Hungatella

What was studied?

This study examined the fecal microbiome of children newly diagnosed with Crohn's disease (CD) before any treatment was started. The researchers compared microbial composition between these CD patients and children with functional gastrointestinal disorders. They also looked at whether specific microbial patterns correlated with the severity of CD, as measured by the Pediatric Crohn's Disease Activity Index (PCDAI).

Who was studied?

The cohort included 43 newly diagnosed, treatment-naive pediatric CD patients. They were compared against 139 age- and sex-matched controls who had other functional gastrointestinal disorders rather than CD. All participants were pediatric patients, and the comparison group was matched specifically to isolate microbial differences attributable to CD rather than age or sex.

What were the most important findings?

Microbial richness and diversity were significantly lower in children with CD compared to controls. Taxonomic analysis showed enrichment of pro-inflammatory bacteria, specifically Fusobacteria and Proteobacteria, alongside depletion of favorable taxa, Firmicutes and Verrucomicrobia. Higher PCDAI scores (indicating greater disease activity) were linked to enrichment of pro-inflammatory genera, Hungatella and Veillonella, and depletion of protective Lachnospiraceae.

What are the greatest implications of this study?

The findings support fecal microbiome profiling as a potential tool for distinguishing CD from other functional gastrointestinal disorders in children at diagnosis. The correlation between specific microbial shifts and disease activity suggests the microbiome could help track or predict clinical course. This could ultimately aid clinicians in making more informed treatment decisions for a disease whose course is otherwise unpredictable.

What was studied?

This randomized, double-blind, placebo-controlled trial tested whether daily supplementation with two specific probiotic strains, Bifidobacterium animalis subsp. lactis XLTG11 and Lactiplantibacillus plantarum CCFM8661, could reduce recurrent respiratory tract infections (RRTIs) in children. Over 180 days, the study tracked infection frequency and duration alongside changes in gut microbiota composition, functional metabolic pathways, and immune biomarkers. The design allowed the researchers to link clinical respiratory outcomes to underlying shifts in the gut microbial community and immune regulation.

Who was studied?

The study enrolled 120 children who had been diagnosed with recurrent respiratory tract infections. Participants were randomly assigned to receive either the probiotic combination or a matched placebo daily for 180 days. The abstract does not provide further demographic details such as age range or sex distribution.

What were the most important findings?

Children receiving the probiotics had significantly reduced duration and frequency of fever, cough, upper respiratory tract infections, trachea or bronchitis, pneumonia, and overall RRTI recurrence compared with placebo (all p < 0.05). Gut microbiota profiling at day 180 showed clear community differences between groups, with the probiotic group showing greater abundance of beneficial commensal taxa and the placebo group showing more opportunistic genera. Functional pathway analysis pointed to enhanced metabolic stability in the probiotic recipients, and immune biomarker patterns showed comparatively stable IgG, IgM, and complement C3 levels, suggesting a more regulated humoral immune response. Growth trajectories remained normal in both groups.

What are the greatest implications of this study?

These findings support strain-defined probiotic supplementation as a viable adjunct strategy for reducing the burden of recurrent respiratory infections in children. The parallel shifts in gut microbial composition, metabolic function, and humoral immune stability suggest the respiratory benefit may be mediated through gut-immune axis modulation rather than a direct respiratory-tract effect. Because growth remained normal, the intervention appears well tolerated over a six-month period, supporting its potential for longer-term pediatric preventive use pending further confirmatory trials.

What was studied?

Intestinal fibrous stenosis due to Crohn's disease (CD) is highly prevalent. Although several clinical risk factors for fibrous stenosis have been identified, such as perianal fistulizing disease, small bowel disease location, and deep mucosal ulceration, predicting fibrous stenosis remains challenging. The intestinal microbiota plays a crucial role in the development and progression of CD. However, its role in intestinal fibrous stenosis is poorly understood. Leveraging a single-center cross-sectional study, we aimed to investigate the role of fecal microbiota in CD-associated fibrous stenosis.

Who was studied?

Using metagenomic analysis, we examined the differences in fecal microbiota between CD patients with intestinal fibrous stenosis and those without stenosis. We identified specific microbiota and assessed their predictive accuracy for intestinal fibrous stenosis. Additionally, we explored functional differences in intestinal microbiota between the two groups.

What were the most important findings?

: Our investigation of fecal samples revealed no significant differences in the gut microbiota structure between patients with fibrous stenosis and those without stenosis in CD. However, taxonomically, we found 70 taxa with significantly different abundance (p < 0.05) between the two groups. Furthermore, LEfSe analysis indicated that g_Bacteroides and g_Enterocloster could predict intestinal fibrous stenosis while p_Actinobacteria, c_Actinomycetia, c_Bacilli, o_Lactobacillales, f_Streptococcaceae and g_Streptococcus could predict CD without stenosis. Functional analysis revealed differential enrichment in five metabolic pathways at the KEGG pathway level in CD patients with fibrous stenosis, including sphingolipid metabolism, lipoic acid metabolism, and biosynthesis of neomycin, kanamycin and gentamicin. In the eggNOG database, we observed differences in four functional categories between the two groups, encompassing cellular process, signaling, and metabolism.

What are the greatest implications of this study?

Fecal microbiota significantly impacted intestinal fibrous stenosis in CD. Although there were no significant differences in alpha and beta diversities, fibrous stenosis was associated with changes in microbiota composition and function, suggesting the potential of fecal microbiota in predicting CD-associated fibrous stenosis.

What was studied?

This study investigated the smoking paradox, in which smokers tend to have lower body mass index but higher risk of obesity-related disease, through the lens of the gut microbiota. Researchers used 16S rRNA sequencing to identify smoking-related microbial genera and built a smoking-related microbiota index (SMI). They then tested whether SMI was associated with obesity indices and with incident obesity-related diseases, including analyses designed to control for shared familial and environmental confounders.

Who was studied?

The analysis drew on 4000 male participants from two cohorts, the WELL-China cohort and the Lanxi cohort. Obesity indices were derived using dual-energy X-ray absorptiometry (DEXA) scans in these participants. A subset of participants with siblings was used for sibling comparison analyses via a between-within (BW) model, allowing the researchers to account for unmeasured familial confounding.

What were the most important findings?

The smoking-related microbiota index (SMI) was positively associated with BMI and other DEXA-derived obesity indices. Higher SMI was also linked to greater risk of incident obesity-related disease, with hazard ratios of 1.97 for diabetes, 1.31 for major adverse cardiovascular events, and 1.70 for obesity-related cancers. These associations held up in sibling comparison analyses, which help rule out shared family environment or genetics as the explanation.

What are the greatest implications of this study?

The findings suggest that smoking-associated shifts in gut microbiota may help explain why smokers face elevated cardiometabolic and cancer risk despite often having lower BMI. This reframes the smoking-obesity paradox as partly a microbiome-mediated phenomenon rather than a purely anthropometric one. The sibling comparison design strengthens confidence that the microbiota signal is not simply a marker of shared family background. These results point to the gut microbiota as a potential target or biomarker for assessing metabolic and disease risk in people who smoke.

What was studied?

This study investigated the gut microbiota of older adults with sarcopenic obesity (SO) and sarcopenia without obesity (Sar), compared with age-matched controls. Researchers used 16S rRNA gene sequencing targeting the V3-V4 regions to characterize microbial composition and diversity. The goal was to determine whether gut dysbiosis is associated with the development and progression of sarcopenia and sarcopenic obesity, a link previously suspected but not well documented.

Who was studied?

The sample was drawn from a community-based cohort of 1558 older adults (age 65 and older) in Shanghai, China, who underwent sarcopenia screening with the SARC-F questionnaire. Of these, 351 completed further assessment, and 60 participants were ultimately categorized using the Asian Working Group for Sarcopenia 2019 criteria and World Health Organization obesity criteria. The final groups were sarcopenic obesity (n=20), sarcopenia without obesity (n=18), and controls (n=22).

What were the most important findings?

Gut microbiota diversity and composition differed significantly between the sarcopenic obesity, sarcopenia, and control groups. Alpha diversity, measured by the Chao1 and ACE indices, was reduced specifically in the sarcopenic obesity group. Beta diversity, assessed by unweighted UniFrac PCoA, also differed significantly among the three groups, and LEfSe analysis identified 39 taxa with differential abundance across groups.

What are the greatest implications of this study?

The findings support the idea that gut microbiota alterations are distinctly linked to sarcopenic obesity rather than sarcopenia alone, with reduced diversity marking the combined obesity and muscle-loss phenotype. This suggests the gut microbiome could serve as a distinguishing biomarker between these related but distinct conditions in older adults. Identifying these taxa-level differences may help guide future microbiome-targeted approaches for prevention or management of sarcopenic obesity in aging populations.

What was studied?

This study conducted a machine learning meta-analysis of gut microbiome data from multiple prior Parkinson's disease (PD) studies, pooling an unprecedented 4,489 samples. The researchers built classification models to identify microbiome features associated with PD and tested how well these models generalized across different, independently collected datasets. They also performed meta-analysis of shotgun metagenomic data to identify PD-associated microbial functional pathways.

Who was studied?

The analysis drew on 4,489 samples pooled from multiple existing PD microbiome studies, rather than a single new patient cohort. The abstract does not specify demographic details of the underlying individuals, but the dataset includes both PD patients and comparison samples, since models were evaluated for their ability to distinguish PD from other neurodegenerative diseases. This makes the population effectively a large, multi-study compilation of previously published microbiome sequencing data.

What were the most important findings?

Machine learning models trained within a single study classified PD patients accurately, with an average AUC of 71.9 percent, but these models performed much worse when applied to other studies, dropping to an average AUC of 61 percent, showing poor generalizability. Training models on multiple combined datasets improved generalizability, raising the average leave-one-study-out AUC to 68 percent, and improved specificity for PD compared to other neurodegenerative diseases. Meta-analysis of shotgun metagenomes identified PD-associated microbial pathways linked to gut health deterioration and potential translocation of pathogenic molecules along the gut-brain axis. Notably, microbial pathways involved in solvent and pesticide biotransformation were enriched in PD samples.

What are the greatest implications of this study?

The findings suggest that single-study PD microbiome signatures do not reliably generalize, so meaningful diagnostic use requires models trained across multiple, diverse datasets. The enrichment of pesticide and solvent biotransformation pathways aligns with epidemiological evidence linking these exposures to increased PD risk, raising the possibility that gut microbes modulate toxicity from environmental chemicals. Overall, the study points toward the gut-brain axis and microbial detoxification pathways as promising targets for understanding PD risk and improving diagnostic tools.

What was studied?

This study examined whether rifaximin, a gut-specific non-absorbable antibiotic, could reduce gut-derived systemic inflammation in severe acute pancreatitis (SAP). The researchers combined murine experimental models with a single-center, open-label randomized controlled trial (ChiCTR2100049794). They assessed pancreatic injury, systemic inflammatory markers, and gut microbiota composition, and tested whether rifaximin's effects depended on modulating the microbiota by using antibiotic-treated and germ-free mice.

Who was studied?

The animal component used murine models of severe acute pancreatitis, including antibiotic-treated and germ-free mice used to probe the mechanism. The clinical component enrolled 60 patients with predicted severe acute pancreatitis, randomized to receive rifaximin or standard control treatment. No further demographic details are given in the abstract.

What were the most important findings?

In mice, rifaximin reduced pancreatic injury and systemic inflammation and decreased mucin-degrading gut genera such as Akkermansia, but its protective effects persisted even in antibiotic-treated and germ-free mice, indicating mechanisms beyond microbiota modulation. In patients, rifaximin significantly lowered systemic inflammation, with white blood cell count falling from a median of 11.50 x10^9/L to 8.49 x10^9/L and TNF-alpha falling from 15.05 pg/mL to 11.00 pg/mL. However, the rate of culture-confirmed infection was identical between rifaximin and control groups (13.3% vs 13.3%), and adverse events were comparable between groups.

What are the greatest implications of this study?

The findings suggest rifaximin can dampen systemic inflammation in severe acute pancreatitis through mechanisms that are not solely dependent on reshaping the gut microbiota, pointing to a possible direct anti-inflammatory or barrier-protective effect. Because inflammation markers improved without any change in infection risk, rifaximin may offer a safe adjunct for controlling inflammatory injury in SAP without added infectious risk. This supports further investigation of rifaximin as a therapeutic strategy for gut-derived inflammation in acute pancreatitis, alongside continued study of its non-microbiota-dependent mechanisms.

What was studied?

