Publications by authors named "M J Zarco Perinan"
Background And Objectives: In the era of precision medicine, genetic test results have become increasingly relevant in the care of patients with Parkinson disease (PD). While large research consortia are performing widespread research genetic testing to accelerate discoveries, debate continues about whether, and to what extent, the results should be returned to patients. Ethically, it is imperative to keep participants informed, especially when findings are potentially actionable.
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- Copy Number Variations (CNVs) are crucial in understanding complex diseases and vary across different populations, necessitating large sample studies for accurate analysis.
- The CNV-Finder pipeline utilizes deep learning, specifically Long Short-Term Memory (LSTM) networks, to streamline the identification of CNVs in specific genomic areas, making subsequent analyses like genome sequencing more efficient.
- The tool has been validated with data from various cohorts, focusing on genes related to neurological diseases, and includes an interactive web application for researchers to visualize and refine their findings based on model predictions.
Background And Purpose: Parkinson disease (PD) is a complex and heterogeneous neurodegenerative disorder with a broad spectrum of clinical manifestations, determined by a complex interplay of environmental and genetic factors. This study aimed to investigate genetic variants associated with PD and assess their impact on the disease phenotype through genotype-phenotype correlations.
Methods: We employed a targeted resequencing panel to analyze 27 genes linked to PD in a cohort of 1185 PD patients from southern Spain.