Assessing the causal relationships between human blood metabolites and the risk of NAFLD: A comprehensive mendelian randomization study

Elucidating the role of genetically determined metabolites in Diabetic Retinopathy: insights from a mendelian randomization analysis

AIMS

Diabetic retinopathy (DR) results from complex genetic and metabolic interactions. Unraveling the links between blood metabolites and DR can advance risk prediction and therapy.

METHODS

Leveraging Mendelian Randomization (MR) and Linkage Disequilibrium Score Regression (LDSC), we analyzed 10,413 DR cases and 308,633 controls. Data was sourced from the Metabolomics GWAS server and the FinnGen project.

RESULTS

Our research conducted a comprehensive MR analysis across 486 serum metabolites to investigate their causal role in DR. After stringent selection and validation of instrumental variables, we focused on 480 metabolites for analysis. Our findings revealed 38 metabolites potentially causally associated with DR. Specifically, 4-androsten-3beta,17beta-diol disulfate 2 was identified as significantly associated with a reduced risk of DR (OR = 0.471, 95% CI = 0.324-0.684, p = 7.87 × 10- 5), even after rigorous adjustments for multiple testing. Sensitivity analyses further validated the robustness of this association, and linkage disequilibrium score regression analyses showed no significant genetic correlation between this metabolite and DR, suggesting a specific protective effect against DR.

CONCLUSIONS

Our study identifies 4-androsten-3beta,17beta-diol disulfate 2, a metabolite of androgens, as a significant protective factor against diabetic retinopathy, suggesting androgens as potential therapeutic targets.

Betaine and I-LG may have a predictive value for ATB: A causal study in a large European population

PURPOSE

To analyze the causal relationship between 486 human serum metabolites and the active tuberculosis (ATB) in European population.

METHODS

In this study, the causal relationship between human serum metabolites and the ATB was analyzed by integrating the genome-wide association study (GWAS). The 486 human serum metabolites were used as the exposure variable, three different ATB GWAS databases in the European population were set as outcome variables, and single nucleotide polymorphisms were used as instrumental variables for Mendelian Randomization. The inverse variance weighting was estimated causality, the MR-Egger intercept to estimate horizontal pleiotropy, and the combined effects of metabolites were also considered in the meta-analysis. Furthermore, the web-based MetaboAnalyst 6.0 was engaged for enrichment pathway analysis, while R (version 4.3.2) software and Review Manager 5.3 were employed for statistical analysis.

RESULTS

A total of 21, 17, and 19 metabolites strongly associated with ATB were found in the three databases after preliminary screening (P < 0.05). The intersecting metabolites across these databases included tryptophan, betaine, 1-linoleoylglycerol (1-monolinolein) (1-LG), 1-eicosatrienoylglycerophosphocholine, and oleoylcarnitine. Among them, betaine (I2 = 24%, P = 0.27) and 1-LG (I2 = 0%, P = 0.62) showed the lowest heterogeneity among the different ATB databases. In addition, the metabolic pathways of phosphatidylethanolamine biosynthesis (P = 0.0068), methionine metabolism (P = 0.0089), betaine metabolism (P = 0.0205) and oxidation of branched-chain fatty acids (P = 0.0309) were also associated with ATB.

CONCLUSION

Betaine and 1-LG may be biomarkers or auxiliary diagnostic tools for ATB. They may provide new guidance for medical practice in the early diagnosis and surveillance of ATB. In addition, by interfering with phosphatidylethanolamine biosynthesis, methionine metabolism, betaine metabolism, oxidation of branched-chain fatty acids, and other pathways, it is helpful to develop new anti-tuberculosis drugs and explore the virulence or pathogenesis of ATB at a deeper level, providing an effective reference for future studies.

The causal relationship between blood metabolites and rosacea: A Mendelian randomization

BACKGROUND

An increasing amount of research demonstrates that metabolic disorders are related to rosacea. However, the correlations and causal relationships among them remain unknown.

METHODS

We conducted not only forward 2-sample MR (Mendelian randomization) analyses but also reverse MR analyses which showed positive results in the forward MR analysis. In the forward MR analyses, inverse-variance weighted (IVW) and MR-Egger were performed as MR analyses. Cochran's Q test and the MR-Egger Intercept were used for sensitivity analyses. Concerning reverse MR analyses, IVW, MR-Egger, weighted median, simple mode, and weighted mode were applied. Cochran's Q test, MR-Egger Intercept, and MR pleiotropy residual sum and outlier (MR-PRESSO) outlier test were applied as sensitivity analyses.

