Search

Background: The symbiotic gut microbiota is pivotal for human health, with its composition linked to various diseases and metabolic disorders. Despite its significance, there remains a gap in systematically evaluating how host phenotypes, such as gender, age, and body mass index (BMI), influence gut microbiota., Methodology/principal Findings: We conducted an analysis of the gut microbiota of 185 Chinese adults based on whole-metagenome shotgun sequencing of fecal samples. Our investigation focused on assessing the effects of gender, age, and BMI on gut microbiota across three levels: diversity, gene/phylogenetic composition, and functional composition. Our findings suggest that these phenotypes have a minor impact on shaping the gut microbiome compared to enterotypes, they do not correlate significantly within- or between-sample diversity. We identified a substantial number of phenotype-associated genes and metagenomic linkage groups (MLGs), indicating variations in gut microflora composition. Specifically, we observed a decline in beneficial Firmicutes microbes, such as Eubacterium , Roseburia , Faecalibacterium and Ruminococcus spp., in both older individuals and those with higher BMI, while potentially harmful microbes like Erysipelotrichaceae , Subdoligranulum and Streptococcus spp. increased with age. Additionally, Blautia and Dorea spp. were found to increase with BMI, aligning with prior research. Surprisingly, individuals who were older or overweight exhibited a lack of Bacteroidetes, a dominant phylum in the human gut microbiota that includes opportunistic pathogens, while certain species of the well-known probiotics Bifidobacterium were enriched in these groups, suggesting a complex interplay of these bacteria warranting further investigation. Regarding gender, several gender-associated MLGs from Bacteroides , Parabacteroides , Clostridium and Akkermansia were enriched in females. Functional analysis revealed a multitude of phenotype-associated KEGG orthologs (KOs)., Conclusions/significance: Our study underscores the influence of gender, age, and BMI on gut metagenomes, affecting both phylogenetic and functional composition. However, further investigation is needed to elucidate the precise roles of these bacteria, including both pathogens and probiotics., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2024 Li, Fan, Ma, Xia and Yan.)

Objectives: Many studies have confirmed that antibacterial agents can disrupt the human gut microbiota. In China, Tanreqing injection (TRQ) is a drug with antibacterial activity that is widely used in the treatment of respiratory infections. However, its specific influence on gut microbiota remains unclear. This study aimed to investigate the effect of TRQ on the gut microbiota of healthy volunteers., Methods: Twelve healthy adults received 20 ml of TRQ intravenously daily for 7 consecutive days. At six timepoints (Pre, on D1, D3, D5, D7 and follow-up visit) fecal samples were collected and analyzed using 16S rRNA gene sequencing., Results: Eleven people were included in the analysis finally. TRQ did not significantly alter gut microbiota diversity or richness (Shannon and Simpson and Chao1 index) in healthy people during the intervention. Gut microbial structure was stable (weighted and unweighted Unifrac). Using a machine learning method based on PLS-DA analysis, the separation trend on D7 at the genus level was found, returning to baseline two days after discontinuation. The abundance of major genus fluctuated on D7 compared with that prior to treatment, including an increase of unclassified_f_Enterobacteriaceae (13.0611%), a decrease of Bifidobacterium and Escherichia-Shigella (6.887%, 10.487%). Functional prediction analysis did not reveal any significant difference., Conclusions: Our study showed short-term use of TRQ at conventional doses may not cause perturbations to the gut microbiota in healthy adults. This finding provides some useful information for the safe use of TRQ in the treatment of respiratory infections., Clinical Trial Registration: https://www.medicalresearch.org.cn/, identifier MR-31-24-014367., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Li, Zhang, Liu, Zhou, Liu, Yuan and He.)

Background: The causal relationship between gut microbiota and insulin-like growth factor 1 (IGF-1) remains unclear. The purpose of this study was to explore the causal relationship between gut microbiota and IGF-1 in men and women., Methods: Single-nucleotide polymorphisms (SNPs) related to gut microbiota were derived from pooled statistics from large genome-wide association studies (GWASs) published by the MiBioGen consortium. Pooled data for IGF-1 were obtained from a large published GWAS. We conducted Mendelian randomization (MR) analysis, primarily using the inverse variance weighted (IVW) method. Additionally, we performed sensitivity analyses to enhance the robustness of our results, focusing on assessing heterogeneity and pleiotropy., Results: In forward MR analysis, 11 bacterial taxa were found to have a causal effect on IGF-1 in men; 14 bacterial taxa were found to have a causal effect on IGF-1 in women (IVW, all P < 0.05). After false discovery rate (FDR) correction, all bacterial traits failed to pass the FDR correction. In reverse MR analysis, IGF-1 had a causal effect on nine bacterial taxa in men and two bacterial taxa in women respectively (IVW, all P < 0.05). After FDR correction, the causal effect of IGF-1 on order Actinomycetales ( P FDR = 0.049) remains in men. The robustness of the IVW results was further confirmed after heterogeneity and pleiotropy analysis., Conclusion: Our study demonstrates a bidirectional causal link between the gut microbiota and IGF-1, in both men and women., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Zheng, Qian and Wang.)

Background: The relationship between dysbiosis of the gastrointestinal microbiota and gastric cancer (GC) has been extensively studied. However, microbiota alterations in GC patients vary widely across studies, and reproducible diagnostic biomarkers for early GC are still lacking in multiple populations. Thus, this study aimed to characterize the gastrointestinal microbial communities involved in gastric carcinogenesis through a meta-analysis of multiple published and open datasets., Methods: We analyzed 16S rRNA sequencing data from 1,642 gastric biopsy samples and 394 stool samples across 11 independent studies. VSEARCH, QIIME and R packages such as vegan, phyloseq, cooccur, and random forest were used for data processing and analysis. PICRUSt software was employed to predict functions., Results: The α-diversity results indicated significant differences in the intratumoral microbiota of cancer patients compared to non-cancer patients, while no significant differences were observed in the fecal microbiota. Network analysis showed that the positive correlation with GC-enriched bacteria increased, and the positive correlation with GC-depleted bacteria decreased compared to healthy individuals. Functional analyses indicated that pathways related to carbohydrate metabolism were significantly enriched in GC, while biosynthesis of unsaturated fatty acids was diminished. Additionally, we investigated non- Helicobacter pylori (HP) commensals, which are crucial in both HP -negative and HP -positive GC. Random forest models, constructed using specific taxa associated with GC identified from the LEfSe analysis, revealed that the combination of Lactobacillus and Streptococcus included alone could effectively discriminate between GC patients and healthy individuals in fecal samples (area under the curve (AUC) = 0.7949). This finding was also validated in an independent cohort (AUC = 0.7712)., Conclusions: This study examined the intratumoral and fecal microbiota of GC patients from a dual microecological perspective and identified Lactobacillus, Streptococcus, Roseburia, Faecalibacterium and Phascolarctobacterium as intratumoral and intestinal-specific co-differential bacteria. Furthermore, it confirmed the validity of the combination of Lactobacillus and Streptococcus as GC-specific microbial markers across multiple populations, which may aid in the early non-invasive diagnosis of GC., Competing Interests: Author XL is employed by Liaoning Kanghui Biotechnology Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Wang, Wang, Han, Han, Liu, Dai, Dong, Sun and Xu.)

Background: The diagnosis and treatment of lung, colon, and gastric cancer through the histologic characteristics and genomic biomarkers have not had a strong impact on the mortality rates of the top three global causes of death by cancer., Methods: Twenty-five transcriptomic analyses (10 lung cancer, 10 gastric cancer, and 5 colon cancer datasets) followed our own bioinformatic pipeline based on the utilization of specialized libraries from the R language and DAVID´s gene enrichment analyses to identify a regulatory metafirm network of transcription factors and target genes common in every type of cancer, with experimental evidence that supports its relationship with the unlocking of cell phenotypic plasticity for the acquisition of the hallmarks of cancer during the tumoral process. The network's regulatory functional and signaling pathways might depend on the constant crosstalk with the microbiome network established in the oral-gut-lung axis., Results: The global transcriptomic network analysis highlighted the impact of transcription factors (SOX4, TCF3, TEAD4, ETV4, and FOXM1) that might be related to stem cell programming and cancer progression through the regulation of the expression of genes, such as cancer-cell membrane receptors, that interact with several microorganisms, including human T-cell leukemia virus 1 (HTLV-1), the human papilloma virus (HPV), the Epstein-Barr virus (EBV), and SARS-CoV-2. These interactions can trigger the MAPK, non-canonical WNT, and IFN signaling pathways, which regulate key transcription factor overexpression during the establishment and progression of lung, colon, and gastric cancer, respectively, along with the formation of the microbiome network., Conclusion: The global transcriptomic network analysis highlights the important interaction between key transcription factors in lung, colon, and gastric cancer, which regulates the expression of cancer-cell membrane receptors for the interaction with the microbiome network during the tumorigenic process., Competing Interests: Authors JL-R and CÁ-M were employed by the company Clínica Colsanitas S.A. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Otálora-Otálora, Payán-Gómez, López-Rivera, Pedroza-Aconcha, Aristizábal-Guzmán, Isaza-Ruget and Álvarez-Moreno.)

Background: Temporomandibular joint disorders (TMD) are highly prevalent among people. Numerous investigations have revealed the impact of gut microbiota in many diseases. However, the causal relationship between Temporomandibular joint disorders and gut microbiota remains unclear., Methods: Genome-Wide Association Studies (GWAS) refer to the identification of sequence variations, namely single nucleotide polymorphisms (SNPs), existing across the entire human genome. GWAS data were collected on gut microbiota and TMD. Then, instrumental variables were screened through F-values and removal of linkage disequilibrium. These SNPs underwent mendelian analysis using five mathematical models. Sensitivity analysis was conducted to further verify the stability of the results. Pathogenic factors of TMD mediate the causal relationship between gut microbiota and TMD were explored through a two-step Mendelian randomization analysis. Finally, reverse mendelian analysis was conducted to account for potential reverse effects., Results: The analysis of the data in this article suggests that some gut microbiota, including Coprobacter, Ruminococcus torques group, Catenibacterium, Lachnospiraceae, Turicibacter, Victivallis, MollicutesRF9, Methanobacteriales, Methanobacteriaceae, FamilyXI, Methanobacteria were identified as risk factors, while Peptococcaceae provides protection for TMD., Conclusion: The research reveals the relation of gut microbiota in TMD. These findings provide insights into the underlying mechanisms and suggest potential therapeutic strategy., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Zhao, JI, Jiang, Qian and Zhang.)

