Mouse model systems of autism spectrum disorder: Replicability and informatics signature.

Phenotyping mouse model systems of human disease has proven to be a difficult task, with frequent poor inter- and intra-laboratory replicability, particularly in behavioral domains such as social and cognitive function. However, establishing robust animal model systems with strong construct validity is of fundamental importance as they are central tools for understanding disease pathophysiology and developing therapeutics. To complete our studies of mouse model systems relevant to autism spectrum disorder (ASD), we present a replication of the main findings from our two published studies of five genetic mouse model systems of ASD. To assess the intra-laboratory robustness of previous results, we chose the two model systems that showed the greatest phenotypic differences, the Shank3/F and Cntnap2, and repeated assessments of general health, activity and social behavior. We additionally explored all five model systems in the same framework, comparing all results obtained in this three-yearlong effort using informatics techniques to assess commonalities and differences. Our results showed high intra-laboratory replicability of results, even for those with effect sizes that were not particularly large, suggesting that discrepancies in the literature may be dependent on subtle but pivotal differences in testing conditions, housing enrichment, or background strains and less so on the variability of the behavioral phenotypes. The overall informatics analysis suggests that in our behavioral assays we can separate the set of tested mouse model system into two main classes that in some aspects lie on opposite ends of the behavioral spectrum, supporting the view that autism is not a unitary concept.

Large-scale phenome analysis defines a behavioral signature for Huntington's disease genotype in mice.

Rapid technological advances for the frequent monitoring of health parameters have raised the intriguing possibility that an individual's genotype could be predicted from phenotypic data alone. Here we used a machine learning approach to analyze the phenotypic effects of polymorphic mutations in a mouse model of Huntington's disease that determine disease presentation and age of onset. The resulting model correlated variation across 3,086 behavioral traits with seven different CAG-repeat lengths in the huntingtin gene (Htt). We selected behavioral signatures for age and CAG-repeat length that most robustly distinguished between mouse lines and validated the model by correctly predicting the repeat length of a blinded mouse line. Sufficient discriminatory power to accurately predict genotype required combined analysis of >200 phenotypic features. Our results suggest that autosomal dominant disease-causing mutations could be predicted through the use of subtle behavioral signatures that emerge in large-scale, combinatorial analyses. Our work provides an open data platform that we now share with the research community to aid efforts focused on understanding the pathways that link behavioral consequences to genetic variation in Huntington's disease.

Comprehensive Analysis of the 16p11.2 Deletion and Null Cntnap2 Mouse Models of Autism Spectrum Disorder.

Autism spectrum disorder comprises several neurodevelopmental conditions presenting symptoms in social communication and restricted, repetitive behaviors. A major roadblock for drug development for autism is the lack of robust behavioral signatures predictive of clinical efficacy. To address this issue, we further characterized, in a uniform and rigorous way, mouse models of autism that are of interest because of their construct validity and wide availability to the scientific community. We implemented a broad behavioral battery that included but was not restricted to core autism domains, with the goal of identifying robust, reliable phenotypes amenable for further testing. Here we describe comprehensive findings from two known mouse models of autism, obtained at different developmental stages, using a systematic behavioral test battery combining standard tests as well as novel, quantitative, computer-vision based systems. The first mouse model recapitulates a deletion in human chromosome 16p11.2, found in 1% of individuals with autism. The second mouse model harbors homozygous null mutations in Cntnap2, associated with autism and Pitt-Hopkins-like syndrome. Consistent with previous results, 16p11.2 heterozygous null mice, also known as Del(7Slx1b-Sept1)4Aam weighed less than wild type littermates displayed hyperactivity and no social deficits. Cntnap2 homozygous null mice were also hyperactive, froze less during testing, showed a mild gait phenotype and deficits in the three-chamber social preference test, although less robust than previously published. In the open field test with exposure to urine of an estrous female, however, the Cntnap2 null mice showed reduced vocalizations. In addition, Cntnap2 null mice performed slightly better in a cognitive procedural learning test. Although finding and replicating robust behavioral phenotypes in animal models is a challenging task, such functional readouts remain important in the development of therapeutics and we anticipate both our positive and negative findings will be utilized as a resource for the broader scientific community.

The potent and selective α4ß2*/α6*-nicotinic acetylcholine receptor partial agonist 2-[5-[5-((S)Azetidin-2-ylmethoxy)-3-pyridinyl]-3-isoxazolyl]ethanol demonstrates antidepressive-like behavior in animal models and a favorable ADME-tox profile.

