期刊
METABOLITES
卷 12, 期 6, 页码 -出版社
MDPI
DOI: 10.3390/metabo12060475
关键词
Alzheimer's disease; cerebrospinal fluid; MTHFD1; folate; single nucleotide polymorphism
资金
- African Healthcare Development Trust
- Waite Hydrocephalus Student Research Bursary from the Society for Research into Hydrocephalus and Spina Bifida
- CharlesWolfson Charitable Trust
Metabolic disorders may contribute to the development of Alzheimer's disease (AD). Changes in cerebrospinal fluid and cerebral folate metabolism are associated with AD. This study found that a specific SNP in the MTHFD1 gene is significantly predictive of AD and is associated with increased tissue glutathione. Other genes related to folate and aging are also associated with AD. These findings provide potential biomarkers for identifying individuals at risk for AD.
Metabolic disorders may be important potential causative pathways to Alzheimer's disease (AD). Cerebrospinal fluid (CSF) decreasing output, raised intracranial pressure, and ventricular enlargement have all been linked to AD. Cerebral folate metabolism may be a key player since this is significantly affected by such changes in CSF, and genetic susceptibilities may exist in this pathway. In the current study, we aimed to identify whether any single nucleotide polymorphism (SNPs) affecting folate and the associated metabolic pathways were significantly associated with AD. We took a functional nutrigenomics approach to look for SNPs in genes for the linked folate, methylation, and biogenic amine neurotransmitter pathways. Changes in metabolism were found with the SNPs identified. An abnormal SNP in methylene tetrahydrofolate dehydrogenase 1 (MTHFD1) was significantly predictive of AD and associated with an increase in tissue glutathione. Individuals without these SNPs had normal levels of glutathione but significantly raised MTHFD1. Both changes would serve to decrease potentially neurotoxic levels of homocysteine. Seven additional genes were associated with Alzheimer's and five with normal ageing. MTHFD1 presents a strong prediction of susceptibility and disease among the SNPs associated with AD. Associated physiological changes present potential biomarkers for identifying at-risk individuals.
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