Large-scale correlation analysis of deep venous thrombosis and gut microbiota

The gut microbiota in thrombosis

The gut microbiota has emerged as an environmental risk factor that affects thrombotic phenotypes in several cardiovascular diseases. Evidence includes the identification of marker species by sequencing studies of the gut microbiomes of patients with thrombotic disease, the influence of antithrombotic therapies on gut microbial diversity, and preclinical studies in mouse models of thrombosis that have demonstrated the functional effects of the gut microbiota on vascular inflammatory phenotypes and thrombus formation. In addition to impaired gut barrier function promoting low-grade inflammation, gut microbiota-derived metabolites have been shown to act on vascular cell types and promote thrombus formation. Therefore, these meta-organismal pathways that link the metabolic capacities of gut microorganisms with host immune functions have emerged as potential diagnostic markers and novel drug targets. In this Review, we discuss the link between the gut microbiota, its metabolites and thromboembolic diseases.

Is the occurrence of deep vein thrombosis related to the fracture site? A two-sample mendelian randomization study

OBJECTIVE

Deep vein thrombosis (DVT) is a known complication of fractures. This study aimed to explore the genetic causal relationship between DVT and fracture sites.

RESEARCH DESIGN AND METHODS

The exposures analyzed in this study included fracture of femur (FFE), fracture of lower leg, including ankle (FLLA), fracture of shoulder and upper arm (FSUA), fracture of forearm (FFO), fracture of rib, sternum and thoracic spine (FRSTS) and fracture of lumbar spine and pelvis (FLSP). DVT as the outcome. A two-sample Mendelian randomization (MR) approach was employed to investigate the genetic causal relationship, and a series of sensitivity analyses were conducted.

RESULTS

The findings indicated no genetic causal relationship between FFE (p = 0.569, OR 95% CI = 1.001 [0.998-1.003]), FLLA (p = 0.371, OR 95% CI = 0.999 [0.995-1.002]), FSUA (p = 0.871, OR 95% CI = 1.000 [0.998-1.002]), FFO (p = 0.281, OR 95% CI = 1.001 [0.999-1.002]), FRSTS (p = 0.346, OR 95% CI = 0.999 [0.996-1.001]) or FLSP (p = 0.759, OR 95% CI = 1.000 [0.999-1.002]) and DVT. Sensitivity analyses reinforced the robustness.

CONCLUSIONS

This study indicate that no genetic causal relationship exists between DVT and fracture site, the observed association may be attributable to non-genetic factors.

Causal effect of gut microbiota on venous thromboembolism: a two-sample mendelian randomization study

BACKGROUND

The gut microbiota of venous thromboembolism (VTE) patients exhibited significant alterations. However, the causal relationship between gut microbiota and VTE has not been fully understood. This study aimed to assess the causal relationship between gut microbiota and the risk of VTE using a two-sample Mendelian Randomization (MR) study.

METHODS

The gut microbiota and VTE genetic data were collected from the MiBioGen consortium and the UK biobank, respectively. The potential causal relationship between gut microbiota and VTE was investigated using a two-sample MR analysis, including inverse variance weighted (IVW), weighted median, MR-Egger, simple mode, and weighted mode methods. Cochran's Q-test, MR-PRESSO, and MR-Egger regression intercept analysis were utilized to perform sensitivity analysis.

RESULTS

At the genus level, the results of MR analysis found that Coprococcus1 (OR: 1.0029, 95% CI: 1.0005-1.0054, p = 0.0202) was suggestively linked with an increased risk of VTE, while Slackia (odds ratio (OR): 0.9977, 95% confidence interval (CI): 0.9957-0.9998, p = 0.0298), Butyricicoccus (OR: 0.9971, 95% CI: 0.9945-0.9997, p = 0.0309), Eubacterium coprostanoligenes group (OR: 0.9972, 95% CI: 0.9946-0.9999, p = 0.0445), and Bacteroides (OR: 0.9964, 95% CI: 0.9932-0.9995, p = 0.0234) were suggestively associated with a reduced risk of VTE. No heterogeneity and horizontal pleiotropy was detected.

CONCLUSION

This study found that there were potential causal relationships between five gut microbiota and VTE. Our findings may provide new insights into the mechanisms of VTE.

