Current Medicinal Chemistry - Online First

This study aimed to explore potential causal relationships between mitochondria-related genes and irritable bowel syndrome (IBS) using integrative multi-omics analysis.

Genome-wide association study data for IBS (1,480 cases and 454,868 controls) were integrated with mitochondrial gene data from DNA methylation quantitative trait loci, blood expression quantitative trait loci, and protein quantitative trait loci. Molecular trait associations with IBS were assessed through summary-based Mendelian randomization and co-localization analyses. Steiger filtering analysis was applied to identify causal directions, and candidate genes were independently replicated by two-sample MR in the FinnGen R11 cohort.

Three primary genes supported by multi-omics evidence—CASP3, GATM, and PDK1—were identified. Increased CASP3 methylation, expression, and protein were positively associated with IBS risk, indicating pro-apoptotic and pro-inflammatory mechanisms, whereas elevated GATM expression and protein were negatively associated, consistent with a protective role via creatine-mediated energy homeostasis.

Additionally, 19 genes were classified as secondary evidence genes and 5 as tertiary evidence genes. Among these, genes such as ACAD10 and MSRA were validated using FinnGen data.

This study represents the first application of multi-omics techniques to elucidate the relationship between mitochondrial genes and IBS. The findings indicate multiple candidate pathogenic genes and highlight the role of mitochondrial dysfunction in IBS pathogenesis. These findings offer new opportunities for the discovery of IBS biomarkers and the development of therapeutic strategies.

Curcuma longa, commonly known as turmeric, contains curcumin, which is its main compound and has been reported to possess a wide variety of pharmacological activities, such as anti-carcinogenic, anti-malarial, antioxidant, antibacterial, anti-mutagenic, anti-inflammatory, and immunomodulatory effects. Even though it has many strong biological properties, curcumin lacks solubility, which affects its clinical efficacy. DK1 is a curcumin analogue that has been found to possess selective cytotoxicity on breast cancer cells compared to normal breast cells; however, its effectiveness in colon cancer has yet to be validated. This study was performed to investigate the effects of DK1 on colon cancer using an in vivo model in terms of its anti-apoptotic, immunoregulatory, and antioxidant potential. The pathways affected by the DK1 treatment were also evaluated.

In this study, male BALB/c mice induced with colon cancer were utilized, and the resulting tumours and spleen were subjected to TUNEL, immunophenotyping, and several antioxidant assays, such as nitric oxide, malondialdehyde, and superoxide dismutase, as well as gene and protein expression analyses.

K1 treatment led to tumor shrinkage, an increase in apoptotic tumor cells, and elevated populations of helper and cytotoxic T cells by 5% and 3%, respectively. Besides that, the NO and MDA levels were also significantly reduced. This study also observed dysregulations in several oncogenes in the VEGF pathway, such as CMYC, iNOS, and IL-1β genes, which are involved in angiogenesis and inflammation.

The effects of DK1 treatment included antitumor and anti-inflammatory properties against the inoculated CT26 tumour. DK1 showed potential in regulating the inflammation via the VEGF pathway by the significant downregulation of TNF-α and IL-1β pro-inflammatory genes, as well as PTX3, OPN, and serpin-E1 pro-angiogenic proteins.

The results suggested that DK1 may potentially function as an immunoregulator and anti-cancer agent for colon cancer therapy.

Ischemic stroke (IS) is a major cause of death and disability worldwide. The transcriptional mechanism of neutrophil extracellular trap-related genes (NRGs) and their diagnostic potential remain unknown. This study aims to explore the mechanism of NRGs in IS through machine learning and single-cell RNA sequencing (scRNA-seq).

We conducted differential analysis and functional enrichment analysis on the GEO dataset. Machine learning algorithms were used to identify NRGs related to IS. ScRNA-seq analysis was employed to verify the expression of NRGs in different cell types, and cellchat was used to explore the interactions between cell types in the IS. The expression of Eno1 was also verified in the mouse model of middle cerebral artery occlusion (MCAO).

We identified 26 differentially expressed NRGs (DE-NRGs). The diagnostic models constructed from five DE-NRGs (ENO1, HMGB1, ILK, ORAI1, SUCNR1) demonstrated high predictive ability. Single-cell analysis revealed that NRGs were highly expressed in the IS group. The experiment verified the significant upregulation of Eno1.

This study employed machine learning and scRNA-seq to identify the DE-NRGs-related diagnostic model, providing a certain theoretical basis for IS risk stratification. More experiments are needed to verify the role of DE-NRGs in IS in the future.

This study identified DE-NRGs with diagnostic capabilities in IS and verified their high expression through scRNA and experimental methods. DE-NRGs may be potential therapeutic targets for IS.

Ischemic Stroke (IS) represents the most prevalent subtype of cerebrovascular disease, characterized by complex pathophysiological mechanisms that remain inadequately characterized, particularly concerning mitochondrial dysfunctions. These mitochondrial impairments are increasingly recognized as contributory factors in IS pathogenesis, emphasizing the need for further investigation into the underlying molecular mechanisms involved.