Objective: This study aimed to explore the correlation between microbiota dysbiosis and hypothyroidism in early pregnancy by 16S rRNA amplicon sequencing combined with metagenomic sequencing., Methods: Sixty pregnant women (30 with hypothyroidism and 30 normal controls) were recruited for 16S rRNA amplicon sequencing, and 6 patients from each group were randomly selected for metagenomic sequencing to assess the gut microbiome profile., Results: The 16S rRNA results showed that beta-diversity in the hypothyroidism group was decreased. The relative abundances of the Prevotella and Paraprevotella genera increased in the hypothyroidism group, and Blautia predominated in the controls. The metagenomics results revealed that Prevotella&#95;stercorea&#95;CAG&#95;629 , Prevotella&#95;hominis , Prevotella&#95;sp&#95;AM34&#95;19LB , etc. were enriched in the hypothyroidism group at the species level. Functional analysis revealed that the pyridoxal 5'-phosphate synthase pdxT subunit module was decreased, and the short-chain fatty acid (SCFA) transporter and phospholipase/carboxylesterase modules were strongly enriched in the hypothyroidism group. Hypothyroidism patients had increased C-reactive protein (CRP), interleukin-2 (IL-2), IL-4, IL-10, and tumor necrosis factor (TNF)-α levels. The pyridoxal 5'-phosphate synthase pdxT subunit, the SCFA transporter, and the phospholipase/carboxylesterase module were associated with different Prevotella species., Conclusion: In early pregnancy, women with hypothyroidism exhibit microbiota dysbiosis, and Prevotella may affect the metabolism of glutamate, SCFA, and phospholipases, which could be involved in the development of hypothyroidism during pregnancy., Competing Interests: The authors declare that the research was conducted without any commercial or financial relationships that could be construed as potential conflicts of interest., (Copyright © 2024 Hu, Xu, Li, Zhang, Sun, Ban, Tian, Liu and Hu.)

Background: Gut microbiota is closely related to the occurrence and development of sepsis. However, the causal effects between the gut microbiota and sepsis, and whether circulating inflammatory proteins act as mediators, remain unclear., Methods: Gut microbiota, circulating inflammatory proteins, and four sepsis-related outcomes were identified from large-scale genome wide association studies (GWAS) summary data. Inverse Variance Weighted (IVW) was the primary statistical method. Additionally, we investigated whether circulating inflammatory proteins play a mediating role in the pathway from gut microbiota to the four sepsis-related outcomes., Results: There were 14 positive and 15 negative causal effects between genetic liability in the gut microbiota and four sepsis-related outcomes. Additionally, eight positive and four negative causal effects were observed between circulating inflammatory proteins and the four sepsis-related outcomes. Circulating inflammatory proteins do not act as mediators., Conclusions: Gut microbiota and circulating inflammatory proteins were causally associated with the four sepsis-related outcomes. However, circulating inflammatory proteins did not appear to mediate the pathway from gut microbiota to the four sepsis-related outcomes., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Li, Lin, Kong, Feng, Ren, Wang, Chen, Wu, Yang, Li, Liu, Lu and Chen.)

Background: Recent studies have shown that gut microbiota may be related to the occurrence of brain tumors, but direct evidence is lacking. This study used the Mendelian randomization study (MR) method to explore the potential causal link between gut microbiota and brain tumors., Method: We analyzed the genome-wide association data between 211 gut microbiota taxa and brain tumors, using the largest existing gut microbiota Genome-Wide Association Studies meta-analysis data (n=13266) and combining it with brain tumor data in the IEU OpenGWAS database. We use inverse-variance weighted analysis, supplemented by methods such as Mendelian randomization-Egger regression, weighted median estimator, simple mode, and weighted mode, to assess causality. In addition, we also conducted the Mendelian randomization-Egger intercept test, Cochran's Q test, and Mendelian randomization Steiger directionality test to ensure the accuracy of the analysis. Quality control includes sensitivity analysis, horizontal gene pleiotropy test, heterogeneity test, and MR Steiger directionality test., Result: Our study found that specific gut microbial taxa, such as order Lactobacillales and family Clostridiaceae1, were positively correlated with the occurrence of brain tumors, while genus Defluviitaleaceae UCG011 and genus Flavonifractor were negatively correlated with the occurrence of brain tumors. The Mendelian randomization-Egger intercept test showed that our analysis was not affected by pleiotropy (P>0.05)., Conclusion: This study reveals for the first time the potential causal relationship between gut microbiota and brain tumors, providing a new perspective for the prevention and treatment of early brain tumors. These findings may help develop new clinical intervention strategies and point the way for future research., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Yang, Lu, Dong, Wei, Christian, Huang, Kuang and Cao.)

Objective: This study aims to investigate the associations between specific bacterial taxa of the gut microbiome and the development of aortic aneurysm diseases, utilizing Mendelian Randomization (MR) to explore these associations and overcome the confounding factors commonly present in observational studies., Methods: Employing the largest available gut microbiome and aortic aneurysm Genome-Wide Association Study databases, including MiBioGen, Dutch Microbiome Project, FinnGen, UK Biobank, and Michigan Genomics Initiative, this study performs two-sample bidirectional MR analyses. Instrumental variables, linked to microbiome taxa at significant levels, were selected for identifying relationships with abdominal aortic aneurysms (AAA), thoracic aortic aneurysms (TAA), and aortic dissection (AD). Methods like inverse variance weighted, MR-PRESSO, MR-Egger, weighted median, simple mode, and mode-based estimate were used for MR analysis. Heterogeneity was assessed with the Cochran Q test. MR-Egger regression and MR-PRESSO addressed potential unbalanced horizontal pleiotropy., Results: The analysis did not find any evidence of statistically significant associations between the gut microbiome and aortic aneurysm diseases after adjusting for the false discovery rate (FDR). Specifically, while initial results suggested correlations between 19 taxa and AAA, 25 taxa and TAA, and 13 taxa with AD, these suggested associations did not hold statistical significance post-FDR correction. Therefore, the role of individual gut microbial taxa as independent factors in the development and progression of aortic aneurysm diseases remains inconclusive. This finding underscores the necessity for larger sample sizes and more comprehensive studies to further investigate these potential links., Conclusion: The study emphasizes the complex relationship between the gut microbiome and aortic aneurysm diseases. Although no statistically significant associations were found after FDR correction, the findings provide valuable insights and highlight the importance of considering gut microbiota in aortic aneurysm diseases research. Understanding these interactions may eventually contribute to identifying new therapeutic and preventive strategies for aortic aneurysm diseases., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Sun, Dong, Sun, Du, Gao, Voevoda, Knyazev and Wu.)

Background: Some observational studies and clinical experiments suggest a close association between gut microbiota and metabolic diseases. However, the causal effects of gut microbiota on adrenal diseases, including Adrenocortical insufficiency, Cushing syndrome, and Hyperaldosteronism, remain unclear., Methods: This study conducted a two-sample Mendelian randomization analysis using summary statistics data of gut microbiota from a large-scale genome-wide association study conducted by the MiBioGen Consortium. Summary statistics data for the three adrenal diseases were obtained from the FinnGen study. The study employed Inverse variance weighting, MR-Egger, and MR-PRESSO methods to assess the causal relationship between gut microbiota and these three adrenal diseases. Additionally, a reverse Mendelian randomization analysis was performed for bacteria found to have a causal relationship with these three adrenal diseases in the forward Mendelian randomization analysis. Cochran's Q statistic was used to test for heterogeneity of instrumental variables., Results: The IVW test results demonstrate that class Deltaproteobacteria, Family Desulfovibrionaceae, and Order Desulfovibrionales exhibit protective effects against adrenocortical insufficiency. Conversely, Family Porphyromonadaceae, Genus Lachnoclostridium, and Order MollicutesRF9 are associated with an increased risk of adrenocortical insufficiency. Additionally, Family Acidaminococcaceae confers a certain level of protection against Cushing syndrome. In contrast, Class Methanobacteria, Family Lactobacillaceae, Family Methanobacteriaceae, Genus. Lactobacillus and Order Methanobacteriales are protective against Hyperaldosteronism. Conversely, Genus Parasutterella, Genus Peptococcus, and Genus Veillonella are identified as risk factors for Hyperaldosteronism., Conclusions: This two-sample Mendelian randomization analysis revealed a causal relationship between microbial taxa such as Deltaproteobacteria and Desulfovibrionaceae and Adrenocortical insufficiency, Cushing syndrome, and Hyperaldosteronism. These findings offer new avenues for comprehending the development of adrenal diseases mediated by gut microbiota., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Zhang, Liu, Chen and Wan.)

Background: Postpartum depression (PPD) is a common complication of pregnancy that imposes a heavy health and economic burden on individuals, families and society. The etiology of PPD is complex and incompletely defined, and recent studies have identified an important role for gut microbiota (GM) and their metabolites in neurological disorders. However, fewer studies on GM and PPD are available and have not yielded uniform results., Methods: Instrumental variables for GM and blood metabolites were obtained from the MiBioGen consortium and metabolomics GWAS server. Single nucleotide polymorphisms (SNPs) associated with PPD phenotypes were obtained from the FinnGen consortium. Inverse variance weighted (IVW), weighted median, weighted mode, and MR-Egger methods were used to assess causal effects. Inverse MR analysis and sensitivity analysis were also utilized to improve the stability of the results., Results: In this study, 5 intestinal species and 24 blood metabolites causally associated with PPD were identified using MR analysis. In addition, MR analysis showed that Prevotellaceae and Bifidobacteria may reduce the risk of PPD by elevating Xanthine and 1-arachidonoylglycerophosphoinositol (LysoPI) levels., Conclusions: This study identified GM and blood metabolites causally associated with PPD. The results of this study may provide a theoretical basis for the discovery of PPD-related biomarkers and the treatment of the disease by regulating the gut microenvironment., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Cui, Zhai, Yang and Liu.)

The intestinal microbiota assumes a pivotal role in modulating host metabolism, immune responses, overall health, and additional physiological dimensions. The structural and functional characteristics of the intestinal microbiota may cause alterations within the host's body to a certain extent. The composition of the gut microbiota is associated with environmental factors, dietary habits, and other pertinent conditions. The investigation into the gut microbiota of yaks remained relatively underexplored. An examination of yak gut microbiota holds promise in elucidating the complex relationship between microbial communities and the adaptive responses of the host to its environment. In this study, yak were selected from two distinct environmental conditions: those raised in sheds (NS, n=6) and grazed in Nimu County (NF, n=6). Fecal samples were collected from the yaks and subsequently processed for analysis through 16S rDNA and ITS sequencing methodologies. The results revealed that different feeding styles result in significant differences in the Alpha diversity of fungi in the gut of yaks, while the gut microbiota of captive yaks was relatively conserved. In addition, significant differences appeared in the abundance of microorganisms in different taxa, phylum Verrucomicrobiota was significantly enriched in group NF while Firmicutes was higher in group NS. At the genus level, Akkermansia , Paenibacillus , Roseburia , Dorea , UCG&#95;012 , Anaerovorax and Marvinbryantia were enriched in group NF while Desemzia , Olsenella , Kocuria , Ornithinimicrobium and Parvibacter were higher in group NS (P<0.05 or P<0.01). There was a significant difference in the function of gut microbiota between the two groups. The observed variations are likely influenced by differences in feeding methods and environmental conditions both inside and outside the pen. The findings of this investigation offer prospective insights into enhancing the yak breeding and expansion of the yak industry., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Zhu, Lu, Cidan, Wang, Li and Basang.)

