Cross-talks between gut microbiota and tobacco smoking: a two-sample Mendelian randomization study

The gut microbiota-brain axis in neurological disorders

Previous studies have shown a bidirectional communication between human gut microbiota and the brain, known as the microbiota-gut-brain axis (MGBA). The MGBA influences the host's nervous system development, emotional regulation, and cognitive function through neurotransmitters, immune modulation, and metabolic pathways. Factors like diet, lifestyle, genetics, and environment shape the gut microbiota composition together. Most research have explored how gut microbiota regulates host physiology and its potential in preventing and treating neurological disorders. However, the individual heterogeneity of gut microbiota, strains playing a dominant role in neurological diseases, and the interactions of these microbial metabolites with the central/peripheral nervous systems still need exploration. This review summarizes the potential role of gut microbiota in driving neurodevelopmental disorders (autism spectrum disorder and attention deficit/hyperactivity disorder), neurodegenerative diseases (Alzheimer's and Parkinson's disease), and mood disorders (anxiety and depression) in recent years and discusses the current clinical and preclinical gut microbe-based interventions, including dietary intervention, probiotics, prebiotics, and fecal microbiota transplantation. It also puts forward the current insufficient research on gut microbiota in neurological disorders and provides a framework for further research on neurological disorders.

Relationships between the gut microbiome and brain functional alterations in first-episode, drug-naïve patients with major depressive disorder

OBJECTIVE

Increasing evidence has shown that the microbiota-gut-brain axis (MGB) is involved in the mechanism of major depressive disorder (MDD). However, the relationship between the gut microbiome and brain function in MDD patients has not been determined. Here, we intend to identify specific changes in the gut microbiome and brain function in first-episode, drug-naïve MDD patients and then explore the associations between the two omics to elucidate how the MGB axis plays a role in MDD development.

METHODS

We recruited 38 first-episode, drug-naïve MDD patients and 37 healthy controls (HC). The composition of the fecal microbiome and neural spontaneous activity alterations were examined using 16S rRNA gene amplicon sequencing analysis and regional homogeneity (ReHo). Spearman correlation analyses were conducted to assess the associations between the gut microbiome and brain function.

RESULTS

Compared with HC, MDD patients exhibited distinct alterations in the gut microbiota and elevated ReHo in the frontal regions. In the MDD group, a positive relationship was noted between the relative abundance of Blautia and the HAMD-17 and HAMA scores, as well as between the relative abundance of Oxalobacteraceae and the HAMD-17 score. The relative abundances of Porphyromonadaceae and Parabacteroides were negatively correlated with the ReHo values of frontal regions.

LIMITATIONS

Our study utilized a cross-sectional design, and the number of subjects was relatively small.

CONCLUSION

We found that some specific gut microbiomes were associated with frontal function, and others were associated with clinical symptoms in MDD patients, which may support the role of the MGB axis underlying MDD.

Plasma proteins and psoriatic arthritis: a proteome-wide Mendelian randomization study

Background

Previous epidemiological studies have identified a correlation between serum protein levels and Psoriatic Arthritis (PsA). However, the precise nature of this relationship remains uncertain. Therefore, our objective was to assess whether circulating levels of 2,923 plasma proteins are associated with the risk of PsA, utilizing the Mendelian randomization (MR) approach.

Methods

Two-sample MR analysis was performed to assess the causal impact of proteins on PsA risk. Exposure data for plasma proteins were sourced from a genome-wide association study (GWAS) conducted within the UK Biobank Pharma Proteomics Project, which encompassed 2,923 unique plasma proteins. The outcome data for PsA were sourced from the FinnGen study, a large-scale genomics initiative, comprising 3,537 cases and 262,844 controls. Additionally, colocalization analysis, Phenome-wide MR analysis, and candidate drug prediction were employed to identify potential causal circulating proteins and novel drug targets.

Results

We thoroughly assessed the association between 1,837 plasma proteins and PsA risk, identifying seven proteins associated with PsA risk. An inverse association of Interleukin-10 (IL-10) with PsA risk was observed [odds ratio (OR)=0.45, 95% confidence interval (CI), 0.28 to 0.70, P FDR=0.072]. Additionally, Apolipoprotein F (APOF) has a positive effect on PsA risk (OR=2.08, 95% CI, 1.51 to 2.86, P FDR=0.005). Subsequently, we found strong evidence indicating that IL-10 and APOF were colocalized with PsA associations (PP.H4 = 0.834 for IL-10 and PP.H4 = 0.900 for APOF). Phenome-wide association analysis suggested that these two proteins may have dual effects on other clinical traits (P FDR<0.1).

