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Autism spectrum disorder (ASD) and Attention-deficit/hyperactivity disorder (ADHD) are often comorbid. The purpose of this study is to explore the relationships between ASD and ADHD symptoms by applying causal modeling. We used a large phenotypic data set of 417 children with ASD and/or ADHD, 562 affected and unaffected siblings, and 414 controls, to infer a structural equation model using a causal discovery algorithm. Three distinct pathways between ASD and ADHD were identified: (1) from impulsivity to difficulties with understanding social information, (2) from hyperactivity to stereotypic, repetitive behavior, (3) a pairwise pathway between inattention, difficulties with understanding social information, and verbal IQ. These findings may inform future studies on understanding the pathophysiological mechanisms behind the overlap between ASD and ADHD.

Tourette’s disorder (TD) is a highly heritable childhood-onset neurodevelopmental disorder and is caused by a complex interplay of multiple genetic and environmental factors. Yet, the molecular mechanisms underlying the disorder remain largely elusive. In this study, we used the available omics data to compile a list of TD candidate genes, and we subsequently conducted tissue/cell type specificity and functional enrichment analyses of this list. Using genomic data, we also investigated genetic sharing between TD and blood and cerebrospinal fluid (CSF) metabolite levels. Lastly, we built a molecular landscape of TD through integrating the results from these analyses with an extensive literature search to identify the interactions between the TD candidate genes/proteins and metabolites. We found evidence for an enriched expression of the TD candidate genes in four brain regions and the pituitary. The functional enrichment analyses implicated two pathways (‘cAMP-mediated signaling’ and ‘Endocannabinoid Neuronal Synapse Pathway’) and multiple biological functions related to brain development and synaptic transmission in TD etiology. Furthermore, we found genetic sharing between TD and the blood and CSF levels of 39 metabolites. The landscape of TD not only provides insights into the (altered) molecular processes that underlie the disease but, through the identification of potential drug targets (such as FLT3, NAALAD2, CX3CL1-CX3CR1, OPRM1, and HRH2), it also yields clues for developing novel TD treatments.

Serotonin (5-hydroxytryptamine, or 5-HT) is strongly implicated in the ability to shift behavior in response to changing stimulus-reward contingencies. However, there is little information on the contribution of different 5-HT receptors in reversal learning. Thus, we investigated the effects of systemic administration of the 5-HT 2A antagonist M100907 (0, 0.01, 0.03, and 0.1 mg/kg, i.p.) and the 5-HT 2C antagonist SB 242084 (0, 0.1, 0.3, and 1.0 mg/kg, i.p.) on the performance of an instrumental two-lever spatial discrimination and serial spatial reversal learning task, where both levers were presented and only one was reinforced. The rat was required to respond on the reinforced lever under a fixed ratio 3 schedule of reinforcement. Following attainment of criterion, a series of within-session reversals was presented. Neither M100907 nor SB 242084 altered performance during spatial discrimination and retention of the previously reinforced contingencies. M100907 significantly impaired reversal learning by increasing both trials to criterion (only at the highest dose) and incorrect responses to criterion in Reversal 1, a pattern of behavior manifested as increased perseverative responding on the previously reinforced lever. In contrast, SB 242084 improved reversal learning by decreasing trials and incorrect responses to criterion in Reversal 1, with significantly fewer perseverative responses. These data support the view that 5-HT 2A and 5-HT 2C receptors have distinct roles in cognitive flexibility and response inhibition. The improved performance in reversal learning observed following 5-HT 2C receptor antagonism suggests these receptors may offer the potential for therapeutic advances in a number of neuropsychiatric disorders where cognitive deficits are a feature, including obsessive-compulsive disorder.