Preclinical and clinical studies demonstrated that the inhibition of cholinergic supersensitivity through nicotinic antagonists and partial agonists can be used successfully to treat depressed patients, especially those who are poor responders to selective serotonin reuptake inhibitors (SSRIs). In our effort to develop novel antidepressant drugs, LF-3-88 was identified as a potent nicotinic acetylcholine receptor (nAChR) partial agonist with subnanomolar to nanomolar affinities for ß2-containing nAChRs (α2ß2, α3ß2, α4ß2, and α4ß2*) and superior selectivity away from α3ß4 - (K i > 10(4) nmol/L) and α7-nAChRs (K i > 10(4) nmol/L) as well as 51 other central nervous system (CNS)-related neurotransmitter receptors and transporters. Functional activities at different nAChR subtypes were characterized utilizing (86)Rb(+) ion efflux assays, two-electrode voltage-clamp (TEVC) recording in oocytes, and whole-cell current recording measurements. In mouse models, administration of LF-3-88 resulted in antidepressive-like behavioral signatures 15 min post injection in the SmartCube® test (5 and 10 mg/kg, i.p.; about 45-min session), decreased immobility in the forced swim test (1-3 mg/kg, i.p.; 1-10 mg/kg, p.o.; 30 min pretreatment, 6-min trial), and decreased latency to approach food in the novelty-suppressed feeding test after 29 days chronic administration once daily (5 mg/kg but not 10 mg/kg, p.o.; 15-min trial). In addition, LF-3-88 exhibited a favorable profile in pharmacokinetic/ADME-Tox (absorption, distribution, metabolism, excretion, and toxicity) assays. This compound was also shown to cause no mortality in wild-type Balb/CJ mice when tested at 300 mg/kg. These results further support the potential of potent and selective nicotinic partial agonists for use in the treatment of depression.

SAHA enhances synaptic function and plasticity in vitro but has limited brain availability in vivo and does not impact cognition.

Suberoylanilide hydroxamic acid (SAHA) is an inhibitor of histone deacetylases (HDACs) used for the treatment of cutaneous T cell lymphoma (CTCL) and under consideration for other indications. In vivo studies suggest reducing HDAC function can enhance synaptic function and memory, raising the possibility that SAHA treatment could have neurological benefits. We first examined the impacts of SAHA on synaptic function in vitro using rat organotypic hippocampal brain slices. Following several days of SAHA treatment, basal excitatory but not inhibitory synaptic function was enhanced. Presynaptic release probability and intrinsic neuronal excitability were unaffected suggesting SAHA treatment selectively enhanced postsynaptic excitatory function. In addition, long-term potentiation (LTP) of excitatory synapses was augmented, while long-term depression (LTD) was impaired in SAHA treated slices. Despite the in vitro synaptic enhancements, in vivo SAHA treatment did not rescue memory deficits in the Tg2576 mouse model of Alzheimer's disease (AD). Along with the lack of behavioral impact, pharmacokinetic analysis indicated poor brain availability of SAHA. Broader assessment of in vivo SAHA treatment using high-content phenotypic characterization of C57Bl6 mice failed to demonstrate significant behavioral effects of up to 150 mg/kg SAHA following either acute or chronic injections. Potentially explaining the low brain exposure and lack of behavioral impacts, SAHA was found to be a substrate of the blood brain barrier (BBB) efflux transporters Pgp and Bcrp1. Thus while our in vitro data show that HDAC inhibition can enhance excitatory synaptic strength and potentiation, our in vivo data suggests limited brain availability may contribute to the lack of behavioral impact of SAHA following peripheral delivery. These results do not predict CNS effects of SAHA during clinical use and also emphasize the importance of analyzing brain drug levels when interpreting preclinical behavioral pharmacology.

Characterization of maleimide-based glycogen synthase kinase-3 (GSK-3) inhibitors as stimulators of steroidogenesis.

Inhibition of GSK-3ß has been well documented to account for the behavioral actions of the mood stabilizer lithium in various animal models of mood disorders. Recent studies have showed that genetic or pharmacological inhibition of GSK-3ß resulted in anxiolytic-like and pro-social behavior. In our ongoing efforts to develop GSK-3ß inhibitors for the treatment of mood disorders, SAR studies on maleimide-based compounds were undertaken. We present herein for the first time that some of these GSK-3ß inhibitors, in particular analogues 1 and 9, were able to stimulate progesterone production in the MA-10 mouse tumor Leydig cell model of steroidogenesis without any significant toxicity. These two compounds were tested in the SmartCube behavioral assay and showed anxiolytic-like signatures following daily dose administration (50 mg/kg, ip) for 13 days. Taken together, these results support the hypothesis that GSK-3ß inhibition could influence neuroactive steroid production thereby mediating the modulation of anxiety-like behavior in vivo.

Insights into the structural determinants required for high-affinity binding of chiral cyclopropane-containing ligands to α4ß2-nicotinic acetylcholine receptors: an integrated approach to behaviorally active nicotinic ligands.

Structure-based drug design can potentially accelerate the development of new therapeutics. In this study, a cocrystal structure of the acetylcholine binding protein (AChBP) from Capitella teleta (Ct) in complex with a cyclopropane-containing selective α4ß2-nicotinic acetylcholine receptor (nAChR) partial agonist (compound 5) was acquired. The structural determinants required for ligand binding obtained from this AChBP X-ray structure were used to refine a previous model of the human α4ß2-nAChR, thus possibly providing a better understanding of the structure of the human receptor. To validate the potential application of the structure of the Ct-AChBP in the engineering of new α4ß2-nAChR ligands, homology modeling methods, combined with in silico ADME calculations, were used to design analogues of compound 5. The most promising compound, 12, exhibited an improved metabolic stability in comparison to the parent compound 5 while retaining favorable pharmacological parameters together with appropriate behavioral end points in the rodent studies.