This study examined how common lifestyle factors relate to the risk of colorectal high-risk adenomas (HRAs), precursor lesions to colorectal cancer. It focused on whether gut microbiota composition helps explain, or mediates, the connection between lifestyle habits and HRA risk. Researchers combined lifestyle questionnaires with 16S rRNA sequencing of fecal samples, then used multivariate models and causal mediation analysis to link lifestyle exposures, microbial taxa, and HRA outcomes.

Who was studied?

A total of 3,827 participants were enrolled from a multicenter colorectal cancer screening cohort. Within this group, 272 participants had high-risk adenomas and 1,253 served as controls. Lifestyle information covering the 12 months before enrollment was collected via questionnaires, and fecal samples were taken at enrollment for microbiome analysis.

What were the most important findings?

High body mass index, smoking more than 30 pack-years, and drinking more than 4 alcoholic units per week were each identified as independent risk factors for high-risk adenoma. Using MaAsLin2, the researchers found associations between these lifestyle risk factors and specific gut microbial taxa. The abstract does not specify Desulfovibrio, sulfate-reducing bacteria, or hydrogen sulfide among the implicated taxa or pathways.

What are the greatest implications of this study?

The findings suggest that gut microbiota do not merely correlate with colorectal adenoma risk but may actively mediate how obesity, smoking, and heavy alcohol use translate into higher risk of high-risk adenomas. This positions the microbiome as a potential intermediary target for reducing lifestyle-driven colorectal cancer precursor risk. Identifying the specific mediating taxa could inform future screening or prevention strategies aimed at modifying gut microbial composition in high-risk individuals.

What was studied?

Background: Autism Spectrum Disorder (ASD) is increasingly associated with alterations in gut microbiota, intestinal permeability, and immune dysregulation. However, integrative studies exploring these mechanisms in Latin American populations are lacking. Objective: To characterize gut microbiota profiles in Colombian children with ASD and evaluate the effects of two microbiota-targeted interventions, an anti-inflammatory diet and a probiotic formulation, on microbial diversity and taxonomic composition. Methods: In a two-phase study, shotgun metagenomic sequencing was performed on fecal samples from 23 children with ASD and 7 typically developing (TD) controls. In the second phase, 17 children with ASD were randomized to receive a 12-week intervention (anti-inflammatory diet, probiotics, or no intervention). Alpha diversity indices (Shannon, Pielou, and Chao1) and differential abundance analyses were conducted. Results: Compared to TD children, those with ASD showed a higher Firmicutes/Bacteroidetes ratio and a significantly increased abundance of genera such as Clostridioides, Thomasclavelia, Alistipes, and Coprococcus. The presence of functional gastrointestinal disorders (FGIDs) in ASD patients is associated with reduced microbial richness. POST-intervention, the anti-inflammatory diet group showed that no statistically significant changes in alpha diversity were observed, although a slight upward trend was noted and significant enrichment of six bacterial genera, including Moraxella and Eubacterium. The probiotic group exhibited a significant increase in Romboutsia and a decrease in Lachnospira. Cytokine-microbiota networks in ASD were fragmented and dominated by IFN-γ and MCP-1 hubs, indicating systemic immune activation. Interventions induced functional remodeling: The anti-inflammatory diet increased the number of beneficial genera (Eubacterium, Adlercreutzia) and shifted networks toward positive correlations involving IL-8 and MIP-1β. Probiotics increased Romboutsia, reduced Lachnospira, and restructured networks with regulatory cytokines (SDF-1α, Eotaxin) and SCFA-producing taxa (Blautia, Roseburia). Conclusions: Children with ASD in Colombia displayed distinct microbial profiles characterized by pro-inflammatory taxa and altered richness. Both the anti-inflammatory diet and probiotics produced compositional shifts in the gut microbiota, although global changes in diversity were limited. These findings support the potential of microbiota-targeted nutritional strategies for ASD and underscore the need for precision interventions tailored to specific clinical and microbial phenotypes.

What was studied?

This study examined whether person-to-person transmission of gut microbes, not just diet, helps explain why traditional microbiomes shift toward an industrialized pattern after immigration. Researchers used germ-free mice colonized with human donor stool to test how sharing air and physical contact between mice carrying different donor microbiomes affects microbial composition. They then exposed the resulting microbiomes to dietary ingredients and food additives common in industrialized diets to see how composition changes translated into metabolic outcomes, including weight gain.

Who was studied?

The study did not involve human subjects directly. Instead, germ-free mice were colonized with human donor stool collected from the United States and from Thailand, creating humanized mouse models representing an industrialized and a traditional microbiome. Transmission and metabolic effects were then measured in these colonized mice under shared-air or co-housing conditions.

What were the most important findings?

Both shared air and physical contact enabled bidirectional microbial transmission between the U.S. and Thai humanized mice. U.S. mucus-degrading taxa such as Akkermansia transferred into Thai microbiomes, while potentially health-promoting Thai-derived bacteria colonized U.S. microbiomes, with the host's baseline microbiome shaping how much remodeling occurred. When exposed to industrialized dietary ingredients and food additives, the U.S. microbiome responded differently than the Thai microbiome, with food additives reducing Akkermansia and the U.S. microbiome showing a predisposition toward weight gain under these dietary conditions.

What are the greatest implications of this study?

The findings suggest that shared living environments, not diet alone, are an underappreciated route by which industrialized-style microbiomes and their metabolic consequences spread between people. Notably, sharing air supply or co-housing with a Thai-derived microbiome mitigated the U.S. microbiome's predisposition toward diet-induced weight gain, pointing to a protective effect of microbial transmission from traditional microbiomes. This implies that interventions aimed at preventing microbiome-related metabolic disease may need to consider household and community-level microbial exposure alongside dietary changes.

What was studied?

This study aimed to reveal the association between the gut microbiota (GM) and six diabetic complications: diabetic hypoglycemia; ketoacidosis; nephropathy; neuropathy; retinopathy; and Charcot's foot.

Who was studied?

GM data were obtained from the MiBioGen consortium and Dutch Microbiome Project while data on the six diabetic complications were obtained from the FinnGen consortium. Two-sample Mendelian randomization (TSMR) was performed to explore the association between GM and the common diabetic complications. Inverse MR analysis was conducted to examine the effect of diabetic complications on the identified GM. Sensitivity tests were conducted to validate the stability of the results. Finally, multivariate MR (MVMR) was performed to determine whether GM had a direct influence on the diabetic complications.

What were the most important findings?

After multiple corrections, the inverse variance weighted (IVW) results predicted 61 suggestive markers between GM and six diabetic complications. In particular, the IVW results revealed that the Bacteroidia class and Bacteroidales order were positively associated with diabetic hypoglycemia while the Verrucomicrobiae class and Verrucomicrobiales order were positively associated with diabetic nephropathy. Based on the replication analysis, these results were identified to be stable. MVMR showed that the results remained stable after accounting for traditional risk factors.

What are the greatest implications of this study?

Extensive causal associations were found between GM and diabetic complications, which may provide new insights into the mechanisms of microbiome-mediated complications of diabetes.

What was studied?

Gut microbiome differences between people with Parkinson's disease (PD) and control subjects without Parkinsonism are widely reported, but potential alterations related to PD with mild cognitive impairment (MCI) have yet to be comprehensively explored. We compared gut microbial features of PD with MCI (n = 58) to cognitively unimpaired PD (n = 60) and control subjects (n = 90) with normal cognition. Our results did not support a specific microbiome signature related to MCI in PD.

What was studied?

This pilot prospective cohort study examined whether ethnicity influences gut microbiome dysbiosis in pregnancies complicated by gestational diabetes mellitus (GDM). The researchers also investigated whether diet and lifestyle modifications made after a GDM diagnosis could modulate the gut microbiome. Fecal samples were collected at two time points, 24 to 28 weeks and 36 to 40 weeks of gestation, and analyzed using targeted 16S rRNA gene-based amplicon sequencing. Statistical comparisons between groups used PERMANOVA, differential abundance testing used DeSeq2, and functional predictions were generated with PICRUSt2.

Who was studied?

The cohort included 53 women with GDM and 16 women without GDM, all residing in Singapore. Participants belonged to three Asian ethnic groups: Chinese, Malay, and Indian. This design allowed comparison of gut dysbiosis patterns both across GDM status and across ethnic background within the same population.

What were the most important findings?

Among women with GDM, gut microbiomes from the different ethnic groups shared common features rather than diverging by ethnicity. This suggests that GDM-related dysbiosis is a relatively consistent phenomenon across the Chinese, Malay, and Indian groups studied. The abstract indicates that ethnicity was not a major driver of the microbiome differences observed in these GDM pregnancies.

What are the greatest implications of this study?

If GDM-associated gut dysbiosis is largely independent of Asian ethnic background, microbiome-targeted strategies for GDM may generalize across these ethnic groups rather than needing ethnicity-specific approaches. This supports the idea that dietary and lifestyle interventions after a GDM diagnosis could be evaluated and applied similarly across diverse populations. As a pilot study, these findings point to the need for larger cohorts to confirm whether microbiome-based interventions can be standardized across ethnicities.

What was studied?

This study examined gut microbial features associated with Parkinson's disease (PD) by meta-analyzing shotgun metagenomic sequencing data across six independent datasets from different countries. The researchers also established GC-MS and LC-MS/MS assays to directly quantify fecal short-chain fatty acids (SCFAs) and fecal polyamines. They analyzed taxonomic composition, functional gene pathways, and carbohydrate-active enzymes (CAZymes) in relation to PD status, adjusting for confounding factors.

Who was studied?

The core dataset consisted of 94 PD patients and 73 controls whose fecal samples were shotgun sequenced in Japan. This Japanese cohort was combined with five previously reported datasets from the USA, Germany, China (two separate cohorts), and Taiwan. In total, the meta-analysis spanned six countries, giving the study an international, multi-cohort scope rather than a single-population sample.

What were the most important findings?

Across all six datasets, alpha-diversity was consistently increased in PD. Taxonomic analysis showed Akkermansia muciniphila was increased in PD, while Roseburia intestinalis and Faecalibacterium prausnitzii, both associated with anti-inflammatory, butyrate-related commensal activity, were decreased. Genes for riboflavin and biotin biosynthesis and five of six CAZyme categories were markedly decreased in PD, and fecal SCFAs and polyamines were significantly reduced, with riboflavin/biotin gene abundance positively correlated with these metabolite levels.

What are the greatest implications of this study?

The convergent, cross-country decrease in Faecalibacterium prausnitzii, Roseburia intestinalis, SCFAs, and polyamines suggests a reproducible loss of beneficial, anti-inflammatory commensal function in PD gut microbiota. Because the specific bacteria driving reduced riboflavin biosynthesis differed between Japan/USA/Germany and China1/China2/Taiwan, the findings imply that shared functional deficits in PD can arise from different taxonomic routes depending on population. This points toward B-vitamin biosynthesis and short-chain fatty acid/polyamine metabolism as potential functional biomarkers or intervention targets for PD that generalize better across populations than single-taxon signatures.

What was studied?

This study examined how gut microbiota composition differs in children with diarrhea versus children with constipation, compared to healthy children. The researchers used 16S rRNA sequencing on stool samples to profile bacterial communities and looked for microbial diversity changes and specific taxa shifts. They also ran pathway analysis to identify functional mechanisms that might link the two opposite digestive conditions through a shared microbial driver.

Who was studied?

The study included 618 Chinese children aged 0 to 3 years, drawn from a cross-sectional case-control design. Of these, 66 children had diarrhea, 138 had constipation, and 414 were healthy controls. Stool samples were collected from each child for gut microbiota analysis.

What were the most important findings?

Children with diarrhea showed significantly lower gut microbial diversity than healthy controls, while children with constipation showed significantly higher diversity (p < 0.05). Ruminococcus was identified as a key differentiator: it increased in constipation (p = 0.03) and decreased in diarrhea (p < 0.01) relative to healthy children. Pathway analysis linked Ruminococcus to five shared pathways (membrane transport, nervous system, energy metabolism, signal transduction, and endocrine system), suggesting one underlying regulatory mechanism connects both conditions.

What are the greatest implications of this study?

The findings point to Ruminococcus as a core microorganism whose imbalance may disrupt gut steady-state in opposite directions, contributing to either diarrhea or constipation in young children. Because the same genus and overlapping metabolic pathways appear to regulate both conditions, it may serve as a useful reference point for diagnosis. The authors suggest this shared mechanism could inform future treatment approaches that target gut microbial balance rather than treating diarrhea and constipation as unrelated conditions.

