Autism spectrum disorder (ASD) is a prevalent neurodevelopmental disorder characterized by atypical patterns of social interaction and communication, as well as restrictive and repetitive behaviors. In addition, patients with ASD often presents with sleep disturbances. Delta (δ) catenin protein 2 (CTNND2) encodes δ-catenin protein, a neuron-specific catenin implicated in many complex neuropsychiatric diseases. Our previous study demonstrated that the deletion of Ctnnd2 in mice led to autism-like behaviors. However, to our knowledge, no study has investigated the effects of Ctnnd2 deletion on sleep in mice. In this study, we investigated whether the knockout (KO) of exon 2 of the Ctnnd2 gene could induce sleep–wake disorders in mice and identified the effects of oral melatonin (MT) supplementation on Ctnnd2 KO mice. Our results demonstrated that the Ctnnd2 KO mice exhibited ASD-like behaviors and sleep–wake disorders that were partially attenuated by MT supplementation. Overall, our current study is the first to identify that knockdown of Ctnnd2 gene could induce sleep–wake disorders in mice and suggests that treatment of sleep–wake disturbances by MT may benefit to autism-like behaviors causing by Ctnnd2 gene deletion.
Anxiety disorders are common and can be debilitating, with effective treatments remaining hampered by an incomplete understanding of the underlying genetic etiology. Improvements have been made in understanding the genetic influences on mouse behavioral models of anxiety, yet it is unclear the extent to which genes identified in these experimental systems contribute to genetic variation in human anxiety phenotypes. Leveraging new and existing large-scale human genome-wide association studies, we tested whether sets of genes previously identified in mouse anxiety-like behavior studies contribute to a range of human anxiety disorders. When tested as individual genes, 13 mouse-identified genes were associated with human anxiety phenotypes, suggesting an overlap of individual genes contributing to both mouse models of anxiety-like behaviors and human anxiety traits. When genes were tested as sets, we did identify 14 significant associations between mouse gene sets and human anxiety, but the majority of gene sets showed no significant association with human anxiety phenotypes. These few significant associations indicate a need to identify and develop more translatable mouse models by identifying sets of genes that “match” between model systems and specific human phenotypes of interest. We suggest that continuing to develop improved behavioral paradigms and finer-scale experimental data, for instance from individual neuronal subtypes or cell-type-specific expression data, is likely to improve our understanding of the genetic etiology and underlying functional changes in anxiety disorders.
The gut-brain axis is increasingly recognized as an important pathway involved in cocaine use disorder. Microbial products of the murine gut have been shown to affect striatal gene expression, and depletion of the microbiome by antibiotic treatment alters cocaine-induced behavioral sensitization in C57BL/6J male mice. Some reports suggest that cocaine-induced behavioral sensitization is correlated with drug self-administration behavior in mice. Here, we profile the composition of the naïve microbiome and its response to cocaine sensitization in two collaborative cross (CC) strains. These strains display extremely divergent behavioral responses to cocaine sensitization. A high-responding strain, CC004/TauUncJ (CC04), has a gut microbiome that contains a greater amount of Lactobacillus than the cocaine-nonresponsive strain CC041/TauUncJ (CC41). The gut microbiome of CC41 is characterized by an abundance of Eisenbergella, Robinsonella and Ruminococcus. In response to cocaine, CC04 has an increased Barnsiella population, while the gut microbiome of CC41 displays no significant changes. PICRUSt functional analysis of the functional potential of the gut microbiome in CC04 shows a significant number of potential gut-brain modules altered after exposure to cocaine, specifically those encoding for tryptophan synthesis, glutamine metabolism, and menaquinone synthesis (vitamin K2). Depletion of the microbiome by antibiotic treatment revealed an altered cocaine-sensitization response following antibiotics in female CC04 mice. Depleting the microbiome by antibiotic treatment in males revealed increased infusions for CC04 during a cocaine intravenous self-administration dose–response curve. Together these data suggest that genetic differences in cocaine-related behaviors may involve the microbiome.
Impulsivity refers to a number of conceptually related phenotypes reflecting self-regulatory capacity that are considered promising endophenotypes for mental and physical health. Measures of impulsivity can be broadly grouped into three domains, namely, impulsive choice, impulsive action, and impulsive personality traits. In a community-based sample of ancestral Europeans (n = 1534), we conducted genome-wide association studies (GWASs) of impulsive choice (delay discounting), impulsive action (behavioral inhibition), and impulsive personality traits (UPPS-P), and evaluated 11 polygenic risk scores (PRSs) of phenotypes previously linked to self-regulation. Although there were no individual genome-wide significant hits, the neuroticism PRS was positively associated with negative urgency (adjusted R2 = 1.61%, p = 3.6 × 10−7) and the educational attainment PRS was inversely associated with delay discounting (adjusted R2 = 1.68%, p = 2.2 × 10−7). There was also evidence implicating PRSs of attention-deficit/hyperactivity disorder, externalizing, risk-taking, smoking cessation, smoking initiation, and body mass index with one or more impulsivity phenotypes (adjusted R2s: 0.35%–1.07%; FDR adjusted ps = 0.05–0.0006). These significant associations between PRSs and impulsivity phenotypes are consistent with established genetic correlations. The combined PRS explained 0.91%–2.46% of the phenotypic variance for individual impulsivity measures, corresponding to 8.7%–32.5% of their reported single-nucleotide polymorphism (SNP)-based heritability, suggesting a non-negligible portion of the SNP-based heritability can be recovered by PRSs. These results support the predictive validity and utility of PRSs, even derived from related phenotypes, to inform the genetics of impulsivity phenotypes.
