Transcriptional profiling of SHR/NCrl prefrontal cortex shows hyperactivity-associated genes responsive to amphetamine challenge

Relationship between Traumatic Experiences, Circadian Preference and ADHD Symptoms in Adolescents with ADHD Residing in Institutional Care: A Controlled Study

Circadian preference, describes biological and behavioural characteristics that influence the ability to plan daily activities according to optimal waking times. It is divided into three main categories: morning, evening and intermediate. In particular, the evening chronotype is associated with conditions such as Attention Deficit Hyperactivity Disorder (ADHD) and Post Traumatic Stress Disorder (PTSD). This study was conducted in three groups aged 14-18 years: The first group consisted of 34 adolescents diagnosed with ADHD who had been in institutional care for at least two years and had not used medication in the last six months. The second group included 29 adolescents with ADHD living with their families who had not used medication in the last six months. The third control group consisted of 32 healthy adolescents. The study utilized sociodemographic data forms, the Turgay DSM-IV Disruptive Behavior Disorders Rating Scale (T-DSM-IV-S) to measure ADHD symptoms, the Childhood Chronotype Questionnaire (CCQ), and the Childhood Trauma Questionnaire (CTQ). In institutionalized adolescents with diagnosed ADHD, ADHD and disruptive behavior symptoms were more severe. Increased trauma scores were associated with higher ADHD and disruptive behaviour symptom severity and evening chronotype. In the conducted mediation analysis, evening chronotype was identified as a full mediator in the relationship between trauma symptoms and ADHD symptoms, while it was determined as a partial mediator in the relationship between trauma symptoms and PTSD symptoms. In conclusion, traumatic experiences in institutionalized adolescents with diagnosed ADHD may exacerbate ADHD and disruptive behavior symptoms. Evening chronotype is associated with ADHD and disruptive behavior symptoms, and therefore, the chronotypes of these adolescents should be assessed. Chronotherapeutic interventions may assist in reducing inattention, hyperactivity, and behavioral problems.

Thrsp Gene and the ADHD Predominantly Inattentive Presentation

There are three presentations of attention-deficit/hyperactivity disorder (ADHD): the predominantly inattention (ADHD-PI), predominantly hyperactive-impulsive (ADHD-HI), and combined (ADHD-C) presentations of ADHD. These may represent distinct childhood-onset neurobehavioral disorders with separate etiologies. ADHD diagnoses are behaviorally based, so investigations into potential etiologies should be founded on behavior. Animal models of ADHD demonstrate face, predictive, and construct validity when they accurately reproduce elements of the symptoms, etiology, biochemistry, and disorder treatment. Spontaneously hypertensive rats (SHR/NCrl) fulfill many validation criteria and compare well with clinical cases of ADHD-C. Compounding the difficulty of selecting an ideal model to study specific presentations of ADHD is a simple fact that our knowledge regarding ADHD neurobiology is insufficient. Accordingly, the current review has explored a potential animal model for a specific presentation, ADHD-PI, with acceptable face, predictive, and construct validity. The Thrsp gene could be a biomarker for ADHD-PI presentation, and THRSP OE mice could represent an animal model for studying this distinct ADHD presentation.

Sleep-related traits and attention-deficit/hyperactivity disorder comorbidity: Shared genetic risk factors, molecular mechanisms, and causal effects

OBJECTIVES

To evaluate the shared genetic components, common pathways and causal relationship between ADHD and sleep-related phenotypes.

METHODS

We used the largest genome-wide association summary statistics available for attention-deficit/hyperactivity disorder (ADHD) and various sleep-related phenotypes (insomnia, napping, daytime dozing, snoring, ease getting up, daytime sleepiness, sleep duration and chronotype). We estimated the genomic correlation using cross-trait linkage disequilibrium score regression (LDSR) and investigated the potential common mechanisms using gene-based cross-trait metanalyses and functional enrichment analyses. The causal effect was estimated using two-sample Mendelian randomisation (TSMR), using the inverse variance weighted method as the main estimator.

RESULTS

A positive genomic correlation between insomnia, daytime napping, daytime dozing, snoring, daytime sleepiness, short and long sleep duration, and ADHD was observed. Insomnia, daytime sleepiness, and snoring shared genes with ADHD, that are involved in neurobiological functions and regulatory signalling pathways. The TSMR supported a causal effect of insomnia, daytime napping, and short sleep duration on ADHD, and of ADHD on long sleep duration and chronotype.

CONCLUSION

Comorbidity between sleep phenotypes and ADHD may be mediated by common genetic factors that play an important role in neuronal signalling pathways. A causal effect of sleep disturbances and short sleep duration on ADHD reinforced their role as predictors of ADHD.

Categorizing SHR and WKY rats by chi2 algorithm and decision tree

Classifying mental disorder is a big issue in psychology in recent years. This article focuses on offering a relation between decision tree and encoding of fMRI that can simplify the analysis of different mental disorders and has a high ROC over 0.9. Here we encode fMRI information to the power-law distribution with integer elements by the graph theory in which the network is characterized by degrees that measure the number of effective links exceeding the threshold of Pearson correlation among voxels. When the degrees are ranked from low to high, the network equation can be fit by the power-law distribution. Here we use the mentally disordered SHR and WKY rats as samples and employ decision tree from chi2 algorithm to classify different states of mental disorder. This method not only provides the decision tree and encoding, but also enables the construction of a transformation matrix that is capable of connecting different metal disorders. Although the latter attempt is still in its fancy, it may have a contribution to unraveling the mystery of psychological processes.

