-LP/MPV17L-knockout (KO) cells using CRISPR-Cas9 technology has revealed that M-LP/MPV17L exerts cyclic nucleotide phosphodiesterase (PDE) activity despite lacking the conserved catalytic region and other structural motifs characteristic of the PDE family, and is one of the key components of pathways such as cAMP/cAMP-dependent protein kinase A (PKA) signaling. Moreover, generation of M-LP/Mpv17L-KO mice has revealed that deficiency of M-LP/Mpv17L results in development of β-cell hyperplasia and improved glucose tolerance, as well as physiological afferent cardiac hypertrophy. M-LP/MPV17L is a protein of great interest as it is a potential target for drug development. Therefore, in this review, we overview the molecular characteristics, regulation of expression, cellular functions, phenotypes detected in KO mice, and disease relevance of M-LP/MPV17L.

Maladaptive Peripheral Ketogenesis in Schwann Cells Mediated by CB1R Contributes to Diabetic Neuropathy

Diabetic peripheral neuropathy (DPN) is the most common complication of diabetes. Although studies have previously investigated metabolic disruptions in the peripheral nervous system (PNS), the exact metabolic mechanisms underlying DPN remain largely unknown. Herein, a specific form of metabolic remodeling involving aberrant ketogenesis within Schwann cells (SCs) in streptozotocin (STZ)-induced type I diabetes mellitus is identified. The PNS adapts poorly to such aberrant ketogenesis, resulting in disrupted energy metabolism, mitochondrial damage, and homeostatic decompensation, ultimately contributing to DPN. Additionally, the maladaptive peripheral ketogenesis is highly dependent on the cannabinoid type-1 receptor (CB1R)-Hmgcs2 axis. Silencing CB1R reprogrammed the metabolism of SCs by blocking maladaptive ketogenesis, resulting in rebalanced energy metabolism, reduced histopathological changes, and improved neuropathic symptoms. Moreover, this metabolic reprogramming can be induced pharmacologically using JD5037, a peripheral CB1R blocker. These findings revealed a new metabolic mechanism underlying DPN, and promoted CB1R as a promising therapeutic target for DPN.

Acyl-CoA Synthetase Long-Chain Isoenzymes in Kidney Diseases: Mechanistic Insights and Therapeutic Implications

Long-chain acyl-CoA synthetases (ACSLs) are pivotal enzymes in fatty acid metabolism, essential for maintaining cellular homeostasis and energy production. Recent research has uncovered their significant involvement in the pathophysiology of various kidney diseases, including acute kidney injury (AKI), chronic kidney disease (CKD), diabetic kidney disease (DKD), and renal cell carcinoma (RCC). While ACSL1, ACSL3, ACSL4, and ACSL5 have been extensively studied for their roles in processes such as ferroptosis, lipid peroxidation, renal fibrosis, epithelial-mesenchymal transition, and tumor progression, the role of ACSL6 in kidney diseases remain largely unexplored. Notably, these isoenzymes exhibit distinct functions in different kidney diseases. Therefore, to provide a comprehensive understanding of their involvement, this review highlights the molecular pathways influenced by ACSLs and their roles in modulating cell death, inflammation, and fibrosis during kidney disease progression. By examining these mechanisms in detail, this review underscores the potential of ACSLs as biomarkers and therapeutic targets, advocating for further research to elucidate the precise roles of individual ACSL isoenzymes in kidney disease progression. Understanding these mechanisms opens new avenues for developing targeted interventions and improving therapeutic outcomes for patients with kidney diseases.

Multi-omics analysis of kidney tissue metabolome and proteome reveals the protective effect of sheep milk against adenine-induced chronic kidney disease in mice

Chronic kidney disease (CKD) is characterized by impaired renal function and is associated with inflammation, oxidative stress, and fibrosis. Sheep milk contains several bioactive molecules with protective effects against inflammation and oxidative stress. In the current study, we investigated the potential renoprotective effects of sheep milk and the associated mechanisms of action in an adenine-induced CKD murine model. Sheep milk delayed renal chronic inflammation (e.g., significant reduction in levels of inflammatory factors Vcam1, Icam1, Il6, and Tnfa), fibrosis (significant reduction in levels of fibrosis factors Col1a1, Fn1, and Tgfb), oxidative stress (significant increase in levels of antioxidants and decrease in oxidative markers), mineral disorders, and renal injury in adenine-treated mice (e.g. reduced levels of kidney injury markers NGAL and KIM-1). The combined proteomics and metabolomics analyses showed that sheep milk may affect the metabolic processes of several compounds, including proteins, lipids, minerals, and hormones in mice with adenine-induced chronic kidney disease. In addition, it may regulate the expression of fibrosis-related factors and inflammatory factors through the JAK1/STAT3/HIF-1α signaling pathway, thus exerting its renoprotective effects. Therefore, sheep milk may be beneficial for patients with CKD and should be evaluated in preclinical and clinical studies.