Conclusion

This study identified 7 plasma proteins associated with PsA risk, particularly IL-10 and APOF, which offer new insights into its etiology. Further studies are needed to assess the utility and effectiveness of these candidate proteins.

The Diagnosis of Intestinal Fibrosis in Crohn's Disease-Present and Future

Crohn's disease (CD) progresses with periods of remission and exacerbations. During exacerbations, chronic inflammation leads to tissue destruction. As a result, intestinal fibrosis may develop in response to the ongoing inflammatory process. Fibrosis in CD should be considered the result of the response of the intestinal wall (over) to the presence of inflammation in the deep structures of the intestinal wall. In the absence of ideal noninvasive methods, endoscopic evaluation in combination with biopsy, histopathological analysis, stool analysis, and blood analysis remains the gold standard for assessing both inflammation and fibrosis in CD. On the contrary, the ability to identify markers of intestinal fibrosis would help to develop new diagnostic and therapeutic methods to detect early stages of fibrosis. It is speculated that miRNAs may, in the future, become biomarkers for early noninvasive diagnosis in the treatment of intestinal fibrosis. The purpose of this review is to summarise existing diagnostic methods for Crohn's disease and present recent scientific reports on molecular testing.

Shenfu injection improves isoproterenol-induced heart failure in rats by modulating co-metabolism and regulating the trimethylamine-N-oxide - inflammation axis

Heart failure (HF) is a chronic condition that progressively worsens and continues to be a major financial burden and public health concern. The "gut-heart" axis provides an innovative perspective and therapeutic strategy for preventing and treating heart failure. Shenfu injection (SFI) is a Traditional Chinese Medicine-based treatment demonstrating potential as a therapeutic strategy for heart failure. However, the precise therapeutic mechanisms of SFI in heart failure are not completely characterized. In this study, HF models were established utilizing subcutaneous multipoint injection of isoproterenol (ISO) at a dosage of 5 mg kg-1·d-1 for 7 days. Serum levels of inflammatory biomarkers were quantified using protein microarrays. Rat feces were analyzed using untargeted metabolomics research and 16S rRNA sequencing. The link between gut microbiota and metabolites was examined using a MetOrigin and Spearman correlation analysis. Our results show that Shenfu injection effectively enhances cardiac function in rats with ISO-induced heart failure by potentially modulating pro-/anti-inflammatory imbalance and reducing serum and urine Trimethylamine-N-oxide (TMAO) levels. Moreover, SFI significantly increases the abundance of Bacteroidota at the phylum level, thereby improving disrupted gut microbiota composition. Additionally, SFI supplementation enriches specific genera known for their capacity to produce short-chain fatty acids. SFI was found to be associated with three key metabolic pathways, as revealed by fecal metabonomics analysis, including the pentose phosphate pathway, pyrimidine metabolism, and purine metabolism. Metabolite tracing analysis revealed that Taurine and hypotaurine metabolism was found to be specific to the microbial community. The biosynthesis of Pyrimidine metabolism, Purine metabolism, beta-alanine metabolism, Naphthalene degradation, Pantothenate, and CoA biosynthesis were identified as co-metabolic pathways between microbes and host. The Spearman correlation analysis was also significantly correlated to differentially expressed metabolites regulated by SFI and the gut microbiota. These results suggest that SFI improves ISO-induced heart failure by modulating co-metabolism and regulating the TMAO-inflammation axis.

Metabolic profiling of smoking, associations with type 2 diabetes and interaction with genetic susceptibility

BACKGROUND

Smokers are at increased risk of type 2 diabetes (T2D), but the underlying mechanisms are unclear. We investigated if the smoking-T2D association is mediated by alterations in the metabolome and assessed potential interaction with genetic susceptibility to diabetes or insulin resistance.

METHODS

In UK Biobank (n = 93,722), cross-sectional analyses identified 208 metabolites associated with smoking, of which 131 were confirmed in Mendelian Randomization analyses, including glycoprotein acetyls, fatty acids, and lipids. Elastic net regression was applied to create a smoking-related metabolic signature. We estimated hazard ratios (HR) of incident T2D in relation to baseline smoking/metabolic signature and calculated the proportion of the smoking-T2D association mediated by the signature. Additive interaction between the signature and genetic risk scores for T2D (GRS-T2D) and insulin resistance (GRS-IR) on incidence of T2D was assessed as relative excess risk due to interaction (RERI).

