Identification of host gene-microbiome associations in colorectal cancer patients using mendelian randomization

Causal relationships between gut microbiome and aplastic anemia: a Mendelian randomization analysis

BACKGROUND

Previous observational studies have hinted at a potential correlation between aplastic anemia (AA) and the gut microbiome. However, the precise nature of this bidirectional causal relationship remains uncertain.

METHODS

We conducted a bidirectional two-sample Mendelian randomization (MR) study to investigate the potential causal link between the gut microbiome and AA. Statistical analysis of the gut microbiome was based on data from an extensive meta-analysis (genome-wide association study) conducted by the MiBioGen Alliance, involving 18,340 samples. Summary statistical data for AA were obtained from the Integrative Epidemiology Unit database. Single -nucleotide polymorphisms (SNPs) were estimated and summarized using inverse variance weighted (IVW), MR Egger, and weighted median methods in the bidirectional MR analysis. Cochran's Q test, MR Egger intercept test, and sensitivity analysis were employed to assess SNP heterogeneity, horizontal pleiotropy, and stability.

RESULTS

The IVW analysis revealed a significant correlation between AA and 10 bacterial taxa. However, there is currently insufficient evidence to support a causal relationship between AA and the composition of gut microbiome.

CONCLUSION

This study suggests a causal connection between the prevalence of specific gut microbiome and AA. Further investigation into the interaction between particular bacterial communities and AA could enhance efforts in prevention, monitoring, and treatment of the condition.

Causal Relationships Between Retinal Diseases and Psychiatric Disorders Have Implications for Precision Psychiatry

Observational studies and clinical trials have reported potential associations between retinal diseases and psychiatric disorders. However, the causal associations between them have remained elusive. In this study, we used bi-directional two-sample Mendelian randomization (MR) analysis to explore unconfounded causal relationships between retinal diseases and psychiatric disorders using large-scale genome-wide association study (GWAS) summary statistics of over 500,000 participants of European ancestry from the FinnGen project, the Psychiatric Genomics Consortium, the European Bioinformatics Institute, and the UK Biobank. Our MR analysis revealed significant causal relationships between major retinal diseases and specific psychiatric disorders. Specifically, susceptibility to dry age-related macular degeneration was associated with a reduced risk of anorexia nervosa (OR = 0.970; 95% CI = 0.930 ~ 0.994; P = 0.025). Furthermore, we found some evidence that exposure to diabetic retinopathy was associated with an increased risk of schizophrenia (OR = 1.021; 95% CI 1.012 ~ 1.049; P = 0.001), and exposure to retinal detachments and breaks was associated with an increased risk of attention deficit hyperactivity disorder (OR = 1.190; 95% CI 1.063 ~ 1.333; P = 0.003). These causal relationships were not confounded by biases of pleiotropy and reverse causation. Our study highlights the importance of preventing and managing retinal disease as a potential avenue for improving the prevention, management and treatment of major psychiatric disorders.

The causal relationship between gut microbiota and constipation: a two-sample Mendelian randomization study

BACKGROUND

Constipation is one of the most common gastrointestinal disorders afflicting the population, with recent observational studies implicating dysfunction of the gut microbiota in constipation. Despite observational studies indicating a relationship, a clear causality remains unclear. This study aims to use two-sample Mendelian randomization (MR) to establish a clearer causal relationship between the two.

METHODS

A two-sample Mendelian randomization (MR) study was performed using the gut microbiota summary Genome-Wide Association Studies (GWAS) statistics from MiBioGen consortium (n = 13,266) and constipation GWAS summary statistics from the IEU OpenGWAS database. The causality between gut microbiota and constipation is primarily analyzed using the inverse-variance weighted (IVW) method and reinforced by an additional four methods, including MR-Egger, Weighted Median, Simple Mode, and Weighted Mode. Finally, funnel plot, heterogeneity test, horizontal pleiotropy test, and leave-one-out test were used to evaluate the reliability of MR results.

RESULTS

IVW estimates suggested that the bacterial species Anaerotruncus, Butyricimonas, and Hungatella were causally associated with constipation. The odds ratio (OR) values of Anaerotruncus, Butyricimonas, and Hungatella were 1.08 (95% CI = 1.02-1.13; P = 0.007), 1.07 (95% CI = 1.01-1.13; P = 0.015), 1.03 (95% CI = 1.00-1.06; P = 0.037) respectively. Meanwhile, Ruminiclostridium 9 and Intestinibacter have been shown to be associated with a reduced risk of constipation. The OR of Ruminiclostridium 9 = 0.75(95% CI = 0.73-0.78, P < 0.001 and Intestinibacter of OR = 0.89 (95% CI = 0.86-0.93, P < 0.001). Furthermore, validation by funnel plot, heterogeneity test, and horizontal pleiotropy test showed that MR results were reliable.