The integration of multi-omics information (e.g., epigenetics and transcriptomics) can be useful for interpreting findings from genome-wide association studies (GWAS). It has been suggested that multi-omics could circumvent or greatly reduce the need to increase GWAS sample sizes for novel variant discovery. We tested whether incorporating multi-omics information in earlier and smaller-sized GWAS boosts true-positive discovery of genes that were later revealed by larger GWAS of the same/similar traits. We applied 10 different analytic approaches to integrating multi-omics data from 12 sources (e.g., Genotype-Tissue Expression project) to test whether earlier and smaller GWAS of 4 brain-related traits (alcohol use disorder/problematic alcohol use, major depression/depression, schizophrenia, and intracranial volume/brain volume) could detect genes that were revealed by a later and larger GWAS. Multi-omics data did not reliably identify novel genes in earlier less-powered GWAS (PPV <0.2; 80% false-positive associations). Machine learning predictions marginally increased the number of identified novel genes, correctly identifying 1–8 additional genes, but only for well-powered early GWAS of highly heritable traits (i.e., intracranial volume and schizophrenia). Although multi-omics, particularly positional mapping (i.e., fastBAT, MAGMA, and H-MAGMA), can help to prioritize genes within genome-wide significant loci (PPVs = 0.5–1.0) and translate them into information about disease biology, it does not reliably increase novel gene discovery in brain-related GWAS. To increase power for discovery of novel genes and loci, increasing sample size is required.
Dry eye disease (DED) affects nearly 55% of people worldwide; several studies have proposed that central sensitization and neuroinflammation may contribute to the developing corneal neuropathic pain of DED, while the underlying mechanisms of this contribution remain to be investigated. Excision of extra orbital lacrimal glands established the dry eye model. Corneal hypersensitivity was examined through chemical and mechanical stimulation, and open field test measured the anxiety levels. Restingstate fMRI is a method of functional magnetic resonance imaging (rs-fMRI) was performed for anatomical involvement of the brain regions. The amplitude of low-frequency fluctuation (ALFF) determined brain activity. Immunofluorescence testing and Quantitative real-time polymerase chain reaction were also performed to further validate the findings. Compared with the Sham group, ALFF signals in the supplemental somatosensory area, secondary auditory cortex, agranular insular cortex, temporal association areas, and ectorhinal cortex brain areas were increased in the dry eye group. This change of ALFF in the insular cortex was linked with the increment in corneal hypersensitivity (p < 0.01), c-Fos (p < 0.001), brain-derived neurotrophic factor (p < 0.01), TNF-α, IL-6, and IL-1β (p < 0.05). In contrast, IL-10 levels (p < 0.05) decreased in the dry eye group. DED-induced corneal hypersensitivity and upregulation of inflammatory cytokines could be blocked by insular cortex injection of Tyrosine Kinase receptor B agonist cyclotraxin-B (p < 0.01) without affecting anxiety levels. Our study reveals that the functional activity of the brain associated with corneal neuropathic pain and neuroinflammation in the insular cortex might contribute to dry eye-related corneal neuropathic pain.
Mathematical ability is moderately heritable, and it is a complex trait which can be evaluated in several different categories. A few genetic studies have been published on general mathematical ability. However, no genetic study focused on specific mathematical ability categories. In this study, we separately performed genome-wide association studies on 11 mathematical ability categories in 1146 students from Chinese elementary schools. We identified seven genome-wide significant single nucleotide polymorphisms (SNPs) with strong linkage disequilibrium among each other (all r2 > 0.8) associated with mathematical reasoning ability (top SNP: rs34034296, p = 2.01 × 10−8, nearest gene: CUB and Sushi multiple domains 3, CSMD3). We replicated one SNP (rs133885) from 585 SNPs previously reported to be associated with general mathematical ability associated with division ability in our data (p = 1.053 × 10−5). In the gene- and gene-set enrichment analysis by MAGMA, we found three significant enrichments of associations with three mathematical ability categories for three genes (LINGO2, OAS1 and HECTD1). We also observed four significant enrichments of associations with four mathematical ability categories for three gene sets. Our results suggest new candidate genetic loci for the genetics of mathematical ability.