FINDINGS

The HR of T2D was 1·73 (95% confidence interval (CI) 1·54 - 1·94) for current versus never smoking, and 38·3% of the excess risk was mediated by the metabolic signature. The metabolic signature and its mediation role were replicated in TwinGene. The metabolic signature was associated with T2D (HR: 1·61, CI 1·46 - 1·77 for values above vs. below median), with evidence of interaction with GRS-T2D (RERI: 0·81, CI: 0·23 - 1·38) and GRS-IR (RERI 0·47, CI: 0·02 - 0·92).

INTERPRETATION

The increased risk of T2D in smokers may be mediated through effects on the metabolome, and the influence of such metabolic alterations on diabetes risk may be amplified in individuals with genetic susceptibility to T2D or insulin resistance.

Correlation between cigarette smoking and alcohol consumption and Rosacea: A two-sample Mendelian randomization study

BACKGROUND

Controversy persists regarding the causal relationship between Cigarette smoking, alcohol consumption, and Rosacea. This paper employs the Mendelian randomization (MR) method to elucidate the correlation between Cigarette smoking, alcohol consumption, and Rosacea. The aim is to contribute valuable insights to aid in the prevention and early treatment of Rosacea.

METHOD

Summary datasets for cigarette smoking parameters (Cigarettes smoked per day, Smoking status: Previous, smoking status: Current) and alcohol consumption (Alcoholic drinks per week) were selected alongside data for Rosacea from genome-wide association studies (GWAS). The Two-sample MR method was employed to analyze the correlation between cigarette smoking, alcohol consumption, and Rosacea. Various MR analysis methods, including inverse variance weighting (IVW), MR-Egger, Simple Mode, Weighted Mode, and Weighted Median, were chosen. IVW served as the primary analysis method.

RESULTS

The results indicate a significant negative association between Cigarettes smoked per day and Rosacea. Moreover, a significant positive correlation was observed between Smoking status: Previous and Rosacea. However, no significant associations were found between Smoking status: Current, Alcoholic drinks per week, and Rosacea.

CONCLUSION

This study provides further clarity on the association between cigarette smoking, drinking, and Rosacea through a two-sample MR analysis. Notably, the number of cigarettes smoked per day appears to be associated with a reduced incidence of Rosacea, while cigarette smoking cessation may increase the risk. Surprisingly, alcohol consumption does not emerge as a significant risk factor for Rosacea. These findings contribute to a nuanced understanding of the complex relationship between lifestyle factors and the occurrence of Rosacea, offering potential insights for preventive measures and early intervention.

Microbiome interactions with different risk factors in development of myocardial infarction

Among all non-communicable diseases, Cardiovascular Diseases (CVDs) stand as the leading global cause of mortality. Within this spectrum, Myocardial Infarction (MI) strikingly accounts for over 15 % of all deaths. The intricate web of risk factors for MI, comprising family history, tobacco use, oral health, hypertension, nutritional pattern, and microbial infections, is firmly influenced by the human gut and oral microbiota, their diversity, richness, and dysbiosis, along with their respective metabolites. Host genetic factors, especially allelic variations in signaling and inflammatory markers, greatly affect the progression or severity of the disease. Despite the established significance of the human microbiome-nutrient-metabolite interplay in associations with CVDs, the unexplored terrain of the gut-heart-oral axis has risen as a critical knowledge gap. Moreover, the pivotal role of the microbiome and the complex interplay with host genetics, compounded by age-related changes, emerges as an area of vital importance in the development of MI. In addition, a distinctive disease susceptibility and severity influenced by gender-based or ancestral differences, adds a crucial insights to the association with increased mortality. Here, we aimed to provide an overview on interactions of microbiome (oral and gut) with major risk factors (tobacco use, alcohol consumption, diet, hypertension host genetics, gender, and aging) in the development of MI and therapeutic regulation.

Causal relationships between interleukins, interferons and COVID-19 risk: a Mendelian randomization study

Observational studies have shown close associations between COVID-19 risk and cytokines, especially interleukins (ILs) and interferons (IFNs). However, the causal relationships between ILs, IFNs and COVID-19 were still unclear. To resolve the problem, we conducted a Mendelian randomization analysis between COVID-19 and 47 cytokines, including 35 ILs and 12 IFNs. First, three methods were applied to estimate causal effects by using single nucleotide polymorphisms as instrumental variables (IVs). Subsequently, the MR-Egger method was used to estimate the horizontal pleiotropy of IVs. Finally, sensitivity analyses were applied to assess the robustness of results. As a result, one IFN (IFN-W1) and five ILs (IL-5, IL-6, IL-13, IL-16 and IL-37) were identified to significantly decrease the COVID-19 risk. In contrast, one IFN (IFNG) and five ILs (IL-3, IL-8, IL-27, IL-31 and IL-36β) were found to be significantly associated with an increased risk of COVID-19. In summary, the findings of this study provide insights into potential therapeutic interventions for COVID-19.

