Causal effects of serum metabolites on amyotrophic lateral sclerosis: A Mendelian randomization study

Relationship between human serum metabolites and angina pectoris: a Mendelian randomization study

PURPOSE

We aimed to explore the causal relationship between human serum metabolites and angina pectoris.

METHODS

This study used two-sample Mendelian randomization (MR) analysis to assess the association between 486 serum metabolites and angina pectoris. The analytical methods employed to reduce study bias included inverse variance weighted, MR-Egger, and weighted median method. A comprehensive sensitivity analysis was performed using the leave-one-out method, while instrumental variable pleiotropy was tested with MR-Pleiotropy RESidual Sum and Outlier. Metabolic pathways of angina-associated metabolites were analysed on the MetaboAnalyst metabolomics analysis tool platform.

RESULTS

In this study, 42 serum metabolites were found to be strongly associated with angina pectoris. They mainly belonged to seven groups: amino acids, carbohydrates, cofactors and vitamins, lipids, nucleotides, unknown metabolites, and exogenous substances. Pipecolate posed the highest risk for the development of angina pectoris among the 42 serum metabolites. The main metabolic pathways associated with angina pectoris were glycine, serine, threonine metabolism, primary bile acid biosynthesis, and caffeine metabolism.

CONCLUSION

We identified 25 high-risk and 17 protective human serum metabolites associated with angina pectoris. Their associated major metabolic pathways were also determined. The serum metabolite pipecolate was significantly and positively correlated with the risk of angina pectoris. This finding may serve as a valuable reference for testing serum markers associated with angina pectoris.

Genetic Insights into the Association and Causality Between Blood Metabolites and Alzheimer's Disease

Background

Alzheimer's disease (AD) is an increasing public health concern with the aging of the global population. Understanding the genetic correlation and potential causal relationships between blood metabolites and AD may provide important insights into the metabolic dysregulation underlying this neurodegenerative disorder.

Objective

The aim of this study was to investigate the causal relationship between blood metabolites and AD using Mendelian randomization (MR) analysis.

Methods

Association data were obtained from three large-scale genome-wide association studies of 486 blood metabolites (N = 7,824), AD (71,880 cases and 383,378 controls), early-onset AD (N = 303,760), and late-onset AD (N = 307,112). Causal associations between blood metabolites and AD were assessed using inverse variance weighting (IVW), MR-Egger, and weighted median methods. Bidirectional two-sample MR analysis was used to identify causal blood metabolites. MR-PRESSO, MR-Egger, and Cochran-Q were used to quantify instrumental variable heterogeneity and horizontal pleiotropy.

Results

Using MR and sensitivity analysis, we identified 40 blood metabolites with potential causal associations with AD. After applying false discovery rate (FDR) correction, two metabolites, gamma-glutamylphenylalanine (OR = 1.15, 95% CI: 1.06-1.24, p = 3.88×10-4, q = 0.09) and X-11317 (OR = 1.16, 95% CI: 1.08-1.26, p = 1.14×10-4, q = 0.05), retained significant associations with AD. Reverse MR analysis indicated no significant causal effect of AD on blood metabolites. No significant instrumental variable heterogeneity or horizontal pleiotropy was found.

Conclusions

This two-sample MR study provides compelling evidence for a potential causal relationship between blood metabolic dysregulation and susceptibility to AD. Further investigation of the biological relevance of the identified metabolites to AD and additional supporting evidence is warranted.

Circulating metabolites and depression: a bidirectional Mendelian randomization

Background

Studies have shown an association between depression and circulating metabolites, but the causal relationship between them has not been elucidated. The purpose of this study was to elucidate the causal relationship between circulating metabolites and depression and to explore the role of circulating metabolites in depression.

Methods

In this study, the top single-nucleotide polymorphisms (SNPs) associated with circulating metabolites (n = 24,925) and depression (n = 322,580) were obtained based on the publicly available genome-wide association study using two-sample Mendelian randomization (MR). SNP estimates were summarized through inverse variance weighted, MR Egger, weighted median, MR pleiotropy residual sum and outlier, and "leave-one-out" methods.

Results

Apolipoprotein A-I (OR 0.990, 95% CI 981-0.999) and glutamine (OR 0.985, 95% CI 0.972-0.997) had protective causal effects on depression, whereas acetoacetate (OR 1.021, 95% CI 1.009-1.034), glycoproteins (OR 1.005, 95% CI 1.000-1.009), isoleucine (OR 1.013, 95% CI 1.002-1.024), and urea (OR 1.020, 95% CI 1.000-1.039) had an anti-protective effect on depression. Reversed MR showed no effect of depression on the seven circulating metabolites.

