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Frontiers in Cellular and Infection... 2023Recent studies have suggested a relationship between gut microbiota and non-alcoholic fatty liver disease (NAFLD)/nonalcoholic steatohepatitis (NASH). However, the...
BACKGROUND
Recent studies have suggested a relationship between gut microbiota and non-alcoholic fatty liver disease (NAFLD)/nonalcoholic steatohepatitis (NASH). However, the nature and direction of this potential causal relationship are still unclear. This study used two-sample Mendelian randomization (MR) to clarify the potential causal links.
METHODS
Summary-level Genome-Wide Association Studies (GWAS) statistical data for gut microbiota and NAFLD/NASH were obtained from MiBioGen and FinnGen respectively. The MR analyses were performed mainly using the inverse-variance weighted (IVW) method, with sensitivity analyses conducted to verify the robustness. Additionally, reverse MR analyses were performed to examine any potential reverse causal associations.
RESULTS
Our analysis, primarily based on the IVW method, strongly supports the existence of causal relationships between four microbial taxa and NAFLD, and four taxa with NASH. Specifically, associations were observed between Enterobacteriales ( =0.04), ( =0.04), ( =0.02), and ( =0.04) and increased risk of NAFLD. ( =0.03) and ( =0.04) could increase the risks of NASH while ( =0.04) and (=0.005) could decrease them. We also identified that NAFLD was found to potentially cause an increased abundance in ( =0.007) and ( =0.002). However, we found no evidence of reverse causation in the microbial taxa associations with NASH.
CONCLUSION
This study identified several specific gut microbiota that are causally related to NAFLD and NASH. Observations herein may provide promising theoretical groundwork for potential prevention and treatment strategies for NAFLD and its progression to NASH in future.
Topics: Humans; Non-alcoholic Fatty Liver Disease; Gastrointestinal Microbiome; Genome-Wide Association Study; Mendelian Randomization Analysis; Clostridiaceae; Clostridiales
PubMed: 38106475
DOI: 10.3389/fcimb.2023.1294826 -
Frontiers in Cellular and Infection... 2023Insomnia is the second most common mental health issue, also is a social and financial burden. Insomnia affects the balance between sleep, the immune system, and the...
INTRODUCTION
Insomnia is the second most common mental health issue, also is a social and financial burden. Insomnia affects the balance between sleep, the immune system, and the central nervous system, which may raise the risk of different systemic disorders. The gut microbiota, referred to as the "second genome," has the ability to control host homeostasis. It has been discovered that disruption of the gut-brain axis is linked to insomnia.
METHODS
In this study, we conducted MR analysis between large-scale GWAS data of GMs and insomnia to uncover potential associations.
RESULTS
Ten GM taxa were detected to have causal associations with insomnia. Among them, class , genus , genus , genus , genus , and order were linked to a higher risk of insomnia. In reverse MR analysis, we discovered a causal link between insomnia and six other GM taxa.
CONCLUSION
It suggested that the relationship between insomnia and intestinal flora was convoluted. Our findings may offer beneficial biomarkers for disease development and prospective candidate treatment targets for insomnia.
Topics: Humans; Gastrointestinal Microbiome; Sleep Initiation and Maintenance Disorders; Mendelian Randomization Analysis; Central Nervous System; Clostridiaceae; Genome-Wide Association Study
PubMed: 38089822
DOI: 10.3389/fcimb.2023.1296417 -
Frontiers in Endocrinology 2023The risk of developing micro- and macrovascular complications is higher for individuals with type 1 diabetes (T1D). Numerous studies have indicated variations in gut...
OBJECTIVE
The risk of developing micro- and macrovascular complications is higher for individuals with type 1 diabetes (T1D). Numerous studies have indicated variations in gut microbial composition between healthy individuals and those with T1D. These changes in the gut ecosystem may lead to inflammation, modifications in intestinal permeability, and alterations in metabolites. Such effects can collectively impact the metabolic regulation system, thereby influencing blood glucose control. This review aims to explore the relationship between the gut microbiome, inflammation, and blood glucose parameters in patients with T1D.
METHODS
Google Scholar, PubMed, and Web of Science were systematically searched from 2003 to 2023 using the following keywords: "gut microbiota," "gut microbiome," "bacteria," "T1D," "type 1 diabetes," "autoimmune diabetes," "glycemic control," "glucose control," "HbA1c," "inflammation," "inflammatory," and "cytokine." The examination has shown 18,680 articles with relevant keywords. After the exclusion of irrelevant articles, seven observational papers showed a distinct gut microbial signature in T1D patients.
