Neuroscience & Biobehavioral ReviewsNeurosciencePeer-reviewed journal article
The behavioral phenotype of early life adversity: a 3-level meta-analysis of rodent studies
Valeria BonapersonaiD, Jiska KentropiD, Caspar J. Van LissaiD, Rixt van der VeeniD, Marian JoëlsiD, Ratna Angela SarabdjitsinghiD
Abstract
1BackgroundAltered cognitive performance has been suggested as an intermediate phenotype mediating the effects of early life adversity (ELA) on later-life development of mental disorders, e.g. depression. Whereas most human studies are limited to correlational conclusions, rodent studies can prospectively investigate how ELA alters cognitive performance in a number of domains. Despite the vast volume of reports, no consensus has yet been reached on the i) behavioral domains being affected by ELA and ii) the extent of these effects.\n\nMethodsTo test how ELA (here: aberrant maternal care) affects specific behavioral domains, we used a 3-level mixed-effect meta-analysis, a flexible model that accounts for the dependency of observations. We thoroughly explored heterogeneity with MetaForest, a machine-learning data-driven analysis never applied before in preclinical literature. We validated the robustness of our findings with substantial sensitivity analyses and bias assessments.\n\nResultsOur results, based on >400 independent experiments, yielded >700 comparisons, involving ~8600 animals. Especially in males, ELA promotes memory formation during stressful learning but impairs non-stressful learning. Furthermore, ELA increases anxiety and decreases social behavior. The ELA phenotype was strongest when i) combined with other negative experiences (\"hits\"); ii) in rats; iii) in ELA models of ~10days duration.\n\nConclusionProspective and well-controlled animal studies demonstrate that ELA durably and differentially impacts distinct behavioral domains. All data is now easily accessible with MaBapp (https://osf.io/ra947/), which allows researchers to run tailor-made meta-analyses on the topic, thereby revealing the optimal choice of experimental protocols and study power.
- organism: rat
- research focus: benchmarking
- approach: statistical model
- approach: machine learning (classical)
- Citations
- 92
- FWCI
- 1.62
- Field percentile
- top 16%
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