RESULTS

A total of 24 metabolites and 1 metabolite ratio were shown to have a causal effect on rosacea. N-lactoyl phenylalanine (N-Lac-Phe) was estimated as statistically significant by Bonferroni correction. Interestingly, we found three metabolites that were negatively associated with rosacea, especially caffeine, which are in line with the results of a large cohort study of females. For reverse MR analysis, we revealed that rosacea could potentially decrease the generation of two metabolites: octadecenedioate (C18:1-DC) and methyl vanillate sulfate.

CONCLUSION

This study identified blood metabolites that may be associated with the development of rosacea. However, the exact mechanism by which these positive metabolites influence rosacea remains uncertain due to the paucity of experimental investigations. The combination of genetics and metabolomics offers novel viewpoints on the research of underlying mechanisms of rosacea and has significant value in screening and prevention of rosacea.

The causal relationship between genetically predicted blood metabolites and idiopathic pulmonary fibrosis: A bidirectional two-sample Mendelian randomization study

BACKGROUND

Numerous metabolomic studies have confirmed the pivotal role of metabolic abnormalities in the development of idiopathic pulmonary fibrosis (IPF). Nevertheless, there is a lack of evidence on the causal relationship between circulating metabolites and the risk of IPF.

METHODS

The potential causality between 486 blood metabolites and IPF was determined through a bidirectional two-sample Mendelian randomization (TSMR) analysis. A genome-wide association study (GWAS) involving 7,824 participants was performed to analyze metabolite data, and a GWAS meta-analysis involving 6,257 IPF cases and 947,616 control European subjects was conducted to analyze IPF data. The TSMR analysis was performed primarily with the inverse variance weighted model, supplemented by weighted mode, MR-Egger regression, and weighted median estimators. A battery of sensitivity analyses was performed, including horizontal pleiotropy assessment, heterogeneity test, Steiger test, and leave-one-out analysis. Furthermore, replication analysis and meta-analysis were conducted with another GWAS dataset of IPF containing 4,125 IPF cases and 20,464 control subjects. Mediation analyses were used to identify the mediating role of confounders in the effect of metabolites on IPF.

RESULTS

There were four metabolites associated with the elevated risk of IPF, namely glucose (odds ratio [OR] = 2.49, 95% confidence interval [95%CI] = 1.13-5.49, P = 0.024), urea (OR = 6.24, 95% CI = 1.77-22.02, P = 0.004), guanosine (OR = 1.57, 95%CI = 1.07-2.30, P = 0.021), and ADpSGEGDFXAEGGGVR (OR = 1.70, 95%CI = 1.00-2.88, P = 0.0496). Of note, the effect of guanosine on IPF was found to be mediated by gastroesophageal reflux disease. Reverse Mendelian randomization analysis displayed that IPF might slightly elevate guanosine levels in the blood.

CONCLUSION

Conclusively, hyperglycemia may confer a promoting effect on IPF, highlighting that attention should be paid to the relationship between diabetes and IPF, not solely to the diagnosis of diabetes. Additionally, urea, guanosine, and ADpSGEGDFXAEGGGVR also facilitate the development of IPF. This study may provide a reference for analyzing the potential mechanism of IPF and carry implications for the prevention and treatment of IPF.

Causality of genetically determined blood metabolites on irritable bowel syndrome: A Mendelian randomization study

BACKGROUND

Irritable bowel syndrome (IBS) is one of the most common functional bowel disorders and dysmetabolism plays an important role in the pathogenesis of disease. Nevertheless, there remains a lack of information regarding the causal relationship between circulating metabolites and IBS. A two-sample Mendelian randomization (MR) analysis was conducted in order to evaluate the causal relationship between genetically proxied 486 blood metabolites and IBS.

METHODS

A two-sample MR analysis was implemented to assess the causality of blood metabolites on IBS. The study utilized a genome-wide association study (GWAS) to examine 486 metabolites as the exposure variable while employing a GWAS study with 486,601 individuals of European descent as the outcome variable. The inverse-variance weighted (IVW) method was used to estimate the causal relationship of metabolites on IBS, while several methods were performed to eliminate the pleiotropy and heterogeneity. Another GWAS data was used for replication and meta-analysis. In addition, reverse MR and linkage disequilibrium score regression (LDSC) were employed for additional assessment. Multivariable MR analysis was conducted in order to evaluate the direct impact of metabolites on IBS.

RESULTS

Three known and two unknown metabolites were identified as being associated with the development of IBS. Higher levels of butyryl carnitine (OR(95%CI):1.10(1.02-1.18),p = 0.009) and tetradecanedioate (OR(95%CI):1.13(1.04-1.23),p = 0.003)increased susceptibility of IBS and higher levels of stearate(18:0)(OR(95%CI):0.72(0.58-0.89),p = 0.003) decreased susceptibility of IBS.