The identification of a novel shared therapeutic target and drug across all insulin-sensitive tissues under insulin resistance

Background

To identify key and shared insulin resistance (IR) molecular signatures across all insulin-sensitive tissues (ISTs), and their potential targeted drugs.

Methods

Three datasets from Gene Expression Omnibus (GEO) were acquired, in which the ISTs (fat, muscle, and liver) were from the same individual with obese mice. Integrated bioinformatics analysis was performed to obtain the differentially expressed genes (DEGs). Weighted gene co-expression network analysis (WGCNA) was carried out to determine the "most significant trait-related genes" (MSTRGs). Enrichment analysis and PPI network were performed to find common features and novel hub genes in ISTs. The shared genes of DEGs and genes between DEGs and MSTRGs across four ISTs were identified as key IR therapeutic target. The Attie Lab diabetes database and obese rats were used to verify candidate genes. A medical drug-gene interaction network was conducted by using the Comparative Toxicogenomics Database (CTD) to find potential targeted drugs. The candidate drug was validated in Hepa1-6 cells.

Results

Lipid metabolic process, mitochondrion, and oxidoreductase activity as common features were enriched from ISTs under an obese context. Thirteen shared genes (Ubd, Lbp, Hp, Arntl, Cfd, Npas2, Thrsp., Tpx2, Pkp1, Sftpd, Mthfd2, Tnfaip2, and Vnn3) of DEGs across ISTs were obtained and confirmed. Among them, Ubd was the only shared gene between DEGs and MSTRGs across four ISTs. The expression of Ubd was significantly upregulated across four ISTs in obese rats, especially in the liver. The IR Hepa1-6 cell models treated with dexamethasone (Dex), palmitic acid (PA), and 2-deoxy-D-ribose (dRib) had elevated expression of Ubd. Knockdown of Ubd increased the level of p-Akt. A lowing Ubd expression drug, promethazine (PMZ) from CTD analysis rescued the decreased p-Akt level in IR Hepa1-6 cells.

Conclusion

This study revealed Ubd, a novel and shared IR molecular signature across four ISTs, as an effective biomarker and provided new insight into the mechanisms of IR. PMZ was a candidate drug for IR which increased p-Akt level and thus improved IR by targeting Ubd and downregulation of Ubd expression. Both Ubd and PMZ merit further clinical translational investigation to improve IR.

Integration of Vitreous Lipidomics and Metabolomics for Comprehensive Understanding of the Pathogenesis of Proliferative Diabetic Retinopathy

As a vision-threatening complication of diabetes mellitus (DM), proliferative diabetic retinopathy (PDR) is associated with sustained metabolic disorders. Herein, we collected the vitreous cavity fluid of 49 patients with PDR and 23 control subjects without DM for metabolomics and lipidomics analyses. Multivariate statistical methods were performed to explore relationships between samples. For each group of metabolites, gene set variation analysis scores were generated, and we constructed a lipid network by using weighted gene co-expression network analysis. The association between lipid co-expression modules and metabolite set scores was investigated using the two-way orthogonal partial least squares (O2PLS) model. A total of 390 lipids and 314 metabolites were identified. Multivariate statistical analysis revealed significant vitreous metabolic and lipid differences between PDR and controls. Pathway analysis showed that 8 metabolic processes might be associated with the development of PDR, and 14 lipid species were found to be altered in PDR patients. Combining metabolomics and lipidomics, we identified fatty acid desaturase 2 (FADS2) as an important potential contributor to the pathogenesis of PDR. Collectively, this study integrates vitreous metabolomics and lipidomics to comprehensively unravel metabolic dysregulation and identifies genetic variants associated with altered lipid species in the mechanistic pathways for PDR.

