Human Serum Metabolites as Potential Mediators from Type 2 Diabetes and Obesity to COVID-19 Severity and Susceptibility: Evidence from Mendelian Randomization Study

Causality of genetically determined blood metabolites on inflammatory bowel disease: a two-sample Mendelian randomization study

Inflammatory bowel disease (IBD) is a chronic and recurrent inflammatory disease of the gastrointestinal tract, including two subtypes: Crohn's disease (CD) and ulcerative colitis (UC). Metabolic disorders are important factors in the development of IBD. However, the evidence for the causal relationship between blood metabolites and IBD remains limited. A two-sample MR analysis was applied to evaluate relationships between 486 blood metabolites and IBD. The inverse variance weighted method was chosen as the primary MR analysis method. False discovery rate correction was used to control for false positives in multiple testing. Following complementary and sensitivity analyses were conducted using methods such as weight median, MR-egger, weighted mode, simple mode, Cochran Q test, and MR-PRESSO. Moreover, we performed replication, meta-analysis, Steiger test, and linkage disequilibrium score regression to enhance the robustness of the results. Additionally, we performed metabolic pathway analysis to identify potential metabolic pathways. As a result, we identified four significant causal associations between four blood metabolites and two IBD subtypes. Specifically, one metabolite was identified as being associated with the development of CD (mannose: odds ratio (OR) = 0.19, 95% confidence interval (CI) 0.08-0.43, P = 8.54 × 10-5). Three metabolites were identified as being associated with the development of UC (arachidonate (20:4n6): OR = 0.18, 95% CI 0.11-0.30, P = 2.09 × 10-11; 1, 5-anhydroglucitol: OR = 2.21, 95% CI 1.47-3.34, P = 1.50 × 10-4; 2-stearoylglycerophosphocholine: OR = 2.66, 95% CI 1.53-4.63, P = 5.30 × 10-4). The findings of our study suggested that the identified metabolites and metabolic pathways can be considered as useful circulating metabolic biomarkers for the screening and prevention of IBD in clinical practice, as well as candidate molecules for future mechanism exploration and drug target selection.

Identifying serum metabolite biomarkers for autoimmune diseases: a two-sample mendelian randomization and meta-analysis

Background

Extensive evidence suggests a link between alterations in serum metabolite composition and various autoimmune diseases (ADs). Nevertheless, the causal relationship underlying these correlations and their potential utility as dependable biomarkers for early AD detection remain uncertain.

Objective

The objective of this study was to employ a two-sample Mendelian randomization (MR) approach to ascertain the causal relationship between serum metabolites and ADs. Additionally, a meta-analysis incorporating data from diverse samples was conducted to enhance the validation of this causal effect.

Materials and methods

A two-sample MR analysis was performed to investigate the association between 486 human serum metabolites and six prevalent autoimmune diseases: systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), inflammatory bowel disease (IBD), dermatomyositis (DM), type 1 diabetes (T1D), and celiac disease (CeD). The inverse variance weighted (IVW) model was employed as the primary analytical technique for the two-sample MR analysis, aiming to identify blood metabolites linked with autoimmune diseases. Independent outcome samples were utilized for further validation of significant blood metabolites. Additional sensitivity analyses, including heterogeneity test, horizontal pleiotropy test, and retention rate analysis, were conducted. The results from these analyses were subsequently meta-integrated. Finally, metabolic pathway analysis was performed using the KEGG and Small Molecule Pathway Databases (SMPD).

Results

Following the discovery and replication phases, eight metabolites were identified as causally associated with various autoimmune diseases, encompassing five lipid metabolism types: 1-oleoylglycerophosphoethanolamine, 1-arachidonoylglycerophosphoethanolamine, 1-myristoylglycerophosphocholine, arachidonate (20:4 n6), and glycerol. The meta-analysis indicated that three out of these eight metabolites exhibited a protective effect, while the remaining five were designated as pathogenic factors. The robustness of these associations was further confirmed through sensitivity analysis. Moreover, an investigation into metabolic pathways revealed a significant correlation between galactose metabolism and autoimmune diseases.