RESULTS
This review shows that, in T1D patients, HbA1c level was negatively correlated with abundance of , , and and positively correlated with abundance of , , , and . Instead, was negatively correlated with fasting blood glucose. In addition, there was a positive correlation between and time in range. Furthermore, a positive correlation between inflammatory parameters and gut dysbiosis was revealed in T1D patients.
CONCLUSION
We draw the conclusion that the gut microbiome profiles of T1D patients and healthy controls differ. Patients with T1D may experience leaky gut, bacterial translocation, inflammation, and poor glucose management due to microbiome dysbiosis. Direct manipulation of the gut microbiome in humans and its effects on gut permeability and glycemic control, however, have not been thoroughly investigated. Future research should therefore thoroughly examine other potential pathophysiological mechanisms in larger studies.
Topics: Humans; Blood Glucose; Diabetes Mellitus, Type 1; Dysbiosis; Gastrointestinal Microbiome; Glycated Hemoglobin; Glycemic Control; Inflammation
PubMed: 38034007
DOI: 10.3389/fendo.2023.1265696 -
Frontiers in Microbiology 2023Obesity-related metabolic diseases such as type 2 diabetes (T2D) are major global health issues, affecting hundreds of millions of people worldwide. The underlying...
Obesity-related metabolic diseases such as type 2 diabetes (T2D) are major global health issues, affecting hundreds of millions of people worldwide. The underlying factors are both diverse and complex, incorporating biological as well as cultural considerations. A role for ethnicity - a measure of self-perceived cultural affiliation which encompasses diet, lifestyle and genetic components - in susceptibility to metabolic diseases such as T2D is well established. For example, Asian populations may be disproportionally affected by the adverse 'TOFI' (Thin on the Outside, Fat on the Inside) profile, whereby outwardly lean individuals have increased susceptibility due to excess visceral and ectopic organ fat deposition. A potential link between the gut microbiota and metabolic disease has more recently come under consideration, yet our understanding of the interplay between ethnicity, the microbiota and T2D remains incomplete. We present here a 16S rRNA gene-based comparison of the fecal microbiota of European-ancestry and Chinese-ancestry cohorts with overweight and prediabetes, residing in New Zealand. The cohorts were matched for mean fasting plasma glucose (FPG: mean ± SD, European-ancestry: 6.1 ± 0.4; Chinese-ancestry: 6.0 ± 0.4 mmol/L), a consequence of which was a significantly higher mean body mass index in the European group (BMI: European-ancestry: 37.4 ± 6.8; Chinese-ancestry: 27.7 ± 4.0 kg/m; < 0.001). Our findings reveal significant microbiota differences between the two ethnicities, though we cannot determine the underpinning factors. In both cohorts was by far the dominant bacterial phylum (European-ancestry: 93.4 ± 5.5%; Chinese-ancestry: 79.6 ± 10.4% of 16S rRNA gene sequences), with and the next most abundant. Among the more abundant (≥1% overall relative sequence abundance) genus-level taxa, four zero-radius operational taxonomic units (zOTUs) were significantly higher in the European-ancestry cohort, namely members of the , , and genera. Differential abundance analysis further identified a number of additional zOTUs to be disproportionately overrepresented across the two ethnicities, with the majority of taxa exhibiting a higher abundance in the Chinese-ancestry cohort. Our findings underscore a potential influence of ethnicity on gut microbiota composition in the context of individuals with overweight and prediabetes.
PubMed: 38033566
DOI: 10.3389/fmicb.2023.1244179 -
Translational Animal Science 2023is the most pathogenic blood-feeding parasitic in sheep, causing anemia and consequently changes in the color of the ocular conjunctiva, from the deep red of healthy...
is the most pathogenic blood-feeding parasitic in sheep, causing anemia and consequently changes in the color of the ocular conjunctiva, from the deep red of healthy sheep to shades of pink to practically white of non-healthy sheep. In this context, the Famacha method has been created for detecting sheep unable to cope with the infection by , through visual assessment of ocular conjunctiva coloration. Thus, the objectives of this study were (1) to extract ocular conjunctiva image features to automatically classify Famacha score and compare two classification models (multinomial logistic regression-MLR and random forest-RF) and (2) to evaluate the applicability of the best classification model on three sheep farms. The dataset consisted of 1,156 ocular conjunctiva images from 422 animals. RF model was used to segment the images, i.e., to select the pixels that belong to the ocular conjunctiva. After segmentation, the quantiles (1%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, and 99%) of color intensity in each image channel (red, blue, and green) were determined and used as explanatory variables in the classification models, and the Famacha scores 1 (non-anemic) to 5 (severely anemic) were the target classes to be predicted (scores 1 to 5, with 162, 255, 443, 266, and 30 images, respectively). For objective 1, the performance metrics (precision and sensitivity) were obtained using MLR and RF models considering data from all farms randomly split. For objective 2, a leave-one-farm-out cross-validation technique was used to assess prediction quality across three farms (farms A, B, and C, with 726, 205, and 225 images, respectively). The RF provided the best performances in predicting anemic animals, as indicated by the high values of sensitivity for Famacha score 3 (80.9%), 4 (46.2%), and 5 (60%) compared to the MLR model. The precision of the RF was 72.7% for Famacha score 1 and 62.5% for Famacha score 2. These results indicate that is possible to successfully predict Famacha score, especially for scores 2 to 4, in sheep via image analysis and RF model using ocular conjunctiva images collected in farm conditions. As expected, model validation excluding entire farms in cross-validation presented a lower prediction quality. Nonetheless, this setup is closer to reality because the developed models are supposed to be used across farms, including new ones, and with different environments and management conditions.