Multi-omics-based investigation of Bifidobacterium's inhibitory effect on glioma: regulation of tumor and gut microbiota, and MEK/ERK cascade

Glioma, the most prevalent primary tumor of the central nervous system, is characterized by a poor prognosis and a high recurrence rate. The interplay between microbes, such as gut and tumor microbiota, and the host has underscored the significant impact of microorganisms on disease progression. Bifidobacterium, a beneficial bacterial strain found in the human and animal intestines, exhibits inhibitory effects against various diseases. However, the existing body of evidence pertaining to the influence of Bifidobacterium on glioma remains insufficient. Here, we found that Bifidobacterium reduces tumor volume and prolongs survival time in an orthotopic mouse model of glioma. Experiments elucidated that Bifidobacterium suppresses the MEK/ERK cascade. Additionally, we noted an increase in the α-diversity of the tumor microbiota, along with an augmented relative abundance of Bifidobacterium in the gut microbiota. This rise in Bifidobacterium levels within the intestine may be attributed to a concurrent increase in Bifidobacterium within the glioma. Additionally, Bifidobacterium induced alterations in serum metabolites, particularly those comprised of organonitrogen compounds. Thus, our findings showed that Bifidobacterium can suppress glioma growth by inhibiting the MEK/ERK cascade and regulating tumor, and gut microbiota, and serum metabolites in mice, indicating the promising therapeutic prospects of Bifidobacterium against glioma.

Exploring the gut microbiota and its potential as a biomarker in gliomas

Gut microbiome alterations are associated with various cancers including brain tumours such as glioma and glioblastoma. The gut communicates with the brain via a bidirectional pathway known as the gut-brain axis (GBA) which is essential for maintaining homeostasis. The gut microbiota produces many metabolites including short chain fatty acids (SCFAs) and essential amino acids such as glutamate, glutamine, arginine and tryptophan. Through the modulation of these metabolites the gut microbiome is able to regulate several functions of brain cells, immune cells and tumour cells including DNA methylation, mitochondrial function, the aryl hydrocarbon receptor (AhR), T-cell proliferation, autophagy and even apoptosis. Here, we summarise current findings on gut microbiome with respect to brain cancers, an area of research that is widely overlooked. Several studies investigated the relationship between gut microbiota and brain tumours. However, it remains unclear whether the gut microbiome variation is a cause or product of cancer. Subsequently, a biomarker panel was constructed for use as a predictive, prognostic and diagnostic tool with respect to multiple cancers including glioma and glioblastoma multiforme (GBM). This review further presents the intratumoural microbiome, a fascinating microenvironment within the tumour as a possible treatment target that can be manipulated to maximise effectiveness of treatment via personalised therapy. Studies utilising the microbiome as a biomarker and therapeutic strategy are necessary to accurately assess the effectiveness of the gut microbiome as a clinical tool with respect to brain cancers.

Gut microbiota connects the brain and the heart: potential mechanisms and clinical implications

Nowadays, high morbidity and mortality of cardiovascular diseases (CVDs) and high comorbidity rate of neuropsychiatric disorders contribute to global burden of health and economics. Consequently, a discipline concerning abnormal connections between the brain and the heart and the resulting disease states, known as psychocardiology, has garnered interest among researchers. However, identifying a common pathway that physicians can modulate remains a challenge. Gut microbiota, a constituent part of the human intestinal ecosystem, is likely involved in mutual mechanism CVDs and neuropsychiatric disorder share, which could be a potential target of interventions in psychocardiology. This review aimed to discuss complex interactions from the perspectives of microbial and intestinal dysfunction, behavioral factors, and pathophysiological changes and to present possible approaches to regulating gut microbiota, both of which are future directions in psychocardiology.

Association between gut microbiota and Hirschsprung disease: a bidirectional two-sample Mendelian randomization study

Background

Several studies have pointed to the critical role of gut microbiota (GM) and their metabolites in Hirschsprung disease (HSCR) pathogenesis. However, the detailed causal relationship between GM and HSCR remains unknown.

