Lei Zhu

Although gut microbiota dysbiosis is associated with coronary artery disease (CAD), its dynamic alterations across distinct clinical stages remain largely unexplored. This study aimed to identify stage-specific microbial biomarkers across the CAD spectrum. We analyzed 16S rRNA sequencing data from 306 subjects, including non-CAD controls and patients with mild coronary stenosis (MCS), stable angina (SA), unstable angina (UA), and acute myocardial infarction (AMI). Diversity analyses, machine learning, and SPIEC-EASI network modeling were applied to evaluate microbial community shifts and identify core diagnostic markers. Significant structural remodeling of the gut microbiota was observed, particularly during the AMI stage. Veillonella, Intestinimonas, and Streptococcus were identified as the core biomarkers for the MCS, SA, and UA/AMI stages, respectively. From the MCS to the UA stage, ecological network connectivity continuously declined, highlighting critical barrier vulnerability, before transitioning into an antagonism-dominated network in the AMI stage. Machine learning models effectively discriminated among the various disease stages, and key microbial markers remained statistically robust after adjusting for major clinical confounders. The gut microbiota exhibits dynamic, stage-specific dysbiosis throughout CAD progression, providing promising non-invasive biomarkers for precise disease staging and diagnosis.

The secondary metabolites produced by the gut microbiota serve as crucial signaling molecules and substrates for gastrointestinal metabolic reactions, thereby playing a pivotal role in human physiological and pathological processes. In this study, we explore the complex symbiotic relationship between the gut microbiota and the human host by systematically annotating the biosynthetic gene clusters (BGCs) across 4,744 human gut microbiota genomes, sourced from the Unified Human Gastrointestinal Genome database. Our comprehensive analysis compares the differential biosynthetic potentials of microbiota from diverse continents and phyla while also elucidating the biosynthetic profiles of gut archaea. Notably, our findings identify Paenibacillus as a dominant genus within the human gut microbiota, characterized by its extensive biosynthetic capacity. This study presents the first global atlas of BGCs within the human gut microbiome, offering valuable insights into gut-derived secondary metabolic pathways and their intricate interactions with host physiology. These results lay the groundwork for future investigations into the microbiota’s role in health and disease, underscoring the importance of understanding microbiota-derived metabolites in microbiology and gastroenterology. IMPORTANCE: This study provides a comprehensive analysis of biosynthetic gene clusters in the human gut microbiome, revealing a vast diversity of natural products with potential therapeutic applications. We identified Paenibacillus as a key genus with exceptional biosynthetic capabilities, including the production of leinamycin, a potent anticancer compound previously thought to be exclusive to Streptomyces . The findings highlight the gut microbiome as a rich, untapped resource for novel drug discovery, particularly in cancer therapy and immune modulation.

Industrialization has driven lifestyle changes in eastern and western Chinese populations, yet we have a poor understanding of the dynamic changes in their gut microbiome and resistome under industrialization, which is essential for the scientific management of public health. Here, this study employed metagenomics to analyze the gut microbiota of 1,382 healthy individuals from China, including 415 individuals from the eastern region of advanced industrialization and 967 individuals from the western region of developing industrialization. Compared with western populations, eastern populations show a significant increase in interindividual dissimilarity of microbial species composition and metabolic pathways but a significant decrease in intraindividual species and functional diversity. Furthermore, our results found significantly less abundance and richness of antibiotic resistance genes (ARGs) in the gut microbiota of eastern populations, alongside a lower prevalence of unique core ARG subtypes. For the 12 core ARG types shared between eastern and western populations, the mean relative abundance of two types was notably higher in the eastern populations, while eight core ARG types had significantly higher mean relative abundance in the western populations. Based on the reconstruction of metagenomic assembled genomes, we found that Escherichia coli genomes from western populations carried more virulence factor genes (VFGs) and mobile genetic elements (MGEs) compared to those from eastern populations. This large-scale study for the first time revealed industrialization potentially led to unexpected alterations of the gut microbiome and resistome between eastern and western populations that provide a vital implication for Chinese public health and may aid in the development of region-specific strategies for managing pathogenic infections. IMPORTANCE: As China experiences rapid but uneven industrialization, understanding its effect on people’s gut bacteria is critical for public health. This study reveals how industrialization may reshape the health risks related to gut bacteria and antibiotic resistance. This work provides crucial information to help create customized public health policies for different regions.

Elucidating the gene regulatory mechanisms underlying the gut–brain axis is critical for uncovering novel gut–brain interaction pathways and developing therapeutic strategies for gut bacteria-associated neurological disorders. Most studies have primarily investigated how gut bacteria modulate host epigenetics and gene expression; their impact on host alternative splicing, particularly in the brain, remains largely unexplored. Here, we investigated the effects of the gut-associated probiotic Lacidofil^® on alternative splicing across 10 regions of the rat brain using published RNA-sequencing data. The Lacidofil^® altogether altered 2941 differential splicing events, predominantly, skipped exon (SE) and mutually exclusive exon (MXE) events. Protein–protein interactions and a KEGG analysis of differentially spliced genes (DSGs) revealed consistent enrichment in the spliceosome and vesicle transport complexes, as well as in pathways related to neurodegenerative diseases, synaptic function and plasticity, and substance addiction across brain regions. Using the PsyGeNET platform, we found that DSGs from the locus coeruleus (LConly), medial preoptic area (mPOA), and ventral dentate gyrus (venDG) were enriched in depression-associated or schizophrenia-associated genes. Notably, we highlight the App gene, where Lacidofil^® precisely regulated the splicing of two exons causally involved in amyloid β protein-based neurodegenerative diseases. Although the splicing factors exhibited both splicing plasticity and expression plasticity in response to Lacidofil^®, the overlap between DSGs and differentially expressed genes (DEGs) in most brain regions was rather low. Our study provides novel mechanistic insight into how gut probiotics might influence brain function through the modulation of RNA splicing.