What was studied?

This study investigated gut microbiota composition and systemic immune function in patients with schizophrenia comorbid with metabolic syndrome (SZ-MetS). Researchers used 16S rRNA gene sequencing (V3-V4 hypervariable regions) to profile fecal bacterial communities. They paired this with a 27-plex cytokine assay to characterize host immune responses. The goal was to clarify how gut dysbiosis and immune dysfunction relate to one another in this comorbid condition.

Who was studied?

The study enrolled 114 Chinese patients with schizophrenia comorbid with metabolic syndrome and 111 age-matched healthy controls, all recruited from Zhejiang, China. Fecal samples from these participants were sequenced to assess gut bacterial diversity and composition. Blood-based cytokine profiling was performed using the same cohort to link microbial and immune findings.

What were the most important findings?

Patients with SZ-MetS showed decreased bacterial alpha-diversity and significant shifts in beta-diversity compared to healthy controls. LEfSe analysis identified enrichment of acetate-producing genera, specifically Megamonas and Lactobacillus, alongside depletion of butyrate-producing bacteria, including Subdoligranulum and Faecalibacterium. These altered bacterial genera correlated with body mass index and with the severity of clinical measures, linking microbial shifts to metabolic and disease-related parameters. The abstract did not mention Desulfovibrio, sulfate-reducing bacteria, hydrogen sulfide, or sulfur metabolism.

What are the greatest implications of this study?

The findings suggest that gut dysbiosis, marked by loss of butyrate producers and gain of acetate producers, may contribute to the pathogenesis of metabolic syndrome in people with schizophrenia. This supports a role for the gut microbiota as a potential mechanistic link between psychiatric illness and metabolic dysfunction. It also raises the possibility that microbiome-targeted approaches could be explored as adjunctive strategies for this high-risk comorbid population.

What was studied?

This study investigated the relationship between periodontitis and the oral-gut axis in first-trimester pregnant women using integrative microbiome and metabolome profiling. Researchers combined 16S rRNA sequencing of subgingival plaque, saliva, and stool with untargeted metabolomics of serum and other sample types, alongside clinical traits. The goal was to characterize how oral dysbiosis linked to periodontitis translates into distal gut microbial and metabolic changes during early pregnancy.

Who was studied?

The cohort consisted of 54 Chinese pregnant women sampled at the first trimester. Of these, 31 women had maternal periodontitis (the Perio group) and 23 women served as Non-Perio controls. Subgingival plaque, saliva, serum, and stool samples were collected from each participant for multi-omics analysis.

What were the most important findings?

The study identified a novel bacterial distinguisher, Coprococcus, in the feces of women with periodontitis, and this genus was associated with subgingival periodontopathogens. Notably, Coprococcus behaved differently from other fecal genera within the Lachnospiraceae family. The ratio of fecal Coprococcus to Lachnoclostridium was able to discriminate between the Perio and Non-Perio groups, indicating a measurable gut-level signature tied to oral disease status.

What are the greatest implications of this study?

The findings support the existence of a functional oral-gut axis through which periodontitis in early pregnancy is reflected in distinct gut microbial and metabolic alterations. Identifying the fecal Coprococcus to Lachnoclostridium ratio as a discriminating feature suggests potential translational value as a biomarker linking oral and gut health in pregnant women. This integrative multi-omics approach may help clarify how periodontitis contributes to adverse pregnancy outcomes via systemic, gut-mediated pathways.

What was studied?

This study examined how laparoscopic sleeve gastrectomy (LSG), a form of bariatric surgery, affects cognitive function through the microbiota-gut-brain axis (MGBA). Researchers integrated fecal 16S microbiota profiling, serum metabolomics, cognitive assessment scales, and resting-state functional connectivity MRI (rs-fMRI) to capture changes across the gut, blood, and brain simultaneously. Correlation-based statistical methods, including Spearman correlation and Co-inertia analysis, were used to link microbiota shifts and metabolite changes to changes in brain connectivity and cognitive scores.

Who was studied?

The cohort consisted of 39 obese patients who underwent laparoscopic sleeve gastrectomy. Each patient was assessed at two time points, before surgery and six months after, using demographic data, serum samples, fecal samples, cognitive testing, and rs-fMRI scans. The abstract does not specify age, sex distribution, or geographic location of the cohort.

What were the most important findings?

LSG produced substantial weight loss, with reductions of up to 28% of body weight at six months. The surgery was accompanied by measurable changes in gut microbiota composition, serum metabolite profiles, and brain functional connectivity networks identified through rs-fMRI. The abstract indicates that these multi-omics changes were statistically correlated with alterations in cognitive assessment scores, suggesting coordinated shifts across the gut-brain axis, though the specific taxa, metabolites, and brain regions most strongly implicated are not detailed in the available text.

What are the greatest implications of this study?

The findings support the idea that bariatric surgery's cognitive benefits may be mediated in part by changes in gut microbiota and their downstream metabolic effects on the brain, rather than weight loss alone. This multi-omics approach, linking microbiota, serum metabolomics, and neuroimaging, offers a framework for identifying specific microbial and metabolic targets that could explain or potentially enhance post-surgical cognitive improvement. Further work identifying the exact bacterial taxa and metabolites involved could inform future non-surgical interventions aimed at the same gut-brain pathways.

What was studied?

This study examined whether iron overload in thalassemia patients is linked to gut dysbiosis and cognitive impairment through the gut-brain axis. Researchers assessed iron burden, cognitive function, and both gut and blood microbiome composition across different blood-transfusion regimens. The goal was to determine whether specific microbial shifts track with iron accumulation and cognitive status in this population.

Who was studied?

Sixty participants were recruited, comprising healthy controls, transfusion-dependent thalassemia (TDT) patients, and non-transfusion-dependent thalassemia (NTDT) patients. TDT patients receive more frequent blood transfusions and, consistent with this, showed greater iron overload than NTDT patients. This design allowed comparisons of gut and blood microbiota across a spectrum of iron-overload severity within the same disease population.

What were the most important findings?

Most thalassemia patients developed gut dysbiosis, and about 25% developed minor cognitive impairment. Both TDT and NTDT groups showed increased Fusobacteriota and Verrucomicrobiota with decreased Fibrobacterota, and TDT patients had more abundant Verrucomicrobia, described as beneficial bacteria. Iron overload correlated with cognitive impairment, and increased Butyricimonas with decreased Paraclostridium was associated with higher cognitive function. No blood microbiota was detected, and blood bacterial profiles did not differ significantly between thalassemia patients and controls.

What are the greatest implications of this study?

The findings suggest that iron overload in thalassemia is associated with gut microbial imbalance that may relate to cognitive outcomes through the gut-brain axis. Specific gut taxa such as Butyricimonas and Paraclostridium emerge as candidate markers linked to cognitive function, while the blood compartment appears not to harbor a distinct microbiome signal in this context. This points to the gut, rather than blood, as the more relevant site for future investigation of microbiome-cognition relationships in iron-overloaded thalassemia patients.

What was studied?

This study examined the gut microbiome in people who inject drugs, comparing those with and without HIV-1 infection. Researchers used amplicon-based 16S rDNA sequencing to identify amplicon sequence variants (ASVs) and detect shifts in bacterial community composition. The goal was to disentangle how HIV status and injection drug use, separately and together, shape the gut microbiota. Effects of multiple drug use on the microbiome were also assessed in both HIV-infected and non-infected participants.

Who was studied?

The study drew on a well-established cohort of people who inject drugs in Puerto Rico, a region with historically high rates of injection drug use and an HIV incidence disproportionately linked to it. Participants included both HIV-positive and HIV-negative individuals, and both drug-injecting and non-injecting individuals, allowing comparison across these groups. The abstract does not give an exact sample size.

What were the most important findings?

HIV-positive individuals had a higher abundance of ASVs from the genera Prevotella, Alloprevotella, Sutterella, Megasphaera, Fusobacterium, and Mitsuokella. In contrast, Bifidobacteria and Lactobacillus ASVs were more abundant in people who inject drugs compared to non-injectors, regardless of HIV status. The study also found that using multiple drugs significantly affected the composition of the gut microbial community. These patterns show that HIV status and drug use each leave distinct, identifiable signatures on the gut microbiome.

What are the greatest implications of this study?

The findings suggest that HIV infection and injection drug use independently reshape the gut microbiome, producing distinguishable bacterial signatures rather than a single combined effect. Identifying HIV-associated genera separately from drug-use-associated genera could help researchers understand how each factor contributes to health outcomes in this population. Recognizing that multiple drug use further alters the microbial community underscores the need to account for drug use patterns in microbiome research on people with HIV. This work supports using gut microbiota profiling as a tool to better understand the intersecting effects of infection and substance use.

What was studied?

Gut microbiota are associated with the pathological features and development of colorectal cancer (CRC); however, how gut microbiota changes in patients with CRC is unknown. This study investigated the role of gut microbiota in the development and progression of CRC by retrospectively comparing the structural differences between the gut microbiota of patients with CRC and healthy individuals.

Who was studied?

Together with clinical data, we collected fecal samples from patients with CRC (n = 18) and healthy controls (n = 18) and performed 16S rRNA gene sequencing and alpha and beta diversity analysis to compare microbiota richness and diversity. Based on the differences in microbiota between the CRC and control groups, we identified disease-specific microbial communities after relevant factors. PICRUSt2 software was used to predict the differential microbial functions.

What were the most important findings?

The CRC and control groups differed in both composition and abundance of intestinal microbiota. Firmicutes and Bacteroidetes were the most abundant phyla in both groups, while Verrucomicrobi was significantly more abundant in the CRC group. Megamonas, Lachnospira, and Romboutsia were more abundant in the control group; 18 genera differed significantly in abundance between the groups, which were found to involve 21 metabolic pathways. The distribution and abundance of gut microbiota differed significantly between patients with CRC with and without lymph node metastasis; at the genus level, the abundance of Rothia and Streptococcus was significantly higher and that of Bacteroides, Parabacteroides, and Oscillibacter was significantly lower in patients with lymph node metastasis.

What are the greatest implications of this study?

The gut microbiota is altered in CRC patients compared with healthy individuals, with specific changes in the microbiota associated with clinical and pathological features such as tumor stage, lymph node involvement, and tumor differentiation. Our findings elaborate to some extent on the link between the gut microbiota and CRC.

What was studied?

This study examined how gut microbiome composition and function differ across subtypes of irritable bowel syndrome (IBS), including IBS with diarrhea (IBS-D), IBS with constipation (IBS-C), and unclassified IBS (IBS-U). Researchers used 16S sequencing data to compare taxonomic and functional profiles of gut bacteria between these IBS subtypes and matched non-IBS controls. They also examined how clinical characteristics, dietary factors, and depression status related to microbial composition within IBS.

Who was studied?

The study drew on deeply phenotyped individuals enrolled in the American Gut Project, a large public microbiome dataset with associated clinical and dietary information. A total of 942 subjects with IBS (spanning IBS-D, IBS-C, and IBS-U) were included and matched by age, gender, body mass index, geography, and dietary patterns with 942 non-IBS controls. This design allowed comparison of microbiome features across IBS subtypes while controlling for major demographic and lifestyle confounders.

What were the most important findings?

Subjects with IBS-D or IBS-U, but not IBS-C, showed significantly reduced bacterial diversity compared to controls. Each IBS subtype was associated with a distinct bacterial signature and corresponding functional shifts tied to disease pathogenesis. Notably, IBS-D was linked to an increased hydrogen sulfide production pathway, while IBS-C was linked to increased palmitoleate biosynthesis. Among IBS subjects, those with depression showed lower Bifidobacterium, Sutterella, and Butyricimonas and higher Proteus than those without depression, and short-chain fatty acid production pathways were reduced in affected patients.

What are the greatest implications of this study?

These findings support treating IBS as a heterogeneous condition with subtype-specific microbial and metabolic signatures rather than a single uniform disorder. The elevated hydrogen sulfide production pathway identified in IBS-D points to sulfur metabolism, potentially involving sulfate-reducing bacterial activity, as a mechanistic feature worth further investigation in diarrhea-predominant disease. The link between depression and specific bacterial taxa also suggests that mental health status should be considered when characterizing IBS microbiome profiles. Together, these results could inform more precise, subtype-tailored approaches to diagnosing and managing IBS.

What was studied?