Background: The relationship between gut microbiota and hematologic malignancies has attracted considerable attention. As research progresses, it has become increasingly clear that the composition of gut microbiota may influence the onset and progression of hematologic malignancies. However, our understanding of this association remains limited., Methods: In our study, we classified gut microbiota into five groups based on information at the phylum, class, order, family, and genus levels. Subsequently, we obtained data related to common hematologic malignancies from the IEU Open GWAS project. We then employed a bidirectional Mendelian Randomization (MR) approach to determine whether there is a causal relationship between gut microbiota and hematologic malignancies. Additionally, we conducted bidirectional MR analyses to ascertain the directionality of this causal relationship., Results: Through forward and reverse MR analyses, we found the risk of lymphoid leukemia was significantly associated with the abundance of phylum Cyanobacteria, order Methanobacteriales, class Methanobacteria, family Peptococcaceae, family Methanobacteriaceae, and genera Lachnospiraceae UCG010, Methanobrevibacter, Eubacterium brachy group, and Butyrivibrio. The risk of myeloid leukemia was significantly associated with the abundance of phylum Actinobacteria, phylum Firmicutes, order Bifidobacteriales, order Clostridiales, class Actinobacteria, class Gammaproteobacteria, class Clostridia, family Bifidobacteriaceae, and genera Fusicatenibacter, Eubacterium hallii group, Blautia, Collinsella, Ruminococcus gauvreauii group, and Bifidobacterium. The risk of Hodgkin lymphoma was significantly associated with the abundance of family Clostridiales vadinBB60 group, genus Peptococcus, and genus Ruminococcaceae UCG010. The risk of malignant plasma cell tumor was significantly associated with the abundance of genera Romboutsia and Eubacterium rectale group. The risk of diffuse large B-cell lymphoma was significantly associated with the abundance of genera Erysipelatoclostridium and Eubacterium coprostanoligenes group. The risk of mature T/NK cell lymphomas was significantly associated with the abundance of phylum Verrucomicrobia, genus Ruminococcaceae UCG013, genus Lachnoclostridium, and genus Eubacterium rectale group. Lastly, the risk of myeloproliferative neoplasms was significantly associated with the abundance of genus Coprococcus 3 and Eubacterium hallii group., Conclusion: Our study provided new evidence for the causal relationship between gut microbiota and hematologic malignancies, offering novel insights and approaches for the prevention and treatment of these tumors., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Chen, Guo, Wang, Feng, Qin, Hu, Lyu and Wang.)

Background: The microbiota-gut-lung axis has elucidated a potential association between gut microbiota and idiopathic pulmonary fibrosis (IPF). However, there is a paucity of population-level studies with providing robust evidence for establishing causality. This two-sample Mendelian randomization (MR) analysis aimed to investigate the causal relationship between the gut microbiota and IPF as well as lung function., Materials and Methods: Adhering to Mendel's principle of inheritance, this MR analysis utilized summary-level data from respective genome-wide association studies (GWAS) involving 211 gut microbial taxa, IPF, and lung function indicators such as FEV 1 , FVC, and FEV 1 /FVC. A bidirectional two-sample MR design was employed, utilizing multiple MR analysis methods, including inverse variance-weighted (IVW), weighted median, MR-Egger, and weighted mode. Multivariable MR (MVMR) was used to uncover mediating factors connecting the exposure and outcome. Additionally, comprehensive sensitivity analyses were conducted to ensure the robustness of the results., Results: The MR results confirmed four taxa were found causally associated with the risk of IPF. Order Bifidobacteriales (OR=0.773, 95% CI: 0.610-0.979, p=0.033), Family Bifidobacteriaceae (OR=0.773, 95% CI: 0.610-0.979, p=0.033), and Genus RuminococcaceaeUCG009 (OR=0.793, 95% CI: 0.652-0.965, p=0.020) exerted protective effects on IPF, while Genus Coprococcus2 (OR=1.349, 95% CI: 1.021-1.783, p=0.035) promote the development of IPF. Several taxa were causally associated with lung function, with those in Class Deltaproteobacteria, Order Desulfovibrionales, Family Desulfovibrionaceae, Class Verrucomicrobiae , Order Verrucomicrobiales and Family Verrucomicrobiaceae being the most prominent beneficial microbiota, while those in Family Lachnospiraceae, Genus Oscillospira , and Genus Parasutterella were associated with impaired lung function. As for the reverse analysis, MR results confirmed the effects of FEV 1 and FVC on the increased abundance of six taxa ( Phylum Actinobacteria, Class Actinobacteria, Order Bifidobacteriales, Family Bifidobacteriaceae, Genus Bifidobacterium , and Genus Ruminiclostridium9 ) with a boosted level of evidence. MVMR suggested monounsaturated fatty acids, total fatty acids, saturated fatty acids, and ratio of omega-6 fatty acids to total fatty acids as potential mediating factors in the genetic association between gut microbiota and IPF., Conclusion: The current study suggested the casual effects of the specific gut microbes on the risk of IPF and lung function. In turn, lung function also exerted a positive role in some gut microbes. A reasonable dietary intake of lipid substances has a certain protective effect against the occurrence and progression of IPF. This study provides novel insights into the potential role of gut microbiota in IPF and indicates a possible gut microbiota-mediated mechanism for the prevention of IPF., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Ren, Zhang, Cheng, Qin and Zhao.)

Introduction: The oral cavity and gut tract, being interconnected and rich in microbiota, may have a shared influence on gingivitis. However, the specific role of distinct gut microbiota taxa in gingivitis remains unexplored. Utilizing Mendelian Randomization (MR) as an ideal method for causal inference avoiding reverse causality and potential confounding factors, we conducted a comprehensive two-sample MR study to uncover the potential genetic causal impact of gut microbiota on gingivitis., Methods: Instrumental variables were chosen from single nucleotide polymorphisms (SNPs) strongly associated with 418 gut microbiota taxa, involving 14,306 individuals. Gingivitis, with 4,120 cases and 195,395 controls, served as the outcome. Causal effects were assessed using random-effect inverse variance-weighted, weighted median, and MR-Egger methods. For replication and meta-analysis, gingivitis data from IEU OpenGWAS were employed. Sensitivity analyses included Cochran's Q tests, funnel plots, leave-one-out analyses, and MR-Egger intercept tests. This study aimed to assess the genetic correlation between the genetically predicted gut microbiota and gingivitis using linkage disequilibrium score regression (LDSC)., Results: Three gut microbiota taxa (class Actinobacteria id.419, family Defluviitaleaceae id.1924, genus Defluviitaleaceae UCG011 id.11287) are predicted to causally contribute to an increased risk of gingivitis (P< 0.05). Additionally, four gut microbiota taxa (class Actinobacteria id.419, genus Escherichia Shigella id.3504, genus Ruminococcaceae UCG002 id.11360) potentially exhibit inhibitory causal effects on the risk of gingivitis (P< 0.05). No significant evidence of heterogeneity or pleiotropy is detected. Our findings indicate a suggestive genetic correlation between class Actinobacteria id.419, class Bacteroidia id.912, family Defluviitaleaceae id.1924, genus Escherichia Shigella id.3504 and gingivitis., Conclusion: Our study establishes the genetic causal effect of 418 gut microbiota taxa on gingivitis, offering insights for clinical interventions targeting gingivitis. Subsequent research endeavors are essential to corroborate the findings of our present study., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Hang, Rouyi and Sen.)

Objective: To investigate the structure, composition, and functions of the gut microbiota in elderly patients with hyperlipidemia., Methods: Sixteen older patients diagnosed with hyperlipidemia (M group) and 10 healthy, age-matched normal volunteers (N group) were included. These groups were further subdivided by sex into the male normal (NM, n = 5), female normal (NF, n = 5), male hyperlipidemia (MM, n = 8), and female hyperlipidemia (MF, n = 8) subgroups. Stool samples were collected for high-throughput sequencing of 16S rRNA genes. Blood samples were collected for clinical biochemical index testing., Results: Alpha- and beta-diversity analyses revealed that the structure and composition of the gut microbiota were significantly different between the M and N groups. The relative abundances of Bacteroides , Parabacteroides , Blautia , Peptococcus , and Bifidobacterium were significantly decreased, while those of Lactobacillus , Helicobacter , and Desulfovibrio were significantly higher in the M group. There were also significant sex-related differences in microbial structure between the NM and NF groups, and between the MM and MF groups. Through functional prediction with PICRUSt 2, we observed distinct between-group variations in metabolic pathways associated with the gut microbiota and their impact on the functionality of the nervous system. Pearson's correlation coefficient was used as a distance metric to build co-abundance networks. A hypergeometric test was used to detect taxonomies with significant enrichment in specific clusters. We speculated that modules with Muribaculaceae and Lachnospiraceae as the core microbes play an important ecological role in the intestinal microbiota of the M group. The relative intestinal abundances of Agathobacter and Faecalibacterium in the M group were positively correlated with serum triglyceride and low-density lipoprotein levels, while the relative abundance of Bifidobacterium was negatively correlated with the serum lipoprotein a level., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Xia, Xu, Li, Huang, Zhou, Gao and Han.)

Background: Multiple studies have suggested a possible connection between the gut microbiota and the development of lymphoma, though the exact nature of this relationship remains unclear. This study aimed to explore whether a causal association exists between gut microbiota and lymphoma., Methods: A bidirectional two-sample Mendelian randomization (MR) approach was conducted to investigate potential causal effects between gut microbiota and various lymphoma subtypes. The primary method employed for MR analysis was inverse variance weighted (IVW), supplemented by additional methods including MR-Egger, weighted median, and weighted mode approaches. The Cochrane Q test, MR-PRESSO global test and MR-Egger intercept test were performed to assess pleiotropy and heterogeneity. Furthermore, a reverse MR analysis was performed to explore potential reverse causal effect., Results: The primary MR analysis identified 36 causal relationships between genetic liabilities in gut microbiota and different lymphoma subtypes. Neither the MR-PRESSO test nor the MR-Egger regression detected any pleiotropy, and Cochran's Q test indicated no significant heterogeneity., Conclusions: Our MR analysis revealed substantial causal associations between gut microbiota and lymphoma, offering new insights into lymphoma prevention and management microbiota., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Liang, Liu, Wang and Xue.)