PubMed: 38023419
DOI: 10.1093/tas/txad118 -
Frontiers in Immunology 2023Nicotine dependence is a key factor influencing the diversity of gut microbiota, and targeting gut microbiota may become a new approach for the prevention and treatment...
BACKGROUND
Nicotine dependence is a key factor influencing the diversity of gut microbiota, and targeting gut microbiota may become a new approach for the prevention and treatment of nicotine dependence. However, the causal relationship between the two is still unclear. This study aims to investigate the causal relationship between nicotine dependence and gut microbiota.
METHODS
A two-sample bidirectional Mendelian randomization (MR) study was conducted using the largest existing gut microbiota and nicotine dependence genome-wide association studies (GWAS). Causal relationships between genetically predicted nicotine dependence and gut microbiota abundance were examined using inverse variance weighted, MR-Egger, weighted median, simple mode, weighted mode, and MR-PRESSO approaches. Cochrane's Q test, MR-Egger intercept test, and leave-one-out analysis were performed as sensitivity analyses to assess the robustness of the results. Multivariable Mendelian randomization analysis was also conducted to eliminate the interference of smoking-related phenotypes. Reverse Mendelian randomization analysis was then performed to determine the causal relationship between genetically predicted gut microbiota abundance and nicotine dependence.
RESULTS
Genetically predicted nicotine dependence had a causal effect on (β: -0.52, 95% CI: -0.934-0.106, P = 0.014). The group (OR: 1.106, 95% CI: 1.004-1.218), (OR: 1.118, 95% CI: 1.001-1.249) and (OR: 1.08, 95% CI: 1.001-1.167) were risk factors for nicotine dependence. (OR: 0.905, 95% CI: 0.837-0.977), (OR: 0.014, 95% CI: 0.819-0.977), (OR: 0.841, 95% CI. 0.731-0.968), (OR: 0.831, 95% CI: 0.735-0.939) and (OR: 0.838, 95% CI: 0.739-0.951) were protective factor for nicotine dependence. The sensitivity analysis showed consistent results.
CONCLUSION
The Mendelian randomization study confirmed the causal link between genetically predicted risk of nicotine dependence and genetically predicted abundance of gut microbiota. Gut microbiota may serve as a biomarker and offer insights for addressing nicotine dependence.
Topics: Humans; Tobacco Use Disorder; Gastrointestinal Microbiome; Genome-Wide Association Study; Mendelian Randomization Analysis; Smoking; Clostridiales
PubMed: 38022531
DOI: 10.3389/fimmu.2023.1244272 -
Foods (Basel, Switzerland) Nov 2023Constipation is a major health concern worldwide and requires effective and safe treatment options. In this study, we selected ten strains of two species of lactobacilli...
Constipation is a major health concern worldwide and requires effective and safe treatment options. In this study, we selected ten strains of two species of lactobacilli to identify whether they were effective against constipation induced by loperamide administration in BALB/c mice. Monitoring of constipation-related indicators indicated that () mainly acted on the whole intestinal peristalsis to relieve constipation. Furthermore, through the detection of biological, chemical, mechanical, and immune barriers in mice, it was discovered that changed the relative abundance of bacteria related to the levels of acetic acid and 5-hydroxytryptamine (5-HT) (such as by increasing the relative abundance of and , and reducing the relative abundance of , , , and ), increased the concentration of acetic acid in the intestine, which stimulated enterochromaffin cells, promoted 5-HT synthesis in the colon, enhanced intestinal motility, and relieved constipation. In conclusion, this study provides a theoretical foundation for the development of personalized products for the treatment of constipation.
PubMed: 38002233
DOI: 10.3390/foods12224176 -
Toxics Oct 2023This study evaluates the use of mercury (Hg) concentrations in fish muscle tissue to determine a species' trophic position (TP) in its environment. A campaign conducted...