Research on the gut microbiota in irritable bowel syndrome (IBS) shows discordant results due to inconsistent study designs or small sample sizes. This study aimed to characterize how gut microbiota in IBS patients differs from that in healthy controls by performing a case-control study and cross- and mega-cohort analysis. Multiple publicly shared data sets were examined by using a unified analytical approach. We performed 16S rRNA gene (V3-4) sequencing and taxonomic profiling of the gut bacterial communities. Fecal samples from children with IBS (n = 19) and age-matched healthy controls (n = 24) were used. Next, we analyzed 10 separate data sets using a unified data-processing and analytical approach. In total, 567 IBS patients and 487 healthy controls were examined. In our data sets, no significant differences existed in stool α-diversity between IBS patients and healthy controls. After combining all the data sets using a unified data-processing method, we found significantly lower α-diversity in IBS patients than in healthy controls. In addition, the relative abundance of 21 bacterial species differed between the IBS patients and healthy participants. Although the causal relationship is uncertain, gut bacterial dysbiosis is associated with IBS. Further functional studies are needed to assess whether the change in gut microorganisms contributes to the development of IBS. IMPORTANCE Research on the gut bacteria in irritable bowel syndrome (IBS) shows discordant results due to inconsistent study designs or small sample sizes. To overcome these issues, we analyzed microbiota of 567 IBS patients and 487 healthy people from 10 shared data sets using a unified method. We demonstrated that gut bacteria are less diverse in IBS patients than in healthy people. In addition, the abundance of 21 bacterial species is different between the two groups. Altered bacterial balance, called dysbiosis, has been reported in several disease states. Although the causal relationship is uncertain, gut bacterial dysbiosis also seems to be associated with IBS.

What was studied?

This study investigated the mucosal microbiota at multiple biopsy sites across the spectrum of colorectal cancer (CRC) progression. Researchers used Illumina Miseq sequencing of the 16S rRNA V4 region to profile microbial composition and dynamics in biopsy samples. They also used MinION nanopore sequencing of Fusobacterium-specific amplicons to characterize tumor-associated Fusobacterium nucleatum at the species and subspecies level. The goal was to map how microbial communities shift as tissue progresses from healthy to adenomatous polyp to cancer.

Who was studied?

The abstract describes three groups of biopsy patients from Norway: cancer patients, patients with adenomatous polyps, and healthy controls. Biopsy samples from these groups were sequenced and compared to identify microbiota alterations associated with CRC progression. Fusobacterium-positive tumor biopsies were further subjected to targeted nanopore sequencing. Exact sample sizes for each group are not given in the abstract.

What were the most important findings?

Cancer patients showed enrichment of oral biofilm-associated bacteria compared to adenomatous polyp and control patients, including Fusobacterium, Gemella, Parvimonas, Granulicatella, Leptotrichia, Peptostreptococcus, Campylobacter, Selenomonas, Porphyromonas, and Prevotella. Cancer-associated samples also showed higher abundance of amplicon sequence variants classified as Phascolarctobacterium, Bacteroides vulgatus, Bacteroides plebeius, Bacteroides eggerthii, Tyzzerella, Desulfovibrio, Frisingicoccus, and Eubacterium among others. The presence of Desulfovibrio, a sulfate-reducing bacterial genus capable of producing hydrogen sulfide, was notably elevated alongside these oral pathobionts in cancer tissue. The study further characterized Fusobacterium subspecies within Fusobacterium-positive tumor biopsies using nanopore sequencing.

What are the greatest implications of this study?

These findings support a model in which oral biofilm-associated bacteria, together with sulfate-reducing organisms like Desulfovibrio, colonize and accumulate in colorectal tissue as it progresses toward malignancy. Mapping these site-specific microbial shifts across polyp and cancer stages could help identify microbial markers of CRC progression. Characterizing Fusobacterium at the subspecies level may also refine understanding of which strains are most relevant to tumorigenesis. Together, this work strengthens the rationale for using mucosal microbiota profiles, including sulfide-producing taxa, as part of CRC risk assessment.

What was studied?

This study examined the relationship between gastrointestinal (GI) microbial composition and GI symptoms in patients with systemic sclerosis (SSc). It also compared GI symptoms and microbial composition between SSc patients following a low FODMAP diet versus those not following a low FODMAP diet. Stool specimens underwent bacterial 16S rRNA gene sequencing, and microbial differences were assessed using alpha diversity (species richness, evenness, phylogenetic diversity) and beta diversity (overall composition). Differential abundance analysis was used to identify specific bacterial genera linked to the SSc-GI phenotype and to diet group.

Who was studied?

The study included 66 adult patients with systemic sclerosis who were consecutively recruited and provided stool samples. Patients also completed the UCLA Scleroderma Clinical Trial Consortium Gastrointestinal Tract Instrument (GIT 2.0) to assess GI symptoms and the Diet History Questionnaire (DHQ) II to assess dietary intake. Based on their reported intake, patients were classified as adhering to a low or non-low FODMAP diet.

What were the most important findings?

The abstract provided does not include the specific results, so the detailed findings on microbial diversity, differential genera, or symptom associations cannot be reported here. The study design indicates that both alpha diversity and beta diversity metrics were used to compare gut microbial composition across SSc-GI phenotypes and across diet groups. Differential abundance analysis was intended to pinpoint particular bacterial genera associated with GI symptoms and with FODMAP diet status in this SSc cohort.

What are the greatest implications of this study?

By pairing validated GI symptom instruments with dietary history and 16S rRNA sequencing, this approach helps disentangle whether GI microbial alterations in systemic sclerosis are driven by disease-related changes, dietary patterns, or both. Clarifying this distinction could inform whether dietary interventions such as a low FODMAP diet meaningfully influence gut microbial composition and symptom burden in SSc patients. This kind of design lays groundwork for future studies testing whether dietary modification can be used as a targeted strategy to manage SSc-associated GI symptoms.

What was studied?

Type 2 diabetes mellitus (T2DM) is an independent risk factor for colorectal cancer (CRC), and the patients with CRC and T2DM have worse survival. The human gut microbiota (GM) is linked to the development of CRC and T2DM, respectively. However, the GM characteristics in patients with CRC and T2DM remain unclear.

Who was studied?

We performed fecal metagenomic and targeted metabolomics studies on 36 samples from CRC patients with T2DM (DCRC group, n = 12), CRC patients without diabetes (CRC group, n = 12), and healthy controls (Health group, n = 12). We analyzed the fecal microbiomes, characterized the composition and function based on the metagenomics of DCRC patients, and detected the short-chain fatty acids (SCFAs) and bile acids (BAs) levels in all fecal samples. Finally, we performed a correlation analysis of the differential bacteria and metabolites between different groups.

What were the most important findings?

Compared with the CRC group, LefSe analysis showed that there is a specific GM community in DCRC group, including an increased abundance of Eggerthella , Hungatella , Peptostreptococcus , and Parvimonas , and decreased Butyricicoccus , Lactobacillus , and Paraprevotella . The metabolomics analysis results revealed that the butyric acid level was lower but the deoxycholic acid and 12-keto-lithocholic acid levels were higher in the DCRC group than other groups ( P < 0.05). The correlation analysis showed that the dominant bacterial abundance in the DCRC group ( Parvimonas , Desulfurispora , Sebaldella , and Veillonellales , among others) was negatively correlated with butyric acid, hyodeoxycholic acid, ursodeoxycholic acid, glycochenodeoxycholic acid, chenodeoxycholic acid, cholic acid and glycocholate. However, the abundance of mostly inferior bacteria was positively correlated with these metabolic acid levels, including Faecalibacterium , Thermococci , and Cellulophaga .

What are the greatest implications of this study?

Unique fecal microbiome signatures exist in CRC patients with T2DM compared to those with non-diabetic CRC. Alterations in GM composition and SCFAs and secondary BAs levels may promote CRC development.

What was studied?

Gut microecosystem has been shown to play an important role in human health. In recent years, the concept of the gut-kidney axis has been proposed to explain the potential association between gut microbiota and chronic kidney disease (CKD). Here, a cohort of fecal samples collected from patients with CKD (n = 13) were involved. The composition of gut microbial communities and clinical features in CKD and end-stage renal disease (ESRD) were characterized. Our study focused on the changes in gut microbiome and the correlation with clinical features in patients with CKD and ESRD by analyzing high-throughput sequencing results of collected feces. We elucidated the alterations of gut microbiota in CKD patients at different stages of disease and initially identified the gut microbiota associated with CKD progression. We also combined correlation analysis to identify clinical features closely related to the gut microbiome. Our results offered the possibility of using non-invasive gut microbiome in the early diagnosis of course from CKD to ESRD and provide new insights into the association between clinical features and gut microbiota in CKD.

What was studied?

This study examined the gut microbiome and serum metabolome in patients with functional constipation (FC), a common gastrointestinal disorder that significantly affects physical and mental health. The researchers used 16S rRNA microbial genomics to profile gut microbiota composition and non-target metabolomics based on liquid chromatography-mass spectrometry to characterize serum metabolic profiles. The study was designed to address inconsistent prior findings on the gut microbiome and FC, and to better link microbiome changes to host metabolites.

Who was studied?

The study included 30 patients with functional constipation and 28 healthy individuals as a comparison group. Fecal samples were used for 16S rRNA gut microbiota analysis and serum samples were used for metabolomic profiling in these participants. The abstract does not specify additional demographic details such as age or sex distribution.

What were the most important findings?

FC patients had distinct gut microbiota structures and serum metabolic profiles compared to healthy individuals. Patients with FC showed increased levels of Bacteroides and of several butyrate-producing bacteria, including Roseburia, Faecalibacterium, and Butyricicoccus. Serum levels of upstream products of host arginine biosynthesis, specifically 2-oxoglutaric acid, L-glutamic acid, N-acetylornithine, and L-ornithine, were significantly reduced in FC patients.

What are the greatest implications of this study?

The findings suggest that functional constipation may be associated with an altered gut microbiota, including increased Bacteroidetes, alongside downregulation of host arginine biosynthesis intermediates. This points to a potential link between specific gut bacteria and disrupted host amino acid metabolism in FC. The pairing of microbiome and metabolome data offers a more integrated view of FC pathophysiology than microbiome data alone, which could inform future mechanistic or therapeutic research.

What was studied?

Atrial fibrillation (AF) is an important heart rhythm disorder in aging populations. The gut microbiome composition has been previously related to cardiovascular disease risk factors. Whether the gut microbial profile is also associated with the risk of AF remains unknown.

Who was studied?

We examined the associations of prevalent and incident AF with gut microbiota in the FINRISK 2002 study, a random population sample of 6763 individuals. We replicated our findings in an independent case-control cohort of 138 individuals in Hamburg, Germany.

What were the most important findings?

Multivariable-adjusted regression models revealed that prevalent AF (N = 116) was associated with nine microbial genera. Incident AF (N = 539) over a median follow-up of 15 years was associated with eight microbial genera with false discovery rate (FDR)-corrected P < 0.05. Both prevalent and incident AF were associated with the genera Enorma and Bifidobacterium (FDR-corrected P < 0.001). AF was not significantly associated with bacterial diversity measures. Seventy-five percent of top genera (Enorma, Paraprevotella, Odoribacter, Collinsella, Barnesiella, Alistipes) in Cox regression analyses showed a consistent direction of shifted abundance in an independent AF case-control cohort that was used for replication.

What are the greatest implications of this study?

Our findings establish the basis for the use of microbiome profiles in AF risk prediction. However, extensive research is still warranted before microbiome sequencing can be used for prevention and targeted treatment of AF.

What was studied?

This study investigated the relationship between gut microbiome composition, dietary habits, and breast cancer (BCa) risk. Researchers used 16S rRNA amplicon sequencing to characterize gut microbial composition and to assess alpha and beta diversity. Dietary intake was assessed using the National Cancer Institute Diet History Questionnaire (DHQ), and microbial findings were linked to Healthy Eating Index (HEI2015) components such as vegetables, dairy, and whole fruits.

Who was studied?

The study enrolled newly diagnosed breast cancer patients alongside age-matched, cancer-free controls in a case-control design. Demographic characteristics were reported as well-balanced between the two groups. The abstract does not specify an exact sample size for either group.

What were the most important findings?

Breast cancer patients showed reduced gut microbial diversity compared to controls. Three genera, Acidaminococcus, Tyzzerella, and Hungatella, were enriched in fecal samples from BCa patients relative to cancer-free controls. These genera showed significant associations with specific dietary components: Hungatella with vegetable and dairy intake, and Acidaminococcus with whole fruit intake.

What are the greatest implications of this study?