Methods

In this study, we used two-sample Mendelian randomization (MR) analysis to investigate the causal relationship between GM and HSCR, based on the MiBioGen Consortium's genome-wide association study (GWAS) and the GWAS Catalog's HSCR data. Reverse MR analysis was performed subsequently, and the sensitivity analysis, Cochran's Q-test, MR pleiotropy residual sum, outlier (MR-PRESSO), and the MR-Egger intercept were used to analyze heterogeneity or horizontal pleiotropy. 16S rDNA sequencing and targeted mass spectrometry were developed for initial validation.

Results

In the forward MR analysis, inverse-variance weighted (IVW) estimates suggested that Eggerthella (OR: 2.66, 95%CI: 1.23-5.74, p = 0.01) was a risk factor for HSCR, while Peptococcus (OR: 0.37, 95%CI: 0.18-0.73, p = 0.004), Ruminococcus2 (OR: 0.32, 95%CI: 0.11-0.91, p = 0.03), Clostridiaceae1 (OR: 0.22, 95%CI: 0.06-0.78, p = 0.02), Mollicutes RF9 (OR: 0.27, 95%CI: 0.09-0.8, p = 0.02), Ruminococcaceae (OR: 0.16, 95%CI: 0.04-0.66, p = 0.01), and Paraprevotella (OR: 0.45, 95%CI: 0.21-0.98, p = 0.04) were protective factors for HSCR, which had no heterogeneity or horizontal pleiotropy. However, reverse MR analysis showed that HSCR (OR: 1.02, 95%CI: 1-1.03, p = 0.049) is the risk factor for Eggerthella. Furthermore, some of the above microbiota and short-chain fatty acids (SCFAs) were altered in HSCR, showing a correlation.

Conclusion

Our analysis established the relationship between specific GM and HSCR, identifying specific bacteria as protective or risk factors. Significant microbiota and SCFAs were altered in HSCR, underlining the importance of further study and providing new insights into the pathogenesis and treatment.

The Role of the Gut-Joint Axis in the Care of Psoriatic Arthritis: A Two-Sample Bidirectional Mendelian Randomization Study

INTRODUCTION

Observational studies and clinical trials have supported the association between gut microbiota and psoriatic arthritis. However, the causal link between gut microbiota and psoriatic arthritis is still unclear.

METHODS

A two-sample bi-directional Mendelian randomization analysis was performed using the summary statistics of gut microbiota from the largest available genome-wide association study meta-analysis (n = 13,266) conducted by the MiBioGen consortium. The summary statistics of psoriatic arthritis were extracted directly from the FinnGen consortium, which consists of 3186 psoriatic arthritis patients and 24,086 controls. Sensitivity analyses were conducted to assess the validity of our findings. Enrichment analyses were used to investigate the biofunction and pathways.

RESULTS

Inverse variance weighted (IVW) estimates suggested that family Rikenellaceae (P = 0.032) and genus Ruminococcaceae UCG011 (P = 0.014) had a detrimental effect on psoriatic arthritis. We also noticed the negative association between the class Methanobacteria (P = 0.032), order Methanobacteriales (P = 0.032), family Methanobacteriaceae (P = 0.032), genus Eubacterium fissicatena group (P = 0.010), genus Methanobrevibacter (P = 0.031), and genus Butyricicoccus (P = 0.041) with psoriatic arthritis. Sensitivity analyses showed that genus Butyricicoccus had pleiotropy and heterogeneity. According to the results of reverse MR analysis, the causal effect of psoriatic arthritis was found on six taxa, respectivelyc family Clostridiaceae1, family Defluviitaleaceae, genus Butyrivibrio, genus Defluviitaleaceae UCG011, genus Clostridium sensu stricto1, and genus Ruminococcaceae UCG011.

CONCLUSION

This two-sample bidirectional Mendelian randomization analysis suggested that the gut microbiota had a causal effect on psoriatic arthritis and implied the potential role of probiotics in the management and prevention of psoriatic arthritis.

Causal relationship between gut microbiota and myasthenia gravis: a two-sample Mendelian randomization study

Background

Previous observational studies have provided cumulative data linking gut microbiota to myasthenia gravis (MG). However, the causal link between the two remains unexplored. Hence, the current study was performed to explore the causal link between them.

Methods

Mendelian randomization (MR) analysis was conducted using the summary statistics of 211 gut microbiota taxa and the largest genome-wide association studies (GWAS) for MG currently available. The inverse variance-weighted (IVW), MR-Egger, weighted median, and weighted mode methods were employed to ascertain the causal influence. Sensitivity studies utilizing several methodologies were then used to assess the robustness of the findings. Lastly, to evaluate reverse causality, a reverse MR analysis was performed.

