PhD Scientific Days 2023

Neurosciences - Posters G

Cognitive and Emotional Factors Underlying Comorbid Anxiety and Depression.

Előadó neve

Pejtsik, Diana, MSc

Neptun code

VXMST6

Előadó munkahelye

Institute of Experimental Medicine

Előadó telefonszáma

+36209726773

Előadó e-mail címe

pejtsikdiana@gmail.com

Az előadás címe

Cognitive and Emotional Factors Underlying Comorbid Anxiety and Depression.

Szerző(k) neve és munkahelye

D. Pejtsik1;3, ZK. Varga1, O. Wronikowska2, M. Aliczki1, Zs. Borhegyi1, K. Demeter1, M. Toth1, E. Mikics1
1 Insitute of Experimental Medicine, Laboratory of Translational Behavioural Neuroscience, Budapest
2 Medical University of Lublin, Lublin
3 Semmelweis University, Budapest

Bemutatás módja

Poszter

Szekció

Neurosciences - Posters G

Language of the presentation

English

Preferred session

Neurosciences

Összefoglaló szövege

Anxiety and depression are widespread mental disorders that often co-occur, resulting in more severe and persistent symptoms and less successful pharmacotherapy. To better understand the neurobiological, emotional, and cognitive factors underlying comorbid anxiety and depression (CAD), we aimed to create a mouse model of CAD with high clinical translational validity. We conducted a multi-sampling behavioural battery involving repeated testing with 3 anxiety and 3 coping tests to identify stable traits, followed by a depression model. Using machine learning, the test battery was reduced to three tests that could reproducibly characterise a distinct subpopulation of animals that stably show high trait anxiety, high passive coping, and high learned helplessness, which could model the core symptoms of CAD. Further, to examine the underlying cognitive factors that are associated with stable CAD-like traits, we exposed a new population of mice to an automated home-cage system, where they were tested in cognitive tasks for three months. We found that the comorbid subpopulation was also present in this cohort, and compared to other subgroups, they showed impaired spatial learning, heightened impulsivity, and stronger punishment aversion. Moreover, the comorbid population showed a difference in sensitivity to anxiolytic treatment. In conclusion, we developed a translational model of CAD using machine learning-based reduction of an extensive test battery. We showed that comorbid animals a priori had different emotional and cognitive traits. Further examining the predisposing factors and neurobiology of CAD susceptibility could lead to the development of preventive measures, as well as more effective pharmacotherapy for CAD patients.

This work was supported by the ÚNKP-22-3-I-SE-33 New National Excellence Program of the Ministry for Culture and Innovation from the source of the National Research, Development and Innovation Fund, as well as the Hungarian Brain Research Program Grant No. 2017-1.2.1-NKP-2017-00002 and the Eötvös Loránd Research Network Grant No. SA-49/2021.

University and Doctoral School

Semmelweis University, János Szentágothai Doctoral School of Neurosciences

Supervisor

Dr. Varga Zoltán Kristóf, Dr. Mikics Éva

Publication of my abstract

I do not give consent to the publication of my abstract on the website of the congress.

Kind

Szabad

Status

elfogadva

Accepted presentation method

poszter

Előadás fájl jóváhagyás

nem rendelkezett róla

Előadó

7384

Start

11:30

End

11:35

Authors (legacy)

D. Pejtsik1;3, ZK. Varga1, O. Wronikowska2, M. Aliczki1, Zs. Borhegyi1, K. Demeter1, M. Toth1, E. Mikics1
1 Insitute of Experimental Medicine, Laboratory of Translational Behavioural Neuroscience, Budapest
2 Medical University of Lublin, Lublin
3 Semmelweis University, Budapest