Translational models of stress and resilience: An applied neuroscience methodology review

Abstract

Stress, encompassing psychological, physical, and physiological challenges, is an important factor affecting an individual's well-being and potentially leading to psychiatric, neurodegenerative, immune, and metabolic disorders. However, not everyone exposed to stress develops these conditions, highlighting the concept of resilience. Resilience is a dynamic process categorized into four dimensions: pre-existing resilience capacity, ongoing resilience processes, post-stress resilience outcomes, and recovery from psychopathologies. These dimensions involve genomic, cellular, and systemic interactions influenced by genetic factors, early life experiences, adult life experiences in addition to community/environmental factors, and health behaviors. The biological response to stress encompasses endocrine, autonomic, immunological, and behavioral components, modulated by stressor characteristics and individual traits. Due to the limitations in studying stress and resilience in humans, translational models using rodents and cell cultures are essential. Rodent models include acute, chronic, and traumatic stress paradigms, aiding the study of stress-related behavioral and molecular outcomes. Additionally, early life stress models, such as prenatal stress and maternal separation, provide insights into developmental impacts. In this review, first, rodent models for lifelong stress exposure will be summarized considering their validity, advantages, and limitations. Subsequently, an overview of models designed to enhance resilience capacity and process in rodents, and later the behavioral models employed to study the outcomes of resilience will be given. Lastly, the focus will be shifted to cell culture and iPSCs models. Finally, future considerations focused on improving translational models used to study stress and resilience will be discussed. It is aimed to provide an overview of designs for translational stress and resilience models to access more effective translational biomarkers associated with stress and resilience. Stress and resilience are complex phenomena influenced by various factors, spanning molecular to behavioral levels. Integrating data across dimensions remains crucial for unraveling the complexities of stress-related disorders and resilience.