Results

Seven suggestive causal associations between the gastrointestinal microbiota and MG were identified based on the outcomes of the MR analysis. Specifically, phylum Actinobacteria (OR: 0.602, 95% CI: 0.405-0.896, p = 0.012), class Gammaproteobacteria (OR: 0.587, 95% CI: 0.357-0.968, p = 0.037), and families Defluviitaleaceae (OR: 0.695, 95% CI: 0.485-0.996, p = 0.047), Family XIII (OR: 0.614, 95% CI: 0.412-0.916, p = 0.017), and Peptococcaceae (OR: 0.698, 95% CI: 0.505-0.964, p = 0.029) had suggestive protective effects on MG, while order Mollicutes RF9 (OR: 1.424, 95% CI: 1.015-1.998, p = 0.041) and genus Faecalibacterium (OR: 1.763, 95% CI: 1.220-2.547, p = 0.003) were suggestive risk factors for MG. The outcomes indicate that neither heterogeneity nor horizontal pleiotropy had any discernible impact. Nevertheless, this reverse analysis did not reveal any apparent effect of MG on the gut microbiota composition.

Conclusion

The MR investigation has substantiated the suggestive causal connection between gut microbiota and MG, which may provide helpful insights for innovative therapeutic and preventative approaches for MG. Further randomized controlled trials are needed to elucidate the gut microbiota's precise role and therapeutic potential in the pathogenesis of MG.

Modulation of the Gut Microbiota by Nutrition and Its Relationship to Epigenetics

The intestinal microbiota is a community of microorganisms inhabiting the human intestines, potentially influencing both physiological and pathophysiological processes in the human body. Existing evidence suggests that nutrients can influence the modulation of the gut microbiota. However, there is still limited evidence regarding the effects of vitamin and mineral supplementation on the human gut microbiota through epigenetic modification. It is plausible that maintaining an adequate dietary intake of vitamin D, iron, fibre, zinc and magnesium may have a beneficial effect on alleviating inflammation in the body, reducing oxidative stress, and improving the condition of the intestinal microbiota through various epigenetic mechanisms. Moreover, epigenetics involves alterations in the phenotype of a cell without changing its fundamental DNA sequence. It appears that the modulation of the microbiota by various nutrients may lead to epigenetic regulation. The correlations between microbiota and epigenetics are potentially interdependent. Therefore, the primary objective of this review is to identify the complex relationships between diet, gut microbiota, and epigenetic regulation. These interactions could play a crucial role in systemic health.

Advancing lifelong precision medicine for cardiovascular diseases through gut microbiota modulation

The gut microbiome is known as the tenth system of the human body that plays a vital role in the intersection between health and disease. The considerable inter-individual variability in gut microbiota poses both challenges and great prospects in promoting precision medicine in cardiovascular diseases (CVDs). In this review, based on the development, evolution, and influencing factors of gut microbiota in a full life circle, we summarized the recent advances on the characteristic alteration in gut microbiota in CVDs throughout different life stages, and depicted their pathological links in mechanism, as well as the highlight achievements of targeting gut microbiota in CVDs prevention, diagnosis and treatment. Personalized strategies could be tailored according to gut microbiota characteristics in different life stages, including gut microbiota-blood metabolites combined prediction and diagnosis, dietary interventions, lifestyle improvements, probiotic or prebiotic supplements. However, to fulfill the promise of a lifelong cardiovascular health, more mechanism studies should progress from correlation to causality and decipher novel mechanisms linking specific microbes and CVDs. It is also promising to use the burgeoning artificial intelligence and machine learning to target gut microbiota for developing diagnosis system and screening for new therapeutic interventions.

Association between the use of lipid-lowering drugs and the risk of inflammatory bowel disease

BACKGROUND

Observational studies have suggested an association between lipid-lowering drugs and inflammatory bowel disease (IBD) risk. This study aimed to assess the causal influence of lipid-lowering agents on IBD risk using Mendelian randomization analysis.

METHOD

In a population of 173,082 individuals of European ancestry, 55 single-nucleotide polymorphisms were identified as instrumental variables for 6 lipid-lowering drug targets (HMGCR, NPC1LC, PCSK9, LDLR, CETP and APOB). Summary statistics for the genome-wide association study of IBD, ulcerative colitis (UC) and Crohn's disease (CD) were obtained from the FinnGen consortium, Program in Complex Trait Genomics and UK Biobank. Inverse-variance weighted was employed as the primary MR method, and odds ratios (ORs) with 95% confidence intervals were reported as the results. Sensitivity analyses using conventional MR methods were conducted to assess result robustness.