This study evaluates the use of mercury (Hg) concentrations in fish muscle tissue to determine a species' trophic position (TP) in its environment. A campaign conducted in 2019 along 375 km in the middle Araguaia River basin, Brazil, resulted in 239 organisms from 20 species collected. The highest total mercury (THg) concentrations were found in (6.93 µg·g, wet weight) and in (3.18 µg·g, wet weight), whose TPs were different according to the FishBase database. However, they occupied the same trophic level in this study. The intra-specific comparison showed a difference in Hg concentrations between individuals captured in distinct sites. The study of the biota-sediment accumulation factor (BSAF) showed that spatiality interferes with a species' TP. Statistical analyses revealed that when we used a predicted species' TP based on each individual's size, it explained 72% of the variability in THg concentration across all fish species. Multiple regression analysis confirmed that standard length and FishBase values are positively associated with THg (R = 0.943). These results point to Hg as a viable indicator of a fish species' TP since it reflects regional, biological, and environmental factors, as demonstrated here for the middle Araguaia River.
PubMed: 37999538
DOI: 10.3390/toxics11110886 -
Nature Communications Nov 2023The gut microbiota may have an effect on the therapeutic resistance and toxicity of immune checkpoint inhibitors (ICIs). However, the associations between the highly...
The gut microbiota may have an effect on the therapeutic resistance and toxicity of immune checkpoint inhibitors (ICIs). However, the associations between the highly variable genomes of gut bacteria and the effectiveness of ICIs remain unclear, despite the fact that merely a few gene mutations between similar bacterial strains may cause significant phenotypic variations. Here, using datasets from the gut microbiome of 996 patients from seven clinical trials, we systematically identify microbial genomic structural variants (SVs) using SGV-Finder. The associations between SVs and response, progression-free survival, overall survival, and immune-related adverse events are systematically explored by metagenome-wide association analysis and replicated in different cohorts. Associated SVs are located in multiple species, including Akkermansia muciniphila, Dorea formicigenerans, and Bacteroides caccae. We find genes that encode enzymes that participate in glucose metabolism be harbored in these associated regions. This work uncovers a nascent layer of gut microbiome heterogeneity that is correlated with hosts' prognosis following ICI treatment and represents an advance in our knowledge of the intricate relationships between microbiota and tumor immunotherapy.
Topics: Humans; Gastrointestinal Microbiome; Immune Checkpoint Inhibitors; Microbiota; Metagenome; Bacteria; Neoplasms
PubMed: 37973916
DOI: 10.1038/s41467-023-42997-7 -
Nutrients Nov 2023The objective of this study was to examine the correlation between gut microbiota and both age-related macular degeneration (AMD) and glaucoma. Mendelian randomization...
The objective of this study was to examine the correlation between gut microbiota and both age-related macular degeneration (AMD) and glaucoma. Mendelian randomization studies were conducted utilizing the data sourced from the genome-wide association study (GWAS) database for the gut microbiome, AMD, and glaucoma. Single nucleotide polymorphism (SNP) estimates were summarized through five Mendelian randomization (MR) methods. We utilized Cochran's Q statistic to evaluate the heterogeneity of the instrumental variables (IVs). Additionally, we employed a "leave-one-out" approach to verify the stability of our findings. Inverse variance weighted (IVW) suggests that Eubacterium (oxidoreducens group) and Parabacteroides had a protective effect on AMD. Both weighted median and IVW suggest that Lachnospiraceae (NK4A136 group) and Ruminococcaceae (UCG009) had a protective effect on AMD. However, both weighted median and IVW suggest that Dorea had a risk effect on AMD. Similarly, The IVW of Eubacterium (ventriosum group) showed a risk effect on AMD. The weighted median of Eubacterium (nodatum group), Lachnospiraceae (NC2004 group), and Roseburia had a risk effect on glaucoma. IVW suggested that Ruminococcaceae (UCG004) had a risk effect on glaucoma. Reverse MR analysis found a causal link between Eubacterium (nodatum group) and glaucoma. No causal relationships were found between AMD or glaucoma and the other mentioned bacterial groups. No significant heterogeneity or evidence of horizontal pleiotropy was detected. This study found that certain gut bacteria had protective effects on AMD, while others may be risk factors for AMD or glaucoma. Likewise, reverse MR found that glaucoma led to an increased abundance of certain gut bacteria. Further trials are needed to clarify the specific mechanisms involved.
Topics: Humans; Gastrointestinal Microbiome; Genome-Wide Association Study; Mendelian Randomization Analysis; Glaucoma; Macular Degeneration; Clostridiales; Lactobacillales
PubMed: 37960299
DOI: 10.3390/nu15214646