A translational research framework for enhanced validity of mouse models of psychopathological states in depression

Depression presents as a disorder of feelings and thoughts that debilitate daily functioning and can be life threatening. Increased understanding of these specific emotional-cognitive pathological states and their underlying pathophysiologies and neuropathologies is fundamental to an increased understanding of the disorder and, therefore, to development of much-needed improved therapies. Despite this, there is a current lack of emphasis on development and application of translational (i.e. valid) neuropsychological measures in depression research. The appropriate strategy is neuropsychological research translated, bi-directionally, between epidemiological and clinical human research and in vivo - ex vivo preclinical research conducted, primarily, with mice. This paper presents a translational framework to stimulate and inform such research, in four inter-dependent sections. (1) A depression systems-model describes the pathway between human environment-gene (E-G) epidemiology, pathophysiology, psycho- and neuropathology, symptoms, and diagnosis. This model indicates that G→emotional-cognitive endophenotypes and E-G/endophenotype→emotional-cognitive state markers are central to experimental and translational depression research. (2) Human neuropsychological tests with (potential) translational value for the quantitative study of these endophenotypes and state markers are presented. (3) The analogous rodent behavioural tests are presented and their translational validity in terms of providing analogue emotional-cognitive endophenotypes and state markers are discussed. (4) The need for aetiological validity of mouse models in terms of G→endophenotypes and E-G→state markers is presented. We conclude that the informed application of the proposed neuropsychological translational framework will yield mouse models of high face, construct and aetiological validity with respect to emotional-cognitive dysfunction in depression. These models, together with the available technological tools, can then be studied to increase understanding of depression pathophysiology and neuropathology, leading to identification and validation of novel therapeutic targets and the development of effective, personalized antidepressant treatments.