RESULTS

Gene-proxied inhibition of Niemann-Pick C1-like 1 (NPC1L1) was associated with an increased IBD risk (OR [95% CI]: 2.31 [1.38, 3.85]; p = .001), particularly in UC (OR [95% CI]: 2.40 [1.21, 4.74], p = .012), but not in CD. This finding was replicated in the validation cohort. Additionally, gene-proxied inhibition of low-density lipoprotein receptor was associated with reduced IBD (OR [95% CI]: .72 [.60, .87], p < .001) and UC risk (OR [95% CI]: .74 [.59, .92], p = .006), although this result was not replicated in the validation cohort. Other drug targets did not show significant associations with IBD, UC or CD risk.

CONCLUSION

Inhibition of the lipid-lowering drug-target NPC1L1 leads to an increased IBD risk, mainly in the UC population.

Association of nicotine dependence and gut microbiota: a bidirectional two-sample Mendelian randomization study

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 Christensenellaceae (β: -0.52, 95% CI: -0.934-0.106, P = 0.014). The Eubacterium xylanophilum group (OR: 1.106, 95% CI: 1.004-1.218), Lachnoclostridium (OR: 1.118, 95% CI: 1.001-1.249) and Holdemania (OR: 1.08, 95% CI: 1.001-1.167) were risk factors for nicotine dependence. Peptostreptococcaceae (OR: 0.905, 95% CI: 0.837-0.977), Desulfovibrio (OR: 0.014, 95% CI: 0.819-0.977), Dorea (OR: 0.841, 95% CI. 0.731-0.968), Faecalibacterium (OR: 0.831, 95% CI: 0.735-0.939) and Sutterella (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.

Association between gut microbiota and sensorineural hearing loss: a Mendelian randomization study

Background

Several recent studies speculated that the gut microbiota is associated with sensorineural hearing loss (SNHL) and proposed the concept of the gut-inner ear axis. However, the causal effect of gut microbiota on SNHL is still unknown. In this study, we performed a two-sample Mendelian randomization (MR) analysis to estimate the causal effect of gut microbiota on SNHL.

Methods

Gut microbiota data were obtained from the largest available genome-wide association study (n = 18,340) conducted by the MiBioGen consortium. The summary statistics of SNHL were obtained from the FinnGen consortium R8 release data (28,310 cases and 302,750 controls). The causal effects were estimated with inverse-variance weighted, MR-Egger, and weighted median. Reverse Mendelian randomization analysis was performed on the bacteria that were found to be associated with SNHL in forward Mendelian randomization analysis. We then performed sensitivity analyses, including Cochran's Q-test, MR-Egger intercept test, MR-PRESSO, cML-MA-BIC, and leave-one-out analysis, to detect heterogeneity and pleiotropy.

Results

The inverse-variance weighted results suggested that Lachnospiraceae (UCG001) had a significant protective effect against SNHL (odds ratio = 0.85, 95% confidence interval: 0.78-0.93, P = 6.99 × 10-4). In addition, Intestinimonas (odds ratio = 0.89, 95% confidence interval: 0.82-0.97, P = 8.53 × 10-3) presented a suggestively protective effect on SNHL. Rikenellaceae (RC9gutgroup) (odds ratio = 1.08, 95% confidence interval: 1.02-1.15, P = 0.01) and Eubacterium (hallii group) (odds ratio = 1.12, 95% confidence interval: 1.00-1.24, P = 0.048) suggestively increase the risk of SNHL. The results of the reverse MR analysis showed that there is no significant causal effect of SNHL on the gut microbiota. No significant heterogeneity of instrumental variables or pleiotropy was detected.

Conclusion

The evidence that the four genera mentioned above are associated with SNHL supports the hypothesis of a gut-inner ear axis. Our study provides microbial markers for the prevention and treatment of SNHL, and further studies are needed to explore the mechanisms of the gut microbiome-inner ear axis in health and diseases.

A Large Genetic Causal Analysis of the Gut Microbiota and Urological Cancers: A Bidirectional Mendelian Randomization Study

BACKGROUND

Several observational studies and clinical trials have shown that the gut microbiota is associated with urological cancers. However, the causal relationship between gut microbiota and urological cancers remains to be elucidated due to many confounding factors.

METHODS

In this study, we used two thresholds to identify gut microbiota GWAS from the MiBioGen consortium and obtained data for five urological cancers from the UK biobank and Finngen consortium, respectively. We then performed a two-sample Mendelian randomization (MR) analysis with Wald ratio or inverse variance weighted as the main method. We also performed comprehensive sensitivity analyses to verify the robustness of the results. In addition, we performed a reverse MR analysis to examine the direction of causality.

