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Context-dependent biological variation presents a unique challenge to the reproducibility of results in experimental animal research, because organisms’ responses to experimental treatments can vary with both genotype and environmental conditions. In March 2019, experts in animal biology, experimental design and statistics convened in Blonay, Switzerland, to discuss strategies addressing this challenge. In contrast to the current gold standard of rigorous standardization in experimental animal research, we recommend the use of systematic heterogenization of study samples and conditions by actively incorporating biological variation into study design through diversifying study samples and conditions. Here we provide the scientific rationale for this approach in the hope that researchers, regulators, funders and editors can embrace this paradigm shift. We also present a road map towards better practices in view of improving the reproducibility of animal research.In this Perspective, Hanno Würbel and colleagues argue that a disregard for incorporating biological variation in study design is an important cause of poor reproducibility in animal research. They put the case for the use of systematic heterogenization of study samples and conditions in studies to improve reproducibility.

The influence of protocol standardization between laboratories on their replicability of preclinical results has not been addressed in a systematic way. While standardization is considered good research practice as a means to control for undesired external noise (i.e., highly variable results), some reports suggest that standardized protocols may lead to idiosyncratic results, thus undermining replicability. Through the EQIPD consortium, a multi-lab collaboration between academic and industry partners, we aimed to elucidate parameters that impact the replicability of preclinical animal studies. To this end, 3 experimental protocols were implemented across 7 laboratories. The replicability of results was determined using the distance travelled in an open field after administration of pharmacological compounds known to modulate locomotor activity (MK-801, diazepam, and clozapine) in C57BL/6 mice as a worked example. The goal was to determine whether harmonization of study protocols across laboratories improves the replicability of the results and whether replicability can be further improved by systematic variation (heterogenization) of 2 environmental factors (time of testing and light intensity during testing) within laboratories. Protocols were tested in 3 consecutive stages and differed in the extent of harmonization across laboratories and standardization within laboratories: stage 1, minimally aligned across sites (local protocol); stage 2, fully aligned across sites (harmonized protocol) with and without systematic variation (standardized and heterogenized cohort); and stage 3, fully aligned across sites (standardized protocol) with a different compound. All protocols resulted in consistent treatment effects across laboratories, which were also replicated within laboratories across the different stages. Harmonization of protocols across laboratories reduced between-lab variability substantially compared to each lab using their local protocol. In contrast, the environmental factors chosen to introduce systematic variation within laboratories did not affect the behavioral outcome. Therefore, heterogenization did not reduce between-lab variability further compared to the harmonization of the standardized protocol. Altogether, these findings demonstrate that subtle variations between lab-specific study protocols may introduce variation across independent replicate studies even after protocol harmonization and that systematic heterogenization of environmental factors may not be sufficient to account for such between-lab variation. Differences in replicability of results within and between laboratories highlight the ubiquity of study-specific variation due to between-lab variability, the importance of transparent and fine-grained reporting of methodologies and research protocols, and the importance of independent study replication.

Mesenchymal stem cell (MSC) administration via the intranasal route could become an effective therapy to treat neonatal hypoxic-ischemic (HI) brain damage. We analyzed long-term effects of intranasal MSC treatment on lesion size, sensorimotor and cognitive behavior, and determined the therapeutic window and dose response relationships. Furthermore, the appearance of MSCs at the lesion site in relation to the therapeutic window was examined. Nine-day-old mice were subjected to unilateral carotid artery occlusion and hypoxia. MSCs were administered intranasally at 3, 10 or 17 days after hypoxia-ischemia (HI). Motor, cognitive and histological outcome was investigated. PKH-26 labeled cells were used to localize MSCs in the brain. We identified 0.5 × 10(6) MSCs as the minimal effective dose with a therapeutic window of at least 10 days but less than 17 days post-HI. A single dose was sufficient for a marked beneficial effect. MSCs reach the lesion site within 24 h when given 3 or 10 days after injury. However, no MSCs were detected in the lesion when administered 17 days following HI. We also show for the first time that intranasal MSC treatment after HI improves cognitive function. Improvement of sensorimotor function and histological outcome was maintained until at least 9 weeks post-HI. The capacity of MSCs to reach the lesion site within 24 h after intranasal administration at 10 days but not at 17 days post-HI indicates a therapeutic window of at least 10 days. Our data strongly indicate that intranasal MSC treatment may become a promising non-invasive therapeutic tool to effectively reduce neonatal encephalopathy.