The dose-dependent mechanism behind the protective effect of lentinan against acute alcoholic liver injury via proliferating intestinal probiotics

Acute alcoholic liver injury (AALI) is a widespread disease that can develop into hepatitis, liver fibrosis, and cirrhosis. In severe cases, it can be life-threatening, while drug treatment presents various side effects. This study characterized the structure of natural lentinan (LNT) from the Qinba Mountain area and investigated the protective mechanism of different LNT doses (100 mg kg-1, 200 mg kg-1, and 400 mg kg-1) on AALI. The results showed that LNT was a glucose-dominated pyran polysaccharide with a triple-helical structure and a molecular weight (Mw) of 7.56 × 106 Da. An AALI mouse model showed that all the LNT doses protected liver function, reduced hepatic steatosis, alleviated oxidative stress and inflammatory response, and stimulated probiotic proliferation. Low-dose LNT increased anti-oxidant-associated beneficial bacteria, medium-dose LNT improved liver swelling and promoted anti-oxidant-associated probiotics, and high-dose LNT increased the probiotics that helped protect liver function and anti-oxidant and anti-inflammatory properties. All the LNT doses inhibited pathogenic growth, including Oscillospiraceae, Weeksellaceae, Streptococcaceae, Akkermansiaceae, Morganellaceae, and Proteus. These results indicated that the protective effect of LNT against AALI was mediated by the proliferation of various intestinal probiotics and was related to the consumption doses. These findings offer new strategies for comprehensively utilizing Lentinula edodes from the Qinba Mountain area and preventing AALI using natural food-based substances.

Genetic evidence for a causal link between gut microbiota and arterial embolism and thrombosis: a two-sample Mendelian randomization study

Background

Previous research has hinted at a crucial link between gut microbiota and arterial embolism and thrombosis, yet the causal relationship remains enigmatic. To gain a deeper understanding, we aimed to comprehensively explore the causal relationship and elucidate the impact of the gut microbiota on the risk through a two-sample Mendelian randomization (MR) study.

Methods

Genetic instrumental variables for gut microbiota were identified from a genome-wide association study (GWAS) of 18,340 participants. Summary statistics for IBS were drawn from a GWAS including 1,076 cases and 381,997 controls. We used the inverse-variance weighted (IVW) method as the primary analysis. To test the robustness of our results, we further performed the weighted median method, MR-Egger regression, and MR pleiotropy residual sum and outlier test.

Results

We identified three bacterial traits that were associated with the risk of arterial embolism and thrombosis: odds ratio (OR): 1.58, 95% confidence interval (CI): 1.08-2.31, p = 0.017 for genus Catenibacterium; OR: 0.64, 95% CI: 0.42-0.96, p = 0.031 for genus Dialister; and OR: 2.08, 95% CI: 1.25-3.47, p = 0.005 for genus Odoribacter. The results of sensitivity analyses for these bacterial traits were consistent (P<0.05).

Conclusion

Our systematic analyses provided evidence to support a potential causal relationship between several gut microbiota taxa and the risk of arterial embolism and thrombosis. More studies are required to show how the gut microbiota affects the development of arterial embolism and thrombosis.

Genetic causal relationship between gut microbiota and cutaneous melanoma: a two-sample Mendelian randomization study

Currently, numerous studies suggest a potential association between the gut microbiota and the progression of melanoma. Hence, our objective was to examine the genetic impact of the gut microbiota on melanoma through the utilization of the Mendelian randomization (MR) approach. This research employed Bacteroides, Streptococcus, Proteobacteria, and Lachnospiraceae as exposure variables and cutaneous melanoma (CM) as the outcome in a two-sample MR analysis. In this MR research, the primary analytical approach was the random-effects inverse-variance weighting (IVW) model. Complementary methods included weighted median, MR Egger, and basic and weighted models. We assessed both heterogeneity and horizontal pleiotropy in our study, scrutinizing whether the analysis results were affected by any individual SNP. The random-effects IVW outcomes indicated that Streptococcus, Bacteroides, Lachnospiraceae and Proteobacteria had no causal relationship with CM, with odds ratios of 1.001 [95% confidence interval (CI) = 0.998-1.004, P  = 0.444], 0.999 (95% CI = 0.996-1.002, P  = 0.692), 1.001 (95% CI = 0.998-1.003, P  = 0.306), and 0.999 (95% CI = 0.997-1.002, P  = 0.998), respectively. No analyses exhibited heterogeneity, horizontal pleiotropy, or deviations. Our research determined that Bacteroides, Streptococcus, Proteobacteria, and Lachnospiraceae do not induce CM at the genetic level. However, we cannot dismiss the possibility that these four gut microbiotas might influence CM through other mechanisms.

Male infertility risk and gut microbiota: a Mendelian randomization study

Background

In recent decades, the decline of male sperm quality has become a worldwide phenomenon, with sperm quality of critical importance for the ability to conceive naturally. Recent studies suggest that male fertility function is closely linked to the gut microbiota, however, the cause-and-effect association between the gut microbiota and male infertility risk is currently unclear.