The findings support a link between altered gut microbiome composition and breast cancer, with diet acting as a potential factor shaping that microbial signature. Identifying enriched genera tied to specific dietary patterns suggests the gut microbiome could serve as a modifiable target connecting diet to breast cancer risk. This raises the possibility that dietary interventions influencing these microbial taxa could be explored as part of breast cancer risk reduction strategies.

What was studied?

Recent studies reveal that imbalanced microbiota is related to thyroid diseases. However, studies on the alterations in fecal metabolites in Graves' disease and clinical hypothyroidism patients are insufficient. Here, we identified 21 genera and 53 metabolites that were statistically significant among Graves' disease patients, hypothyroidism patients, and controls integrating microbiome and untargeted metabolome analysis. Disease groups revealed a decreased abundance in butyrate-producing microbiota and an increased abundance in potentially pathogenic microbiota. Lipids molecules were the major differential metabolites identified in all fecal samples. Network analysis recognized that microbiota may affect thyroid function by targeting specific metabolites. We further identified specific microbiota and metabolites that could distinguish Graves' disease patients, hypothyroidism patients, and controls. Our study reveals a distinct microbial and metabolic signature in hypothyroidism patients and Graves' disease patients and further validates the potential role of microbiota in thyroid diseases, providing new ideas for future research into the etiology and clinical intervention of thyroid diseases.

What was studied?

This study aims to explore the relationship between gut microbiota and the development of thyroid carcinoma.

Who was studied?

Stool samples were collected from 90 thyroid carcinoma patients (TCs) and 90 healthy controls (HCs). Microbiota were analyzed using 16S ribosomal RNA gene sequencing. A cross-sectional study of an exploratory cohort of 60 TCs and 60 HCs was conducted. The gut microbiota signature of TCs was established by LEfSe, stepwise logistic regression, lasso regression, and random forest model analysis. An independent cohort of 30 TCs and 30 HCs was used to validate the findings. Functional prediction was achieved using Tax4Fun and PICRUSt2. TC patients were subsequently divided into subgroups to analyze the relationship between microbiota and metastatic lymphadenopathy.

What were the most important findings?

In the exploratory cohorts, TCs had reduced richness and diversity of gut microbiota compared to HCs. No significant difference was found between TCs and HCs on the phylum level, though 70% of TCs had increased levels of Proteobacteria-types based on dominant microbiota typing. A prediction model of 10 genera generated with LEfSe analysis and lasso regression distinguished TCs from HCs with areas under the curves of 0.809 and 0.746 in the exploration and validation cohorts respectively. Functional prediction suggested that the microbial changes observed in TCs resulted in a decline in aminoacyl-tRNA biosynthesis, homologous recombination, mismatch repair, DNA replication, and nucleotide excision repair. A four-genus microbial signature was able to distinguish TC patients with metastatic lymphadenopathy from those without metastatic lymphadenopathy.

What are the greatest implications of this study?

Our study shows that thyroid carcinoma patients demonstrate significant changes in gut microbiota, which will help delineate the relationship between gut microbiota and TC pathogenesis.

What was studied?

Although the etiology of obsessive-compulsive disorder (OCD) is largely unknown, it is accepted that OCD is a complex disorder. There is a known bi-directional interaction between the gut microbiome and brain activity. Several authors have reported associations between changes in gut microbiota and neuropsychiatric disorders, including depression or autism. Furthermore, a pediatric-onset neuropsychiatric OCD-related syndrome occurs after streptococcal infection, which might indicate that exposure to certain microbes could be involved in OCD susceptibility. However, only one study has investigated the microbiome of OCD patients to date. We performed 16S ribosomal RNA gene-based metagenomic sequencing to analyze the stool and oropharyngeal microbiome composition of 32 OCD cases and 32 age and gender matched controls. We estimated different α- and β-diversity measures and performed LEfSe and Wilcoxon tests to assess differences in bacterial distribution. OCD stool samples showed a trend towards lower bacterial α-diversity, as well as an increase of the relative abundance of Rikenellaceae, particularly of the genus Alistipes, and lower relative abundance of Prevotellaceae, and two genera within the Lachnospiraceae: Agathobacer and Coprococcus. However, we did not observe a different Bacteroidetes to Firmicutes ratio between OCD cases and controls. Analysis of the oropharyngeal microbiome composition showed a lower Fusobacteria to Actinobacteria ratio in OCD cases. In conclusion, we observed an imbalance in the gut and oropharyngeal microbiomes of OCD cases, including, in stool, an increase of bacteria from the Rikenellaceae family, associated with gut inflammation, and a decrease of bacteria from the Coprococcus genus, associated with DOPAC synthesis.

What was studied?

This pilot study examined the gut microbiota of patients with brain tumors to determine whether benign and malignant tumors are associated with distinct microbial patterns. It compared microbial diversity and composition across benign meningioma, malignant glioma, and healthy control groups. The work builds on prior evidence linking gut microbiota to tumor growth, including malignant gliomas, via the brain-gut axis.

Who was studied?

The study included 32 patients with benign meningioma, 27 patients with malignant glioma, and 41 healthy individuals as controls. This gives a total pilot cohort of 100 participants across the three groups. No further demographic details are provided in the abstract.

What were the most important findings?

Brain tumor patients, both meningioma and glioma groups, showed lower gut microbial diversity than healthy controls, with no significant diversity difference between the two tumor groups. Microbial composition differed significantly between tumor patients and healthy participants. Meningioma patients had increased pathogenic bacteria such as Enterobacteriaceae, while glioma patients showed overrepresentation of carcinogenic bacteria including Fusobacterium and Akkermansia. Both benign and malignant tumor groups lacked SCFA-producing probiotic bacteria.

What are the greatest implications of this study?

The findings suggest that gut microbial alterations, including reduced diversity and loss of SCFA-producing bacteria, are associated with the presence of brain tumors generally, while specific taxa may distinguish benign from malignant disease. The identification of a candidate microbial biomarker panel, including Fusobacterium, Akkermansia, Escherichia/Shigella, Lachnospira, and Agathobacter, points toward potential non-invasive markers for differentiating tumor types. As a pilot study, these results support further investigation into the brain-gut axis as a factor in brain tumor pathology.

What was studied?

The microbial population of the intestinal tract and its relationship to specific diseases has been extensively studied during the past decade. However, reports characterizing the bile microbiota are rare. This study aims to investigate the microbiota composition in patients with pancreaticobiliary cancers and benign diseases by 16S rRNA gene amplicon sequencing and to evaluate its potential value as a biomarker for the cancer of the bile duct, pancreas, and gallbladder.

What were the most important findings?

We enrolled patients who were diagnosed with cancer, cystic lesions, and inflammation of the pancreaticobiliary tract. The study cohort comprised 244 patients. We extracted microbiome-derived DNA from the bile juice in surgically resected gallbladders. The microbiome composition was not significantly different according to lesion position and cancer type in terms of alpha and beta diversity. We found a significant difference in the relative abundance of Campylobacter, Citrobacter, Leptotrichia, Enterobacter, Hungatella, Mycolicibacterium, Phyllobacterium and Sphingomonas between patients without and with lymph node metastasis.

What are the greatest implications of this study?

There was a significant association between the relative abundance of certain microbes and overall survival prognosis. These microbes showed association with good prognosis in cholangiocarcinoma, but with poor prognosis in pancreatic adenocarcinoma, and vice versa. Our findings suggest that pancreaticobiliary tract cancer patients have an altered microbiome composition, which might be a biomarker for distinguishing malignancy.

What was studied?

This study investigated whether the gut microbiota differs in patients with brain tumors compared to healthy people. The researchers characterized the fecal microbial community using 16S rRNA gene amplicon sequencing. They then examined correlations between microbiota composition and clinical features of the tumors, and explored whether specific microbial markers could help diagnose brain tumors.

Who was studied?

The study recruited 158 participants in total. This included 101 patients with brain tumors, made up of 65 benign and 36 malignant cases, along with 57 age- and sex-matched healthy controls.

What were the most important findings?

Patients with brain tumors had markedly lower gut microbial ecosystem richness and evenness than healthy controls. The overall structure of the gut microbiota community was also profoundly altered in the brain tumor group. This shift included increased abundance of pathogenic bacteria such as Fusobacteriota and Proteobacteria, alongside a reduction in other taxa.

What are the greatest implications of this study?

These findings support a gut-brain crosstalk in which gut dysbiosis is associated with the presence of brain tumors, extending prior work on microbiota alterations in other CNS diseases to this tumor context. The distinct shifts toward pathogenic taxa such as Fusobacteriota and Proteobacteria suggest the gut microbiota could potentially serve as a diagnostic marker for brain tumors. Further work would be needed to determine whether these microbial changes are a cause, consequence, or bystander effect of tumor presence.

What was studied?

This study investigated the connection between the oral and gut microbiome in Parkinson's disease (PD) using shotgun metagenomic sequencing. Researchers examined both the taxonomic composition and the functional gene content of these microbial communities. The aim was to determine whether oral microbiome changes relate to gut microbiome changes in PD, and whether these shifts produce functional alterations rather than just compositional differences.

Who was studied?

The abstract does not report specific sample sizes, ages, or recruitment details. The study compared PD patients to healthy controls, using paired oral and gut microbiome samples analyzed by shotgun metagenomic sequencing. Beyond the PD-versus-control design, no further cohort characteristics are given in the abstract.

What were the most important findings?

The taxonomic composition of both the oral and gut microbiome differed significantly between PD patients and healthy controls (P = 0.003 and 0.001, respectively). Oral Lactobacillus was more abundant in PD patients and was associated with opportunistic pathogens in the gut (FDR-adjusted P < 0.038). Functionally, microbial gene markers for glutamate and arginine biosynthesis were downregulated, while antimicrobial resistance gene markers were upregulated in PD patients compared to healthy controls (all P < 0.001).

What are the greatest implications of this study?

The findings suggest a connection between the oral and gut microbiota in PD that may drive functional, not just compositional, alterations of the microbiome. The rise in oral Lactobacillus alongside opportunistic gut pathogens points to the oral cavity as a potential contributor to gut dysbiosis in PD. Reduced glutamate and arginine biosynthesis and increased antimicrobial resistance gene markers highlight functional microbial pathways that may warrant further investigation as they relate to PD pathophysiology.

What was studied?

In recent years, many studies have suggested that ancient wheat products might have beneficial effects on cardiometabolic risk profile, but little is known about their effect on gut microbiota (GM). The aim of the present study was to evaluate whether a replacement diet with pasta made from ancient wheat (AD) could influence the GM composition and its metabolites' production compared to a replacement diet with pasta made from modern wheat (CD).

Who was studied?

A randomized, double-blinded crossover trial with two intervention phases was conducted on 20 clinically healthy adults (9 females; 11 males; mean age 43.1 ± 12.5 years). Study participants were assigned to consume pasta made using semi-whole flour from organic wheat that was either from ancient or modern control wheat for 8 weeks in a random order. An 8-week washout period was implemented between the interventions. Stool samples were collected from all subjects at the beginning and at the end of each intervention period. GM composition, and short- (SCFAs) and medium- chain fatty acids (MCFAs) production was evaluated.

What were the most important findings?

Dietary interventions did not produce significant diversity in the GM composition at higher ranks (phylum, class, order and family), but only at genus level. In detail, the AD significantly (adj. p < 0.05) changed the abundance of Erysipelatoclostridium spp., Bacteroides_pectinophilus_group spp., CAG-873 spp., and Holdemanella spp. The CD significantly affected the abundance of Akkermansia spp., CAG-873 spp., Hungatella spp., Lachnospiraceae_UCG-008 spp., NK4A214_group spp., Frisingicoccus spp., Megasphaera spp., Synergistes spp., and Tyzzerella spp. Regarding the production of SCFAs and MCFAs, AD resulted in a significant increase of fecal acetic (+0.7%), isobutyric (+30.1%), 2-methylbutyric (+64.2%), and isovaleric (+22.5%) acids. On the other hand, CD resulted in increased levels of isobutyric (+71.4%), 2-methylbutyric (+116.2%), isovaleric (+99%), and valeric (+21.4%) acids, and a reduction of butyric (-31.6%) and hexanoic (-66.4%) acids.

What are the greatest implications of this study?

A short-term replacement diet with both ancient and modern wheat pasta determined significant changes in GM composition at the genus level but notably the AD resulted in a greater beneficial impact on anti-inflammatory SCFAs.

What was studied?

This study investigated the ocular surface microbiome in patients with unilateral or asymmetric glaucoma who were using topical ophthalmic medications in only one eye. Researchers used V3-V4 16S rRNA sequencing on ocular surface swabs to characterize microbial diversity and composition. They then tested whether differences in microbial composition were related to measures of ocular surface disease, including tear meniscus height, tear break-up time, and Dry Eye Questionnaire scores.

