Abstract
Background: Neurodegenerative diseases (NDDs) are the leading cause of disability worldwide while their metabolic pathogenesis is unclear. Genome-wide association studies (GWASs) offer an unprecedented opportunity to untangle the relationship between metabolites and NDDs.Methods: By leveraging two-sample Mendelian randomization (MR) approaches and relying on GWASs summary statistics, we here explore the causal association between 486 metabolites and five NDDs including Alzheimer’s Disease (AD), amyotrophic lateral sclerosis (ALS), frontotemporal dementia (FTD), Parkinson’s disease (PD), and multiple sclerosis (MS). We validated our MR results with extensive sensitive analyses including MR-PRESSO and MR-Egger regression. We also performed linkage disequilibrium score regression (LDSC) and colocalization analyses to distinguish causal metabolite-NDD associations from genetic correlation and LD confounding of shared causal genetic variants. Finally, a metabolic pathway analysis was further conducted to identify potential metabolite pathways.Results: We detected 164 metabolites which were suggestively associated with the risk of NDDs. Particularly, 2-methoxyacetaminophen sulfate substantially affected ALS (OR = 0.971, 95%CIs: 0.961 ∼ 0.982, FDR = 1.04E-4) and FTD (OR = 0.924, 95%CIs: 0.885 ∼ 0.964, FDR = 0.048), and X-11529 (OR = 1.604, 95%CIs: 1.250 ∼ 2.059, FDR = 0.048) and X-13429 (OR = 2.284, 95%CIs: 1.457 ∼ 3.581, FDR = 0.048) significantly impacted FTD. These associations were further confirmed by the weighted median and maximum likelihood methods, with MR-PRESSO and the MR-Egger regression removing the possibility of pleiotropy. We also observed that ALS or FTD can alter the metabolite levels, including ALS and FTD on 2-methoxyacetaminophen sulfate. The LDSC and colocalization analyses showed that none of the identified associations could be driven by genetic correlation or confounding by LD with common causal loci. Multiple metabolic pathways were found to be involved in NDDs, such as “urea cycle” (P = 0.036), “arginine biosynthesis” (P = 0.004) on AD and “phenylalanine, tyrosine and tryptophan biosynthesis” (P = 0.046) on ALS.Conclusion: our study reveals robust bidirectional causal associations between servaral metabolites and neurodegenerative diseases, and provides a novel insight into metabolic mechanism for pathogenesis and therapeutic strategies of these diseases.
Highlights
Neurodegenerative diseases (NDDs) are the leading cause of disability worldwide while their metabolic pathogenesis is unclear
It was demonstrated lipids and amino acids were associated with cognitive decline and the progression of dementia (Jiang et al, 2019); primary fatty amides in plasma were associated with brain amyloid burden and memory (Kim et al, 2019); blood metabolite changes in the periphery reflected the asymptomatic, prodromal and symptomatic stages of memory and Alzheimer’s disease (AD) (Kiddle et al, 2014; Mapstone et al, 2014)
We identified a total of 164 suggestive associations (136 unique metabolites) (P < 0.05), including 99 associations for 85 known metabolites and 65 associations for 51 unknown metabolites (Supplementary Table 3)
Summary
Neurodegenerative diseases (NDDs) are the leading cause of disability worldwide while their metabolic pathogenesis is unclear. There is a growing literature indicating that profiling metabolites in biofluids offers deep insights into biomarkers of NDDs (Wang et al, 2012; Mendelsohn and Larrick, 2013; Jové et al, 2014; González-Domínguez et al, 2015; Kori et al, 2016; To et al, 2019; Chatterjee et al, 2020; Shang et al, 2020) It was demonstrated lipids and amino acids were associated with cognitive decline and the progression of dementia (Jiang et al, 2019); primary fatty amides in plasma were associated with brain amyloid burden and memory (Kim et al, 2019); blood metabolite changes in the periphery reflected the asymptomatic, prodromal and symptomatic stages of memory and AD (Kiddle et al, 2014; Mapstone et al, 2014). Due Abbreviations: NDD, neurodegenerative disease; GWAS, genome-wide association study; MR, Mendelian randomization; AD, Alzheimer’ s Disease; ALS, amyotrophic lateral sclerosis; FTD, frontotemporal dementia; PD, Parkinson’ s disease; MS, multiple sclerosis; MR-PRESSO, Mendelian Randomization Pleiotropy RESidual Sum and Outlier; LDSC, linkage disequilibrium score regression; LD, linkage disequilibrium; FDR, false discover rate; SNP, single nucleotide polymorphisms; PVE, phenotypic variance explained; IVW, inverse-variance-weighted
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