The TMEM43 S358L mutation affects cardiac, small intestine, and metabolic homeostasis in a knock-in mouse model

The transmembrane protein 43 (TMEM43/LUMA) p.S358L mutation causes arrhythmogenic cardiomyopathy named as ARVC5, a fully penetrant disease with high risk of ventricular arrhythmias, sudden death, and heart failure. Male gender and vigorous exercise independently predicted deleterious outcome. Our systems genetics analysis revealed the importance of Tmem43 for cardiac and metabolic pathways associated with elevated lipid absorption from small intestine. This study sought to delineate gender-specific cardiac, intestinal, and metabolic phenotypes in vivo and investigate underlying pathophysiological mechanisms of S358L mutation. Serial echocardiography, surface electrocardiography (ECG), treadmill running, and body EchoMRI have been used in knock-in heterozygous (Tmem43WT/S358L), homozygous (Tmem43S358L), and wildtype (Tmem43WT) littermate mice. Electron microscopy, histology, immunohistochemistry, transcriptome, and protein analysis have been performed in cardiac and intestinal tissues. Systolic dysfunction was apparent in 3-mo-old Tmem43S358L and 6-mo-old Tmem43WT/S358L mutants. Both mutant lines displayed intolerance to acute stress at 6 mo of age, arrhythmias, fibro-fatty infiltration, and subcellular abnormalities in the myocardium. Microarray analysis found significantly differentially expressed genes between left ventricular (LV) and right ventricular (RV) myocardium. Mutants displayed diminished PPARG activities and significantly reduced TMEM43 and β-catenin expression in the heart, whereas junctional plakoglobin (JUP) translocated into nuclei of mutant cardiomyocytes. Conversely, elongated villi, fatty infiltration, and overexpression of gut epithelial proliferation markers, β-catenin and Ki-67, were evident in small intestine of mutants. We defined Tmem43 S358L-induced pathological effects on cardiac and intestinal homeostasis via distinctly disturbed WNT-β-catenin and PPARG signaling thereby contributing to ARVC5 pathophysiology. Results suggest that cardiometabolic assessment in mutation carriers may be important for predictive and personalized care.NEW & NOTEWORTHY This manuscript describes the findings of our investigation of cardiac, small intestine, and metabolic features of Tmem43-S358L mouse model. By investigating interorgan pathologies, we uncovered multiple mechanisms of the S358L-induced disease, and these unique mechanisms likely appear to contribute to the disease pathogenesis. We hope our findings are important and novel and open new avenues in the hunting for additional diagnostic and therapeutic targets in subjects carrying TMEM43 mutation.

Biomarker and genomic analyses reveal molecular signatures of non-cardioembolic ischemic stroke

Acute ischemic stroke (AIS) is a major cause of disability and mortality worldwide. Non-cardioembolic ischemic stroke (NCIS), which constitutes the majority of AIS cases, is highly heterogeneous, thus requiring precision medicine treatments. This study aimed to investigate the molecular mechanisms underlying NCIS heterogeneity. We integrated data from the Third China National Stroke Registry, including clinical phenotypes, biomarkers, and whole-genome sequencing data for 7695 patients with NCIS. We identified 30 molecular clusters based on 63 biomarkers and explored the comprehensive landscape of biological heterogeneity and subpopulations in NCIS. Dimensionality reduction revealed fine-scale subpopulation structures associated with specific biomarkers. The subpopulations with biomarkers for inflammation, abnormal liver and kidney function, homocysteine metabolism, lipid metabolism, and gut microbiota metabolism were associated with a high risk of unfavorable clinical outcomes, including stroke recurrence, disability, and mortality. Several genes encoding potential drug targets were identified as putative causal genes that drive the clusters, such as CDK10, ERCC3, and CHEK2. We comprehensively characterized the genetic architecture of these subpopulations, identified their molecular signatures, and revealed the potential of the polybiomarkers and polygenic prediction for assessing clinical outcomes. Our study demonstrates the power of large-scale molecular biomarkers and genomics to understand the underlying biological mechanisms of and advance precision medicine for NCIS.

Identification of diagnostic markers related to oxidative stress and inflammatory response in diabetic kidney disease by machine learning algorithms: Evidence from human transcriptomic data and mouse experiments

INTRODUCTION

Diabetic kidney disease (DKD) is a long-term complication of diabetes and causes renal microvascular disease. It is also one of the main causes of end-stage renal disease (ESRD), which has a complex pathophysiological process. Timely prevention and treatment are of great significance for delaying DKD. This study aimed to use bioinformatics analysis to find key diagnostic markers that could be possible therapeutic targets for DKD.