Who was studied?

The study included 17 subjects total. Ten were patients with asymmetric or unilateral glaucoma who used topical glaucoma therapy in only one eye, allowing comparison between their treated and untreated eyes. Seven were age-matched healthy controls with no history of ocular disease or eyedrop use, and samples were grouped into three categories: treated glaucomatous eyes, untreated contralateral eyes, and healthy control eyes.

What were the most important findings?

Both the treated and the untreated eyes of glaucoma patients showed significantly greater alpha-diversity and a greater relative abundance of gram-negative organisms compared to healthy control eyes. This pattern occurred even in the contralateral eye that received no eyedrops, suggesting a systemic or bilateral effect rather than one confined to the treated eye alone. The microbial composition of patient eyes was also associated with decreased tear meniscus height and decreased tear break-up time, linking microbiome alterations to signs of ocular surface disease.

What are the greatest implications of this study?

The findings suggest that topical glaucoma therapy is associated with ocular surface microbiome shifts that extend beyond the directly treated eye, potentially through systemic exposure or shared tear film dynamics. Because these microbial changes correlated with impaired tear film stability, the results implicate the ocular surface microbiome as a factor in medication-related ocular surface disease among glaucoma patients. This raises the possibility that microbiome monitoring could inform strategies to reduce ocular surface complications in long-term glaucoma treatment.

What was studied?

This study examined the composition, structure, and function of gut microbiota in patients with diabetic retinopathy (DR), a common complication of type 2 diabetes mellitus. Researchers used 16S ribosomal RNA gene sequencing on stool samples to characterize microbial community differences. They also explored correlations between gut microbiota features and the clinical characteristics of DR.

Who was studied?

The study included 50 total participants who provided stool samples: 25 patients with diabetic retinopathy and 25 healthy controls. DNA was extracted from the fecal samples and analyzed using the MiSeq sequencing platform. No further demographic details were given in the abstract.

What were the most important findings?

The gut microbial structure and composition of DR patients differed from that of healthy controls, and microbial richness was higher in the DR group. These alterations were associated with disrupted levels of the Firmicutes, Bacteroidetes, Synergistota, and Desulfobacterota phyla. At the genus level, Bacteroides, Megamonas, Ruminococcus_torques_group, Lachnoclostridium, and Alistipes were increased, while Blautia, Eubacterium_hallii_group, Collinsella, Dorea, Romboutsia, Anaerostipes, and Fusicatenibacter were decreased in DR patients. Notably, the Desulfobacterota phylum, which includes sulfate-reducing bacteria capable of hydrogen sulfide production, was among the disrupted taxa in DR.

What are the greatest implications of this study?

These findings suggest that gut microbiota alterations, including shifts in sulfate-reducing Desulfobacterota, may be linked to the development or progression of diabetic retinopathy. The distinct microbial signature identified in DR patients raises the possibility that gut microbiota could serve as a biomarker or contributing factor in this diabetic complication. Further research building on the stochastic forest model mentioned in the abstract could help clarify whether specific taxa have diagnostic or mechanistic relevance to DR.

What was studied?

Gestation is linked to changes in gut microbiota composition and function. Since gestational diabetes mellitus (GDM) can develop at any time of the pregnancy, we stratified the women into four groups according to the time and test used for the diagnosis. We focused on the gut microbiota pattern in early pregnancy to detect changes which could be linked to later GDM development.

Who was studied?

We collected stool samples from 104 pregnant women including obese individuals (first trimester body mass index median was 26.73). We divided the women into four groups according to routine screening of fasting plasma glucose (FPG) levels and oral glucose tolerance test (oGTT) in the first and third trimesters, respectively. We processed the stool samples for bacterial 16S rRNA and fungal ITS1 genes sequencing by Illumina MiSeq approach and correlated the gut microbiota composition with plasma short-chain fatty acid levels (SCFA).

What were the most important findings?

We found that gut bacterial microbiota in the first trimester significantly differs among groups with different GDM onset based on unweighted UniFrac distances (p=0.003). Normoglycemic women had gut microbiota associated with higher abundance of family Prevotellaceae, and order Fusobacteriales, and genus Sutterella. Women diagnosed later during pregnancy either by FGP levels or by oGTT had higher abundances of genera Enterococcus, or Erysipelotrichaceae UCG-003, respectively. We observed significant enrichment of fungal genus Mucor in healthy pregnant women whereas Candida was more abundant in the group of pregnant women with impaired oGTT. Using correlation analysis, we found that Holdemanella negatively correlated with Blautia and Candida abundances and that Escherichia/Shigella abundance positively correlated and Subdoligranulum negatively correlated with plasma lipid levels. Coprococcus, Akkermansia, Methanobrevibacter, Phascolarctobacterium and Alistipes positively correlated with acetate, valerate, 2-hydroxybutyrate and 2-methylbutyrate levels, respectively, in women with GDM.

What are the greatest implications of this study?

We conclude that there are significant differences in the gut microbiota composition between pregnant women with and without GDM already at the early stage of pregnancy in our cohort that included also overweight and obese individuals. Specific microbial pattern associated with GDM development during early pregnancy and its correlation to plasma lipid or SCFA levels could help to identify women in higher risk of GDM development.

What was studied?

This study examined the gut bacteriome, mycobiome (fungal community), and serum metabolome in people with polycystic ovary syndrome (PCOS) compared to healthy individuals, across both normal-weight and overweight/obese body types. Researchers used 16S rRNA sequencing to profile bacteria, ITS2 gene sequencing to profile fungi, and metabolome analysis to profile serum metabolites. The goal was to characterize multi-omic differences between PCOS and healthy states and to explore whether microbiota-based markers could support a diagnostic method for PCOS. Classifiers combining bacterial, fungal, pathway, and metabolite markers were built to distinguish PCOS from healthy controls.

Who was studied?

The analysis drew on 88 fecal samples for the 16S rRNA and ITS2 sequencing and 87 serum samples for metabolome analysis. Participants included both PCOS patients and healthy volunteers, and both groups were further divided into normal-BMI and overweight/obese subgroups (PCOS-LB, Healthy-LB, PCOS-HB, Healthy-HB). No further demographic details such as age range or geographic origin are given in the abstract.

What were the most important findings?

Significant differences in bacterial, fungal, and metabolite profiles were found between PCOS patients and healthy controls in both normal-weight and overweight/obese groups. Healthy overweight/obese individuals showed less abnormal metabolism than PCOS patients and a uniquely higher abundance of the fungal genus Mortierella. Nine bacterial genera, four predicted functional pathways, eleven fungal genera, and the top 30 metabolites were identified as distinguishing features, with classification accuracies (AUC) of 0.84, 0.64, 0.85, and 1.0 respectively. The metabolite-based model outperformed the microbe-based model at distinguishing PCOS from healthy controls within both BMI strata, and featured bacteria, fungi, pathways, and metabolites showed strong associations with the free androgen index in a cooccurrence network.

What are the greatest implications of this study?

The findings suggest that serum metabolites, more than gut bacterial or fungal composition alone, may offer the most accurate biomarker signal for distinguishing PCOS from healthy states regardless of body weight. The strong links between featured multiomic markers and the free androgen index point to a mechanistic connection between gut microbiota, metabolism, and androgen excess in PCOS. This multiomics approach could support development of non-invasive diagnostic tools for PCOS that account for BMI status rather than treating all patients uniformly.

What was studied?

Myostatin (MSTN) negatively regulates the muscle growth in animals and MSTN deficient sheep have been widely reported previously. The goal of this study was to explore how MSTN inactivation influences their gut microbiota composition and potential functions.

What were the most important findings?

We compared the slaughter parameters and meat quality of 3 MSTN-edited male sheep and 3 wild-type male sheep, and analyzed the gut microbiome of the MSTN-edited sheep (8 female and 8 male sheep) and wild-type sheep (8 female and 8 male sheep) through metagenomic sequencing. The results showed that the body weight, carcass weight and eye muscle area of MSTN-edited sheep were significantly higher, but there were no significant differences in the meat quality indexes. At the microbial level, the alpha diversity was significantly higher in the MSTN-edited sheep (P < 0.05), and the microbial composition was significantly different by PCoA analysis in the MSTN-edited and wild-type sheep. The abundance of Firmicutes significantly increased and Bacteroidota significantly decreased in the MSTN-edited sheep. At genus level, the abundance of Flavonifractor, Subdoligranulum, Ruthenibacterium, Agathobaculum, Anaerotignum, Oribacterium and Lactobacillus were significantly increased in the MSTN-edited sheep (P < 0.05). Further analysis of functional differences was found that the carotenoid biosynthesis was significantly increased and the peroxisome, apoptosis, ferroptosis, N-glycan biosynthesis, thermogenesis, and adipocytokines pathways were decreased in the MSTN-edited sheep (P < 0.05). Moreover, carbohydrate-active enzymes (CAZymes) results certified the abundance of the GH13_39, GH4, GH137, GH71 and PL17 were upregulated, and the GT41 and CBM20 were downregulated in the MSTN-edited sheep (P < 0.05).

What are the greatest implications of this study?

Our study suggested that MSTN inactivation remarkably influenced the composition and potential function of hindgut microbial communities of the sheep, and significantly promoted growth performance without affecting meat quality.

What was studied?

This study examined the gut microbiome in Parkinson's disease (PD) using large-scale, high-resolution shotgun metagenomic sequencing of fecal DNA. The researchers applied uniform, standardized methods throughout, followed by metagenome-wide association studies requiring agreement between two independent statistical methods (ANCOM-BC and MaAsLin2) before declaring a disease association. They also conducted network analysis to identify clusters of co-occurring microbial species and functional profiling to characterize microbial genes and pathways.

Who was studied?

The study enrolled 490 individuals with Parkinson's disease and 234 control individuals. Fecal samples from this cohort underwent deep shotgun sequencing to generate the metagenomic data analyzed in the study. The abstract does not provide further demographic detail on the participants.

What were the most important findings?

Over 30 percent of the species, genes, and pathways tested showed altered abundances in Parkinson's disease, indicating widespread dysbiosis. PD-associated species organized into polymicrobial clusters that grew, shrank, or competed together rather than acting independently. The PD microbiome was disease permissive: it showed overabundance of pathogens and immunogenic components, dysregulated neuroactive signaling, an excess of molecules that induce alpha-synuclein pathology, and overproduction of toxicants, alongside a reduction in anti-inflammatory and neuroprotective factors that would otherwise support recovery.

What are the greatest implications of this study?

By validating in human PD patients findings previously seen only in experimental models, this study strengthens the case that the gut microbiome contributes to multiple disease mechanisms in Parkinson's disease. The reconciliation of prior human PD microbiome literature helps resolve inconsistencies across earlier studies and establishes a more standardized foundation for future research. The reduction in anti-inflammatory and neuroprotective microbial factors points to a loss of protective capacity that may limit the body's ability to counteract disease processes, suggesting the microbiome as a potential target for future mechanistic and therapeutic investigation.

What was studied?

Increasing evidence connects the gut microbiome to Parkinson's disease (PD) etiology, but little is known about microbial contributions to PD progression and its clinical features. We aim to explore the association between the gut microbiome with PD, and the microbial association with PD-specific clinical features.

Who was studied?

In a community-based case-control study of 96 PD patients and 74 controls, microbiome data were obtained from 16S rRNA gene sequencing of fecal samples, and analyzed for microbial diversity, taxa abundance, and predicted functional pathways that differed in PD patients and controls, and their association with PD-specific features (disease duration, motor subtypes, L-DOPA daily dose, and motor function).

What were the most important findings?

PD patients' gut microbiome showed lower species diversity (p = 0.04) and were compositionally different (p = 0.002) compared to controls but had a higher abundance of three phyla (Proteobacteria, Verrucomicrobiota, Actinobacteria) and five genera (Akkermansia, Enterococcus, Hungatella, and two Ruminococcaceae) controlling for sex, race, age, and sequencing platform. Also, 35 Metacyc pathways were predicted to be differentially expressed in PD patients including biosynthesis, compound degradation/utilization/assimilation, generation of metabolites and energy, and glycan pathways. Additionally, the postural instability gait dysfunction subtype was associated with three phyla and the NAD biosynthesis pathway. PD duration was associated with the Synergistota phylum, six genera, and the aromatic compound degradation pathways. Two genera were associated with motor function.

What are the greatest implications of this study?