CONCLUSION

The metabolites implicated in the pathogenesis of IBS possess potential as biomarkers and hold promise for elucidating the underlying biological mechanisms of this condition.

Genetically determined metabolites in allergic conjunctivitis: A Mendelian randomization study

Background

Allergic conjunctivitis (AC) afflicts a significant portion of the global populace. Yet, its metabolic foundations remain largely unexplored.

Methods

We applied Mendelian Randomization (MR) and Linkage Disequilibrium Score Regression (LDSC) to scrutinize a cohort comprising 20 958 AC cases and 356 319 controls. Data were amalgamated from the metabolomics GWAS server and the FinnGen project, under strict quality control protocols.

Results

Using two-sample MR analysis, 486 blood metabolites were investigated in relation to AC. The IVW approach highlighted 18 metabolites as closely tied to AC risk; of these, 16 retained significance post sensitivity assessments for heterogeneity and horizontal pleiotropy. LDSC analysis, adopted to bolster our findings and negate confounders from shared genetic markers, revealed 8 metabolites with marked heritability, including: palmitate (OR = 0.614), 3-methoxytyrosine (OR = 0.657), carnitine (OR = 1.368), threonate (OR = 0.828), N-[3-(2-Oxopyrrolidin-1-yl)propyl]acetamide (OR = 1.257), metoprolol acid metabolite (OR = 0.982), oleoylcarnitine (OR = 0.635), and 2-palmitoylglycerophosphocholine (OR = 1.351).

Conclusion

AC is precipitated by ocular responses to environmental allergens. Our study unveils a causal link between 8 blood metabolites and AC. This insight accentuates the role of metabolites in AC onset, suggesting novel avenues for its early prediction, targeted prevention, and tailored therapeutic interventions.

The causal association between serum metabolites and lung cancer based on multivariate Mendelian randomization

This study seeks to understand the causal association between serum metabolites and different lung cancer types, an area yet to be extensively studied. We Used a two-sample Mendelian randomization (TSMR) approach, utilizing 486 blood metabolites as exposures and 3 distinct lung cancer types genome-wide association studies datasets as outcomes. We employed inverse variance weighting, MR-Egger, weighted median, simple mode, and weighted mode to estimate causal effects. We performed sensitivity analyses using Cochran Q test, MR-Egger intercept test, and MR-pleiotropy residual sum and outlier (MR-PRESSO). Linkage disequilibrium score (LDSC) analysis was conducted on the selected metabolites, and common confounding single nucleotide polymorphisms were eliminated using the human genotype-phenotype association Database. Metabolic pathway analysis was performed with MetaboAnalyst 5.0 software. Subsequently, a multivariate Mendelian randomization analysis was conducted to ascertain independent risk exposures. Our findings suggest independent risk factors for specific types of lung cancer: 7-methylxanthine and isoleucine for lung adenocarcinoma, cysteine and 1-arachidonoylglycerophosphocholine are identified as independent protective and risk factors for squamous lung cancer. Undecanoate (11:0) with Linoleate (18:2n6) showed a protective effect for small cell lung cancer. Additionally, 11 metabolic pathways were associated with lung cancer. This novel perspective offers a multidimensional understanding of lung cancer phenotypes, providing valuable guidance for identifying and screening of diverse lung cancer phenotypes.

Investigating causal associations among gut microbiota, metabolites, and psoriatic arthritis: a Mendelian randomization study

Background

Currently, there has been observed a significant alteration in the composition of the gut microbiome (GM) and serum metabolites in patients with psoriatic arthritis (PsA) compared to healthy individuals. However, previous observational studies have shown inconsistent results regarding the alteration of gut microbiota/metabolites. In order to shed light on this matter, we utilized Mendelian randomization to determine the causal effect of GM/metabolites on PsA.

Methods

We retrieved summary-level data of GM taxa/metabolites and PsA from publicly available GWAS statistics. Causal relationships between GM/metabolites and PsA were determined using a two-sample MR analysis, with the IVW approach serving as the primary analysis method. To ensure the robustness of our findings, we conducted sensitivity analyses, multivariable MR analysis (MVMR), and additional analysis including replication verification analysis, LDSC regression, and Steiger test analysis. Furthermore, we investigated reverse causality through a reverse MR analysis. Finally, we conducted an analysis of expression quantitative trait loci (eQTLs) involved in the metabolic pathway to explore potential molecular mechanisms of metabolism.