Many psychiatric and neurological disorders present deficits in both the social and cognitive domain. In this perspectives article, we provide an overview and the potential of the existence of an extensive neurobiological substrate underlying the close relationship between these two domains. By mapping the rodent brain regions involved in the social and/or cognitive domain, we show that the vast majority of brain regions involved in the cognitive domain are also involved in the social domain. The identified neuroanatomical overlap has an evolutionary basis, as complex social behavior requires cognitive skills, and aligns with the reported functional interactions of processes underlying cognitive and social performance. Based on the neuroanatomical mapping, recent (pre-)clinical findings, and the evolutionary perspective, we emphasize that the social domain requires more focus as an important treatment target and/or biomarker, especially considering the presently limited treatment strategies for these disorders.

Recently the 1/f signal of human electroencephalography has attracted attention, as it could potentially reveal a quantitative measure of neural excitation and inhibition in the brain, that may be relevant in a clinical setting. The purpose of this short article is to show that the 1/f signal depends on the vigilance state of the brain in both humans and mice. Therefore, proper labelling of the EEG signal is important as improper labelling may obscure disease-related changes in the 1/f signal. We demonstrate this by comparing EEG results from a longitudinal study in a genetic mouse model for synaptic dysfunction in schizophrenia and autism spectrum disorders to results from a large European cohort study with schizophrenia and mild Alzheimer’s disease patients. The comparison shows when the 1/f is corrected for vigilance state there is a difference between groups, and this effect disappears when vigilance state is not corrected for. In conclusion, more attention should be paid to the vigilance state during analysis of EEG signals regardless of the species.

The Drd2 gene, encoding the dopamine D 2 receptor (D2R), was recently indicated as a potential target in the etiology of lowered sociability (i.e., social withdrawal), a symptom of several neuropsychiatric disorders such as Schizophrenia and Major Depression. Many animal species show social withdrawal in response to stimuli, including the vinegar fly Drosophila melanogaster and mice, which also share most human disease-related genes. Here we will test for causality between Drd2 and sociability and for its evolutionary conserved function in these two distant species, as well as assess its mechanism as a potential therapeutic target. During behavioral observations in groups of freely interacting D. melanogaster , Drd2 homologue mutant showed decreased social interactions and locomotor activity. After confirming Drd2 ’s social effects in flies, conditional transgenic mice lacking Drd2 in dopaminergic cells (autoreceptor KO) or in serotonergic cells (heteroreceptor KO) were studied in semi-natural environments, where they could freely interact. Autoreceptor KOs showed increased sociability, but reduced activity, while no overall effect of Drd2 deletion was observed in heteroreceptor KOs. To determine acute effects of D2R signaling on sociability, we also showed that a direct intervention with the D2R agonist Sumanirole decreased sociability in wild type mice, while the antagonist showed no effects. Using a computational ethological approach, this study demonstrates that Drd2 regulates sociability across evolutionary distant species, and that activation of the mammalian D2R autoreceptor, in particular, is necessary for social functioning.

There is growing evidence of a shared pathogenesis between Alzheimer’s disease and depression. Therefore, we aimed to further investigate their shared disease mechanisms. We made use of publicly available brain-specific eQTL data and gene co-expression networks of previously reported genetic loci associated with these highly comorbid disorders. No direct genetic overlap was observed between Alzheimer’s disease and depression in our dataset, but we did detect six shared brain-specific eQTL genes: SRA1 , MICA , PCDHA7, PCDHA8, PCDHA10 and PCDHA13 . Several pathways were identified as shared between Alzheimer’s disease and depression by conducting clustering pathway analysis on hippocampal co-expressed genes; synaptic signaling and organization, myelination, development, and the immune system. This study highlights trans-synaptic signaling and synaptoimmunology in the hippocampus as main shared pathomechanisms of Alzheimer’s disease and depression.