PD patients differed from controls in gut microbiome composition and its predicted metagenome. Clinical features were also associated with bacterial taxa and altered metabolic pathways of interest for PD progression.

What was studied?

This study examined the composition and functional potential of the gut microbiota in people with type 2 diabetes (T2D) across two distinct populations, Denmark and South India. The researchers used 16S ribosomal RNA gene amplicon sequencing on stool samples to compare the gut microbiota between countries and between people with and without T2D. A central goal was to determine whether any microbiome signature of T2D is universal across ethnicities and diets, or whether such signatures are instead country-specific. The study also looked at microbial associations with treatment using the anti-hyperglycemic drug metformin.

Who was studied?

The study population consisted of 279 Danish study participants and 294 Indian study participants, for a total of 573 people. Stool samples were collected from both cohorts and profiled using 16S rRNA gene amplicon sequencing. The abstract does not specify additional demographic details such as age or sex distribution within these two national cohorts.

What were the most important findings?

The gut microbiota differed measurably between the Danish and Indian populations, reflecting country-specific patterns in diversity and composition. Samples were stratified to look for both global (trans-ethnic) and country-specific microbial signatures associated with T2D and with metformin treatment. This approach allowed the researchers to separate microbial features that might be universal markers of T2D from those that are shaped by local diet or ethnic background. The abstract does not report specific taxa, effect sizes, or statistical values for these comparisons.

What are the greatest implications of this study?

By directly comparing two ethnically and geographically distinct populations, this study helps clarify whether gut microbiota changes linked to type 2 diabetes represent a truly universal signature or are instead dependent on diet and ethnic origin. This distinction matters for whether microbiome-based diagnostics or interventions for T2D could be applied globally or would need to be tailored to specific populations. Separating country-specific findings from trans-ethnic ones also helps prevent overgeneralizing microbiome associations discovered in a single population. The findings support continued large-scale, multi-population microbiome research as a foundation for any future universal T2D biomarkers.

What was studied?

This study is a meta-analysis that re-analyzed ten previously published 16S rRNA gut microbiome datasets from Parkinson's disease (PD) research. The goal was to determine whether a consistent, PD-specific pattern of gut microbiota alterations could be identified across these independently collected cohorts. Prior individual studies had reported gut microbiome changes in PD, but no consensus had emerged on which features were reproducible. By pooling and re-analyzing the existing datasets together, the authors aimed to filter out study-specific technical noise and find robust, shared signals.

Who was studied?

The analysis draws on ten already-published 16S microbiome datasets comparing Parkinson's disease patients to control subjects, rather than a single newly recruited cohort. The abstract does not specify the exact number of participants, their ages, or geographic locations within these combined datasets. What can be said is that this was a cross-cohort meta-analysis of existing PD-versus-control 16S sequencing data assembled from multiple prior studies.

What were the most important findings?

The meta-analysis identified significant, reproducible alterations in the PD-associated gut microbiome that held up across the technical differences between the original studies, even though overall differences in microbiome structure between PD patients and controls were small. The most consistent changes were enrichment of the genera Lactobacillus, Akkermansia, and Bifidobacterium, paired with depletion of bacteria in the Lachnospiraceae family and the Faecalibacterium genus. Lachnospiraceae and Faecalibacterium are both important producers of short-chain fatty acids, so their depletion was a notable shared feature across cohorts.

What are the greatest implications of this study?

The loss of short-chain fatty acid-producing bacteria such as Faecalibacterium and Lachnospiraceae members suggests that PD-associated gut dysbiosis may promote a pro-inflammatory intestinal environment. The authors propose this inflammatory shift could be linked to the gastrointestinal symptoms that commonly recur in PD patients. By establishing a reproducible cross-cohort microbiome signature, this meta-analysis strengthens the case that gut microbiota alterations are a real, consistent feature of PD rather than isolated findings, supporting further research into the gut-brain axis in neurodegeneration.

What was studied?

The aim of this study was to investigate the composition of the intestinal microbiota and its association with fecal short chain fatty acids (SCFAs) in children with drug refractory epilepsy (DRE) before and after treatment with a ketogenic diet (KD).

Who was studied?

Herein, we conducted a cross-sectional study of 12 children with DRE and 12 matched healthy controls to compare the changes in fecal microbiomes and SCFAs. Disease cohort also underwent analysis before and after 6 months of KD treatment.

What were the most important findings?

A higher microbial alpha diversity and a significant increase in Actinobacteria at the phylum level and Enterococcus, Anaerostipes, Bifidobacterium, Bacteroides, and Blautia at the genus level were observed in the children with DRE. The abundance of the eight epileptic-associated genera was reversed after six months of KD treatment with decreases in Bifidobacterium, Akkermansia, Enterococcaceae and Actinomyces and increases in Subdoligranulum, Dialister, Alloprevotella (p < 0.05). In particular, we identified some taxa that were more prevalent in patients with an inadequate response to KD than in those with an adequate response. Further, a significant correlation was observed between the change in the microbiome genera after KD treatment. The SCFA content in the fecal after 6 months of KD treatment increased and was highly correlated with the gut bacteria.

What are the greatest implications of this study?

Dysbiosis of the microbiome could be involved in the pathogenesis of DRE in children, which can be relieved by a KD to a large extent. Gut microbiota and microbial metabolism could contribute to the antiseizure effect of KD.

What was studied?

This study examined the relationship between the intestinal microbiota and SARS-CoV-2 infection in a United States hospital cohort. Researchers collected fecal samples and used 16S rRNA sequencing plus qPCR analysis to compare microbial composition across infection states. They compared actively infected patients, recovered patients, and uninfected controls seen for unrelated respiratory conditions, and also tested for fecal viral shedding.

Who was studied?

The cohort included 50 patients actively infected with SARS-CoV-2, 9 patients who had recovered from SARS-CoV-2 infection, and 34 uninfected control subjects seen at the hospital for unrelated respiratory medical conditions. The study is described as a United States, majority African American and minority-dominated cohort. Fecal DNA and RNA were collected prospectively from all three groups for microbiota analysis.

What were the most important findings?

Fecal microbial composition differed significantly between SARS-CoV-2 patients and controls, independent of antibiotic exposure, with Peptoniphilus, Corynebacterium, and Campylobacter enriched in COVID-19 patients. Actively infected patients also had a distinct gut microbiota compared to recovered patients, with Campylobacter most enriched during active infection and Agathobacter and Faecalibacterium enriched after recovery. Notably, recovered patients showed no difference in microbial community structure or alpha diversity compared to uninfected controls. Nearly half of the COVID-19 patients (24 of 50, 48%) tested positive by RT-qPCR for fecal viral material.

What are the greatest implications of this study?

The findings suggest that SARS-CoV-2 infection is associated with a transient disruption of gut microbial composition that resolves as patients recover, rather than causing lasting dysbiosis. This return to an uninfected-like microbiome state in recovered patients supports the gut as a site of active but reversible interaction with the virus. The high rate of fecal viral detection also reinforces concern about potential fecal-oral transmission during active infection.

What was studied?

This study examined the gut microbiota and fecal metabolome in children with systemic lupus erythematosus (SLE), an autoimmune connective tissue disease with unclear origins. Researchers used 16S rRNA sequencing to profile intestinal bacterial communities and gas chromatography-mass spectrometry (GC-MS) to characterize fecal metabolites. The goal was to correlate microbial composition changes with metabolite shifts to better understand SLE pathogenesis.

Who was studied?

The abstract identifies the population as children with systemic lupus erythematosus, compared against healthy controls (referred to as HCs). No specific sample size, age range, or recruitment site is given in the abstract. The comparison design implies a case-control cohort of pediatric SLE patients and matched or unmatched healthy children.

What were the most important findings?

Alpha diversity of the gut microbiota was unchanged in SLE patients, while beta diversity was partially altered compared to controls. Proteobacteria and Enterobacteriales increased and Ruminococcaceae decreased among SLE patients. Fecal metabolite analysis showed enrichment of amino acids and short-chain fatty acids alongside a decrease in long-chain fatty acids, with KEGG pathway analysis highlighting protein digestion and absorption, and association analysis pointing to 3-phenylpropanoic acid and Sphingomonas as key features. Sphingomonas was also found to be less abundant in healthy periodontal sites of SLE patients than in controls, suggesting possible oral-to-gut transmission of this taxon.

What are the greatest implications of this study?

These findings suggest that gut microbial imbalance and altered fecal metabolites, particularly involving Ruminococcaceae, Proteobacteria, and short-chain and long-chain fatty acids, may contribute to SLE pathogenesis in children. The identification of Sphingomonas and 3-phenylpropanoic acid as correlated features points to a potential oral-gut microbial axis worth further investigation. This work provides a foundation for exploring microbiome-targeted approaches as potential treatments for pediatric SLE.

What was studied?

This study examined the gut microbiome composition of patients with young-onset colorectal cancer (yCRC), a form of sporadic colorectal cancer whose incidence is rising. Researchers used 16S rRNA gene sequencing to identify microbial markers distinguishing yCRC, then validated these findings in an independent cohort. Metagenome sequencing was also performed to characterize species-level and functional differences in bacterial communities associated with yCRC.

Who was studied?

The discovery analysis drew on 728 samples analyzed by 16S rRNA gene sequencing. An independent validation cohort of 310 samples was used to confirm the identified microbial markers. A further subset of 200 samples underwent metagenome sequencing for species-level and functional analysis.

What were the most important findings?

Gut microbial diversity was increased in yCRC compared to other groups studied. Flavonifractor plautii emerged as an important bacterial species associated with yCRC, whereas the genus Streptococcus contained the key phylotype linked to old-onset colorectal cancer. Functional analysis showed that yCRC-associated bacterial communities were distinguished by a dominance of DNA binding and RNA-dependent DNA biosynthetic processes, and a random forest classifier built on these microbial features achieved strong classification performance.

What are the greatest implications of this study?

The findings suggest that gut microbiota biomarkers, particularly Flavonifractor plautii abundance and associated functional signatures, could serve as a non-invasive tool for detecting and distinguishing yCRC. This approach could help address the diagnostic gap for younger patients as sporadic colorectal cancer incidence rises in this age group. The distinct microbial and functional profile of yCRC versus old-onset colorectal cancer also points to potentially different underlying disease biology between the two age groups.

What was studied?

Parkinson's disease (PD) is a degenerative disease of the central nervous system (CNS) and is common among the middle-aged and elderly populations. Increasing evidence shows that the gut microbiota may trigger PD through the "gut-microbiota-brain" axis. A previous study revealed that constipation, one of the non-motor symptoms of PD, affects gut microbiota and the progression of PD. However, whether constipation is involved in gut microbiota-associated PD is largely unknown. Therefore, we investigated the relationship between gut microbiota, PD, and constipation in this study. We carried out 16S rRNA sequencing in 15 constipated PD patients (C-PD), 14 non-constipated PD (NC-PD) patients, and 15 healthy controls to evaluate the microbial population. Furthermore, co-occurrence networks were used to assess the gut ecology of the three groups. Spearman analyses were used to analyze the correlation between the differential microbiota and the clinical features. The results showed that there were differences in the composition of the gut microbiota among the C-PD group, the NC-PD group, and the healthy controls. No significant differences were observed in the alpha diversity among the three groups, but the beta diversity differed significantly among the groups. Compared with the healthy controls, the abundance of Hungatella and Collinsella was increased and the abundance of Lachnospira and Fusicatenibacter was reduced in the PD patients' feces. Compared with the NC-PD group, the relative abundance of Megamonas and Holdemanella were lower, while Hungatella, Streptococcus and Anaerotruncus were enriched in the C-PD group. The co-occurrence network analysis showed that the C-PD group presented a different microbial community relationship compared with the NC-PD group and the healthy controls. Our study provides strong evidence that the gut microbiota may be related to constipation in PD. In addition, our data suggest an association between the differential microbiota genera and the clinical features of PD. Therefore, modulating gut microbiota may be another way to monitor and optimize PD treatment.

What was studied?

This study examined whether gut microbiome composition differs in people with biopsy-proven nonalcoholic steatohepatitis (NASH), the more severe, inflammatory form of nonalcoholic fatty liver disease (NAFLD) that can progress to cirrhosis. Researchers characterized microbial diversity and specific genus-level abundances in NASH patients, both with and without cirrhosis, and compared these to healthy controls. They also tested whether the most NASH-associated genus correlated with blood lipid markers such as triglycerides and cholesterol.

Who was studied?