Methods

We performed one two-sample Mendelian randomization (MR) study, which uses summary data on human gut microbiota from the MiBioGen consortium as factors of exposure. FinnGen Consortium R8 data was used to obtain GWAS data for male infertility. To evaluate cause-and-effect associations linking gut microbiota and male infertility risk with multiple Mendelian randomization methods, we included inverse variance weighted (IVW), MR-Egger, and Maximum Likelihood (ML) Ratio. The heterogeneity of instrumental variables was evaluated through Cochran's Q, Rucker's Q, and leave-one-out analysis methods.

Results

We found a positive association between Allisonella, Anaerotruncus, Barnesiella, Intestinibacter, and Lactococcus with male infertility risk according to the MR analysis results. Bacteroides Romboutsia, Ruminococcaceae (NK4A2140group), and Ruminococcaceae (UCG011) play a protective function in male infertility pathogenesis.

Conclusion

It was found that gut microbiota and infertility are causally related in this study. In subsequent studies, there is a need to build a larger and more comprehensive GWAS database on male infertility, which will reveal the underlying mechanisms for gut microbiota and male infertility. There is a need for randomized controlled trials for validating the protective effect of the associated gut microbiota against male infertility risk, and for exploring the associated mechanisms.

Circulating LPS from gut microbiota leverages stenosis-induced deep vein thrombosis in mice

OBJECTIVE AND DESIGN

An accumulating body of evidence has shown that gut microbiota is involved in regulating inflammation; however, it remains undetermined if and how gut microbiota plays an important role in modulating deep venous thrombosis (DVT), which is an inflammation-involved thrombotic event.

SUBJECTS

Mice under different treatments were used in this study.

METHODS AND TREATMENT

We induced stenosis DVT in mice by partially ligating the inferior vena cava. Mice were treated with antibiotics, prebiotics, probiotics, or inflammatory reagents to modulate inflammatory states, and their effects on the levels of circulating LPS and DVT were examined.

RESULTS

Antibiotic-treated mice or germ-free mice exhibited compromised DVT. Treatment of mice with either prebiotics or probiotics effectively suppressed DVT, which was accompanied with the downregulation of circulating LPS. Restoration of circulating LPS in these mice with a low dose of LPS was able to restore DVT. LPS-induced DVT was blocked by a TLR4 antagonist. By performing proteomic analysis, we identified TSP1 as one of the downstream effectors of circulating LPS in DVT.

CONCLUSION

These results suggest that gut microbiota may play a nonnegligible role in modulating DVT by leveraging the levels of LPS in circulation, thus shedding light on the development of gut microbiota-based strategies for preventing and treating DVT.

No Evidence of a Genetic Causal Relationship between Ankylosing Spondylitis and Gut Microbiota: A Two-Sample Mendelian Randomization Study

Objective: Ankylosing spondylitis (AS) is associated with a variety of gut microbiotas. We aim to analyze the causal relationship between the two at the genetic level. Methods: Mendelian randomization (MR) is a type of instrumental variables (IVs) analysis; MR follows the Mendelian genetic rule of "parental alleles are randomly assigned to offspring" and takes genetic variation as IVs to infer the causal association between exposure factors and study outcome in observational studies. Genome-wide association study (GWAS) summary data of AS were from the FinnGen consortium, and the gut microbiota (Bacteroides, Streptococcus, Proteobacteria, Lachnospiraceae) were from the MiBioGen consortium. The TwoSampleMR and MRPRESSO packages of the R were used to perform a two-sample MR study. Random-effects inverse variance weighted (IVW) was the main analysis method, and MR Egger, weighted median, simple mode, and weighted mode were used as supplementary methods. We examined heterogeneity and horizontal pleiotropy, and examined whether the analysis results were influenced by a single SNP. We applied radial variants of the IVW and MR-Egger model for the improved visualization of the causal estimate. We further examined the causal relationship between AS and gut microbiota, and the robustness of the analysis results. Finally, we performed maximum likelihood, penalized weighted median, and IVW (fixed effects) to further identify the potential causal association. Results: The random-effects IVW results showed that Bacteroides (p = 0.965, OR 95% confidence interval [CI] = 0.990 [0.621-1.579]), Streptococcus (p = 0.591, OR 95% CI = 1.120 [0.741-1.692]), Proteobacteria (p = 0.522, OR 95% CI = 1.160 [0.737-1.826]), and Lachnospiraceae (p = 0.717, OR 95% CI = 1.073 [0.732-1.574]) have no genetic causal relationship with AS. There was no heterogeneity, horizontal pleiotropy or outliers, and results were normally distributed. The MR analysis results were not driven by a single SNP. Conclusions: This study showed that Bacteroides, Streptococcus, Proteobacteria and Lachnospiraceae, four common gut microbiotas associated with AS, had no causal relationship with AS at the genetic level. This study makes a positive contribution to the genetics of AS, but the insufficient number of gut microbiota included is a limitation.

