The impact of the metabotropic glutamate receptor and other gene family interaction networks on autism

Although multiple reports show that defective genetic networks underlie the aetiology of autism, few have translated into pharmacotherapeutic opportunities. Since drugs compete with endogenous small molecules for protein binding, many successful drugs target large gene families with multiple drug binding sites. Here we search for defective gene family interaction networks (GFINs) in 6,742 patients with the ASDs relative to 12,544 neurologically normal controls, to find potentially druggable genetic targets. We find significant enrichment of structural defects (P≤2.40E-09, 1.8-fold enrichment) in the metabotropic glutamate receptor (GRM) GFIN, previously observed to impact attention deficit hyperactivity disorder (ADHD) and schizophrenia. Also, the MXD-MYC-MAX network of genes, previously implicated in cancer, is significantly enriched (P≤3.83E-23, 2.5-fold enrichment), as is the calmodulin 1 (CALM1) gene interaction network (P≤4.16E-04, 14.4-fold enrichment), which regulates voltage-independent calcium-activated action potentials at the neuronal synapse. We find that multiple defective gene family interactions underlie autism, presenting new translational opportunities to explore for therapeutic interventions

The genetic overlap of attention deficit hyperactivity disorder and autistic spectrum disorder

Contains fulltext : 126118.pdf (publisher's version ) (Open Access)Autistic spectrum disorders (ASD) and attention deficit hyperactivity disorder (ADHD) are classified as distinct disorders within the DSM-IV-TR (1994). The manual excludes simultaneous use of both diagnoses in case of overlap on a symptomatic level. However this does not always represent clinical observations and findings of previous studies. This review explores the genetic basis of the phenomenological overlap between ADHD and ASD. Based on an extensive review of twin-, linkage-, association studies, and reported structural genomic abnormalities associated with these disorders, we have identified seventeen regions on the human genome that can be related to both disorders. These regions of shared genetic association are: 2q35, 3p14, 4p16.1, 4p16.3, 5p15.31, 5p15.33, 7p12.3, 7p22, 7q21, 8q24.3, 14q12, 15q11-12, 16p13, 17q11, 18q21-23, 22q11.2, Xp22.3. The presented data are of interest for future genetic studies and appear to suggest the existence of a phenotype partition that may differ from the current classification of psychiatric disorders

Heterogeneous primary nucleation of ice in water and aqueous solutions

The effect of the volume of the liquid sample, the degree of turbulence in the liquid, and the rate of cooling upon the probability of nucleation has been studied for water and aqueous solutions. Nucleation rates were measured for droplets nearly instantaneously cooled to a predetermined temperature. Also threshold temperatures for nucleation were determined in stirred externally cooled vessels. The liquids studied (tap water, distilled water, and orange juice) did not contain particles causing nucleation at supercoolings less than 6°C. Nucleation at smaller supercoolings is attributed to the nucleative action of surface irregularities of the vessel walls. Provided no air bubbles are dispersed in the liquid, the rate of stirring (degree of turbulence) appeared to have no influence upon the nucleation. The experimental results are inconsistent with the stochastic hypothesis of Bigg7), the singular hypothesis of Langham and Mason8) and the pseudo-singular hypothesis of Vali and Stansbury10). They could, including those reported in literature7, 8, 10) be explained by the assumption of three distinct probabilities of nucleation: namely, the probability per unit time that a particular particle can cause nucleation at equilibrium conditions; the probability per unit time that equilibrium is established; and the probability that a particle with characteristic properties is present in the sample

[Guidelines on genetic testing in psychiatry: an overview]

BACKGROUND: In recent years, technological advances have led to the identification of numerous genetic variations that are associated with psychiatric symptoms. Establishing a genetic cause may provide patients and family members with an explanation for the problems and in specific cases allows targeted treatment of psychiatric and somatic (co)morbidity. At present, patients with psychiatric disorders are rarely referred for genetic testing. AIM: To provide an overview of literature and (inter)national guidelines in the field of genetic testing for patients with psychiatric disorder, and to present guidance on indications for genetic testing in clinical practice. METHOD: A systematic search was conducted in PubMed and Embase focusing on articles with recommendations on genetic testing in psychiatric disorders. In addition, national and international guidelines on genetic testing in psychiatry were studied. The main findings were summarized in an infographic. RESULTS: Based on the current literature and (inter)national guidelines, patients with (comorbid) intellectual disability should always be referred to a clinical geneticist. Psychiatrists should consider genetic testing in patients with other psychiatric disorders if there are ‘red flags’ such as a positive family history, congenital abnormalities, developmental delay, dysmorphic features, movement disorders or cognitive decline. Psychiatrists may request genetic testing themselves or refer patients to clinical geneticists. CONCLUSION: Psychiatric disorders may be underpinned by a genetic anomaly, particularly in patients presenting with psychiatric as well as somatic symptomatology. Psychiatrists should recognize symptoms and warning signs indicative of an underlying genetic abnormality, and know when to refer their patients for genetic testing

Effect of disease related biases on the subjective assessment of social functioning in Alzheimer's disease and schizophrenia patients

Background: Questionnaires are the current hallmark for quantifying social functioning in human clinical research. In this study, we compared self- and proxy-rated (caregiver and researcher) assessments of social functioning in Schizophrenia (SZ) and Alzheimer's disease (AD) patients and evaluated if the discrepancy between the two assessments is mediated by disease-related factors such as symptom severity.Methods: We selected five items from the WHO Disability Assessment Schedule 2.0 (WHODAS) to assess social functioning in 53 AD and 61 SZ patients. Caregiver- and researcher-rated assessments of social functioning were used to calculate the discrepancies between self-rated and proxy-rated assessments. Furthermore, we used the number of communication events via smartphones to compare the questionnaire outcomes with an objective measure of social behaviour.Results: WHODAS results revealed that both AD (p < 0.001) and SZ (p < 0.004) patients significantly overestimate their social functioning relative to the assessment of their caregivers and/or researchers. This overestimation is mediated by the severity of cognitive impairments (MMSE; p = 0.019) in AD, and negative symptoms (PANSS; p = 0.028) in SZ. Subsequently, we showed that the proxy scores correlated more strongly with the smartphone communication events of the patient when compared to the patient-rated questionnaire scores (self; p = 0.076, caregiver; p < 0.001, researcher-rated; p = 0.046).Conclusion: Here we show that the observed overestimation of WHODAS social functioning scores in AD and SZ patients is partly driven by disease-related biases such as cognitive impairments and negative symptoms, respectively. Therefore, we postulate the development and implementation of objective measures of social functioning that may be less susceptible to such biases.Stress-related psychiatric disorders across the life spa

Gene-ontology enrichment analysis in two independent family-based samples highlights biologically plausible processes for autism spectrum disorders

Recent genome-wide association studies (GWAS) have implicated a range of genes from discrete biological pathways in the aetiology of autism. However, despite the strong influence of genetic factors, association studies have yet to identify statistically robust, replicated major effect genes or SNPs. We apply the principle of the SNP ratio test methodology described by O'Dushlaine et al to over 2100 families from the Autism Genome Project (AGP). Using a two-stage design we examine association enrichment in 5955 unique gene-ontology classifications across four groupings based on two phenotypic and two ancestral classifications. Based on estimates from simulation we identify excess of association enrichment across all analyses. We observe enrichment in association for sets of genes involved in diverse biological processes, including pyruvate metabolism, transcription factor activation, cell-signalling and cell-cycle regulation. Both genes and processes that show enrichment have previously been examined in autistic disorders and offer biologically plausibility to these findings