The study included UK patients with biopsy-confirmed NASH, split into those without cirrhosis (n = 40) and those with cirrhosis (n = 25), for a combined NASH group of 65 patients. These were compared against 76 healthy controls. All participants had their gut microbiome composition assessed, alongside fasting lipid measurements in at least some individuals.

What were the most important findings?

NASH patients without cirrhosis showed a 7% lower Shannon alpha diversity than controls, and this dropped further to 14% lower in NASH patients with cirrhosis, indicating progressively reduced microbial diversity with disease severity. Beta diversity (unweighted UniFrac distance) was also significantly reduced in both NASH groups compared to controls. The genus Collinsella was most strongly associated with NASH, rising from 0.29% abundance in controls to 3.45% in NASH without cirrhosis and 4.38% in NASH with cirrhosis. Collinsella abundance was also positively correlated with fasting triglycerides and total cholesterol, and negatively correlated with high-density lipoprotein cholesterol.

What are the greatest implications of this study?

These findings strengthen the case that reduced gut microbial diversity and enrichment of specific proinflammatory taxa, particularly Collinsella, are linked to NASH severity and associated lipid abnormalities. Because Collinsella has previously been tied to obesity and atherosclerosis, its elevation in NASH suggests a potentially shared microbial pathway across these metabolic conditions. This supports gut microbiome composition, and Collinsella abundance specifically, as a candidate biomarker or contributor to NASH pathogenesis worth further mechanistic investigation.

What was studied?

This study examined gut microbiota dysbiosis in Parkinson's disease (PD) using 16S ribosomal RNA gene sequencing. The researchers combined their own dataset with four previously reported datasets from other countries to meta-analyze shared patterns of gut dysbiosis in PD. They also developed a new pathway-analysis method, the Kyoto Encyclopedia of Genes and Genomes orthology set enrichment analysis, to interpret functional changes in the microbiota. The goal was to identify gut dysbiosis signatures in PD that hold across different national populations, since microbiota variability across countries had previously obscured shared findings.

Who was studied?

The primary cohort consisted of 223 patients with PD and 137 controls. This dataset was then meta-analyzed together with four previously published datasets from the United States, Finland, Russia, and Germany. An additional 12 datasets not included in the meta-analysis were used afterward to inspect and cross-check specific bacterial findings.

What were the most important findings?

After adjusting for confounders including body mass index, constipation, sex, age, and catechol-O-methyl transferase inhibitor use, the genera Akkermansia and Catabacter, and the family Akkermansiaceae, were increased in PD, while the genera Roseburia and Faecalibacterium and the family Lachnospiraceae ND3007 group were decreased. Catechol-O-methyl transferase inhibitor intake was separately associated with a marked increase in the family Lactobacillaceae. Checking these results against 12 additional independent datasets confirmed that the increase in Akkermansia was a consistent finding.

What are the greatest implications of this study?

By combining datasets across the United States, Finland, Russia, Germany, and the authors' own cohort, the study identifies gut dysbiosis features in PD that are shared across countries rather than population-specific artifacts. The consistent increase in Akkermansia and Akkermansiaceae, alongside depletion of short-chain-fatty-acid-associated taxa like Roseburia and Faecalibacterium, points to reproducible microbial targets for further mechanistic study in PD. The finding that a PD medication itself alters the microbiome (increasing Lactobacillaceae) also underscores the need to account for medication effects when interpreting gut-brain axis research in PD.

What was studied?

This pilot study examined whether gut microbiome disturbances, gut barrier dysfunction, bacterial translocation, and resulting inflammation are associated with cognitive dysfunction in dementia. Researchers assessed gut microbiome composition, gut barrier integrity, bacterial translocation markers, and inflammatory markers using stool and serum samples. Microbiome composition was profiled through 16S rRNA sequencing, with analysis performed using QIIME 2 and Calypso 7.14 tools. Nutritional status and medication use were also documented to characterize the study population.

Who was studied?

The study included 23 patients with dementia and 18 age and sex matched controls without cognitive impairment. Nutritional status was assessed in participants using the Mini Nutritional Assessment Short Form (MNA-SF). Detailed information on drug use was also collected from the cohort. This was a relatively small, matched case control pilot study rather than a large population based investigation.

What were the most important findings?

Dementia was associated with dysbiosis, reflected in differences in beta diversity and shifts in taxonomic composition of the gut microbiome compared to controls. Gut permeability was increased in dementia patients, as shown by elevated serum diamine oxidase (DAO) levels. Systemic inflammation was also confirmed, evidenced by increased soluble cluster of differentiation 14 levels. The abstract does not report findings specific to Faecalibacterium prausnitzii, butyrate, or anti-inflammatory commensals.

What are the greatest implications of this study?

These findings support the hypothesis that gut microbiome disturbances, impaired gut barrier function, and resulting systemic inflammation may contribute to cognitive dysfunction in dementia. The results suggest a potential gut-brain axis mechanism linking dysbiosis and barrier dysfunction to the inflammatory processes implicated in cognitive decline. As a pilot study with a modest sample size, these findings point toward the need for larger studies to confirm causal relationships and explore microbiome-targeted interventions for dementia.

What was studied?

We report on a comprehensive analysis of the gut microbiomes of patients with gastrointestinal (GI) cancer receiving anti-PD-1/PD-L1 treatment. The human gut microbiota has been associated with clinical responses to anti-PD-1/PD-L1 immunotherapy in melanoma, non-small cell lung cancer, and renal cell carcinoma. We aimed to investigate this association in GI cancers. We also identified bacterial taxa with patient stratification potential. We recruited 74 patients with advanced-stage GI cancer receiving anti-PD-1/PD-L1 treatment and collected their fecal samples prior to and during immunotherapy, along with clinical evaluations. Our 16S rRNA taxonomy survey on the fecal samples revealed an elevation of the Prevotella/Bacteroides ratio in patients, with a preferred response to anti-PD-1/PD-L1 treatment, and a particular subgroup of responders harboring a significantly higher abundance of Prevotella, Ruminococcaceae, and Lachnospiraceae The shotgun metagenomes of the same samples showed that patients exhibiting different responses had differential abundance of pathways related to nucleoside and nucleotide biosynthesis, lipid biosynthesis, sugar metabolism, and fermentation to short-chain fatty acids (SCFA). Gut bacteria that were capable of SCFA production, including Eubacterium, Lactobacillus, and Streptococcus, were positively associated with anti-PD-1/PD-L1 response across different GI cancer types. We further demonstrated that the identified bacterial taxa were predictive of patient stratification in both our cohort and melanoma patients from two previously published studies. Our results thus highlight the impact of gut microbiomes on anti-PD-1/PD-L1 outcomes, at least in a subset of patients with GI cancer, and suggest the potential of the microbiome as a marker for immune-checkpoint blockade responses.See articles by Tomita et al., p. 1236, and Hakozaki et al., p. 1243.

What was studied?

This study investigated whether BDB, a natural bromophenol isolated from the marine red alga Rhodomela confervoides, could alleviate type 2 diabetes mellitus (T2DM) by modulating the gut microbiota. Researchers used 16S rRNA gene pyrosequencing of the V3-V4 regions along with metagenomic analysis to characterize microbial community changes during BDB treatment. The study compared BDB against metformin, a standard antidiabetic drug, and a vehicle control to assess effects on fasting blood glucose and gut microbial composition.

Who was studied?

The study used 24 diabetic BKS db mice, randomly assigned in a blinded manner to receive BDB (n = 6), metformin (n = 6), or vehicle (n = 6) for seven weeks. Non-diabetic BKS mice (n = 6) served as a normal control group. This was an animal model study, not a human cohort.

What were the most important findings?

Diabetic mice treated with BDB or metformin showed significant reductions in fasting blood glucose by the seventh week compared with vehicle-treated diabetic mice. Gut microbiota analysis revealed that short-chain fatty acid (SCFA) producing bacteria, including Lachnospiraceae and Bacteroides, were significantly more abundant in the BDB and metformin groups than in the vehicle group. Notably, Akkermansia was significantly elevated at the genus level in the BDB-treatment group specifically. No sulfate-reducing bacteria, Desulfovibrio, hydrogen sulfide, or sulfur metabolism findings were reported in this abstract.

What are the greatest implications of this study?

These findings suggest that BDB's antidiabetic effects in this mouse model may be linked to favorable shifts in gut microbiota composition, particularly increases in SCFA-producing bacteria and Akkermansia. This positions BDB as a candidate natural compound worth further investigation for T2DM management through a gut-microbiota-mediated mechanism. The metagenomic data point toward specific microbial pathways that could be explored in future mechanistic and translational studies.

What was studied?

Association studies have linked microbiome alterations with many human diseases. However, they have not always reported consistent results, thereby necessitating cross-study comparisons. Here, a meta-analysis of eight geographically and technically diverse fecal shotgun metagenomic studies of colorectal cancer (CRC, n = 768), which was controlled for several confounders, identified a core set of 29 species significantly enriched in CRC metagenomes (false discovery rate (FDR) < 1 × 10-5). CRC signatures derived from single studies maintained their accuracy in other studies. By training on multiple studies, we improved detection accuracy and disease specificity for CRC. Functional analysis of CRC metagenomes revealed enriched protein and mucin catabolism genes and depleted carbohydrate degradation genes. Moreover, we inferred elevated production of secondary bile acids from CRC metagenomes, suggesting a metabolic link between cancer-associated gut microbes and a fat- and meat-rich diet. Through extensive validations, this meta-analysis firmly establishes globally generalizable, predictive taxonomic and functional microbiome CRC signatures as a basis for future diagnostics.

What was studied?

This study investigated whether Gegen Qinlian decoction (GQD), a traditional Chinese medicine formula already used for ulcerative colitis and type 2 diabetes, could enhance the effectiveness of anti-PD-1 immunotherapy in microsatellite stable (MSS) colorectal cancer. MSS tumors make up most colorectal cancer cases and typically do not respond to PD-1 blockade alone. The researchers combined GQD with anti-mouse PD-1 antibody and evaluated tumor growth, gut microbiota composition, and metabolomic changes. Systemic pharmacology methods were also used to map the multiple targets and pathways through which GQD may act.

Who was studied?

The study used a CT26 xenograft mouse model of colorectal cancer, meaning the findings come from an animal model rather than human patients. The abstract does not specify the number of mice used or additional cohort details. Gut microbiota and metabolomic analyses were performed on samples from these tumor-bearing mice.

What were the most important findings?

Combination therapy with GQD and anti-PD-1 potently inhibited CT26 tumor growth compared to other conditions tested. Gut microbiota analysis showed the combination significantly enriched Bacteroides acidifaciens and an uncultured organism within the Bacteroidales S24-7 group. Metabolomic analysis revealed profoundly altered metabolites in the combination group, with glycerophospholipid metabolism and sphingolipid metabolism identified as key affected signaling pathways. The abstract does not mention Desulfovibrio, sulfate-reducing bacteria, or sulfur metabolism as part of these findings.

What are the greatest implications of this study?

These results suggest that a classical herbal formula can convert an immunologically unresponsive tumor type into one that benefits from checkpoint blockade, by remodeling both the gut microbiota and the tumor microenvironment. The identification of specific bacterial taxa and lipid metabolic pathways offers potential mechanistic targets for future combination immunotherapy strategies. Because this work was conducted in a mouse xenograft model, further studies would be needed to determine whether GQD combined with PD-1 blockade produces similar benefits in human MSS colorectal cancer patients.

What was studied?

To investigate whether patients with refractory epilepsy and healthy infants differ in gut microbiota (GM), and how ketogenic diet (KD) alters GM.

Who was studied?

A total of 14 epileptic and 30 healthy infants were recruited and seizure frequencies were recorded. Stool samples were collected for 16S rDNA sequencing using the Illumina Miseq platform. The composition of GM in each sample was analyzed with MOTHUR, and inter-group comparison was conducted by R software.

What were the most important findings?

After being on KD treatment for a week, 64% of epileptic infants showed an obvious improvement, with a 50% decrease in seizure frequency. GM structure in epileptic infants (P1 group) differed dramatically from that in healthy infants (Health group). Proteobacteria, which had accumulated significantly in the P1 group, decreased dramatically after KD treatment (P2 group). Cronobacter predominated in the P1 group and remained at a low level both in the Health and P2 groups. Bacteroides increased significantly in the P2 group, in which Prevotella and Bifidobacterium also grew in numbers and kept increasing.

What are the greatest implications of this study?

GM pattern in healthy infants differed dramatically from that of the epileptic group. KD could significantly modify symptoms of epilepsy and reshape the GM of epileptic infants.