Conclusion

In this study, MR analysis showed that apolipoprotein A-I and glutamine had a protective effect on depression, and acetoacetate, glycoprotein, isoleucine, glucose, and urea may be risk factors for depression. Therefore, further research must be conducted to translate the findings into practice.

Metabolic Profile and Pathological Alterations in the Muscle of Patients with Early-Stage Amyotrophic Lateral Sclerosis

Diverse biomarkers and pathological alterations have been found in muscle of patients with Amyotrophic lateral sclerosis (ALS), but the relation between such alterations and dysfunction in energetic metabolism remains to be investigated. We established the metabolome of muscle and serum of ALS patients and correlated these findings with the clinical status and pathological alterations observed in the muscle. We obtained data from 20 controls and 17 ALS patients (disease duration: 9.4 ± 6.8 months). Multivariate metabolomics analysis identified a distinct serum metabolome for ALS compared to controls (p-CV-ANOVA < 0.035) and revealed an excellent discriminant profile for muscle metabolome (p-CV-ANOVA < 0.0012). Citramalate was discriminant for both muscle and serum. High lauroylcarnitine levels in muscle were associated with low Forced Vital Capacity. Transcriptomics analysis of key antioxidant enzymes showed an upregulation of SOD3 (p = 0.0017) and GLRX2(1) (p = 0.0022) in ALS muscle. Analysis of mitochondrial enzymatic activity in muscle revealed higher complex II/CS (p = 0.04) and lower LDH (p = 0.03) activity in ALS than in controls. Our study showed, for the first time, a global dysfunction in the muscle of early-stage ALS patients. Furthermore, we identified novel metabolites to be employed as biomarkers for diagnosis and prognosis of ALS patients.

Emerging insights into the complex genetics and pathophysiology of amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis is a fatal neurodegenerative disease. The discovery of genes associated with amyotrophic lateral sclerosis, commencing with SOD1 in 1993, started fairly gradually. Recent advances in genetic technology have led to the rapid identification of multiple new genes associated with the disease, and to a new understanding of oligogenic and polygenic disease risk. The overlap of genes associated with amyotrophic lateral sclerosis with those of other neurodegenerative diseases is shedding light on the phenotypic spectrum of neurodegeneration, leading to a better understanding of genotype-phenotype correlations. A deepening knowledge of the genetic architecture is allowing the characterisation of the molecular steps caused by various mutations that converge on recurrent dysregulated pathways. Of crucial relevance, mutations associated with amyotrophic lateral sclerosis are amenable to novel gene-based therapeutic options, an approach in use for other neurological illnesses. Lastly, the exposome-the summation of lifetime environmental exposures-has emerged as an influential component for amyotrophic lateral sclerosis through the gene-time-environment hypothesis. Our improved understanding of all these aspects will lead to long-awaited therapies and the identification of modifiable risks factors.

A review of Mendelian randomization in amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis is a relatively common and rapidly progressive neurodegenerative disease that, in the majority of cases, is thought to be determined by a complex gene-environment interaction. Exponential growth in the number of performed genome-wide association studies combined with the advent of Mendelian randomization is opening significant new opportunities to identify environmental exposures that increase or decrease the risk of amyotrophic lateral sclerosis. Each of these discoveries has the potential to shape new therapeutic interventions. However, to do so, rigorous methodological standards must be applied in the performance of Mendelian randomization. We have reviewed Mendelian randomization studies performed in amyotrophic lateral sclerosis to date. We identified 20 Mendelian randomization studies, including evaluation of physical exercise, adiposity, cognitive performance, immune function, blood lipids, sleep behaviours, educational attainment, alcohol consumption, smoking and type 2 diabetes mellitus. We have evaluated each study using gold standard methodology supported by the Mendelian randomization literature and the STROBE-Mendelian randomization checklist. Where discrepancies exist between Mendelian randomization studies, we suggest the underlying reasons. A number of studies conclude that there is a causal link between blood lipids and risk of amyotrophic lateral sclerosis; replication across different datasets and even different populations adds confidence. For other putative risk factors, such as smoking and immune function, Mendelian randomization studies have provided cause for doubt. We highlight the use of positive control analyses in choosing exposure single nucleotide polymorphisms (SNPs) to make up the Mendelian randomization instrument, use of SNP clumping to avoid false positive results due to SNPs in linkage and the importance of multiple testing correction. We discuss the implications of survival bias for study of late age of onset diseases such as amyotrophic lateral sclerosis and make recommendations to mitigate this potentially important confounder. For Mendelian randomization to be useful to the amyotrophic lateral sclerosis field, high methodological standards must be applied to ensure reproducibility. Mendelian randomization is already an impactful tool, but poor-quality studies will lead to incorrect interpretations by a field that includes non-statisticians, wasted resources and missed opportunities.

