Systematic review and meta-analysis of 10 years of unpredictable chronic stress in zebrafish.

The zebrafish (Danio rerio) is a model animal that is being increasingly used in neuroscience research. A decade ago, the first study on unpredictable chronic stress (UCS) in zebrafish was published, inspired by protocols established for rodents in the early 1980s. Since then, several studies have been published by different groups, in some cases with conflicting results. Here we conducted a systematic review to identify studies evaluating the effects of UCS in zebrafish and meta-analytically synthetized the data of neurobehavioral outcomes and relevant biomarkers. Literature searches were performed in three databases (PubMed, Scopus and Web of Science) with a two-step screening process based on inclusion/exclusion criteria. The included studies underwent extraction of qualitative and quantitative data, as well as risk-of-bias assessment. Outcomes of included studies (n = 38) were grouped into anxiety/fear-related behavior, locomotor function, social behavior or cortisol level domains. UCS increased anxiety/fear-related behavior and cortisol levels while decreasing locomotor function, but a significant summary effect was not observed for social behavior. Despite including a substantial number of studies, the high heterogeneity and the methodological and reporting problems evidenced in the risk-of-bias analysis made it difficult to assess the internal validity of most studies and the overall validity of the model. Our review thus evidences the need to conduct well-designed experiments to better evaluate the effects of UCS on diverse behavioral patterns displayed by zebrafish.

Site effects how-to and when: An overview of retrospective techniques to accommodate site effects in multi-site neuroimaging analyses.

Site differences, or systematic differences in feature distributions across multiple data-acquisition sites, are a known source of heterogeneity that may adversely affect large-scale meta- and mega-analyses of independently collected neuroimaging data. They influence nearly all multi-site imaging modalities and biomarkers, and methods to compensate for them can improve reliability and generalizability in the analysis of genetics, omics, and clinical data. The origins of statistical site effects are complex and involve both technical differences (scanner vendor, head coil, acquisition parameters, imaging processing) and differences in sample characteristics (inclusion/exclusion criteria, sample size, ancestry) between sites. In an age of expanding international consortium research, there is a growing need to disentangle technical site effects from sample characteristics of interest. Numerous statistical and machine learning methods have been developed to control for, model, or attenuate site effects - yet to date, no comprehensive review has discussed the benefits and drawbacks of each for different use cases. Here, we provide an overview of the different existing statistical and machine learning methods developed to remove unwanted site effects from independently collected neuroimaging samples. We focus on linear mixed effect models, the ComBat technique and its variants, adjustments based on image quality metrics, normative modeling, and deep learning approaches such as generative adversarial networks. For each method, we outline the statistical foundation and summarize strengths and weaknesses, including their assumptions and conditions of use. We provide information on software availability and comment on the ease of use and the applicability of these methods to different types of data. We discuss validation and comparative reports, mention caveats and provide guidance on when to use each method, depending on context and specific research questions.

Systematic review and meta-analysis of the behavioral effects of methylphenidate in the spontaneously hypertensive rat model of attention-deficit/hyperactivity disorder.

The spontaneously hypertensive rats (SHR) are the most widely used model for ADHD. While face and construct validity are consolidated, questions remain about the predictive validity of the SHR model. We aim at summarizing the evidence for the predictive validity of SHR by evaluating its ability to respond to methylphenidate (MPH), the most well documented treatment for ADHD. A systematic review was carried out to identify studies evaluating MPH effects on SHR behavior. Studies (n=36) were grouped into locomotion, attention, impulsivity or memory, and a meta-analysis was performed. Meta-regression, sensitivity, heterogeneity, and publication bias analyses were also conducted. MPH increased attentional and mnemonic performances in the SHR model and decreased impulsivity in a dose-dependent manner. However, MPH did not reduce hyperactivity in low and medium doses, while increased locomotor activity in high doses. Thus, since the paradoxical effect of stimulant in reducing hyperactivity was not observed in the SHR model, our study does not fully support the predictive validity of SHR, questioning their validity as an animal model for ADHD.

Evidence of sexual dimorphism of HTR1B gene on major adult ADHD comorbidities.

Attention-deficit/hyperactivity disorder (ADHD) is a very common psychiatric disorder across the life cycle and frequently presents comorbidities. Since ADHD is highly heritable, several studies have focused in the underlying genetic factors involved in its etiology. One of the major challenges in this search is the phenotypic heterogeneity, which could be partly attributable to the sexual dimorphism frequently seen in psychiatric disorders. Taking into account the well-known sexual dimorphic effect observed in serotonergic system characteristics, we differentially tested the influence of HTR1B SNPs (rs11568817, rs130058, rs6296 and rs13212041) on ADHD susceptibility and on its major comorbidities according to sex. The sample comprised 564 adults with ADHD diagnosed according to DSM-IV criteria and 635 controls. There was no association of any HTR1B SNPs tested in relation to ADHD susceptibility. As for the comorbidities evaluated, after correction for multiple tests, significant associations were observed for both rs11568817 and rs130058 with substance use disorders (Pcorr = 0.009 and Pcorr = 0.018, respectively) and for rs11568817 with nicotine dependence (Pcorr = 0.025) in men with ADHD. In women with ADHD, the same rs11568817 was associated with generalized anxiety disorder (Pcorr = 0.031). The observed effects of rs11568817 G allele presence conferring risk to either substance use disorders or generalized anxiety disorder according to sex, suggest an overall scenario where a higher transcriptional activity of HTR1B, resulting from the presence of this allele, is related to externalizing behaviors in men and internalizing behaviors in women. These results are consistent with and expand previous evidence of sexual dimorphism of the serotoninergic system.