BackgroundHyperemesis gravidarum (HG), excessive vomiting in pregnancy, occurs in 0.3-10.8% of pregnancies and is associated with maternal and fetal morbidity. Despite the existence of several off-label treatment options that have shown clinical effectiveness in managing HG symptoms, the variability in treatment response highlights the need for more effective therapies. Our study aims to identify novel therapeutic targets that could lead to the development of additional, more effective treatment options.MethodsA two-sample Mendelian randomization (MR) analysis was performed to estimate the causal effects of blood-druggable genes on HG. Summary statistics for HG were obtained from the FinnGen study and UK Biobank. Cis-expression quantitative trait loci (cis-eQTL) for blood druggable genes were obtained from the eQTLGen Consortium and used as genetic instrumental variables. Another MR method, summary level mendelian randomization (SMR), was used to further confirm our results. We also used eQTL data of other vomiting-related tissues, brain regions, and esophagus, to validate our MR results. Finally, the potential side effects of the druggable genes for HG treatment were assessed using a phenome-wide MR.ResultsOverall, 2499 unique druggable genes were gathered. Two blood drug targets (OVGP1 and LGALS1) showed significant MR results in two independent datasets. No significant heterogeneity of instrumental variables or pleiotropy was detected. In addition, SMR analysis further confirmed the significance of these two prior druggable genes in the brain and esophagus tissues. Further phenome-wide MR analysis revealed no association between genetic proxies of OVGP1, and LGALS1 has been detected in increasing the risk of adverse pregnancy outcomes and other common diseases.ConclusionsThis study provides genetic evidence that targeting two druggable genes for HG has potential therapeutic advantages. This information is of considerable value in guiding and prioritizing the development of more effective therapies for HG.

Background: MicroRNAs (miRNAs) have pivotal roles in gene regulation. Circulating miRNAs have been developed as novel candidate non-invasive biomarkers for diagnosis, prognosis, and treatment response for diseases. However, miRNAs that have causal effects on Parkinson’s Disease (PD) remain largely unknown. To investigate the causal relationships between miRNAs and PD, here we conduct a Mendelian randomization (MR) study.Methods: This study utilized the summary-level data of respective genome-wide association studies (GWAS) for 2083 miRNAs and seven PD-related outcomes to comprehensively reveal the causal associations between the circulating miRNAs and PD. Two-sample MR design was deployed and the causal effects were estimated with inverse variance weighted, MR-Egger, and weighted median. Comprehensively sensitive analyses were followed, including Cochran’s Q test, MR-Egger intercept test, MR-PRESSO, and leave-one-out analysis, to validate the robustness of our results. Finally, we investigated the potential role of the MR significant miRNAs by predicting their target genes and functional enrichment analysis.Results: Inverse variance weighted estimates suggested that two miRNAs, miR-205-5p (β = −0.46, 95%CI: −0.690 to −0.229, p = 9.3 × 10⁻⁵) and miR-6800-5p (β = −0.389, 95%CI: −0.575 to −0.202, p = 4.32 × 10⁻⁵), significantly decreased the rate of cognitive decline among PD patients. In addition, eight miRNAs were nominally associated with more than three PD-related outcomes each. No significant heterogeneity of instrumental variables or horizontal pleiotropy was found. Gene Ontology (GO) analysis showed that the targets of these causal miRNAs were significantly enriched in cell cycle, apoptotic, and aging pathways.Conclusion: This MR study identified two miRNAs whose genetically regulated expression might have a causal role in the development of PD dementia. Our findings provided potential miRNA biomarkers to make better and early diagnoses and risk assessments of PD.

Background: Long coronavirus disease (COVID), characterized by persistent and sometimes debilitating symptoms following a severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) infection, has garnered increasing attention as a potential public health crisis. Emerging evidence indicates a higher incidence of hearing loss in individuals who have had COVID 2019 (COVID‐19) compared to the general population. However, the conclusions were inconsistent, and the causal relationship between COVID‐19 and sensorineural hearing loss remains unknown.Methods: To addresses this outstanding issue, we performed Mendelian randomization analysis to detect the causal association between COVID‐19 and hearing loss using the largest genome‐wide association study data to date in the European population and confirmed the results in the East Asian population. Comprehensively sensitive analyses were followed, including Cochran's Q test, Mendelian randomization (MR)‐Egger intercept test, MR‐pleiotropy residual sum and outlier, and leave‐one‐out analysis, to validate the robustness of our results.Results: Our results suggested that there is no causal association between COVID‐19 and the risk of hearing loss in the European population. Neither the susceptibility, hospitalization, and severity of COVID‐19 on hearing loss (inverse variance weighted method: odds ratio (OR) = 1.046, 95% confidence interval (CI) = 0.907–1.205, p = .537; OR = 0.995, 95% CI = 0.956–1.036, p = .823; OR = 0.995, 95% CI = 0.967–1.025, p = .76). Replicated analyses in the East Asian population yielded consistent results. No pleiotropy and heterogeneity were found in our results.Conclusion: In conclusion, our MR results do not support a genetically predicted causal relationship between COVID‐19 and sensorineural hearing loss. Thus, the associations observed in prior observational studies may have been influenced by confounding factors rather than a direct cause‐and‐effect relationship. More clinical and mechanism research are needed to further understand this association in the future.