Can Small Molecules Provide Clues on Disease Progression in Cerebrospinal Fluid from Mild Cognitive Impairment and Alzheimer's Disease Patients?
Begoña Talavera AndújarArnaud MaryCarmen VenegasTiejun ChengLeonid ZaslavskyEvan E BoltonMichael T HenekaEmma L SchymanskiPublished in: Environmental science & technology (2024)
Alzheimer's disease (AD) is a complex and multifactorial neurodegenerative disease, which is currently diagnosed via clinical symptoms and nonspecific biomarkers (such as Aβ 1-42 , t-Tau, and p-Tau) measured in cerebrospinal fluid (CSF), which alone do not provide sufficient insights into disease progression. In this pilot study, these biomarkers were complemented with small-molecule analysis using non-target high-resolution mass spectrometry coupled with liquid chromatography (LC) on the CSF of three groups: AD, mild cognitive impairment (MCI) due to AD, and a non-demented (ND) control group. An open-source cheminformatics pipeline based on MS-DIAL and patRoon was enhanced using CSF- and AD-specific suspect lists to assist in data interpretation. Chemical Similarity Enrichment Analysis revealed a significant increase of hydroxybutyrates in AD, including 3-hydroxybutanoic acid, which was found at higher levels in AD compared to MCI and ND. Furthermore, a highly sensitive target LC-MS method was used to quantify 35 bile acids (BAs) in the CSF, revealing several statistically significant differences including higher dehydrolithocholic acid levels and decreased conjugated BA levels in AD. This work provides several promising small-molecule hypotheses that could be used to help track the progression of AD in CSF samples.
Keyphrases
- mild cognitive impairment
- cerebrospinal fluid
- cognitive decline
- small molecule
- liquid chromatography
- high resolution mass spectrometry
- mass spectrometry
- end stage renal disease
- multiple sclerosis
- tandem mass spectrometry
- machine learning
- protein protein
- peritoneal dialysis
- photodynamic therapy
- simultaneous determination
- ultra high performance liquid chromatography
- deep learning
- prognostic factors
- living cells
- fluorescent probe