Proteome analysis of the prefrontal cortex and the application of machine learning models for the identification of potential biomarkers related to suicide
Our exploratory pathway analysis highlighted oxidative stress responses and neurodevelopmental pathways as key processes perturbed in the DLPFC of suicides. Regarding ML models, KNeighborsClassifier was the best predicting conditions. Here we show that these proteins of the DLPFC may help to identify brain processes associated with suicide and they could be validated as potential biomarkers of this outcome.
Authors
- Luis Felipe Jiménez‐García (ORCID: https://orcid.org/0000-0003-2368-2975)
- Nora Gutiérrez-Nájera
- Humberto Nicolini (ORCID: https://orcid.org/0000-0003-2494-0067)
- Ana Luisa Romero-Pimentel (ORCID: https://orcid.org/0000-0002-4530-5364)
- Jonatan Alexis Torres-Campuzano
- Karla Hernández‐Fonseca (ORCID: https://orcid.org/0000-0002-5932-8911)
- Elier González-Sáenz
- Roberto Mendoza-Morales
- Manuel Alejandro Rojo-Romero
- Mirna Edith Morales-Marín (ORCID: https://orcid.org/0000-0001-5460-6284)
- Fernando García‐Dolores (ORCID: https://orcid.org/0000-0003-2976-1877)
- Xóchitl Helga Castro-Martínez
- Carlos Cruz-Fuentes
- Tania Medina-Sánchez
Institutions
- National Institute of Genomic Medicine (MX)
- Instituto Nacional de Psiquiatría Ramón de la Fuente Muñiz (MX)
- Universidad Nacional Autónoma de México (MX)
Publication Details
- Journal
- Frontiers in Psychiatry
- Published
- 2025-02-20
- DOI
- https://doi.org/10.3389/fpsyt.2024.1429953
- Citations
- 1
- Primary Topic
- 14-3-3 protein interactions
- Type
- article
- Field-Weighted Citation Impact
- 0.81
Funders
- Universidad Nacional Autónoma de México