Introduction: Chronic kidney disease (CKD) is worldwide healthcare burden with growing incidence and death rate. Emerging evidence demonstrated the compositional and functional differences of gut microbiota in patients with CKD. As such, gut microbial features can be developed as diagnostic biomarkers and potential therapeutic target for CKD., Methods: To eliminate the outcome bias arising from factors such as geographical distribution, sequencing platform, and data analysis techniques, we conducted a comprehensive analysis of the microbial differences between patients with CKD and healthy individuals based on multiple samples worldwide. A total of 980 samples from six references across three nations were incorporated from the PubMed, Web of Science, and GMrepo databases. The obtained 16S rRNA microbiome data were subjected to DADA2 processing, QIIME2 and PICRUSt2 analyses., Results: The gut microbiota of patients with CKD differs significantly from that of healthy controls (HC), with a substantial decrease in the microbial diversity among the CKD group. Moreover, a significantly reduced abundance of bacteria Faecalibacterium prausnitzii (F. prausnitzii) was detected in the CKD group through linear discriminant analysis effect size (LEfSe) analysis, which may be associated with the alleviating effects against CKD. Notably, we identified CKD-depleted F. prausnitzii demonstrated a significant negative correlation with three pathways based on predictive functional analysis, suggesting its potential role in regulating systemic acidbase disturbance and pro-oxidant metabolism., Discussion: Our findings demonstrated notable alterations of gut microbiota in CKD patients. Specific gut-beneficial microbiota, especially F. prausnitzii, may be developed as a preventive and therapeutic tool for CKD clinical management., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Zhang, Zhong, Liu, Wang, Lin, Lin, Fang, Mou, Jiang, Huang, Zhao and Zheng.)

The enrichment of oral taxa in the gut has recently been reported as a notable alteration in the microbial balance in patients with intestinal disorders. However, translocation in populations without such diseases remains controversial. In this study, we examined 49 pairs of tongue and rectal samples collected from orthopedic patients without a history of intestinal disorders to verify the presence of oral taxa in the rectal microbiota. The bacterial composition of each sample was determined using 16S rRNA gene sequencing and amplicon sequence variant (ASV) analysis. Although the bacterial compositions of the tongue and rectal microbiota were distinctly different, tongue ASVs were detected in 67.3% of the participants and accounted for 0.0%-9.37% of the rectal microbiota. Particularly, Streptococcus salivarius , Fusobacterium nucleatum , and Streptococcus parasanguinis were abundant in the rectal microbiota. According to the network analysis, tongue taxa, such as S. salivarius and S. parasanguinis , formed a cohabiting group with Klebsiella pneumoniae and Alistipes finegoldii in the rectal microbiota. The total abundance of tongue ASVs in the rectal microbiota was significantly higher in participants with older age, hypertension, and proton pump inhibitor (PPI) use. Our study presents an extensive translocation of oral taxa to the rectum of a population without intestinal disorders and suggests that aging, hypertension, and PPI use are associated with an increased abundance of oral taxa and potential pathogenic bacteria in the rectal microbiota., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Lin, Kageyama, Maeda, Sakamoto, Ma, Asakawa, Furuta, Yamashita and Takeshita.)

Background: Recent studies have emphasized the role of gut microbiota in the onset and progression of osteomyelitis. However, the exact types of gut microbiota and their mechanisms of action remain unclear. Additionally, there is a lack of theoretical support for treatments that improve osteomyelitis by altering the gut microbiota., Methods: In our study, we utilized the largest genome-wide association study (GWAS) meta-analysis to date from the MiBioGen consortium, involving 13,400 participants. The GWAS data for osteomyelitis were sourced from the UK Biobank, which included 4,836 osteomyelitis cases and 486,484 controls. We employed a two-sample Mendelian randomization framework for a detailed investigation into the causal relationship between gut microbiota and osteomyelitis. Our methods included inverse variance weighting, MR-Egger, weighted median, and weighted mode approaches. Additionally, we applied Cochran's Q statistic to assess the heterogeneity of the instrumental variable., Results: At the class level, Bacilli and Bacteroidia were positively correlated with the risk of osteomyelitis. At the order level, only Bacteroidales showed a positive association with osteomyelitis. At the genus level, an increased abundance of Butyricimonas , Coprococcus3 , and Tyzzerella3 was positively associated with the risk of osteomyelitis, whereas Lachnospira was negatively associated. Sensitivity analyses showed no evidence of heterogeneity or pleiotropy., Conclusion: This study reveals that classes Bacilli and Bacteroidia, order Bacteroidales, and genera Butyricimonas , Coprococcus3 , and Tyzzerella3 are implicated in increasing the risk of osteomyelitis, while the genus Lachnospira is associated with a reduced risk. Future investigations are warranted to elucidate the precise mechanisms through which these specific bacterial groups influence the pathophysiology of osteomyelitis., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Zeng, Wu, Liang, Cun, Ma, Zhang, Huang and Jiang.)

Background: Previous studies have suggested a link between gut microbiota and skin diseases, including erysipelas, an inflammatory skin condition. Despite this, the precise nature of the relationship between erysipelas and gut microbiota remains unclear and subject to debate., Methods: We conducted a Mendelian Randomization (MR) analysis using publicly available summary data from genome-wide association studies (GWAS) to explore the potential causal relationship between gut microbiota and erysipelas. Instrumental variables (IVs) were identified using a comprehensive set of screening methods. We then performed MR analyses primarily using the Inverse Variance Weighted (IVW) method, complemented by alternative approaches such as MR Egger, weighted median, simple mode, and weighted mode. A series of sensitivity analyses, including Cochran's Q test, MR-Egger intercept test, Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO) test, and a leave-one-out test, were executed to ensure the robustness and validity of our findings., Results: We identified potential associations between erysipelas and various gut microbiota, including Alcaligenaceae (OR 1.23; 95% CI 1.06-1.43; p=0.006), Rikenellaceae (OR 0.77; 95% CI 0.67-0.90; p=0.001), and others. Notably, associations with Actinomyces , Lachnospiraceae NC2004 group , Ruminiclostridium 9 , Ruminococcaceae UCG014 , Odoribacter , and Actinobacteria were also observed. Sensitivity analyses confirmed the robustness of these associations., Conclusion: Our MR analysis suggests both potentially beneficial and harmful causal relationships between various gut microbiota and the incidence of erysipelas. This study provides new theoretical and empirical insights into the pathogenesis of erysipelas and underscores the potential for innovative preventive and therapeutic approaches., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Bao, Wang, Wu, Luo and Wang.)

Aim: Mendelian randomization (MR) analysis has been used in the exploration of the role of gut microbiota (GM) in type 2 diabetes mellitus (T2DM); however, it was limited to the genus level. This study herein aims to investigate the relationship of GM, especially at the species level, with T2DM in order to provide some evidence for further exploration of more specific GM taxa and pathway abundance in T2DM., Methods: This two-sample MR study was based on the summary statistics of GM from the available genome-wide association study (GWAS) meta-analysis conducted by the MiBioGen consortium as well as the Dutch Microbiome Project (DMP), whereas the summary statistics of T2DM were obtained from the FinnGen consortium released data. Inverse variance weighted (IVW), MR-Egger, strength test ( F ), and weighted median methods were used to examine the causal association between GM and the onset of T2DM. Cochran's Q statistics was employed to quantify the heterogeneity of instrumental variables. Bonferroni's correction was conducted to correct the bias of multiple testing. We also performed reverse causality analysis., Results: The corrected IVW estimates suggested the increased relative abundance of family Oxalobacteraceae (OR = 1.0704) and genus Oxalobacter (OR = 1.0874), respectively, were associated with higher odds of T2DM, while that of species faecis (OR = 0.9460) had a negative relationship with T2DM. The relationships of class Betaproteobacteria , family Lactobacillaceae , species finegoldii , and species longum with T2DM were also significant according to the IVW results (all P < 0.05)., Conclusions: GM had a potential causal association with T2DM, especially species faecis , finegoldii , and longum . Further studies are still needed to clarify certain results that are contradictory with previous findings., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Zhang, Ma, Peng, Wang and Sun.)

Background: Gut microbiota has been associated with dermatological problems in earlier observational studies. However, it is unclear whether gut microbiota has a causal function in dermatological diseases., Methods: Thirteen dermatological diseases were the subject of bidirectional Mendelian randomization (MR) research aimed at identifying potential causal links between gut microbiota and these diseases. Summary statistics for the Genome-Wide Association Study (GWAS) of gut microbiota and dermatological diseases were obtained from public datasets. With the goal of evaluating the causal estimates, five acknowledged MR approaches were utilized along with multiple testing corrections, with inverse variance weighted (IVW) regression serving as the main methodology. Regarding the taxa that were causally linked with dermatological diseases in the forward MR analysis, reverse MR was performed. A series of sensitivity analyses were conducted to test the robustness of the causal estimates., Results: The combined results of the five MR methods and sensitivity analysis showed 94 suggestive and five significant causal relationships. In particular, the genus Eubacterium&#95;fissicatena&#95;group increased the risk of developing psoriasis vulgaris (odds ratio [OR] = 1.32, p FDR = 4.36 × 10 -3 ), family Bacteroidaceae (OR = 2.25, p FDR = 4.39 × 10 -3 ), genus Allisonella (OR = 1.42, p FDR = 1.29 × 10 -2 ), and genus Bacteroides (OR = 2.25, p FDR = 1.29 × 10 -2 ) increased the risk of developing acne; and the genus Intestinibacter increased the risk of urticaria (OR = 1.30, p FDR = 9.13 × 10 -3 ). A reverse MR study revealed insufficient evidence for a significant causal relationship. In addition, there was no discernible horizontal pleiotropy or heterogeneity., Conclusion: This study provides novel insights into the causality of gut microbiota in dermatological diseases and therapeutic or preventive paradigms for cutaneous conditions., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Wang, Yao, Lin, Ge, Huang, Gao and Wu.)