Conclusion

This study revealed a causal relationship between lipid metabolites and ADs, providing novel insights into the mechanism of AD development mediated by serum metabolites and possible biomarkers for early diagnosis.

Genetic associations and potential mediators between psychiatric disorders and irritable bowel syndrome: a Mendelian randomization study with mediation analysis

Objective

Potential causal associations between psychiatric disorders and irritable bowel syndrome have been demonstrated in observational studies; however, these studies are susceptible to underlying confounding and reverse causation biases. We aimed to assess the causal effects of psychiatric disorders on irritable bowel syndrome (IBS) and the potential mediators from a genetic perspective by conducting a Mendelian randomization (MR) study with mediation analysis.

Method

Genetic instruments associated with psychiatric disorders, potential mediators, and IBS were obtained from large-scale genome-wide association studies (GWAS). Three MR methods - the inverse-variance weighted (IVW) method, MR-Egger method, and weighted median method, were used to investigate causal association estimates. Heterogeneity among different genetic instrumental variables (IVs) was assessed using Q tests. Additionally, the MR-PRESSO and MR-Pleiotropy methods were used to verify horizontal pleiotropy and detect outliers that might bias the results, which were removed from further analysis. Consequently, we used MR mediation analysis to investigate potential mediators in the causal associations between psychiatric disorders and IBS.

Results

MR provided evidence of the causal effects of genetically predicted broad depression, major depressive disorder (MDD), anxiety disorder, post-traumatic stress disorder (PTSD), and schizophrenia on IBS. The results of MR mediation analysis demonstrated that the reduction in acetate levels mediated 12.6% of the effects of broad depression on IBS; insomnia mediated 16.00%, 16.20%, and 27.14% of the effects of broad depression, MDD, and PTSD on IBS, respectively; and the increase in blood β-hydroxybutyrate levels mediated 50.76% of the effects of schizophrenia on IBS.

Conclusion

Our study confirmed the brain-gut axis involvement and potential modulators in the pathophysiology of psychiatric disorder-induced IBS from a genetic perspective, and suggests potential therapeutic targets for the disrupted brain-gut axis.

Betaine and L-Carnitine Synergistically Influence the Metabolome and Immune Response in Dogs

This study used thirty-two dogs, which were assigned to a preferred period of 14 days and then assigned to one of the four treatment foods: control (containing no added betaine, no added L-carnitine), control with 0.5% added betaine (Treatment 2), control with no added betaine and 300 ppm added L-carnitine (Treatment 3), or control with 0.5% added betaine and 300 ppm added L-carnitine (Treatment 4). All treatment foods were fed for ninety days. Untargeted blood metabolomic analysis and immune response were measured at the beginning and end of the 90-day feeding trial. Feeding betaine increased single-carbon metabolites while decreasing many carnitine-containing metabolites. Feeding L-carnitine increased many carnitine metabolites, while the combination synergistically influenced the metabolome. The combination of betaine and L-carnitine increased the cytokines released in a Tru-culture system in response to stimulation while numerically decreasing their release when unstimulated. Therefore, the combination of dietary betaine and L-carnitine could have the dual positive effects of reducing cytokine stimulation, controlling inflammation during health, and providing a robust response to bacterial infection.

Human blood metabolites and risk of severe COVID-19: A Mendelian randomization study

BACKGROUND

Evidence supports the observational associations of human blood metabolites with the risk of severe COVID-19. However, little is known about the potential pathological mechanisms and the analysis of blood metabolites may offer a better understanding of the underlying biological processes.

METHODS

We applied a two-sample Mendelian randomization (MR) analysis to evaluate relationships between 486 blood metabolites and the risk of severe COVID-19. The inverse-variance weighted (IVW) model was used as the primary two-sample MR analysis method to estimate the causal relationship of the exposure on the outcome. Sensitivity analyses were implemented with Cochran's Q test, MR-Egger intercept test, MR-PRESSO, leave-one-out analysis and the funnel plot.