Attention – the flexible allocation of processing resources based on behavioural demands – is essential to survival. Mouse research offers unique tools to dissect the underlying pathways, but is hampered by the difficulty of accurately measuring attention in mice. Current attention tasks for mice face several limitations: Binary (hit/miss), temporally imprecise metrics, behavioural confounds and overtraining. Thus, despite the increasing scope of neuronal population measurements, insights are limited without equally precise behavioural measures. Here we present a virtual-environment task for head-fixed mice based on ‘foraging-like’ navigation. The task requires animals to discriminate gratings at orientation differences from 90° to 5°, and can be learned in only 3–5 sessions (<550 trials). It yields single-trial, non-binary metrics of response speed and accuracy, which generate secondary metrics of choice certainty, visual acuity, and most importantly, of sustained and cued attention – two attentional components studied extensively in humans. This allows us to examine single-trial dynamics of attention in mice, independently of confounds like rule learning. With this approach, we show that C57/BL6 mice have better visual acuity than previously measured, that they rhythmically alternate between states of high and low alertness, and that they can be prompted to adopt different performance strategies using minute changes in reward contingencies.

MicroRNAs (miRNAs) are important gene regulators that are abundantly expressed in both the developing and adult mammalian brain. These non-coding gene transcripts are involved in post-transcriptional regulatory processes by binding to specific target mRNAs. Approximately one third of known miRNA genes are located within intronic regions of protein coding and non-coding regions, and previous studies have suggested a role for intronic miRNAs as negative feedback regulators of their host genes. In the present study, we monitored the dynamic gene expression changes of the intronic miR-338-3p and miR-338-5p and their host gene Apoptosis-associated Tyrosine Kinase (AATK) during the maturation of rat hippocampal neurons. This revealed an uncorrelated expression pattern of mature miR-338 strands with their host gene. Sequence analysis of the 3' untranslated region (UTR) of rat AATK mRNA revealed the presence of two putative binding sites for miR-338-3p. Thus, miR-338-3p may have the capacity to modulate AATK mRNA levels in neurons. Transfection of miR-338-3p mimics into rat B35 neuroblastoma cells resulted in a significant decrease of AATK mRNA levels, while the transfection of synthetic miR-338-5p mimics did not alter AATK levels. Our results point to a possible molecular mechanism by which miR-338-3p participates in the regulation of its host gene by modulating the levels of AATK mRNA, a kinase which plays a role during differentiation, apoptosis and possibly in neuronal degeneration.

In the past two decades, functional Magnetic Resonance Imaging (fMRI) has been used to relate neuronal network activity to cognitive processing and behavior. Recently this approach has been augmented by algorithms that allow us to infer causal links between component populations of neuronal networks. Multiple inference procedures have been proposed to approach this research question but so far, each method has limitations when it comes to establishing whole-brain connectivity patterns. In this paper, we discuss eight ways to infer causality in fMRI research: Bayesian Nets, Dynamical Causal Modelling, Granger Causality, Likelihood Ratios, Linear Non-Gaussian Acyclic Models, Patel’s Tau, Structural Equation Modelling, and Transfer Entropy. We finish with formulating some recommendations for the future directions in this area.

Numerous factor analytic studies consistently support a distinction between two symptom domains of attention-deficit/hyperactivity disorder (ADHD), inattention and hyperactivity/impulsivity. Both dimensions show high internal consistency and moderate to strong correlations with each other. However, it is not clear what drives this strong correlation. The aim of this paper is to address this issue. We applied a sophisticated approach for causal discovery on three independent data sets of scores of the two ADHD dimensions in NeuroIMAGE (total N = 675), ADHD-200 (N = 245), and IMpACT (N = 164), assessed by different raters and instruments, and further used information on gender or a genetic risk haplotype. In all data sets we found strong statistical evidence for the same pattern: the clear dependence between hyperactivity/impulsivity symptom level and an established genetic factor (either gender or risk haplotype) vanishes when one conditions upon inattention symptom level. Under reasonable assumptions, e.g., that phenotypes do not cause genotypes, a causal model that is consistent with this pattern contains a causal path from inattention to hyperactivity/impulsivity. The robust dependency cancellation observed in three different data sets suggests that inattention is a driving factor for hyperactivity/impulsivity. This causal hypothesis can be further validated in intervention studies. Our model suggests that interventions that affect inattention will also have an effect on the level of hyperactivity/impulsivity. On the other hand, interventions that affect hyperactivity/impulsivity would not change the level of inattention. This causal model may explain earlier findings on heritable factors causing ADHD reported in the study of twins with learning difficulties.