Assessment of bidirectional relationships between 98 genera of the human gut microbiota and amyotrophic lateral sclerosis: a 2-sample Mendelian randomization study

BACKGROUND

Growing evidence suggests a mutual interaction between gut microbiome alterations and ALS pathogenesis. However, previous studies were susceptible to potential confounding factors and reverse causation bias, likely leading to inconsistent and biased results.

OBJECTIVES

To decipher the potentially mutual relationship between gut microbiota and ALS, we used a bidirectional two-sample MR approach to examine the associations between the gut microbiome and ALS.

RESULTS

Using the inverse variance-weighted method, OTU10032 unclassified Enterobacteriaceae species-level OTU and unclassified Acidaminococcaceae were associated with a higher risk of ALS (per relative abundance: OR, 1.04; 95% CI, 1.01-1.07; P = 0.011 and OR, 1.02; 95% CI, 1.01-1.04; P = 0.009, respectively). Importantly, Gamma-Glu-Phe was showed potential deleterious effects on the risk of ALS (genetically predicted per a 1-standard deviation increase in the level of Gamma-Glu-Phe: OR, 1.96; 95% CI, 1.50-2.55; P = 0.012). Sensitivity analysis of the two candidate genera and metabolites using the MR-Egger and weighted-median methods produced similar estimates, and no horizontal pleiotropy or outliers were observed. Intriguingly, genetically predicted ALS was associated with an increase in the relative abundance of OTU4607_Sutterella (per 1-unit higher log odds: β, 2.23; 95% CI, 1.27-3.18; P = 0.020) and Lactobacillales_ORDER (per 1-unit higher log odds: β, 0.51; 95% CI, 0.09-0.94; P = 0.019).

CONCLUSIONS

Our findings provide novel evidence supporting the bidirectional relationship between the gut microbiota and ALS. These results may contribute to designing microbiome- and microbiome-dependent metabolite interventions in future ALS clinical trials.

Gut microbiome and amyotrophic lateral sclerosis: A systematic review of current evidence

Amyotrophic lateral sclerosis (ALS), characterized by a loss of motor neurons in the brain and spinal cord, is a relatively rare but currently incurable neurodegenerative disease. The global incidence of ALS is estimated as 1.75 per 100,000 person-years and the global prevalence is estimated as 4.1-8.4 per 100,000 individuals. Contributions from outside the central nervous system to the etiology of ALS have been increasingly recognized. Gut microbiome is one of the most quickly growing fields of research for ALS. In this article, we performed a comprehensive review of the results from existing animal and human studies, to provide an up-to-date summary of the current research on gut microbiome and ALS. In brief, we found relatively consistent results from animal studies, suggesting an altered gut microbiome composition in experimental ALS. Publication bias might however be a concern. Findings from human studies are largely inconclusive. A few animal and human studies demonstrated the usefulness of intervention with microbial-derived metabolites in modulating the disease progression of ALS. We discussed potential methodological concerns in these studies, including study design, statistical power, handling process of biospecimens and sequencing data, as well as statistical methods and interpretation of results. Finally, we made a few proposals for continued microbiome research in ALS, with the aim to provide valid, reproducible, and translatable findings.

Glutathione in the Nervous System as a Potential Therapeutic Target to Control the Development and Progression of Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a rare neurological disorder that affects the motor neurons responsible for regulating muscle movement. However, the molecular pathogenic mechanisms of ALS remain poorly understood. A deficiency in the antioxidant tripeptide glutathione (GSH) in the nervous system appears to be involved in several neurodegenerative diseases characterized by the loss of neuronal cells. Impaired antioxidant defense systems, and the accumulation of oxidative damage due to increased dysfunction in GSH homeostasis are known to be involved in the development and progression of ALS. Aberrant GSH metabolism and redox status following oxidative damage are also associated with various cellular organelles, including the mitochondria and nucleus, and are crucial factors in neuronal toxicity induced by ALS. In this review, we provide an overview of the implications of imbalanced GSH homeostasis and its molecular characteristics in various experimental models of ALS.