CONCLUSION

This is the first Mendelian randomization study to explore the causalities between specific gut microbiota taxa and constipation, and as such may be useful in providing insights into the unclear pathology of constipation which can in turn aid in the search for prevention and treatment.

Exploring genetic associations in systemic lupus erythematosus through Mendelian randomization: implications for novel biomarkers and therapeutic targets

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease characterized by a significant health burden. There is an essential need for novel biomarkers and therapeutic targets to improve diagnosis and management. Mendelian randomization (MR) was applied to explore causal links between SLE and various biomarkers like immune cells, metabolites, and inflammatory cytokines using multiple databases. Initially, biomarkers significantly associated with SLE were identified. Bidirectional MR helped clarify these relationships, and a two-step mediation MR examined their effects on SLE risk. Intersection analysis was used to identify biomarkers with consistent effects across datasets. Four biomarkers were identified as having significant associations with SLE risk: 1-palmitoyl-2-arachidonoyl-GPI levels [odds ratio (OR), 1.379; 95% confidence interval (CI), 1.180 to 1.613; FDR, 0.046], IL-17A levels (OR, 2.197; 95% CI, 1.412 to 3.418; FDR, 0.044), N-acetyl-aspartyl-glutamate (NAAG) levels (OR, 0.882; 95% CI, 0.831 to 0.936; FDR, 0.030), and ribitol levels (OR, 0.743; 95% CI, 0.644 to 0.857; FDR, 0.012). Bidirectional MR showed an inverse effect of NAAG on IL-17A levels (OR, 0.978; 95% CI, 0.962 to 0.994; p = 0.006). Mediation analysis indicated that NAAG influenced SLE risk both directly (beta =  - 0.108) and indirectly through IL-17A (beta =  - 0.018), highlighting the potential mediating role of IL-17A. After expanding the significance criteria to p < 0.05, intersection analysis across multiple datasets revealed 29 biomarkers with consistent beta directions, including 19 potential risk factors (beta > 0) and 10 protective factors (beta < 0) for SLE. This research has revealed significant genetic associations with SLE and demonstrated that IL-17A mediates the relationship between NAAG levels and SLE risk, highlighting potential new targets for personalized therapeutic interventions. Key Points • This study employs MR to identify significant genetic associations between various biomarkers and SLE, providing novel insights into potential biomarkers and therapeutic targets. • Four key biomarkers were identified as significantly associated with SLE risk: 1-palmitoyl-2-arachidonoyl-GPI, IL-17A, N-acetyl-aspartyl-glutamate (NAAG), and ribitol. • The findings suggest that NAAG levels have a protective effect against SLE, partly mediated through IL-17A, indicating a complex interplay between these biomarkers in the pathogenesis of SLE. • Intersectional analysis across multiple datasets revealed 29 biomarkers with consistent effects on SLE risk, highlighting new directions for future research and potential personalized therapeutic strategies.

Effect of Organic, Nano, and Inorganic Zinc Sources on Growth Performance, Antioxidant Function, and Intestinal Health of Young Broilers

The study aimed to determine the effects of different zinc sources on growth performance, antioxidant function, and intestinal health of broilers. In total, 240 Ross 308 male broilers with similar weight were randomly assigned to 4 treatments, including zinc sulfate, methionine zinc (Zn-Met), glycine zinc (Zn-Gly), and nano-zinc oxide (ZnO-NPs), with 80 mg zinc/kg diet supplementation. The experiment lasted for 21 days. Results showed dietary supplemental Zn-Gly and Zn-Met increased average daily gain during 1-14 days (P = 0.011), and Zn-Gly, Zn-Met, and ZnO-NP supplementation decreased the ratio of feed to gain during 1-21 days (P = 0.003) compared to zinc sulfate. ZnO-NPs supplementation tended to increase total SOD activity (P = 0.068) and had higher serum IgA content and lower MDA level than the other three groups (P < 0.05). Compared with zinc sulfate, Zn-Met and ZnO-NP supplementation decreased TNF-α mRNA expression (P = 0.048). However, serum biochemical indices, intestinal morphology, and mRNA expressions of tight junction proteins were not affected by different zinc sources (P > 0.05). A differential trend was observed in the beta diversity of bacterial communities among four groups (P = 0.082). The LEfSe analysis showed that bacterial genera Blautia, Ruminococcaceae, Clostridia, Anaerostipes, Eubacterium_ventriosum, Merdibacter, and Oscillospira were enriched in the ZnSO4 group, and the genera Eubacterium_hallii and Anaerotruncus were enriched in the Zn-Gly group. The genera UCG-009 and UCG010 were enriched in ZnO-NPs and Zn-Met groups, respectively. It should be stated dietary supplemental Zn-Met improved growth performance, ZnO-NPs promoted IgA production and reduced occurrences of oxidative stress and inflammation, and different zinc sources enriched different jejunal bacteria genera.

