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1.
Int J Mol Sci ; 24(19)2023 Oct 09.
Artículo en Inglés | MEDLINE | ID: mdl-37834458

RESUMEN

Alzheimer's disease (AD) is a growing global health crisis affecting millions and incurring substantial economic costs. However, clinical diagnosis remains challenging, with misdiagnoses and underdiagnoses being prevalent. There is an increased focus on putative, blood-based biomarkers that may be useful for the diagnosis as well as early detection of AD. In the present study, we used an unbiased combination of machine learning and functional network analyses to identify blood gene biomarker candidates in AD. Using supervised machine learning, we also determined whether these candidates were indeed unique to AD or whether they were indicative of other neurodegenerative diseases, such as Parkinson's disease (PD) and amyotrophic lateral sclerosis (ALS). Our analyses showed that genes involved in spliceosome assembly, RNA binding, transcription, protein synthesis, mitoribosomes, and NADH dehydrogenase were the best-performing genes for identifying AD patients relative to cognitively healthy controls. This transcriptomic signature, however, was not unique to AD, and subsequent machine learning showed that this signature could also predict PD and ALS relative to controls without neurodegenerative disease. Combined, our results suggest that mRNA from whole blood can indeed be used to screen for patients with neurodegeneration but may be less effective in diagnosing the specific neurodegenerative disease.


Asunto(s)
Enfermedad de Alzheimer , Esclerosis Amiotrófica Lateral , Enfermedades Neurodegenerativas , Enfermedad de Parkinson , Humanos , Enfermedad de Alzheimer/diagnóstico , Enfermedad de Alzheimer/genética , Enfermedad de Alzheimer/metabolismo , Esclerosis Amiotrófica Lateral/diagnóstico , Esclerosis Amiotrófica Lateral/genética , Esclerosis Amiotrófica Lateral/metabolismo , Transcriptoma , Enfermedad de Parkinson/diagnóstico , Enfermedad de Parkinson/genética , Enfermedad de Parkinson/metabolismo , Biomarcadores/metabolismo
2.
J Parkinsons Dis ; 13(8): 1303-1311, 2023.
Artículo en Inglés | MEDLINE | ID: mdl-38143373

RESUMEN

BACKGROUND: Multiple system atrophy (MSA) is a rapidly progressive neurodegenerative disease clinically characterized by parkinsonism, cerebellar ataxia, and autonomic dysfunction. A major pathological feature of MSA is the presence of α-synuclein aggregates in oligodendrocytes, the myelinating cells of the central nervous system. A genome-wide association study revealed that the CDH4 gene is associated with MSA. However, virtually nothing is known about the role of CDH4 in the context of MSA. OBJECTIVE: Our aim was to compare the expression of CDH4 between MSA and control brains, and to investigate its relationship with α-synuclein in oligodendrocytes. METHODS: RNA and protein were prepared from putamen, motor cortex white matter, cerebellum, and superior occipital cortex tissues collected from MSA (N = 11) and control (N = 13) brains. The expression of CDH4 was measured at mRNA and protein levels by qPCR and western blotting. Oligodendrocyte cells were cultured on plates and transfected with CDH4 cDNA and its impact on α-synuclein was analyzed. RESULTS: Firstly, we found that CDH4 in MSA brain was significantly elevated in the disease-affected motor cortex white matter in MSA (N = 11) compared to controls (N = 13) and unaltered in the disease-unaffected superior occipital cortex. Secondly, we determined that increases in CDH4 expression caused changes in the cellular levels of α-synuclein in oligodendrocytes. CONCLUSIONS: When put together, these results provide evidence that support the GWAS association of CDH4 with MSA.


Asunto(s)
Cadherinas , Atrofia de Múltiples Sistemas , Enfermedad de Parkinson , Humanos , alfa-Sinucleína/genética , alfa-Sinucleína/metabolismo , Encéfalo/metabolismo , Estudio de Asociación del Genoma Completo , Atrofia de Múltiples Sistemas/metabolismo , Enfermedad de Parkinson/metabolismo , Cadherinas/genética , Cadherinas/metabolismo
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