Large-Scale Genetic Correlation Analysis between Spondyloarthritis and Human Blood Metabolites

The aim was to study the genetic correlation and causal relationship between spondyloarthritis (SpA) and blood metabolites based on the large-scale genome-wide association study (GWAS) summary data. The GWAS summary data (3966 SpA and 448,298 control cases) of SpA were from the UK Biobank, and the GWAS summary data (486 blood metabolites) of human blood metabolites were from a published study. First, the genetic correlation between SpA and blood metabolites was analyzed by linkage disequilibrium score (LDSC) regression. Next, we used Mendelian randomization (MR) analysis to perform access causal relationship between SpA and blood metabolites. Random effects inverse variance weighted (IVW) was the main analysis method, and the MR Egger, weighted median, simple mode, and weighted mode were supplementary methods. The MR analysis results were dominated by the random effects IVW. The Cochran's Q statistic (MR-IVW) and Rucker's Q statistic (MR Egger) were used to check heterogeneity. MR Egger and MR pleiotropy residual sum and outlier (MR-PRESSO) were used to check horizontal pleiotropy. The MR-PRESSO was also used to check outliers. The "leave-one-out" analysis was used to assess whether the MR analysis results were affected by a single SNP and thus test the robustness of the MR results. Finally, we identified seven blood metabolites that are genetically related to SpA: X-10395 (correlation coefficient = -0.546, p = 0.025), pantothenate (correlation coefficient = -0.565, p = 0.038), caprylate (correlation coefficient = -0.333, p = 0.037), pelargonate (correlation coefficient = -0.339, p = 0.047), X-11317 (correlation coefficient = -0.350, p = 0.038), X-12510 (correlation coefficient = -0.399, p = 0.034), and X-13859 (Correlation coefficient = -0.458, p = 0.015). Among them, X-10395 had a positive genetic causal relationship with SpA (p = 0.014, OR = 1.011). The blood metabolites that have genetic correlation and causal relationship with SpA found in this study provide a new idea for the study of the pathogenesis of SpA and the determination of diagnostic indicators.

Genetic causal relationship between age at menarche and benign oesophageal neoplasia identified by a Mendelian randomization study

OBJECTIVE

The occurrence and development of oesophageal neoplasia (ON) is closely related to hormone changes. The aim of this study was to investigate the causal relationships between age at menarche (AAMA) or age at menopause (AAMO) and benign oesophageal neoplasia (BON) or malignant oesophageal neoplasia (MON) from a genetic perspective.

METHODS

Genome-wide association study (GWAS) summary data of exposures (AAMA and AAMO) and outcomes (BON and MON) were obtained from the IEU OpenGWAS database. We performed a two-sample Mendelian randomization (MR) study between them. The inverse variance weighted (IVW) was used as the main analysis method, while the MR Egger, weighted median, simple mode, and weighted mode were supplementary methods. The maximum likelihood, penalized weighted median, and IVW (fixed effects) were validation methods. We used Cochran's Q statistic and Rucker's Q statistic to detect heterogeneity. The intercept test of the MR Egger and global test of MR pleiotropy residual sum and outlier (MR-PRESSO) were used to detect horizontal pleiotropy, and the distortion test of the MR-PRESSO analysis was used to detect outliers. The leave-one-out analysis was used to detect whether the MR analysis was affected by single nucleotide polymorphisms (SNPs). In addition, the MR robust adjusted profile score (MR-RAPS) method was used to assess the robustness of MR analysis.

RESULTS

The random-effects IVW results showed that AAMA had a negative genetic causal relationship with BON (odds ratio [OR] = 0.285 [95% confidence interval [CI]: 0.130-0.623], P = 0.002). The weighted median, maximum likelihood, penalized weighted median, and IVW (fixed effects) were consistent with random-effects IVW (P < 0.05). The MR Egger, simple mode and weighted mode results showed that AAMA had no genetic causal relationship with BON (P > 0.05). However, there were no causal genetic relationships between AAMA and MON (OR = 1.132 [95%CI: 0.621-2.063], P = 0.685), AAMO and BON (OR = 0.989 [95%CI: 0.755-1.296], P = 0.935), or AAMO and MON (OR = 1.129 [95%CI: 0.938-1.359], P = 0.200). The MR Egger, weighted median, simple mode, weighted mode, maximum likelihood, penalized weighted median, and IVW (fixed effects) were consistent with a random-effects IVW (P > 0.05). MR analysis results showed no heterogeneity, the horizontal pleiotropy and outliers (P > 0.05). They were not driven by a single SNP, and were normally distributed (P > 0.05).

CONCLUSION

Only AAMA has a negative genetic causal relationship with BON, and no genetic causal relationships exist between AAMA and MON, AAMO and BON, or AAMO and MON. However, it cannot be ruled out that they are related at other levels besides genetics.