In this study, we integrated transcriptomic datasets from the Gene Expression Omnibus (GEO) with the comprehensive MitoCarta3.0 mitochondrial proteome inventory to elucidate the role of dysregulated Mitochondrial-Related Genes (MRGs) in IS. We employed an advanced bioinformatics and machine learning pipeline, incorporating differential expression profiling alongside network-based prioritization using CytoHubba. Rigorous feature selection was conducted through LASSO regression, Support Vector Machine (SVM), and Random Forest (RF) algorithms to derive a robust core MRG signature. Our methodology included training and validation cohorts to construct diagnostic models, which were critically evaluated via Receiver Operating Characteristic (ROC) curves, nomograms, and calibration analyses.

Our analysis identified a seven-gene signature comprising DNAJA3, ACSL1, HSDL2, ECHDC2, ECHDC3, ALDH2, and PDK4, which demonstrated significant correlation with activated CD8⁺ T-cell and natural killer cell infiltration. Furthermore, integrative network analyses revealed intricate regulatory interactions among MRGs, microRNAs, and transcription factors. Notably, drug-target predictions indicated Bezafibrate as a promising therapeutic agent for modulating mitochondrial homeostasis in the context of IS.

These findings offer a novel framework for ischemic stroke diagnosis and therapy, yet their computational derivation underscores the need for thorough experimental validation of MRGs and drug candidates, along with the integration of diverse clinical data to confirm their real-world applicability.

Our findings underscore mitochondrial dysfunction not only as a critical factor in IS pathogenesis but also as a viable therapeutic target. The identified MRG signature presents potential for clinical application in diagnostic and pharmacological strategies aimed at ameliorating ischemic injury. This study highlights the translational significance of systems biology approaches within cerebrovascular medicine, warranting further mechanistic exploration of mitochondrial-immune interactions in stroke pathology.

Gliomas are aggressive brain tumors with a poor prognosis and high recurrence. Oridonin, a traditional Chinese medicine, has shown potential in treating various cancers, but its role in glioma treatment, especially in modulating Epithelial-Mesenchymal Transition (EMT), remains underexplored.

We identified 371 potential target genes of Oridonin using various bioinformatics databases. Enrichment analyses, including Differential Expression Analysis, Gene Set Enrichment Analysis (GSEA), and Weighted Gene Co-expression Network Analysis (WGCNA), were performed to link these targets to glioma characteristics. in vitro experiments validated Oridonin's impact on EMT-related gene expression in glioma cells.

Enrichment analyses identified 19 common genes between Oridonin and glioma targets, with 12 EMT-related core genes. KEGG enrichment highlighted PI3K-Akt, MAPK pathways, and glioma pathways, while DO enrichment included high-grade gliomas. CCK8 assay showed Oridonin IC50 values of 6.92 μM for H4 and 10.54 μM for SW1783 glioma cell lines. WB results indicated increased E-Cadherin and decreased Vimentin, N-Cadherin, and Snail expression after Oridonin treatment. PPI network and single-cell transcriptome analyses identified key genes linked to glioma progression and immune cell infiltration.

Oridonin may inhibit glioma progression by targeting EMT-related pathways like PI3K-Akt and MAPK. The upregulation of E-Cadherin and downregulation of Vimentin, N-Cadherin, and Snail suggest a reversal of the EMT process. Future work should validate these effects in vivo and explore Oridonin's ability to cross the blood-brain barrier.

Oridonin may provide a novel therapeutic approach for glioma by targeting EMT-related pathways, offering a foundation for further clinical investigation.

Neuroinflammation, primarily mediated by activated microglia, is a significant contributor to neurodegenerative diseases, such as Alzheimer's and Parkinson's disease. Quercetin (QCT), a dietary flavonoid, has demonstrated anti-inflammatory and neuroprotective properties; however, the detailed molecular mechanisms behind these effects remain unclear. This study aimed to investigate the anti-inflammatory actions of QCT, particularly focusing on its potential to suppress the activation of microglia and subsequent neuroinflammation.

BV2 microglial cells were stimulated with lipopolysaccharide (LPS) to induce an inflammatory response and were subsequently treated with various concentrations of QCT. Cell viability was assessed using the MTT assay. Levels of pro-inflammatory cytokines (IL-6, TNF-α) and nitric oxide (NO) were quantified through ELISA and Griess reaction methods, respectively. Western blot analysis was conducted to examine inducible nitric oxide synthase (iNOS), NF-κB, IκBα, and phosphorylated IκBα protein expressions. In silico approaches, including protein-protein interaction (PPI) network analysis and molecular docking, were employed to explore potential molecular mechanisms involving NF-κB signaling pathways.

