PhD Scientific Days 2025
Budapest, 7-9 July 2025
Poster Session I. - Q: Neurosciences
Examining the Cognitive Predictors and Molecular Background of Anxious Depression In a Mouse Model
Előadó neve
Pejtsik Diana, MSc
Neptun code
VXMST6
Előadó munkahelye
HUN-REN Institute of Experimental Medicine
Előadó telefonszáma
+36209726773
Előadó e-mail címe
pejtsikdiana@gmail.com
Az előadás címe
Examining the Cognitive Predictors and Molecular Background of Anxious Depression In a Mouse Model
Szerző(k) neve és munkahelye
Diana Pejtsik MSc1, dr. Zoltan Kristof Varga1, dr. Eva Mikics1
1: HUN-REN Institute of Experimental Medicine
Bemutatás módja
Poszter
Szekció
Poster Session I. - Q: Neurosciences
Language of the presentation
English
Preferred session
Neurosciences
Összefoglaló szövege
When major depressive disorder (MDD) co-occurs with high trait anxiety, it leads to more severe symptoms and reduced effectiveness of pharmacotherapy. The neurobiological mechanisms behind this are not yet fully understood, and there are no sufficient animal models of anxious depression to help with understanding. One of the reasons for this is that clinical diagnoses aim to assess stable traits, while most preclinical tests are only able to measure anxiety- or depression-like behaviors in single sessions, likely capturing transient states rather than stable traits. Therefore, we aimed to characterise traits through repeated behavioral sampling using the most common anxiety- and coping tests. Analyzing multiple large animal cohorts, we found that increasing the variety of test types, repetitions, and variables used strengthened correlations between anxious and coping traits. Further, creating summary scores of different repeated tests for each individual allows for predicting their susceptibility to the learned helplessness depression model (LH). This approach identified subpopulations with stable high trait anxiety, passive coping, and learned helplessness (comorbid), versus those with low anxiety, active coping, and LH resilience (resilient). Using machine learning, we reduced the test battery needed to classify these subpopulations. Applying the reduced model, we have reproduced our results in female mice as well. To understand the cognitive predictors of LH susceptibility, we put animals in the Intellicage, an automated home-cage testing system, which revealed that comorbid animals exhibit impaired spatial learning and cognitive inflexibility. Finally, RNA sequencing of the medial prefrontal cortex and ventral hippocampus showed distinct molecular differences between comorbid and resilient groups, highlighting different mitochondrial, extracellular and translational gene-related expression. Targeting these molecular components may uncover new pharmacotherapeutic interventions for the treatment of anxious depression. Supported by the SE250+ Excellence PhD Scholarship, the Hungarian Brain Research Program 2017-1.2.1-NKP-2017-00002, Eotvos Lorand Research Network SA-49/2021 and National Laboratory of Translational Neuroscience RRF-2.3.1-21-2022-00011
University
Semmelweis University
Supervisor
dr. Mikics Éva
Publication of my abstract
I do not give consent to the publication of my abstract on the website of the congress.
phd.section.field
in doctoral studies after complex exam (PhD)
Kind
Szabad
Status
elfogadva
Accepted presentation method
poszter
Előadás fájl jóváhagyás
nem rendelkezett róla
Előadó
7384
Start
17:00
End
17:06