Background: Growing evidence has shown that gut microbiome composition is associated with Biliary tract cancer (BTC), but the causality remains unknown. This study aimed to explore the causal relationship between gut microbiota and BTC, conduct an appraisal of the gut microbiome's utility in facilitating the early diagnosis of BTC., Methods: We acquired the summary data for Genome-wide Association Studies (GWAS) pertaining to BTC (418 cases and 159,201 controls) from the Biobank Japan (BBJ) database. Additionally, the GWAS summary data relevant to gut microbiota (N = 18,340) were sourced from the MiBioGen consortium. The primary methodology employed for the analysis consisted of Inverse Variance Weighting (IVW). Evaluations for sensitivity were carried out through the utilization of multiple statistical techniques, encompassing Cochrane's Q test, the MR-Egger intercept evaluation, the global test of MR-PRESSO, and a leave-one-out methodological analysis. Ultimately, a reverse Mendelian Randomization analysis was conducted to assess the potential for reciprocal causality., Results: The outcomes derived from IVW substantiated that the presence of Family Streptococcaceae (OR = 0.44, P = 0.034), Family Veillonellaceae (OR = 0.46, P = 0.018), and Genus Dorea (OR = 0.29, P = 0.041) exerted a protective influence against BTC. Conversely, Class Lentisphaeria (OR = 2.21, P = 0.017), Genus Lachnospiraceae FCS020 Group (OR = 2.30, P = 0.013), and Order Victivallales (OR = 2.21, P = 0.017) were associated with an adverse impact. To assess any reverse causal effect, we used BTC as the exposure and the gut microbiota as the outcome, and this analysis revealed associations between BTC and five different types of gut microbiota. The sensitivity analysis disclosed an absence of empirical indicators for either heterogeneity or pleiotropy., Conclusion: This investigation represents the inaugural identification of indicative data supporting either beneficial or detrimental causal relationships between gut microbiota and the risk of BTC, as determined through the utilization of MR methodologies. These outcomes could hold significance for the formulation of individualized therapeutic strategies aimed at BTC prevention and survival enhancement., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Wang, Wang, Qin, Chen, Chen, Wang, Zhang, Guo, Zhou and Zou.)

Background: Graves' disease (GD), characterized by immune aberration, is associated with gut dysbiosis. Despite the growing interest, substantial evidence detailing the precise impact of gut microbiota on GD's autoimmune processes remains exceedingly rare., Objective: This study was designed to investigate the influence of gut microbiota on immune dysregulation in GD., Methods: It encompassed 52 GD patients and 45 healthy controls (HCs), employing flow cytometry and enzyme-linked immunosorbent assay to examine lymphocyte and cytokine profiles, alongside lipopolysaccharide (LPS) levels. Gut microbiota profiles and metabolic features were assessed using 16S rRNA gene sequencing and targeted metabolomics., Results: Our observations revealed a disturbed B-cell distribution and elevated LPS and pro-inflammatory cytokines in GD patients compared to HCs. Significant differences in gut microbiota composition and a marked deficit in short-chain fatty acid (SCFA)-producing bacteria, including ASV263( Bacteroides ), ASV1451( Dialister ), and ASV503( Coprococcus ), were observed in GD patients. These specific bacteria and SCFAs showed correlations with thyroid autoantibodies, B-cell subsets, and cytokine levels. In vitro studies further showed that LPS notably caused B-cell subsets imbalance, reducing conventional memory B cells while increasing naïve B cells. Additionally, acetate combined with propionate and butyrate showcased immunoregulatory functions, diminishing cytokine production in LPS-stimulated cells., Conclusion: Overall, our results highlight the role of gut dysbiosis in contributing to immune dysregulation in GD by affecting lymphocyte status and cytokine production., Competing Interests: HR was employed by Shanghai Mobio Biomedical Technology Corporation Limited. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Liu, Tang, Feng, Xue, Cheng, Su, Wei, Zhang, Huang, Shi, Fang, Yang, Zhang, Deng, Wang, Ren, Wang and Yuan.)

Background: Changes in the gut microbiota are closely related to insomnia, but the causal relationship between them is not yet clear., Objective: To clarify the relationship between the gut microbiota and insomnia and provide genetic evidence for them, we conducted a two-sample Mendelian randomization study., Methods: We used a Mendelian randomized two-way validation method to discuss the causal relationship. First, we downloaded the data of 462,341 participants relating to insomnia, and the data of 18,340 participants relating to the gut microbiota from a genome-wide association study (GWAS). Then, we used two regression models, inverse-variance weighted (IVW) and MR-Egger regression, to evaluate the relationship between exposure factors and outcomes. Finally, we took a reverse MR analysis to assess the possibility of reverse causality., Results: The combined results show 19 gut microbiotas to have a causal relationship with insomnia (odds ratio (OR): 1.03; 95% confidence interval (CI): 1.01, 1.05; p=0.000 for class. Negativicutes; OR: 1.03; 95% CI: 1.01, 1.05; p=0.000 for order.Selenomonadales; OR: 1.01; 95% CI: 1.00, 1.02; p=0.003 for genus.RikenellaceaeRC9gutgroup). The results were consistent with sensitivity analyses for these bacterial traits. In reverse MR analysis, we found no statistical difference between insomnia and these gut microbiotas., Conclusion: This study can provide a new direction for the causal relationship between the gut microbiota (class.Negativicutes, order.Selenomonadales, genus.Lactococcus) and insomnia and the treatment or prevention strategies of insomnia., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Wang, Gao, Zhang, Liu, Li, Chen and Mei.)

Background: Numerous studies have demonstrated the influence of gut microbiota on the development of obesity. In this study, we utilized Mendelian randomization (MR) analysis to investigate the gut microbiota characteristics among different types of obese patients, aiming to elucidate the underlying mechanisms and provide novel insights for obesity treatment., Methods: Two-sample multivariable Mendelian randomization (MR) analysis was employed to assess causal relationships between gut microbiota and various obesity subtypes. Gut microbiota data were obtained from the international consortium MiBioGen, and data on obese individuals were sourced from the Finnish National Biobank FinnGen. Eligible single-nucleotide polymorphisms (SNPs) were selected as instrumental variables. Various analytical methods, including inverse variance weighted (IVW), MR-Egger regression, weighted median, MR-RAPS, and Lasso regression, were applied. Sensitivity analyses for quality control included MR-Egger intercept tests, Cochran's Q tests, and leave-one-out analyses and others., Results: Mendelian randomization studies revealed distinct gut microbiota profiles among European populations with different obesity subtypes. Following multivariable MR analysis, we found that Ruminococcaceae UCG010 [ Odds Ratio (OR) : 0.842, 95% confidence interval (CI) : 0.766-0.926, Adjusted P value: 0.028] independently reduced the risk of obesity induced by excessive calorie intake, while Butyricimonas [ OR : 4.252, 95% CI : 2.177-8.307, Adjusted P value: 0.002] independently increased the risk of medication-induced obesity. For localized adiposity, Pasteurellaceae [ OR : 0.213, 95% CI : 0.115-0.395, Adjusted P value: <0.001] acted as a protective factor. In the case of extreme obesity with alveolar hypoventilation, lactobacillus [ OR : 0.724, 95% CI : 0.609-0.860, Adjusted P value: 0.035] reduced the risk of its occurrence. Additionally, six gut microbiota may have potential roles in the onset of different types of obesity. Specifically, the Ruminococcus torques group may increase the risk of its occurrence. Desulfovibrio and Catenabacterium may serve as protective factors in the onset of Drug-induced obesity. Oxalobacteraceae , Actinomycetaceae , and Ruminiclostridium 9 , on the other hand, could potentially increase the risk of Drug-induced obesity. No evidence of heterogeneity or horizontal pleiotropy among SNPs was found in the above studies (all P values for Q test and MR-Egger intercept > 0.05)., Conclusion: Gut microbiota abundance is causally related to obesity, with distinct gut microbiota profiles observed among different obesity subtypes. Four bacterial species, including Ruminococcaceae UCG010 , Butyricimonas , Pasteurellaceae and lactobacillus independently influence the development of various types of obesity. Probiotic and prebiotic supplementation may represent a novel approach in future obesity management., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Liu, Li, Cai, Ren, Sun, Gang and Wang.)

Background: The elevated mortality rate associated with non-small-cell lung cancer (NSCLC) is a well-established global concern. Considerable attention has been directed toward exploring the association between gut microbiota and various malignant tumors. We herein investigated the associations between the intestinal microbiome and its metabolites, particularly short-chain fatty acids (SCFAs), in patients with NSCLC at different stages, including early and brain metastasis (BM) stages. The findings aim to offer a fresh perspective on the diagnosis and management of NSCLC., Methods: Fecal samples were collected from 115 participants, comprising healthy controls (n = 35) and patients with treatment-naive NSCLC at the early stage (ELC, n = 40) and the BM stage (n = 40). Characterization of the intestinal microbiome and fecal SCFA levels was performed using 16S rRNA gene sequencing and gas chromatography., Results: The microbial diversity in patients with NSCLC was found to be less abundant and uniform, particularly in the BM stage. Significant alterations in the community structure of the gut microbiota were observed in patients with NSCLC, with an increase in pathogens in Fusobacteria and Proteobacteria and a decrease in SCFA-producing bacteria in Firmicutes and Actinobacteria, particularly in the BM stage. Meanwhile, microbial communities displayed intricate associations in patients with NSCLC. A biomarker panel ( Faecalibacterium , Bifidobacterium , Butyricicoccus , Klebsiella , Streptococcus , and Blautia ) successfully distinguished patients in the ELC and BM stages from healthy controls (area under the curve: 0.884). The overall concentration of fecal SCFAs was significantly lower in patients with BM compared to patients with ELC and healthy controls. Subgroup analysis of acetate and butyrate yielded similar results. Moreover, multiple disrupted pathways in the NSCLC group were identified using the Kyoto Encyclopedia of Genes and Genomes annotation, including lipid metabolism and genetic information processing, specifically in the BM stage., Conclusion: Compared with healthy controls, distinct host-microbe interactions were evident in different phases of patients with NSCLC. Furthermore, specific forms of the gut microbiome and SCFAs may serve as valuable biomarkers and therapeutic targets in the diagnosis and treatment of NSCLC., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Jiang, Zeng, Zhang, Li, Wang, Peng and Cao.)

Background: The gut microbiota (GM) is believed to be closely associated with symptomatic carotid atherosclerosis (SCAS), yet more evidence is needed to substantiate the significant role of GM in SCAS. This study, based on the detection of bacterial DNA in carotid plaques, explores the characteristics of GM in SCAS patients with plaque bacterial genetic material positivity, aiming to provide a reference for subsequent research., Methods: We enrolled 27 healthy individuals (NHF group) and 23 SCAS patients (PFBS group). We utilized 16S rDNA V3-V4 region gene sequencing to analyze the microbiota in fecal samples from both groups, as well as in plaque samples from the carotid bifurcation extending to the origin of the internal carotid artery in all patients., Results: Our results indicate significant differences in the gut microbiota (GM) between SCAS patients and healthy individuals. The detection rate of bacterial DNA in plaque samples was approximately 26%. Compared to patients with negative plaques (PRSOPWNP group), those with positive plaques (PRSOPWPP group) exhibited significant alterations in their GM, particularly an upregulation of 11 bacterial genera (such as Klebsiella and Streptococcus) in the gut, which were also present in the plaques. In terms of microbial gene function prediction, pathways such as Fluorobenzoate degradation were significantly upregulated in the GM of patients with positive plaques., Conclusion: In summary, our study is the first to identify significant alterations in the gut microbiota of patients with positive plaques, providing crucial microbial evidence for further exploration of the pathogenesis of SCAS., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2024 Lv, Zhang, Fu, Li, Yin, Liu, Xu, Wang, Li, Hao, Zhang and Wang.)