Treatment with QCT significantly reduced the secretion of IL-6 (96%) and TNF-α (87%), as well as NO production (42%), in a dose-dependent manner. Western blot results demonstrated a marked reduction in iNOS expression and inhibition of NF-κB activation through reduced phosphorylation of IκBα following QCT treatment. Molecular docking indicated a strong binding affinity between QCT and IKKβ, suggesting inhibition of the NF-κB pathway.

The findings indicated QCT to exert potent anti-inflammatory effects in LPS-stimulated BV2 cells by modulating key proteins involved in the NF-κB signaling pathway. Specifically, the docking results implied QCT’s direct interaction with the catalytic subunit IKKβ, inhibiting IκBα phosphorylation and subsequent NF-κB activation. The results have been found to be consistent with previous literature, reinforcing QCT's role in reducing neuroinflammation through specific molecular targets and pathways. Further in vivo studies are necessary to validate the findings.

Quercetin effectively suppressed neuroinflammation in microglial cells through inhibition of the NF-κB signaling pathway, reducing levels of critical pro-inflammatory mediators. The outcomes have highlighted the potential of quercetin as a preventive nutraceutical for neurodegenerative diseases, necessitating future in vivo investigations to confirm its therapeutic efficacy.

The causality between thyroid disorders and Gastroesophageal Reflux Disease (GERD) remains to be deciphered. This two-sample Mendelian Randomization (MR) study was performed to elucidate the causal association between GERD and thyroid diseases and functions.

Summary statistics for GERD were retrieved from a published GWAS dataset deposited in the Integrative Epidemiology Unit OpenGWAS database. Thyroid hormone level data were obtained from the ThyroidOmics Consortium, and genetic variants associated with thyroid disorders were sourced from the FinnGen Project. MR statistical analyses used the Inverse Variance Weighted (IVW) algorithm, followed by various sensitivity and reliability analyses. Odds Ratio (OR) and beta coefficient (β) with 95% Confidence Interval (CI) were estimated for categorical and continuous outcomes, respectively. The significant causal association was determined based on a Bonferroni-corrected threshold of p-value < 0.0021 (calculated as 0.05/24 trait pairs).

The findings of MR analysis tend to favor the causality of GERD for hyperthyroidism (IVW: OR = 1.517, 95% CI: 1.164 to 1.978, p = 2.04E-03) but not the other thyroid disorders. The reverse MR estimates suggested that thyroid disorders may not affect the susceptibility of GERD. Moreover, genetic proxied GERD was significantly negatively associated with circulating Thyroid Stimulating Hormone (TSH) level (IVW: β = -0.048, 95% CI: -0.078 to -0.019, p = 1.17E-03), whereas the causality of this enteropathy on Free Triiodothyronine (FT3), Free Thyroxine (FT4), Total Triiodothyronine (TT3), FT3/FT4 ratio, and TT3/FT4 ratio (and vice versa) is unfounded.

This MR study indicates that the genetic liability to GERD is significantly detrimental to hyperthyroidism risk and the homeostasis of TSH.

The findings suggest that effective GERD management could mitigate hyperthyroidism risk.

Diffuse large B-cell lymphoma (DLBCL) pathogenesis is poorly understood, with limited causal evidence linking circulating inflammatory proteins (CIPs) and metabolites to disease risk. Observational studies face challenges from confounding and reverse causation, while existing Mendelian Randomization (MR) analyses lack bidirectional designs and multi-omics integration.

A bidirectional two-sample MR design was applied using inverse-variance weighting (IVW). Genetic instruments for 91 CIPs derived from Olink proteomic data (14,824 participants). DLBCL genetic associations (1,050 cases; 314,193 controls) were obtained from FinnGen (R10 release). Data for 1,091 blood metabolites and 309 metabolite ratios were sourced from the GWAS Catalog.

Ten CIPs exhibited causal effects on DLBCL. Risk-increasing proteins included: IL-10 (OR=1.46, 95%CI=1.05-2.03), TSLP (1.37,1.01-1.84), IL-17C (1.34,1.05-1.72), NRTN (1.30,1.02-1.66), OPG (1.29,1.01-1.66), and MCP1 (1.26,1.04-1.52). Protective proteins included: CD40 (0.82,0.67-1.00), CXCL9 (0.78,0.61-0.98), CD5 (0.77,0.61-0.97), and MCP3 (0.76,0.58-0.99). Reverse causation was absent for 7 proteins. Mediation analysis revealed 17.2% (p=0.048) of CD5’s protective effect was mediated by 1-methylhistidine.

These findings establish CIPs as causal factors in DLBCL pathogenesis and identify metabolite-mediated pathways as novel mechanistic links. The bidirectional design and multi-omics integration overcome key limitations of prior research, though statistical power for some mediation tests was limited by metabolite GWAS sample sizes.

Plasma inflammatory proteins causally influence DLBCL risk, partially mediated by metabolites. This underscores metabolite pathways as potential targets for therapeutic intervention.