Causal role of blood metabolites in HER-positive and HER-negative breast cancer: a Mendelian randomization (MR) study

BACKGROUND

Previous studies provide evidence that in vivo metabolites are associated with breast cancer (BC). However, the causal relationship between blood metabolites and BC remains unclear.

METHOD

Comprehensive two-sample Mendelian randomization analysis was conducted to determine the causal association between 1400 publicly available genetic data on metabolic factors and human epidermal growth factor receptor positive (HER+) BC or HER- BC in this study.

RESULT

Epiandrosterone sulfate levels (OR = 1.07, 95% CI = 1.02 ~ 1.10, p = 0.0013), 5alpha-androstan-3beta,17beta-diol monosulfate (2) levels (OR = 1.07, 95% CI = 1.03 ~ 1.12, p = 0.0012), glycohyocholate levels (OR = 0.85, 95% CI = 0.77 ~ 0.93, p = 0.0007) and etiocholanolone glucuronide levels (OR = 1.12, 95% CI = 1.05 ~ 1.20, p = 0.0013) were causally correlated with HER+ BC. 5 metabolites were causally correlated with HER- BC: Vanillic acid glycine levels (OR = 1.14, 95% CI = 1.06 ~ 1.22, p = 0.0003), Thyroxine levels (OR = 1.26, 95% CI = 1.11 ~ 1.44, p = 0.0004), 1-palmitoyl-2-linoleoyl-GPI (16:0/18:2) levels (OR = 0.86, 95% CI = 0.79 ~ 0.94, p = 0.0010), N-acetylphenylalanine levels (OR = 1.12, 95% CI = 1.05 ~ 1.19, p = 0.0007) and Glucose-to-mannose ratio (OR = 1.15, 95% CI = 1.06 ~ 1.24, p = 0.0008). Two common causally related metabolites were identified: Gamma-glutamyl glutamate and X-12849 levels.

CONCLUSIONS

Our study has respectively demonstrated the connection between blood metabolites and HER+ or HER- BC by genetic means, thereby offering opportunities for therapeutic targets.

Genetically supported causality between gut microbiota and frailty: a two-sample Mendelian randomization study

Background

A mounting body of evidence suggests a strong connection between gut microbiota and the risk of frailty. However, the question of causality remains unanswered. In this study, we employed a Mendelian randomization (MR) approach to assess potential causal relationships between gut microbiota and the risk of frailty.

Materials and methods

Summary statistics for the gut microbiome were obtained from a genome wide association study (GWAS) meta-analysis of the MiBioGen consortium (N = 18,340). Summary statistics for frailty were obtained from a GWAS meta-analysis, including the UK Biobank and TwinGene (N = 175,226). Our primary analysis utilized the inverse variance weighted (IVW) method. To enhance the robustness of our results, we also applied weighted median methods, MR Egger regression, and MR pleiotropy residual sum and outlier test. Finally, we conducted reverse MR analysis to investigate the potential for reverse causality.

Results

IVW method identified 7 bacterial taxa nominally associated with the risk of FI. Class Bacteroidia (p = 0.033) and genus Eubacterium ruminantium group (p = 0.028) were protective against FI. In addition, class Betaproteobacteria (p = 0.042), genus Allisonella (p = 0.012), genus Bifidobacterium (p = 0.013), genus Clostridium innocuum group (p = 0.036) and genus Eubacterium coprostanoligenes group (p = 0.003) were associated with a higher risk of FI. No pleiotropy or heterogeneity were found.

Conclusion

The MR analysis indicates a causal relationship between specific gut microbiota and FI, offering new insights into the mechanisms underlying FI mediated by gut microbiota.

Effects of loneliness and isolation on cardiovascular diseases: a two sample Mendelian Randomization Study

BACKGROUND

Loneliness and isolation are associated with multiple cardiovascular diseases (CVDs), but there is a lack of research on whether they were causally linked. We conducted a Mendelian Randomization (MR) study to explore causal relationships between loneliness and isolation and multiple CVDs.

METHODS

Single nucleotide polymorphisms associated with loneliness and isolation were identified from a genome-wide association study (GWAS) of 455,364 individuals of European ancestry in the IEU GWAS database. Summary data for 15 CVDs were also obtained from the IEU GWAS database. We used three MR methods including inverse variance weighting, MR-Egger, and weighted median estimation to assess the causal effect of exposure on outcomes. Cochran's Q test and MR-Egger intercept test were used to evaluate the heterogeneity and pleiotropy.