Quantitative analysis of γ-glutamylisoleucine, γ-glutamylthreonine, and γ-glutamylvaline in HeLa cells using UHPLC-MS/MS

γ-Glutamylpeptides have been identified as potential biomarkers for a number of diseases including cancer, diabetes, and liver disease. In this study, we developed and validated a novel quantitative analytical strategy for measuring γ-glutamylisoleucine, γ-glutamylthreonine, and γ-glutamylvaline, all of which have been previously reported as potential biomarkers for prostate cancer in HeLa cells using ultra-high-performance liquid chromatography-tandem mass spectrometry. A BEH C18 column was used as the stationary phase. Mobile phase A was 99:1 water:formic acid and mobile phase B was acetonitrile. Chemical isotope labeling using benzoyl chloride was used as the internal standardization strategy. Sample preparation consisted of the addition of water to a frozen cell pellet, sonication, derivatization, centrifugation, and subsequent addition of an internal standard solution. The method was validated for selectivity, accuracy, precision, linearity, and stability. The determined concentrations of γ-glutamylisoleucine, γ-glutamylthreonine, and γ-glutamylvaline in HeLa cells were 1.92 ± 0.06, 10.8 ± 0.4, and 1.96 ± 0.04 pmol/mg protein, respectively. In addition, the qualitative analysis of these analytes in human serum was achieved using a modified sample preparation strategy. To the best of our knowledge, this is the first report of the use of benzoyl chloride for chemical isotope labeling for metabolite quantitation in cells.

Untargeted metabolomics yields insight into ALS disease mechanisms

OBJECTIVE

To identify dysregulated metabolic pathways in amyotrophic lateral sclerosis (ALS) versus control participants through untargeted metabolomics.

METHODS

Untargeted metabolomics was performed on plasma from ALS participants (n=125) around 6.8 months after diagnosis and healthy controls (n=71). Individual differential metabolites in ALS cases versus controls were assessed by Wilcoxon rank-sum tests, adjusted logistic regression and partial least squares-discriminant analysis (PLS-DA), while group lasso explored sub-pathway-level differences. Adjustment parameters included sex, age and body mass index (BMI). Metabolomics pathway enrichment analysis was performed on metabolites selected by the above methods. Finally, machine learning classification algorithms applied to group lasso-selected metabolites were evaluated for classifying case status.

RESULTS

There were no group differences in sex, age and BMI. Significant metabolites selected were 303 by Wilcoxon, 300 by logistic regression, 295 by PLS-DA and 259 by group lasso, corresponding to 11, 13, 12 and 22 enriched sub-pathways, respectively. 'Benzoate metabolism', 'ceramides', 'creatine metabolism', 'fatty acid metabolism (acyl carnitine, polyunsaturated)' and 'hexosylceramides' sub-pathways were enriched by all methods, and 'sphingomyelins' by all but Wilcoxon, indicating these pathways significantly associate with ALS. Finally, machine learning prediction of ALS cases using group lasso-selected metabolites achieved the best performance by regularised logistic regression with elastic net regularisation, with an area under the curve of 0.98 and specificity of 83%.

CONCLUSION

In our analysis, ALS led to significant metabolic pathway alterations, which had correlations to known ALS pathomechanisms in the basic and clinical literature, and may represent important targets for future ALS therapeutics.

Metabolomics: A Tool to Understand the Impact of Genetic Mutations in Amyotrophic Lateral Sclerosis

Metabolomics studies performed in patients with amyotrophic lateral sclerosis (ALS) reveal a set of distinct metabolites that can shed light on the pathological alterations taking place in each individual. Metabolites levels are influenced by disease status, and genetics play an important role both in familial and sporadic ALS cases. Metabolomics analysis helps to unravel the differential impact of the most common ALS-linked genetic mutations (as C9ORF72, SOD1, TARDBP, and FUS) in specific signaling pathways. Further, studies performed in genetic models of ALS reinforce the role of TDP-43 pathology in the vast majority of ALS cases. Studies performed in differentiated cells from ALS-iPSC (induced Pluripotent Stem Cells) reveal alterations in the cell metabolism that are also found in ALS models and ultimately in ALS patients. The development of metabolomics approaches in iPSC derived from ALS patients allow addressing and ultimately understanding the pathological mechanisms taking place in any patient. Lately, the creation of a "patient in a dish" will help to identify patients that may benefit from specific treatments and allow the implementation of personalized medicine.