Please use this identifier to cite or link to this item: https://repositorio.uca.edu.ar/handle/123456789/17344
Título : The genetic basis of probable rem sleep behavior disorder in Parkinson’s disease
Autor : Pérez Lloret, Santiago 
Chevalier, Guenson 
Bordet, Sofía 
Barbar, Hanny 
Capani, Francisco 
Udovin, Lucas D. 
Otero Losada, Matilde 
Palabras clave : ENFERMEDAD DE PARKINSONENFERMEDADES NEURODEGENERATIVASPOLIMORFISMO DE NUCLEÓTIDO SIMPLETRASTORNOS DE LA CONDUCTASUEÑO REMFISIOPATOLOGÍA
Fecha de publicación : 2023
Editorial : MDPI
Cita : Perez Lloret, S., Chevalier, G., Bordet, S. et al. The genetic basis of probable rem sleep behavior disorder in Parkinson’s disease [en línea]. Brain Sciences. 2023, 13, 1146. doi: 10.3390/brainsci13081146. Disponible en: https://repositorio.uca.edu.ar/handle/123456789/17344
Resumen : Abstract: Patients with Parkinson’s Disease (PD) experience REM sleep behavior disorder (RBD) more frequently than healthy controls. RBD is associated with torpid disease evolution. To test the hypothesis that differential genetic signatures might contribute to the torpid disease evolution in PD patients with RBD we compared the rate of genetic mutations in PD patients with or without probable RBD. Patients with a clinical diagnosis of PD in the Parkinson’s Progression Markers Initiative (PPMI) database entered the study. We excluded those with missing data, dementia, psychiatric conditions, or a diagnosis change over the first five years from the initial PD diagnosis. Probable RBD (pRBD) was confirmed by a REM Sleep Behavior Disorder Screening Questionnaire score > 5 points. Logistic regression and Machine Learning (ML) algorithms were used to relate Single Nucleotide Polymorphism (SNPs) in PD-related genes with pRBD. We included 330 PD patients fulfilling all inclusion and exclusion criteria. The final logistic multivariate model revealed that the following SNPs increased the risk of pRBD: GBA_N370S_rs76763715 (OR, 95% CI: 3.38, 1.45–7.93), SNCA_A53T_rs104893877 (8.21, 2.26–36.34), ANK2. CAMK2D_rs78738012 (2.12, 1.08–4.10), and ZNF184_rs9468199 (1.89, 1.08–3.33). Conversely, SNP COQ7. SYT17_rs11343 reduced pRBD risk (0.36, 0.15–0.78). The ML algorithms led to similar results. The predictive models were highly specific (95–99%) but lacked sensitivity (9–39%). We found a distinctive genetic signature for pRBD in PD. The high specificity and low sensitivity of the predictive models suggest that genetic mutations are necessary but not sufficient to develop pRBD in PD. Additional investigations are needed.
URI : https://repositorio.uca.edu.ar/handle/123456789/17344
ISSN : 2076-3425
Disciplina: MEDICINA
DOI: 10.3390/brainsci13081146
Derechos: Acceso abierto
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