METHODS

We downloaded DKD datasets from the Gene Expression Omnibus (GEO) database. Overexpression enrichment analysis (ORA) was used to explore the underlying biological processes in DKD. Algorithms such as WGCNA, LASSO, RF, and SVM_RFE were used to screen DKD diagnostic markers. The reliability and practicability of the the diagnostic model were evaluated by the calibration curve, ROC curve, and DCA curve. GSEA analysis and correlation analysis were used to explore the biological processes and significance of candidate markers. Finally, we constructed a mouse model of DKD and diabetes mellitus (DM), and we further verified the reliability of the markers through experiments such as PCR, immunohistochemistry, renal pathological staining, and ELISA.

RESULTS

Biological processes, such as immune activation, T-cell activation, and cell adhesion were found to be enriched in DKD. Based on differentially expressed oxidative stress and inflammatory response-related genes (DEOIGs), we divided DKD patients into C1 and C2 subtypes. Four potential diagnostic markers for DKD, including tenascin C, peroxidasin, tissue inhibitor metalloproteinases 1, and tropomyosin (TNC, PXDN, TIMP1, and TPM1, respectively) were identified using multiple bioinformatics analyses. Further enrichment analysis found that four diagnostic markers were closely related to various immune cells and played an important role in the immune microenvironment of DKD. In addition, the results of the mouse experiment were consistent with the bioinformatics analysis, further confirming the reliability of the four markers.

CONCLUSION

In conclusion, we identified four reliable and potential diagnostic markers through a comprehensive and systematic bioinformatics analysis and experimental validation, which could serve as potential therapeutic targets for DKD. We performed a preliminary examination of the biological processes involved in DKD pathogenesis and provide a novel idea for DKD diagnosis and treatment.

Ketone Bodies as Metabolites and Signalling Molecules at the Crossroad between Inflammation and Epigenetic Control of Cardiometabolic Disorders

For many years, it has been clear that a Western diet rich in saturated fats and sugars promotes an inflammatory environment predisposing a person to chronic cardiometabolic diseases. In parallel, the emergence of ketogenic diets, deprived of carbohydrates and promoting the synthesis of ketone bodies imitating the metabolic effects of fasting, has been shown to provide a possible nutritional solution to alleviating diseases triggered by an inflammatory environment. The main ketone body, β-hydroxybutyrate (BHB), acts as an alternative fuel, and also as a substrate for a novel histone post-translational modification, β-hydroxybutyrylation. β-hydroxybutyrylation influences the state of chromatin architecture and promotes the transcription of multiple genes. BHB has also been shown to modulate inflammation in chronic diseases. In this review, we discuss, in the pathological context of cardiovascular risks, the current understanding of how ketone bodies, or a ketogenic diet, are able to modulate, trigger, or inhibit inflammation and how the epigenome and chromatin remodeling may be a key contributor.

Intermittent Fasting—A Healthy Dietary Pattern for Diabetic Nephropathy

Diabetic nephropathy (DN), a metabolic disease, is characterized by severe systemic metabolic disorders. A unique dietary pattern, such as intermittent fasting (IF) has shown promising protective effects on various metabolic diseases, such as diabetes and cardiovascular and nervous system diseases. However, its role in regulating kidney disease, especially in DN, is still being investigated. Here, we summarize the current research progress, highlighting the relationship between IF and the risk factors for the progression of DN, and discuss the potential mechanisms by which IF improves renal injury in DN. Finally, we propose IF as a potential strategy to prevent and delay DN progression. Abbreviation: DN: Diabetic nephropathy; IF: Intermittent fasting; CPT1A: Carnitine palmitoyltransferase 1A; L-FABP: Liver-type fatty acid-binding protein; STZ: Streptozotocin; LDL: Low-density lipoproteins; HIIT: High-intensity interval training; CKD: Chronic kidney disease; ACEI: Angiotensin-converting enzyme inhibitors; ARB: Angiotensin receptor blockers; MDA: Malondialdehyde; mtDNA: Mitochondrial DNA; UCP3: Uncoupling protein-3; MAM: Mitochondria-associated endoplasmic reticulum membrane; PBMCs: Peripheral blood mononuclear cells; ERK1/2: Extracellular signal-regulated kinase 1/2; DRP1: Dynamin-related protein 1; β-HB: β-Hydroxybutyrate; AcAc: Acetoacetate; GEO: Gene Expression Omnibus; NCBI: National Center for Biotechnology Information; mTORC1: Mechanistic target of rapamycin complex 1; HMGCS2: 3-Hydroxy-3-methylglutaryl-CoA synthase 2; GSK3β: Glycogen synthase kinase 3β; AKI: Acute kidney injury; CMA: Chaperone-mediated autophagy; FGF21: Fibroblast growth factor 21.