Anorexia nervosa (AN) and obsessive–compulsive disorder (OCD) are often comorbid and likely to share genetic risk factors. Hence, we examine their shared genetic background using a cross-disorder GWAS meta-analysis of 3495 AN cases, 2688 OCD cases, and 18,013 controls. We confirmed a high genetic correlation between AN and OCD (rg = 0.49 ± 0.13, p = 9.07 × 10−7) and a sizable SNP heritability (SNP h2 = 0.21 ± 0.02) for the cross-disorder phenotype. Although no individual loci reached genome-wide significance, the cross-disorder phenotype showed strong positive genetic correlations with other psychiatric phenotypes (e.g., rg = 0.36 with bipolar disorder and 0.34 with neuroticism) and negative genetic correlations with metabolic phenotypes (e.g., rg = −0.25 with body mass index and −0.20 with triglycerides). Follow-up analyses revealed that although AN and OCD overlap heavily in their shared risk with other psychiatric phenotypes, the relationship with metabolic and anthropometric traits is markedly stronger for AN than for OCD. We further tested whether shared genetic risk for AN/OCD was associated with particular tissue or cell-type gene expression patterns and found that the basal ganglia and medium spiny neurons were most enriched for AN–OCD risk, consistent with neurobiological findings for both disorders. Our results confirm and extend genetic epidemiological findings of shared risk between AN and OCD and suggest that larger GWASs are warranted.

The European Quality In Preclinical Data (EQIPD) consortium was born from the fact that publications report challenges with the robustness, rigor, and/or validity of research data, which may impact decisions about whether to proceed with further preclinical testing or to advance to clinical testing, as well as draw conclusions on the predictability of preclinical models. To address this, a consortium including multiple research laboratories from academia and industry participated in a series of electroencephalography (EEG) experiments in mice aimed to detect sources of variance and to gauge how protocol harmonisation and data analytics impact such variance. Ultimately, the goal of this first ever between-laboratory comparison of EEG recordings and analyses was to validate the principles that supposedly increase data quality, robustness, and comparability. Experiments consisted of a Localisation phase, which aimed to identify the factors that influence between-laboratory variability, a Harmonisation phase to evaluate whether harmonisation of standardized protocols and centralised processing and data analysis reduced variance, and a Ring-Testing phase to verify the ability of the harmonised protocol to generate consistent findings. Indeed, between-laboratory variability reduced from Localisation to Harmonisation and this reduction remained during the Ring-Testing phase. Results obtained in this multicentre preclinical qEEG study also confirmed the complex nature of EEG experiments starting from the surgery and data collection through data pre-processing to data analysis that ultimately influenced the results and contributed to variance in findings across laboratories. Overall, harmonisation of protocols and centralized data analysis were crucial in reducing laboratory-to-laboratory variability. To this end, it is recommended that standardized guidelines be updated and followed for collection and analysis of preclinical EEG data.

Manual scoring of longitudinal electroencephalographical (EEG) data is a slow and time-consuming process. Current advances in the application of machine-learning and artificial intelligence to EEG data are moving fast; however, there is still a need for expert raters to validate scoring of EEG data. We hypothesized that power-frequency profiles are determining the state and ‘set the framework’ for communication between neurons. Based on these assumptions, a scoring method with a set frequency profile for each vigilance state, both in sleep and awake, was developed and validated. We defined seven states of the functional brain with unique profiles in terms of frequency-power spectra, coherence, phase-amplitude coupling, α exponent, functional excitation-inhibition balance (fE/I), and aperiodic exponent. The new method requires a manual check of wake–sleep transitions and is therefore considered semi-automatic. This semi-automatic approach showed similar α exponent and fE/I when compared to traces scored manually. The new method was faster than manual scoring, and the advanced outcomes of each state were stable across datasets and epoch length. When applying the new method to the neurexin-1α ( Nrxn1α ) gene deficient mouse, a model of synaptic dysfunction relevant to autism spectrum disorders, several genotype differences in the 24-h distribution of vigilance states were detected. Most prominent was the decrease in slow-wave sleep when comparing wild-type mice to Nrxn1α -deficient mice. This new methodology puts forward an optimized and validated EEG analysis pipeline for the identification of translational electrophysiological biomarkers for brain disorders that are related to sleep architecture and E/I balance.