Introduction: Asthma is a multifarious disease that manifests in various phenotypes. Among the various factors that contribute to the development of asthma, the gut microbiota has recently emerged as a compelling area of investigation. This study aims to investigate the causal relationships between gut microbiota and distinct asthma phenotypes., Methods: The genome-wide association study (GWAS) summary statistics for 211 gut microbial taxa were used as study exposure. Five traits pertaining to various asthma phenotypes (asthma, allergic asthma, childhood asthma, suggestive for eosinophilic asthma and obesity-related asthma) were included as study outcome. We conducted Mendelian randomization (MR) analysis and sensitivity analysis for each bacterial taxa and asthma phenotypes., Result: We discovered a total of 58 associations that exhibited evidence of causality. Out of these, 4 associations remained significant even after applying multiple correction. An increased risk of asthma was causally associated with higher abundance of genus Holdemanella (OR = 1.11; CI: 1.05-1.17; p = 0.027), genus Oxalobacter (OR = 1.09; CI: 1.04-1.15; p = 0.025) and genus Butyricimonas (OR = 1.14; CI: 1.06-1.22; p = 0.027). Order NB1n was causally linked with an increased risk of obesity-related asthma (OR = 1.17; CI: 1.07-1.29; p = 0.015). There was limited overlap among the taxa that exhibited potential causal relationships with distinct asthma phenotypes., Conclusion: Our research has provided genetic evidence that establishes multiple causal relationships between the gut microbiota and distinct asthma phenotypes, supporting the role of the gut microbiota in various asthma phenotypes. It is possible that different taxa play a role in the development of distinct asthma phenotypes. The causal relationships identified in this study require further investigation., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2024 Cheng, Wu, Jie, Li and Zhang.)

Background: Evidence supports an observational association between the gut microbiome and susceptibility to extraintestinal cancers, but the causal relationship of this association remains unclear., Methods: To identify the specific causal gut microbiota of oral and oropharyngeal cancer, we performed two-sample Mendelian randomization (MR) analysis of gut microbiota on oral and oropharyngeal cancer using a fixed-effects inverse-variance-weighted model. Gut microbiota across five different taxonomical levels from the MiBioGen genome-wide association study (GWAS) were used as exposures. Oral cancer, oropharyngeal cancer and a combination of the two cancers defined from three separate data sources were used as the outcomes. Odds ratios (ORs) and 95% confidence intervals (CIs) for disease per standard deviation (SD) higher abundance of microbiome., Results & Conclusions: There was little evidence for a causal effect of gut microbiota on oral and oropharyngeal cancer when using a genome-wide p-value threshold for selecting instruments. Secondary analyses using a more lenient p-value threshold indicated that there were 90 causal relationships between 58 different microbial features but that sensitivity analyses suggested that these were possibly affected by violations of MR assumptions and were not consistent across MR methodologies or data sources and therefore are also to unlikely reflect causation. These findings provide new insights into gut microbiota-mediated oral and oropharyngeal cancers and warrant further investigation., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Zhang, Wang, Tian, Li, Xin and Jiang.)

Aims: This study aimed to investigate the association between the gut microbiota and the risk of stroke., Methods: Faecal samples from 60 participants in South China, including 45 individuals with risk factors for stroke and 15 healthy controls, were collected and subjected to 16S rRNA sequencing. A bioinformatics analysis was performed to characterise the gut microbial diversity and taxonomic compositions at different risk levels (low, moderate, and high) of stroke. Functional prediction and correlation analyses between the microbiota and laboratory markers were performed to explore the potential mechanisms., Results: A significant difference in beta diversity was observed between the participants from the stroke risk and healthy control groups. Linear discriminant effect size analysis revealed a large number of vascular beneficial bacteria enriched in the participants from the healthy control and low-risk groups, but a few vascular harmful bacteria were more abundant in the participants from the high-risk group than in those from the other groups. In addition, Anaerostipes , Clostridium&#95;XlVb , and Flavonifractor , all of which belonged to the Firmicutes phylum, were enriched in the participants from the low-risk group, and their relative abundances gradually decreased as the stroke risk increased. Spearman's analysis revealed that these outstanding microbiota correlated with the levels of triglycerides, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, white blood cells, neutrophils, and carotid intima-media thickness., Conclusion: The preliminary evidence suggests that gut microbiota is associated with stroke risk. It potentially ameliorates atherosclerosis by targeting lipid metabolism and inflammation. This provides novel insights into the early screening of stroke risk and primary prevention., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Huang, Kuang, Mo, Meng, Cai and Ni.)

Background: Previous research has posited a potential correlation between the gut microbiota and the onset of appendicitis; however, the precise causal connection between appendicitis and the gut microbiota remains an unresolved and contentious issue., Methods: In this investigation, we performed a Mendelian randomization (MR) analysis employing publicly accessible summary data extracted from genome-wide association studies (GWAS) to elucidate the potential causal nexus between the gut microbiota and the development of appendicitis. We initially identified instrumental variables (IVs) through a comprehensive array of screening methodologies, subsequently executing MR analyses using the Inverse Variance Weighted (IVW) technique as our primary approach, supplemented by several alternative methods such as MR Egger, weighted median, simple mode, and weighted mode. Additionally, we implemented a series of sensitivity analysis procedures, encompassing Cochran's Q test, MR-Egger intercept test, Mendelian Randomized Polymorphism Residual and Outlier (MR-PRESSO) test, and a leave-one-out test, to affirm the robustness and validity of our findings., Results: Our investigation indicates that an elevated prevalence of Deltaproteobacteria, Christensenellaceae, Desulfovibrionaceae, Eubacterium ruminantium group, Lachnospiraceae NK4A136 group, Methanobrevibacter, Desulfovibrionales, and Euryarchaeota is inversely associated with the risk of appendicitis. Conversely, we observed a positive correlation between an increased abundance of Family XIII, Howardella, and Veillonella and the susceptibility to appendicitis. Sensitivity analyses have corroborated the robustness of these findings, and Mendelian randomization analyses provided no indications of reverse causality., Conclusion: Our Mendelian randomization (MR) analysis has unveiled potential advantageous or detrimental causal associations between the gut microbiota and the occurrence of appendicitis. This study offers novel theoretical and empirical insights into the understanding of appendicitis pathogenesis, along with its implications for preventive and therapeutic strategies., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Wang, Bao, Wu, Zeng, Feng, Zhou, Luo and Wang.)

Background: In recent years, observational studies have provided evidence supporting a potential association between autism spectrum disorder (ASD) and gut microbiota. However, the causal effect of gut microbiota on ASD remains unknown., Methods: We identified the summary statistics of 206 gut microbiota from the MiBioGen study, and ASD data were obtained from the latest Psychiatric Genomics Consortium Genome-Wide Association Study (GWAS). We then performed Mendelian randomization (MR) to determine a causal relationship between the gut microbiota and ASD using the inverse variance weighted (IVW) method, simple mode, MR-Egger, weighted median, and weighted model. Furthermore, we used Cochran's Q test, MR-Egger intercept test, Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO), and leave-one-out analysis to identify heterogeneity and pleiotropy. Moreover, the Benjamin-Hochberg approach (FDR) was employed to assess the strength of the connection between exposure and outcome. We performed reverse MR analysis on the gut microbiota that were found to be causally associated with ASD in the forward MR analysis to examine the causal relationships. The enrichment analyses were used to analyze the biological function at last., Results: Based on the results of IVW results, genetically predicted family Prevotellaceae and genus Turicibacter had a possible positive association with ASD (IVW OR=1.14, 95% CI: 1.00-1.29, P =3.7×10 -2 ), four gut microbiota with a potential protective effect on ASD: genus Dorea (OR=0.81, 95% CI: 0.69-0.96, P =1.4×10 -2 ), genus Ruminiclostridium5 (OR=0.81, 95% CI: 0.69-0.96, P =1.5×10 -2 ), genus Ruminococcus1 (OR=0.83, 95% CI: 0.70-0.98, P =2.8×10 -2 ), and genus Sutterella (OR=0.82, 95% CI: 0.68-0.99, P =3.6×10 -2 ). After FDR multiple-testing correction we further observed that there were two gut microbiota still have significant relationship with ASD: family Prevotellaceae (IVW OR=1.24; 95% CI: 1.09-1.40, P =9.2×10 -4 ) was strongly positively correlated with ASD and genus RuminococcaceaeUCG005 (IVW OR=0.78, 95% CI: 0.67-0.89, P =6.9×10 -4 ) was strongly negatively correlated with ASD. The sensitivity analysis excluded the influence of heterogeneity and horizontal pleiotropy., Conclusion: Our findings reveal a causal association between several gut microbiomes and ASD. These results deepen our comprehension of the role of gut microbiota in ASD's pathology, providing the foothold for novel ideas and theoretical frameworks to prevent and treat this patient population in the future., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Li, Liu, Liu, Dai, Liang, Lv and Bao.)

Background: Recent studies have suggested a relationship between gut microbiota and non-alcoholic fatty liver disease (NAFLD)/nonalcoholic steatohepatitis (NASH). However, the nature and direction of this potential causal relationship are still unclear. This study used two-sample Mendelian randomization (MR) to clarify the potential causal links., Methods: Summary-level Genome-Wide Association Studies (GWAS) statistical data for gut microbiota and NAFLD/NASH were obtained from MiBioGen and FinnGen respectively. The MR analyses were performed mainly using the inverse-variance weighted (IVW) method, with sensitivity analyses conducted to verify the robustness. Additionally, reverse MR analyses were performed to examine any potential reverse causal associations., Results: Our analysis, primarily based on the IVW method, strongly supports the existence of causal relationships between four microbial taxa and NAFLD, and four taxa with NASH. Specifically, associations were observed between Enterobacteriales ( P =0.04), Enterobacteriaceae ( P =0.04), Lachnospiraceae UCG-004 ( P =0.02), and Prevotella9 ( P =0.04) and increased risk of NAFLD. Dorea ( P =0.03) and Veillonella ( P =0.04) could increase the risks of NASH while Oscillospira ( P =0.04) and Ruminococcaceae UCG-013 ( P =0.005) could decrease them. We also identified that NAFLD was found to potentially cause an increased abundance in Holdemania ( P =0.007) and Ruminococcus2 ( P =0.002). However, we found no evidence of reverse causation in the microbial taxa associations with NASH., Conclusion: This study identified several specific gut microbiota that are causally related to NAFLD and NASH. Observations herein may provide promising theoretical groundwork for potential prevention and treatment strategies for NAFLD and its progression to NASH in future., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Zhai, Wu, Zheng, Zhong, Du, Yuan, Peng, Cai and Li.)