RESULTS

MR analysis showed that loneliness and isolation were significantly associated with essential hypertension (OR = 1.07, 95% CI: 1.03-1.12), atherosclerotic heart disease (OR = 1.04; 95% CI: 1.02-1.06), myocardial infarction (OR = 1.02; 95% CI: 1-1.04) and angina (OR = 1.04; 95% CI =1.02-1.06). No heterogeneity and pleiotropy effects were found in this study.

CONCLUSIONS

Causal relationship of loneliness and isolation with CVDs were found in this study.

Causal relationships between Sjögren's syndrome and Parkinson's disease: A Mendelian randomization study

BACKGROUND

Epidemiological and observational studies have indicated an association between Sjögren's syndrome (SS) and Parkinson's disease (PD). However, consistent conclusions have not been reached due to various limitations. In order to determine whether SS and PD are causally related, we conducted a Mendelian randomization study (MR) with two samples.

METHODS

Data for SS derived from the FinnGen consortium's R9 release (2495 cases and 365 533 controls). Moreover, data for PD were acquired from the publicly available GWAS of European ancestry, which involved 33 674 cases and 449 056 controls. The inverse variance weighted, along with four other effective methodologies, were employed to comprehensively infer the causal relationships between SS and PD. To assess the estimation's robustness, a number of sensitivity studies were performed. To determine the probability of reverse causality, we performed a reverse MR analysis.

RESULTS

There was no evidence of a significant causal effect of SS on PD risks based on the MR [odds ratio (OR) = 1.03; 95% confidence interval (CI) = 0.95-1.11; p = .45]. Similarly, no evidence supported the causal effects of PD on SS (OR = 0.92; 95% CI = 0.81-1.04; p = .20). These findings held up under rigorous sensitivity analysis.

CONCLUSIONS

MR bidirectional analysis did not reveal any cause-and-effect relationship between SS and PD, or vice versa. Further study of the mechanisms that may underlie the probable causal association between SS and PD is needed.

The role of microbiomes in gastrointestinal cancers: new insights

Gastrointestinal (GI) cancers constitute more than 33% of new cancer cases worldwide and pose a considerable burden on public health. There exists a growing body of evidence that has systematically recorded an upward trajectory in GI malignancies within the last 5 to 10 years, thus presenting a formidable menace to the health of the human population. The perturbations in GI microbiota may have a noteworthy influence on the advancement of GI cancers; however, the precise mechanisms behind this association are still not comprehensively understood. Some bacteria have been observed to support cancer development, while others seem to provide a safeguard against it. Recent studies have indicated that alterations in the composition and abundance of microbiomes could be associated with the progression of various GI cancers, such as colorectal, gastric, hepatic, and esophageal cancers. Within this comprehensive analysis, we examine the significance of microbiomes, particularly those located in the intestines, in GI cancers. Furthermore, we explore the impact of microbiomes on various treatment modalities for GI cancer, including chemotherapy, immunotherapy, and radiotherapy. Additionally, we delve into the intricate mechanisms through which intestinal microbes influence the efficacy of GI cancer treatments.

The gut microbiome and metabolites are altered and interrelated in patients with functional constipation

Introduction

Gut microbiota and metabolites have been identified to contribute to the pathogenesis of functional constipation (FC); however, the underlying mechanism(s) have not been elucidated, and the relationship between the gut microbiota and metabolites in FC has received limited attention in the literature.

Methods

16S rDNA sequencing and non-targeted metabolomic detection based on liquid chromatography-mass spectrometry (LC-MS/MS) technologies were combined to analyze the altered gut microbiome and metabolic profile of fecal samples from FC patients and healthy individuals (healthy control; HC).

Results

The richness and diversity of gut microbiota significantly (p < 0.01) increased in FC patients. Compared to the HC group, 18 genera, including Intestinibacter, Klebsiella, and Akkermansia, exhibited statistically significant changes (p < 0.05). Metabolic analysis showed that metabolic profiles were also markedly altered with 79 metabolites, such as (-)-caryophyllene oxide, chenodeoxycholic acid, and biliverdin, indicating significant inter-group differences (p < 0.05). Besides, the primary bile acid biosynthesis, as well as the metabolic profile of porphyrin and chlorophyll, were the most dominant enriched pathways (FDR < 0.01), in which chenodeoxycholic acid and biliverdin were significantly enriched, respectively. Correlation analysis demonstrated a strong relationship between 10 genera and 19 metabolites (r > 0.6, FDR < 0.05), and notably, Intestinibacter showed a negative correlation with biliverdin (FDR < 0.001), which highlighted the interplay of the gut microbiota and metabolites in the pathogenesis of FC.

Conclusion

Our research describes the characteristics of the gut microbiota and metabolic profiles and the correlation between the gut microbiota and metabolites in FC patients. This may contribute to the understanding of the underlying mechanisms involved in FC pathogenesis and may provide novel insights into therapeutic interventions.