RESULTS

Four hunderd and eighty six metabolites were included for MR analysis following rigorous genetic variants selection. After MR analyses and sensitivity analysis filtration, we found weak evidence of an association between 3-hydroxybutyrate (odds ratio [OR] = 1.21, 95% CI, 1.07-1.38, p = .0036) and the risk of severe COVID-19. A series of sensitivity analyses have been carried out to confirm the rigidity of the above results.

CONCLUSION

This study suggested a causal relationship between 3-hydroxybutyrate and the severity of COVID-19, thus providing novel insights into biomarkers and pathways for COVID-19 prevention and clinical interventions.

Association of gut microbiota with COVID-19 susceptibility and severity: A two-sample Mendelian randomization study

Evidence supports the observational associations of gut microbiota with the risk of COVID-19; however, it is unclear whether these associations reflect a causal relationship. This study investigated the association of gut microbiota with COVID-19 susceptibility and severity. Data were obtained from a large-scale gut microbiota data set (n = 18 340) and the COVID-19 Host Genetics Initiative (n = 2 942 817). Causal effects were estimated with inverse variance weighted (IVW), MR-Egger, and weighted median, and sensitivity analyses were implemented with Cochran's Q test, MR-Egger intercept test, MR-PRESSO, leave-one-out analysis, and funnel plots. For COVID-19 susceptibility, IVW estimates suggested that Gammaproteobacteria (odds ratio [OR] = 0.94, 95% confidence interval [CI], 0.89-0.99, p = 0.0295] and Streptococcaceae (OR = 0.95, 95% CI, 0.92-1.00, p = 0.0287) had a reduced risk, while Negativicutes (OR = 1.05, 95% CI, 1.01-1.10, p = 0.0302), Selenomonadales (OR = 1.05, 95% CI, 1.01-1.10, p = 0.0302), Bacteroides (OR = 1.06, 95% CI, 1.01-1.12, p = 0.0283), and Bacteroidaceae (OR = 1.06, 95% CI, 1.01-1.12, p = 0.0283) were associated with an increased risk (all p < 0.05, nominally significant). For COVID-19 severity, Subdoligranulum (OR = 0.80, 95% CI, 0.69-0.92, p = 0.0018), Cyanobacteria (OR = 0.85, 95% CI, 0.76-0.96, p = 0.0062), Lactobacillales (OR = 0.87, 95% CI, 0.76-0.98, p = 0.0260), Christensenellaceae (OR = 0.87, 95% CI, 0.77-0.99, p = 0.0384), Tyzzerella3 (OR = 0.89, 95% CI, 0.81-0.97, p = 0.0070), and RuminococcaceaeUCG011 (OR = 0.91, 95% CI, 0.83-0.99, p = 0.0247) exhibited negative correlations, while RikenellaceaeRC9 (OR = 1.09, 95% CI, 1.01-1.17, p = 0.0277), LachnospiraceaeUCG008 (OR = 1.12, 95% CI, 1.00-1.26, p = 0.0432), and MollicutesRF9 (OR = 1.14, 95% CI, 1.01-1.29, p = 0.0354) exhibited positive correlations (all p < 0.05, nominally significant). Sensitivity analyses validated the robustness of the above associations. These findings suggest that gut microbiota might influence the susceptibility and severity of COVID-19 in a causal way, thus providing novel insights into the gut microbiota-mediated development mechanism of COVID-19.

Long COVID in the context of social determinants of health

The COVID-19 pandemic has been a challenge for the public health system and has highlighted health disparities. COVID-19 vaccines have effectively protected against infection and severe disease, but some patients continue to suffer from symptoms after their condition is resolved. These post-acute sequelae, or long COVID, continues to disproportionately affect some patients based on their social determinants of health (SDOH). This paper uses the World Health Organization's (WHO) SDOH conceptual framework to explore how SDOH influences long COVID outcomes.