Verónica Peña Martínez

Ms. Verónica Peña Martínez


Research Focus & Metrics

Academic Career Length

3Years (2024-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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5 June 2024 in Life
Verified
Journal Article
Open access
PDF file
LBLuis Daniel Bernal-Conde
Luis Daniel Bernal-Conde
VMVerónica Peña Martínez
Verónica Peña Martínez
CMC. Alejandra Morato-Torres
C. Alejandra Morato-Torres
RRRodrigo Ramos-Acevedo
Rodrigo Ramos-Acevedo
Oscar Arias-CarriónOscar Arias-Carrión
Oscar Arias-Carrión
MGMagdalena Guerra-Crespo
Magdalena Guerra-Crespo
Parkinson’s disease (PD) caused by SNCA gene triplication (3XSNCA) leads to early onset, rapid progression, and often dementia. Understanding the impact of 3XSNCA and its absence is crucial. This study investigates the differentiation of human induced pluripotent stem cell (hiPSC)-derived floor-plate progenitors into dopaminergic neurons. Three different genotypes were evaluated in this study: patient-derived hiPSCs with 3XSNCA, a gene-edited isogenic line with a frame-shift mutation on all SNCA alleles (SNCA 4KO), and a normal wild-type control. Our aim was to assess how the substantia nigra pars compacta (SNpc) microenvironment, damaged by 6-hydroxydopamine (6-OHDA), influences tyrosine hydroxylase-positive (Th+) neuron differentiation in these genetic variations. This study confirms successful in vitro differentiation into neuronal lineage in all cell lines. However, the SNCA 4KO line showed unusual LIM homeobox transcription factor 1 alpha (Lmx1a) extranuclear distribution. Crucially, both 3XSNCA and SNCA 4KO lines had reduced Th+ neuron expression, despite initial successful neuronal differentiation after two months post-transplantation. This indicates that while the SNpc environment supports early neuronal survival, SNCA gene alterations—either amplification or knock-out—negatively impact Th+ dopaminergic neuron maturation. These findings highlight SNCA’s critical role in PD and underscore the value of hiPSC models in studying neurodegenerative diseases.