Psychiatric comorbidities in asperger syndrome and high functioning autism: diagnostic challenges.

RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are.Several psychiatric conditions, both internalizing and externalizing, have been documented in comorbidity with Asperger Syndrome (AS) and High Functioning Autism (HFA). In this review we examine the interplay between psychiatric comorbidities and AS/HFA. In particular, we will focus our attention on three main issues. First, we examine which psychiatric disorders are more frequently associated with AS/HFA. Second, we review which diagnostic tools are currently available for clinicians to investigate and diagnose the associated psychiatric disorders in individuals with AS/HFA. Third, we discuss the challenges that clinicians and researchers face in trying to determine whether the psychiatric symptoms are phenotypic manifestations of AS/HFA or rather they are the expression of a distinct, though comorbid, disorder. We will also consider the role played by the environment in the manifestation and interpretation of these symptoms. Finally, we will propose some strategies to try to address these issues, and we will discuss therapeutic implications

Metallothioneins, Saccharomyces cerevisiae, and Heavy Metals: A Biotechnology Triad?

Metal ions are the least sophisticated chemical species that interact or bind to biomolecules. The yeast Saccharomyces cerevisiae represents a versatile model organisms used in both basic and applicative research, and one of the main contributors to the understanding of the molecular mechanisms involved in the transport, accumulation, and homeostasis of heavy metals. With a negatively charged wall, the yeast cells are very good biosorbents for heavy metals. In addition to biosorption, the metabolically active cells take up heavy metals via the normal membrane transport systems. Once in the cell, the toxicity of the heavy metals is controlled by various mechanisms, including sequestration by metal-binding proteins, such as the metallothioneins. