Associations Between Gut Microbiota and Alcohol Abuse: A Mendelian Randomisation and Bioinformatics Study.

Alcohol abuse, also known as Alcohol Use Disorder (AUD), is a substance dependency psychiatric disorder. We aimed to establish a causal relationship between specific gut microbiota and alcohol abuse using Mendelian Randomisation (MR) and bioinformatics methods. We acquired summary data of genome-wide association studies (GWAS) for gut microbiota and alcohol abuse from the Mibiogen and Finngen databases, respectively. We conducted MR analyses using various methodologies and mapped the single nucleotide polymorphisms (SNPs) to genes via the FUMA GWAS platform. We further performed multiple enrichment analyses and a Multi-variable Mendelian Randomisation (MVMR) approach to examine whether gut microbiota influences alcohol abuse by modulating neurotransmitter-related amino acids. The MR analysis revealed an inverse relationship between the genus Eubacterium ventriosum group and the Porphyromonadaceae family with alcohol abuse. Gene enrichment analysis showed that these genes are expressed in brain tissue and are involved in addictive disorders, psychiatric conditions, immunological processes, neurotransmitter synthesis and synaptic regulation. MVMR analysis suggested that the Porphyromonadaceae family as well as genus Eubacterium ventriosum group may suppress alcohol abuse through the metabolism of neurotransmitter-related amino acids, especially Tryptophan. The MR analysis and bioinformatics investigations indicate that the genus Eubacterium ventriosum group and Porphyromonadaceae family confer a protective effect against alcohol abuse, potentially through the modulation of synaptic function.

Multi-omics Analysis Revealed that the CCN Family Regulates Cell Crosstalk, Extracellular Matrix, and Immune Escape, Leading to a Poor Prognosis of Glioma.

The CCN family is a group of matricellular proteins associated with the extracellular matrix. This study aims to explore the role of the CCN family in glioma development and its implications in the tumor microenvironment. Through analysis of bulk RNA-seq cohorts, correlations between CCN family expression and glioma subtypes, patient survival, and bioactive pathway enrichment were investigated. Additionally, single-cell datasets were employed to identify novel cell subgroups, followed by analyses of cell communication and transcription factors. Spatial transcriptomic analysis was utilized to validate the CCN family's involvement in glioma. Results indicate overexpression of CYR61,CTGF, and WISP1 in glioma, associated with unfavorable subtypes and reduced survival. Enrichment analyses revealed associations with oncogenic pathways, while CTGF and WISP1 expression correlated with increased infiltration of regulatory T cells and M2 macrophages. Single-cell analysis identified MES-like cells as the highest CCN expression. Moreover, intercellular signal transduction analysis demonstrated active pathways, including SPP1-CD44, in cell subgroups with elevated CYR61 and CTGF expression. Spatial transcriptomic analysis confirmed co-localization of CYR61,CTGF and SPP1-CD44 with high oncogenic pathway activity. These findings suggest that CCN family members may serve as potential prognostic biomarkers and therapeutic targets for glioma.

A novel set of DNA methylation markers in urine sediments for sensitive/specific detection of bladder cancer.

PURPOSE: This study aims to provide a better set of DNA methylation markers in urine sediments for sensitive and specific detection of bladder cancer. EXPERIMENTAL DESIGN: Fifty-nine tumor-associated genes were profiled in three bladder cancer cell lines, a small cohort of cancer biopsies and urine sediments by methylation-specific PCR. Twenty-one candidate genes were then profiled in urine sediments from 132 bladder cancer patients (8 cases for stage 0a; 68 cases for stage I; 50 cases for stage II; 4 cases for stages III; and 2 cases for stage IV), 23 age-matched patients with noncancerous urinary lesions, 6 neurologic diseases, and 7 healthy volunteers. RESULTS: Despite six incidences of four genes reported in 3 of 23 noncancerous urinary lesion patients analyzed, cancer-specific hypermethylation in urine sediments were reported for 15 genes (P < 0.05). Methylation assessment of an 11-gene set (SALL3, CFTR, ABCC6, HPR1, RASSF1A, MT1A, RUNX3, ITGA4, BCL2, ALX4, MYOD1, DRM, CDH13, BMP3B, CCNA1, RPRM, MINT1, and BRCA1) confirmed the existing diagnosis of 121 among 132 bladder cancer cases (sensitivity, 91.7%) with 87% accuracy. Significantly, more than 75% of stage 0a and 88% of stage I disease were detected, indicating its value in the early diagnosis of bladder cancer. Interestingly, the cluster of reported methylation markers used in the U.S. bladder cancers is distinctly different from that identified in this study, suggesting a possible epigenetic disparity between the American and Chinese cases. CONCLUSIONS: Methylation profiling of an 11-gene set in urine sediments provides a sensitive and specific detection of bladder cancer.