RESULTS

Our study found that family Rikenellaceae, genus Allisonella, genus Lachnospiraceae UCG001, genus Oscillibacter, genus Eubacterium coprostanoligenes group, genus Eubacterium ruminantium group, genus Ruminococcaceae UCG013, and genus Senegalimassilia were related to bladder cancer; genus Ruminococcus torques group, genus Oscillibacter, genus Barnesiella, genus Butyricicoccus, and genus Ruminococcaceae UCG005 were related to prostate cancer; class Alphaproteobacteria, class Bacilli, family Family XI, genus Coprococcus2, genus Intestinimonas, genus Lachnoclostridium, genus Lactococcus, genus Ruminococcus torques group, and genus Eubacterium brachy group were related to renal cell cancer; family Clostridiaceae 1, family Christensenellaceae, genus Eubacterium coprostanoligenes group, genus Clostridium sensu stricto 1, and genus Eubacterium eligens group were related to renal pelvis cancer; family Peptostreptococcaceae, genus Romboutsia, and genus Subdoligranulum were related to testicular cancer. Comprehensive sensitivity analyses proved that our results were reliable.

CONCLUSIONS

Our study confirms the role of specific gut microbial taxa on urological cancers, explores the mechanism of gut microbiota on urological cancers from a macroscopic level, provides potential targets for the screening and treatment of urological cancers, and is dedicated to providing new ideas for clinical research.

Behavioral and Cognitive Performance Following Exposure to Second-Hand Smoke (SHS) from Tobacco Products Associated with Oxidative-Stress-Induced DNA Damage and Repair and Disruption of the Gut Microbiome

Exposure to second-hand Smoke (SHS) remains prevalent. The underlying mechanisms of how SHS affects the brain require elucidation. We tested the hypothesis that SHS inhalation drives changes in the gut microbiome, impacting behavioral and cognitive performance as well as neuropathology in two-month-old wild-type (WT) mice and mice expressing wild-type human tau, a genetic model pertinent to Alzheimer's disease mice, following chronic SHS exposure (10 months to ~30 mg/m3). SHS exposure impacted the composition of the gut microbiome as well as the biodiversity and evenness of the gut microbiome in a sex-dependent fashion. This variation in the composition and biodiversity of the gut microbiome is also associated with several measures of cognitive performance. These results support the hypothesis that the gut microbiome contributes to the effect of SHS exposure on cognition. The percentage of 8-OHdG-labeled cells in the CA1 region of the hippocampus was also associated with performance in the novel object recognition test, consistent with urine and serum levels of 8-OHdG serving as a biomarker of cognitive performance in humans. We also assessed the effects of SHS on the percentage of p21-labeled cells, an early cellular marker of senescence that is upregulated in bronchial cells after exposure to cigarette smoke. Nuclear staining of p21-labeled cells was more prominent in larger cells of the prefrontal cortex and CA1 hippocampal neurons of SHS-exposed mice than in sham-exposed mice, and there was a significantly greater percentage of labelled cells in the prefrontal cortex and CA1 region of the hippocampus of SHS than air-exposed mice, suggesting that exposure to SHS may result in accelerated brain aging through oxidative-stress-induced injury.

Epigenetic Aberrations in Major Psychiatric Diseases Related to Diet and Gut Microbiome Alterations

Nutrition and metabolism modify epigenetic signatures like histone acetylation and DNA methylation. Histone acetylation and DNA methylation in the central nervous system (CNS) can be altered by bioactive nutrients and gut microbiome via the gut-brain axis, which in turn modulate neuronal activity and behavior. Notably, the gut microbiome, with more than 1000 bacterial species, collectively contains almost three million functional genes whose products interact with millions of human epigenetic marks and 30,000 genes in a dynamic manner. However, genetic makeup shapes gut microbiome composition, food/nutrient metabolism, and epigenetic landscape, as well. Here, we first discuss the effect of changes in the microbial structure and composition in shaping specific epigenetic alterations in the brain and their role in the onset and progression of major mental disorders. Afterward, potential interactions among maternal diet/environmental factors, nutrition, and gastrointestinal microbiome, and their roles in accelerating or delaying the onset of severe mental illnesses via epigenetic changes will be discussed. We also provide an overview of the association between the gut microbiome, oxidative stress, and inflammation through epigenetic mechanisms. Finally, we present some underlying mechanisms involved in mediating the influence of the gut microbiome and probiotics on mental health via epigenetic modifications.