Selection in Australian Thoroughbred horses acts on a locus associated with early two-year old speed

Thoroughbred horse racing is a global sport with major hubs in Europe, North America, Australasia and Japan. Regional preferences for certain traits have resulted in phenotypic variation that may result from adaptation to the local racing ecosystem. Here, we test the hypothesis that genes selected for regional phenotypic variation may be identified by analysis of selection signatures in pan-genomic SNP genotype data. Comparing Australian to non-Australian Thoroughbred horses (n = 99), the most highly differentiated loci in a composite selection signals (CSS) analysis were on ECA6 (34.75–34.85 Mb), ECA14 (33.2–33.52 Mb and 35.52–36.94 Mb) and ECA16 (24.28–26.52 Mb) in regions containing candidate genes for exercise adaptations including cardiac function (ARHGAP26, HBEGF, SRA1), synapse development and locomotion (APBB3, ATXN7, CLSTN3), stress response (NR3C1) and the skeletal muscle response to exercise (ARHGAP26, NDUFA2). In a genome-wide association study for field-measured speed in two-year-olds (n = 179) SNPs contained within the single association peak (33.2–35.6 Mb) overlapped with the ECA14 CSS signals and spanned a protocadherin gene cluster. Association tests using higher density SNP genotypes across the ECA14 locus identified a SNP within the PCDHGC5 gene associated with elite racing performance (n = 922). These results indicate that there may be differential selection for racing performance under racing and management conditions that are specific to certain geographic racing regions. In Australia breeders have principally selected horses for favourable genetic variants at loci containing genes that modulate behaviour, locomotion and skeletal muscle physiology that together appear to be contributing to early two-year-old speed.

CLOCK Polymorphisms in Attention-Deficit/Hyperactivity Disorder (ADHD): Further Evidence Linking Sleep and Circadian Disturbances and ADHD

Circadian and sleep disorders, short sleep duration, and evening chronotype are often present in attention-deficit/hyperactivity disorder (ADHD). CLOCK, considered the master gene in the circadian rhythm, has been explored by few studies. Understanding the relationship between ADHD and CLOCK may provide additional information to understand the correlation between ADHD and sleep problems. In this study, we aimed to explore the association between ADHD and CLOCK, using several genetic markers to comprehensively cover the gene extension. A total of 259 ADHD children and their parents from a Brazilian clinical sample were genotyped for eight single nucleotide polymorphisms (SNPs) in the CLOCK locus. We tested the individual markers and the haplotype effects using binary logistic regression. Binary logistic and linear regressions considering ADHD symptoms among ADHD cases were conducted as secondary analysis. As main result, the analysis showed a risk effect of the G-A-T-G-G-C-G-A (rs534654, rs1801260, rs6855837, rs34897046, rs11931061, rs3817444, rs4864548, rs726967) haplotype on ADHD. A suggestive association between ADHD and rs534654 was observed. The results suggest that the genetic susceptibility to circadian rhythm attributed to the CLOCK gene may play an important role on ADHD.

The Atxn7-overexpressing mice showed hyperactivity and impulsivity which were ameliorated by atomoxetine treatment: A possible animal model of the hyperactive-impulsive phenotype of ADHD

Attention-deficit/hyperactivity disorder (ADHD) is a heterogeneous neurodevelopmental disorder characterized by varying levels of hyperactivity, inattention, and impulsivity. Patients with ADHD are often classified as (1) predominantly hyperactive-impulsive, (2) predominantly inattentive, and (3) combined type. There is a growing interest in developing specific animal models that would recapitulate specific clinical forms of ADHD, with the goal of developing specific therapeutic strategies. In our previous study, we have identified Ataxin-7 (Atxn7) as a hyperactivity-associated gene. Here, we generated Atxn7 overexpressing (Atxn7 OE) mice to investigate whether the increased Atxn7 expression in the brain correlates with ADHD-like behaviors. Quantitative real-time polymerase chain reaction and immunofluorescence confirmed overexpression of the Atxn7 gene and protein in the prefrontal cortex (PFC) and striatum (STR) of the Atxn7 OE mice. The Atxn7 OE mice displayed hyperactivity and impulsivity, but not inattention. Interestingly, treatment with the ADHD drug, atomoxetine (3 mg/kg, intraperitoneal), attenuated ADHD-like behaviors and reduced Atxn7 gene expression in the PFC and STR of these mice. These findings suggest that Atxn7 plays a role in the pathophysiology of ADHD, and that the Atxn7 OE mice can be used as an animal model of the hyperactive-impulsive phenotype of this disorder. Although confirmatory studies are warranted, the present study provides valuable information regarding the potential genetic underpinnings of ADHD.

Decoding the transcriptional programs activated by psychotropic drugs in the brain

Analysis of drug-induced gene expression in the brain has long held the promise of revealing the molecular mechanisms of drug actions as well as predicting their long-term clinical efficacy. However, despite some successes, this promise has yet to be fulfilled. Here, we present an overview of the current state of understanding of drug-induced gene expression in the brain and consider the obstacles to achieving a robust prediction of the properties of psychoactive compounds based on gene expression profiles. We begin with a comprehensive overview of the mechanisms controlling drug-inducible transcription and the complexity resulting from expression of noncoding RNAs and alternative gene isoforms. Particular interest is placed on studies that examine the associations within drug classes with regard to the effects on gene transcription, alterations in cell signaling and neuropharmacological drug properties. While the ability of gene expression signatures to distinguish specific clinical classes of psychotropic and addictive drugs remains unclear, some reports show that under specific constraints, drug properties can be predicted based on gene expression. Such signatures offer a simple and effective way to classify psychotropic drugs and screen novel psychoactive compounds. Finally, we note that the amount of data regarding molecular programs activated in the brain by drug treatment has grown exponentially in recent years and that future advances may therefore come in large part from integrating the currently available high-throughput data sets.