The blood transcriptome was examined in relation to disease severity in type I myotonic dystrophy (DM1) patients who participated in the Observational Prolonged Trial In DM1 to Improve QoL- Standards (OPTIMISTIC) study. This sought to (a) ascertain if transcriptome changes were associated with increasing disease severity, as measured by the muscle impairment rating scale (MIRS), and (b) establish if these changes in mRNA expression and associated biological pathways were also observed in the Dystrophia Myotonica Biomarker Discovery Initiative (DMBDI) microarray dataset in blood (with equivalent MIRS/DMPK repeat length). The changes in gene expression were compared using a number of complementary pathways, gene ontology and upstream regulator analyses, which suggested that symptom severity in DM1 was linked to transcriptomic alterations in innate and adaptive immunity associated with muscle-wasting. Future studies should explore the role of immunity in DM1 in more detail to assess its relevance to DM1.

Youth with disruptive behavior showing high callous-unemotional (CU) traits and proactive aggression are often assumed to exhibit distinct impairments in emotion recognition from those showing mainly reactive aggression. Yet, reactive and proactive aggression and CU traits may co-occur to varying degrees across individuals. We aimed to investigate emotion recognition in more homogeneous clusters based on these three dimensions. In a sample of 243 youth (149 with disruptive behavior problems and 94 controls) aged 8–18 years, we used model-based clustering on self-report measures of CU traits and reactive and proactive aggression and compared the resulting clusters on emotion recognition (accuracy and response bias) and working memory. In addition to a Low and Low-Moderate symptom cluster, we identified two high CU clusters. The CU-Reactive cluster showed high reactive and low-to-medium proactive aggression; the CU-Mixed cluster showed high reactive and proactive aggression. Both CU clusters showed impaired fear recognition and working memory, whereas the CU-Reactive cluster also showed impaired recognition of disgust and sadness, partly explained by poor working memory, as well as a response bias for anger and happiness. Our results confirm the importance of CU traits as a core dimension along which youth with disruptive behavior may be characterized, yet challenge the view that high CU traits are closely linked to high proactive aggression per se. Notably, distinct neurocognitive processes may play a role in youth with high CU traits and reactive aggression with lower versus higher proactive aggression.

Serotonin (5-HT) is thought to play an important role in the regulation of behavioral inhibition. Studies manipulating 5-HT function in the rodent brain indicate that 5-HT receptors regulate distinct forms of impulsive behavior, including impulsive responding in the 5-choice serial reaction time task (5CSRTT). The present study investigates the loci of effects mediated by 5-HT 2A and 5-HT 2C receptors in attention and inhibitory response control using microinfusions targeted at the nucleus accumbens (NAc), prelimbic cortex (PL) and infralimbic cortex (IL). Rats were implanted with bilateral guide cannulas and received infusions of the selective 5-HT 2A receptor antagonist M100907 (0.1 and 0.3 μg) or selective 5-HT 2C receptor antagonist SB242084 (0.1 and 0.5 μg) immediately prior to testing. The results show that intra-NAc infusions of M100907 significantly decrease impulsive responding on the 5CSRTT and at the highest dose increased omissions as well. By contrast, infusions of SB242084 into the NAc selectively and dose-dependently increased impulsivity. Neither M100907 nor SB242084 significantly altered impulsive responding following either intra-PL or intra-IL administration. However, SB242084 significantly decreased omissions following intra-PL administration (0.5 μg only). These data reveal opposing effects on impulsivity following 5-HT 2A and 5-HT 2C blockade in the NAc. Our results suggest that the NAc, but not the PL or IL, is implicated in the mediation of the effects of M100907 and SB242084 on inhibitory response control during baseline 5CSRTT performance.