Introduction: Insomnia is the second most common mental health issue, also is a social and financial burden. Insomnia affects the balance between sleep, the immune system, and the central nervous system, which may raise the risk of different systemic disorders. The gut microbiota, referred to as the "second genome," has the ability to control host homeostasis. It has been discovered that disruption of the gut-brain axis is linked to insomnia., Methods: In this study, we conducted MR analysis between large-scale GWAS data of GMs and insomnia to uncover potential associations., Results: Ten GM taxa were detected to have causal associations with insomnia. Among them, class Negativicutes , genus Clostridiuminnocuumgroup , genus Dorea , genus Lachnoclostridium , genus Prevotella7 , and order Selenomonadalesare were linked to a higher risk of insomnia. In reverse MR analysis, we discovered a causal link between insomnia and six other GM taxa., Conclusion: It suggested that the relationship between insomnia and intestinal flora was convoluted. Our findings may offer beneficial biomarkers for disease development and prospective candidate treatment targets for insomnia., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Li, Deng and Liu.)

Objectives: Recent studies pointed out that gut microbiome dysbiosis in HIV infection was possibly confounded in men who have sex with men (MSM), but there is a lack of evidence. It also remained unclear how MSM-associated gut microbiome dysbiosis affected human health. This study aimed to compare the differences in gut microbiome changes between HIV and MSM and reveal the potential impacts of MSM-associated gut microbiome dysbiosis on the immune system., Methods: We searched available studies based on the PubMed database, and all gut microbiome changes associated with HIV infection and MSM were extracted from the enrolled studies. The gutMgene database was used to identify the target genes and metabolites of the gut microbiome. Bioinformatic technology and single-cell RNA sequencing data analysis were utilized to explore the impacts of these gut microbiome changes on human immunity., Results: The results showed significant overlaps between the gut microbiome associated with HIV and that of MSM. Moreover, bioinformatic analysis revealed that gut microbiome dysbiosis in MSM had an impact on several pathways related to immunity, including the IL-17 signaling pathway and Th17 cell differentiation. Additionally, target genes of MSM-associated gut microbiome were found to be highly expressed in monocytes and lymphocytes, suggesting their potential regulatory role in immune cells. Furthermore, we found that MSM-associated gut microbiome could produce acetate and butyrate which were reported to increase the level of inflammatory factors., Conclusion: In conclusion, this study highlighted that MSM-associated gut microbiome dysbiosis might increase the risk of HIV acquisition by activating the immune system. Further studies are expected to elucidate the mechanism by which gut microbiome dysbiosis in MSM modulates HIV susceptibility., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Li, Deng, Zhang, Lai, Xie and Zhong.)

Background: Mounting evidence has demonstrated the associations between gut microbiota, gut microbiota-derived metabolites, and cerebrovascular diseases (CVDs). The major categories of CVD are ischemic stroke (IS), intracerebral hemorrhage (ICH), and subarachnoid hemorrhage (SAH). However, the causal relationship is still unclear., Methods: A two-sample Mendelian randomization (MR) study was conducted leveraging the summary data from genome-wide association studies. The inverse variance-weighted, maximum likelihood, weighted median, and MR.RAPS methods were performed to detect the causal relationship. Several sensitivity analyses were carried out to evaluate potential horizontal pleiotropy and heterogeneity. Finally, reverse MR analysis was conducted to examine the likelihood of reverse causality, and multivariable MR was performed to adjust the potential confounders., Results: We collected 1,505 host single nucleotide polymorphisms (SNPs) linked to 119 gut microbiota traits and 1,873 host SNPs associated with 81 gut metabolite traits as exposure data. Among these, three gut bacteria indicated an elevated risk of IS, two of ICH, and one of SAH. In contrast, five gut bacteria were associated with a reduced risk of IS, one with ICH, and one with SAH. Our study also demonstrated the potential causal associations between 11 gut microbiota-derived metabolites and CVD., Conclusions: This study provided evidence of the causal relationship between gut microbiota, gut microbiota-derived metabolites, and CVD, thereby offering novel perspectives on gut biomarkers and targeted prevention and treatment for CVD., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Lin, Zhu, Tian, Tian, Liang, Peng, Li and Wu.)

Objectives: To investigate the urinary microbiota composition in urolithiasis patients compared to healthy controls and to identify potential microbial markers and their association with clinical parameters., Methods: A total of 66 samples, comprising 45 from urolithiasis patients and 21 from healthy controls, were analyzed. 16S rRNA gene sequencing was employed to determine the microbiota composition. Various statistical and bioinformatics tools, including ANOVA, PCoA, and LEfSe, were utilized to analyze the sequencing data and identify significant differences in microbial abundance., Results: No significant demographic differences were observed between the two groups. Post-quality control, clean tags ranged from 60,979 to 68,736. Significant differences in α-diversity were observed between the two groups. β-diversity analysis revealed distinct clustering of the urinary microbiota in urolithiasis patients and controls. Notably, Ruminococcaceae was predominant in urolithiasis samples, while Proteobacteria was more prevalent in healthy samples. Lactobacillus was significantly overrepresented in samples from healthy females., Conclusion: The urinary microbiota composition in urolithiasis patients is distinct from that of healthy controls. Specific microbial taxa, such as Ruminococcaceae and Proteobacteria, could serve as potential biomarkers for urolithiasis. The findings pave the way for further exploration of the role of microbiota in urolithiasis and the development of microbiome-based therapeutic strategies., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Liu, Hu, Yan, Hao and Liang.)

Background: There is no direct evidence of gut microbiota disturbance in children with gastroesophageal reflux disease (GERD). This study aimed to provide direct evidence and a comprehensive understanding of gut microbiota disturbance in children with GERD through combined metagenomic and metabolomic analysis., Methods: 30 children with GERD and 30 healthy controls (HCs) were continuously enrolled, and the demographic and clinical characteristics of the subjects were collected. First, 16S rRNA sequencing was used to evaluate differences in the gut microbiota between children with GERD and HC group, and 10 children with GERD and 10 children in the HC group were selected for metagenomic analysis. Nontargeted metabolomic analysis was performed using liquid chromatography/mass spectrometry (LC/MS), and metagenomic and metabolomic data were analyzed together., Results: There were significant differences in the gut microbiota diversity and composition between children with GERD and HCs. The dominant bacteria in children with GERD were Proteobacteria and Bacteroidota. At the species level, the top three core bacterial groups were Bacteroides stercoris , Bacteroides vulgatus and Alistipes putredinis . The main differential pathways were identified to be related to energy, amino acid, vitamin, carbohydrate and lipid metabolism. LC/MS detected 288 different metabolites in the positive and negative ion modes between children with GERD and HCs, which were mainly involved in arachidonic acid (AA), tyrosine, glutathione and caffeine metabolism., Conclusion: This study provides new evidence of the pathogenesis of GERD. There are significant differences in the gut microbiota, metabolites and metabolic pathways between HCs and children with GERD, and the differences in metabolites are related to specific changes in bacterial abundance. In the future, GERD may be treated by targeting specific bacteria related to AA metabolism., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Ye, Yu, Zhou, Zhao, Wu and Ni.)

Background: The gut microbiota is closely linked to cholesterol metabolism-related diseases such as obesity and cardiovascular diseases. However, whether gut microbiota plays a causal role in cholelithiasis remains unclear., Aims: This study explored the causal relationship between gut microbiota and cholelithiasis. We hypothesize that the gut microbiota influences cholelithiasis development., Methods: A two-sample Mendelian randomization method was combined with STRING analysis to test this hypothesis. Summary data on gut microbiota and cholelithiasis were obtained from the MiBioGen (n=13,266) and FinnGen R8 consortia (n=334,367), respectively., Results: Clostridium senegalense , Coprococcus3 , and Lentisphaerae increased the risk of cholelithiasis and expressed more bile salt hydrolases. In contrast, Holdemania , Lachnospiraceae UCG010 , and Ruminococcaceae NK4A214 weakly expressed bile salt hydrolases and were implied to have a protective effect against cholelithiasis by Mendelian randomization analysis., Conclusion: Gut microbiota causally influences cholelithiasis and may be related to bile salt hydrolases. This work improves our understanding of cholelithiasis causality to facilitate the development of treatment strategies., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Liu, Qi, Han, Mao and Tian.)

Background: Recent researches have shown a correlation between the gut microbiota (GM) and various diseases. However, it remains uncertain whether the relationship between GM and benign prostatic hyperplasia (BPH) is causal., Methods: We carried out a two-sample Mendelian randomization (MR) analysis, utilizing data from the most extensive GM-focused genome-wide association study by the MiBioGen consortium, with a sample size of 13,266. Data for BPH, encompassing 26,358 cases and 110,070 controls, were obtained from the R8 release of the FinnGen consortium. We employed multiple techniques, such as inverse variance weighted (IVW), constrained maximum likelihood and model averaging methods, maximum likelihood, MR-Pleiotropy RESidual Sum and Outlier (MRPRESSO),MR-Egger, and weighted median methods, to investigate the causal relationship between GM and BPH. To evaluate the heterogeneity among the instrumental variables, Cochran's Q statistics were employed. Additionally, the presence of horizontal pleiotropy was assessed through the application of both MR-Egger and MR-PRESSO tests. The direction of causality was scrutinized for robustness using the MR-Steiger directionality test. A reverse MR analysis examined the GM previously linked to BPH through a causal relationship in the forward MR assessment., Results: According to the analysis conducted using IVW,Eisenbergiella (odds ratio [OR]=0.92, 95% confidence interval [CI]: 0.85-0.99,P=0.022) and Ruminococcaceae (UCG009) (OR=0.88, 95% CI: 0.79-0.99, P=0.027) were found to reduce the risk of BPH, while Escherichia shigella (OR=1.19, 95% CI: 1.05-1.36, P=0.0082) appeared to increase it. The subsequent reverse MR analysis revealed that the three GM were not significantly influenced by BPH, and there was no noticeable heterogeneity or horizontal pleiotropy among the instrumental variables.Conclusion: These results indicated a causal relationship between Eisenbergiella, Ruminococcaceae (UCG009), and Escherichia shigella and BPH. Further randomized controlled trials are needed to explore more comprehensively the roles and operational mechanisms of these GM in relation to BPH., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Xia, Wang, Zhao, Shen, Ling and Liang.)