Results

Our findings reveal that eight GM taxa and twenty-three serum metabolites are causally related to PsA (P < 0.05). Notably, a higher relative abundance of Family Rikenellaceae (ORIVW: 0.622, 95% CI: 0.438-0.883, FDR = 0.045) and elevated serum levels of X-11538 (ORIVW: 0.442, 95% CI: 0.250-0.781, FDR = 0.046) maintain significant causal associations with a reduced risk of PsA, even after adjusting for multiple testing correction and conducting MVMR analysis. These findings suggest that Family Rikenellaceae and X-11538 may have protective effects against PsA. Our sensitivity analysis and additional analysis revealed no significant horizontal pleiotropy, reverse causality, or heterogeneity. The functional enrichment analysis revealed that the eQTLs examined were primarily associated with glycerolipid metabolism and the expression of key metabolic factors influenced by bacterial infections (Vibrio cholerae and Helicobacter pylori) as well as the mTOR signaling pathway.

Conclusion

In conclusion, our study demonstrates that Family Rikenellaceae and X-11538 exhibit a strong and negative causal relationship with PsA. These particular GM taxa and metabolites have the potential to serve as innovative biomarkers, offering valuable insights into the treatment and prevention of PsA. Moreover, bacterial infections and mTOR-mediated activation of metabolic factors may play an important role in this process.

Evaluation of the causal effects of blood metabolites on irritable bowel syndrome: Mendelian randomization

BACKGROUND

Irritable bowel syndrome (IBS) is a common functional gastrointestinal disorder characterized by abdominal pain, discomfort, and changes in bowel habits. The mechanism underlying IBS remains unclear, and little evidence exists for clarifying the causal relationship between blood metabolites and IBS.

METHODS

We conducted a Mendelian randomization (MR) study using two samples. Exposure data for 7824 Europeans were extracted from a genome-wide association study (GWAS) on metabolite levels. The IBS GWAS data from the GWAS database were used for the initial analysis. The primary analysis of causal relationships was conducted using inverse-variance weighting (IVW) with MR-Egger and weighted medians as supplementary analyses. Sensitivity analyses were performed using a combination of the Cochran's Q test, MR-Egger intercept test, Mendelian randomization pleiotropy residual sum and outlier, and leave-one-out analysis. For significant associations, replication and meta-analyses were performed using additional independent IBS case GWAS data released by the FinnGen Consortium R9. To identify the metabolites, score regression, confounding analysis, and reverse MR were performed to further assess the causal relationships between the metabolites.

RESULTS

After rigorous screening, we identified four known metabolites to be associated with IBS (stearate, odds ratio [OR]: 0.74, 95% confidence interval [CI]: 0.59-0.92; arginine, OR: 1.36, 95% CI: 1.07-1.74; 1-palmitoylglycerol, OR:1.49, 95% CI: 1.07-2.07; 1-palmitoylglycerophosphoinositol, OR: 0.84, 95% CI: 0.71-0.99).

CONCLUSIONS

MR analysis revealed a causal relationship between the four metabolites and IBS, providing preliminary evidence for the pathogenesis of IBS. Our results provide novel insights into the potential biomarkers of IBS.

Triglyceride-Glucose Index is Significantly Associated with the Risk of Hyperuricemia in Patients with Nonalcoholic Fatty Liver Disease

Purpose

The triglyceride-glucose (TyG) index is a new index of insulin resistance (IR), and its association with hyperuricemia (HUA) is unclear. The aim of this study was to investigate whether TyG is an independent risk factor for hyperuricemia (HUA) in patients with nonalcoholic fatty liver disease (NAFLD).

Patients and Methods

We retrospectively analyzed 461 patients with ultrasound-confirmed NAFLD and calculated the TyG index. Multivariate logistic regression was used to analyze the relationship between the TyG index and HUA in NAFLD patients. The correlation between the TyG index and HUA was further confirmed by a restricted cubic spline. Furthermore, the stability of the association between TyG index and HUA was examined using subgroup analysis. Receiver operating characteristic (ROC) curves were constructed to evaluate the predictive value of the TyG index on HUA. Multivariate linear regression was used to analyze the linear relationship between the TyG index and serum uric acid.

Results

A total of 166 HUA patients and 295 non-HUA patients were included in the study. The results of multivariate logistic regression analysis showed that after controlling the confounding risk factors, TyG was still an independent risk factor for HUA (OR = 2.00, 95% CI: 1.38 -2.91, p < 0.001). Restricted cubic splines showed that HUA risk increased linearly with TyG across the entire TyG range. The ROC curve showed that TyG index was better than triglyceride in predicting HUA in NAFLD patients, with AUC values of 0.62 and 0.59, respectively. Multiple linear regression analysis showed that TyG index was significantly positively correlated with blood uric acid (B = 1.37, 95% CI: 0.67-2.08, p < 0.001).

Conclusion

TyG index is an independent risk factor for HUA in patients with NAFLD. The increase of the TyG index level is closely related to the occurrence and development of HUA in patients with NAFLD.