Background: Methamphetamine use disorder (MUD) poses a considerable public health threat, and its identification remains challenging due to the subjective nature of the current diagnostic system that relies on self-reported symptoms. Recent studies have suggested that MUD patients may have gut dysbiosis and that gut microbes may be involved in the pathological process of MUD. We aimed to examine gut dysbiosis among MUD patients and generate a machine-learning model utilizing gut microbiota features to facilitate the identification of MUD patients., Method: Fecal samples from 78 MUD patients and 50 sex- and age-matched healthy controls (HCs) were analyzed by 16S rDNA sequencing to identify gut microbial characteristics that could help differentiate MUD patients from HCs. Based on these microbial features, we developed a machine learning model to help identify MUD patients. We also used public data to verify the model; these data were downloaded from a published study conducted in Wuhan, China (with 16 MUD patients and 14 HCs). Furthermore, we explored the gut microbial features of MUD patients within the first three months of withdrawal to identify the withdrawal period of MUD patients based on microbial features., Results: MUD patients exhibited significant gut dysbiosis, including decreased richness and evenness and changes in the abundance of certain microbes, such as Proteobacteria and Firmicutes . Based on the gut microbiota features of MUD patients, we developed a machine learning model that demonstrated exceptional performance with an AUROC of 0.906 for identifying MUD patients. Additionally, when tested using an external and cross-regional dataset, the model achieved an AUROC of 0.830. Moreover, MUD patients within the first three months of withdrawal exhibited specific gut microbiota features, such as the significant enrichment of Actinobacteria . The machine learning model had an AUROC of 0.930 for identifying the withdrawal period of MUD patients., Conclusion: In conclusion, the gut microbiota is a promising biomarker for identifying MUD and thus represents a potential approach to improving the identification of MUD patients. Future longitudinal studies are needed to validate these findings., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Liu, Deng, Liu, Liu, Ma, Zhou, Wang and Tang.)

Objective: The gut micro-biome plays a pivotal role in the progression of lung cancer. However, the specific mechanisms by which the intestinal microbiota and its metabolites are involved in the lung cancer process remain unclear., Method: Stool samples from 52 patients with lung cancer and 29 healthy control individuals were collected and subjected to 16S rRNA gene amplification sequencing and non-targeted gas/liquid chromatography-mass spectrometry metabolomics analysis. Then microbiota, metabolites and potential signaling pathways that may play an important role in the disease were filtered., Results: Firmicutes, Clostridia, Bacteroidacea, Bacteroides, and Lachnospira showed a greater abundance in healthy controls. In contrast, the Ruminococcus gnavus(R.gnavus) was significantly upregulated in lung cancer patients. In this respect, the micro-biome of the squamous cell carcinoma(SCC)group demonstrated a relatively higher abundance of Proteobacteria, Gammaproteobacteria, Bacteroides,and Enterobacteriaceae, as well as higher abundances of Fusicatenibacter and Roseburia in adenocarcinoma(ADC) group. Metabolomic analysis showed significant alterations in fecal metabolites including including quinic acid, 3-hydroxybenzoic acid,1-methylhydantoin,3,4-dihydroxydrocinnamic acid and 3,4-dihydroxybenzeneacetic acid were significantly altered in lung cancer patients. Additionally, the R.gnavus and Fusicatenibacter of lung cancer were associated with multiple metabolite levels., Conclusion: Our study provides essential guidance for a fundamental systematic and multilevel assessment of the contribution of gut micro-biome and their metabolites in lung cancer,which has great potential for understanding the pathogenesis of lung cancer and for better early prevention and targeted interventions., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Lu, Xiong, Zheng, Yu, Xiao and Xie.)

In recent years, with the development of non-cultivation approaches, it has become evident that intestinal bacteria have a significant impact on human health. However, because one-third of the genes cannot be annotated, it is difficult to elucidate the function of all intestinal bacteria by in silico analysis, and it is necessary to study the intestinal bacteria by culturing them. In addition, various media recommended for each individual bacterium have been used for culturing intestinal bacteria; however, the preparation of each medium is complex. To simultaneously culture many bacteria and compare bacterial phenotypes under the same conditions, a medium capable of culturing a wide range of bacteria is needed. In this study, we developed GAM + blood medium (GB medium), which consists of Gifu anaerobic medium containing 5% (v/v) horse blood; it is easy to prepare and it allowed the successful cultivation of 85% of the available predominant species in the human intestinal microbiota., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Hirano, Nishita, Nakai, Bito, Sasabe and Kurihara.)

Background: Cerebral small vessel disease (CSVD) is a cluster of microvascular disorders with unclear pathological mechanisms. The microbiota-gut-brain axis is an essential regulatory mechanism between gut microbes and their host. Therefore, the compositional and functional gut microbiota alterations lead to cerebrovascular disease pathogenesis. The current study aims to determine the alteration and clinical value of the gut microbiota in CSVD patients., Methods: Sixty-four CSVD patients and 18 matched healthy controls (HCs) were included in our study. All the participants underwent neuropsychological tests, and the multi-modal magnetic resonance imaging depicted the changes in brain structure and function. Plasma samples were collected, and the fecal samples were analyzed with 16S rRNA gene sequencing., Results: Based on the alpha diversity analysis, the CSVD group had significantly decreased Shannon and enhanced Simpson compared to the HC group. At the genus level, there was a significant increase in the relative abundances of Parasutterella, Anaeroglobus, Megasphaera, Akkermansia, Collinsella, and Veillonella in the CSVD group. Moreover, these genera with significant differences in CSVD patients revealed significant correlations with cognitive assessments, plasma levels of the blood-brain barrier-/inflammation-related indexes, and structural/functional magnetic resonance imaging changes. Functional prediction demonstrated that lipoic acid metabolism was significantly higher in CSVD patients than HCs. Additionally, a composite biomarker depending on six gut microbiota at the genus level displayed an area under the curve of 0.834 to distinguish CSVD patients from HCs using the least absolute shrinkage and selection operator (LASSO) algorithm., Conclusion: The evident changes in gut microbiota composition in CSVD patients were correlated with clinical features and pathological changes of CSVD. Combining these gut microbiota using the LASSO algorithm helped identify CSVD accurately., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Shi, Zhao, Li, Zhao, Mao, Deng, Ji, Li, Gao, Zeng, Ma, Xi, You, Shao, Fang and Wang.)

Introduction: Identification of key microbiome components has been suggested to help address the maintenance of oral and intestinal health in humans. The core microbiome is similar in all individuals, whereas the diverse microbiome varies across individuals, based on their unique lifestyles and phenotypic and genotypic determinants. In this study, we aimed to predict the metabolism of core microorganisms in the gut and oral environment based on enterotyping and orotyping., Materials and Methods: Gut and oral samples were collected from 83 Korean women aged 50 years or older. The extracted DNA was subjected to next-generation sequencing analysis of 16S rRNA hypervariable regions V3-V4., Results: Gut bacteria were clustered into three enterotypes, while oral bacteria were clustered into three orotypes. Sixty-three of the core microbiome between the gut and oral population were correlated, and different metabolic pathways were predicted for each type. Eubacterium &#95;g11, Actinomyces , Atopobium , and Enterococcus were significantly positively correlated between the gut and oral abundance. The four bacteria were classified as type 3 in orotype and type 2 in enterotype., Conclusion: Overall, the study suggested that collapsing the human body's multidimensional microbiome into a few categories may help characterize the microbiomes better and address health issues more deeply., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Lee, Lee, You, Sung and Hyun.)

Background: Coccidiosis is an intestinal parasitic disease caused by Eimeria protozoa, which endangers the health and growth of animals, and causes huge economic losses to the poultry industry worldwide every year. Studies have shown that poultry gut microbiota plays an important role in preventing the colonization of pathogens and maintaining the health of the host. Coccidia infection also affects host gene expression. However, the underlying potential relationship between gut microbiome and host transcriptome during E. tenella infection in chickens remain unclear., Methods: In this study, metagenomic and transcriptome sequencing were applied to identify microbiota and genes in cecal contents and cecal tissues of infected (JS) and control (JC) chickens on day 4.5 postinfection (pi), respectively., Results: First, microbial sequencing results of cecal contents showed that the abundance of Lactobacillus, Roseburia sp. and Faecalibacterium sp decreased significantly after E. tenella infection ( P < 0.05), while the abundance of Alistipes and Prevotella pectinovora increased significantly ( P < 0.05). Second, transcriptome sequencing results showed that a total of 434 differentially expressed mRNAs were identified, including 196 up-regulated and 238 down-regulated genes. These differentially expressed genes related to inflammation and immunity, such as GAMA, FABP1, F2RL1 and RSAD2 , may play an important role in the process of host resistance to coccidia infection. Functional studies showed that the enriched pathways of differentially expressed genes included the TGF-beta signaling pathway and the ErbB signaling pathways. Finally, the integrated analysis of gut microbiome and host transcriptome suggested that Prevotella pectinovora associated with FABP1 , Butyricicoccus porcorum and Colidextribacter sp. associated with RSAD2 were involved in the immune response upon E. tenella infection., Conclusion: In conclusion, this study provides valuable information on the microbiota and key immune genes after chicken E. tenella infection, with the aim of providing reference for the impact of coccidia infection on cecal microbiome and host., Competing Interests: Hongsheng Wang is employed by Jiangsu Jinghai Poultry Group Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Yu, Wang, Tang, Dong, Dai, Zhang, Zhang, Xie, Wang and Zhao.)

Background: Gut microbiota is the largest population of microorganisms and is closely related to health. Many studies have explored changes in gut microbiota in viral hepatitis. However, the correlation between gut microbiota and the occurrence and progression of viral hepatitis has not been fully clarified., Methods: PubMed and BioProject databases were searched for studies about viral hepatitis disease and 16S rRNA gene sequencing of gut microbiota up to January 2023. With bioinformatics analyses, we explored changes in microbial diversity of viral hepatitis, screened out crucial bacteria and microbial functions related to viral hepatitis, and identified the potential microbial markers for predicting risks for the occurrence and progression of viral hepatitis based on ROC analysis., Results: Of the 1389 records identified, 13 studies met the inclusion criteria, with 950 individuals including 656 patient samples (HBV, n = 546; HCV, n = 86; HEV, n = 24) and 294 healthy controls. Gut microbial diversity is significantly decreased as the infection and progression of viral hepatitis. Alpha diversity and microbiota including Butyricimonas , Escherichia-Shigella , Lactobacillus , and Veillonella were identified as the potential microbial markers for predicting the risk of development of viral hepatitis (AUC>0.7). Microbial functions including tryptophan metabolism, fatty acid biosynthesis, lipopolysaccharide biosynthesis, and lipid metabolism related to the microbial community increased significantly as the development of viral hepatitis., Conclusions: This study demonstrated comprehensively the gut microbiota characteristics in viral hepatitis, screened out crucial microbial functions related to viral hepatitis, and identified the potential microbial markers for predicting the risk of viral hepatitis., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Yang, Mai, Zhou, Li, Wang, Lan, Lu, Yang, Guo, Ye, Cui, Liang and Huang.)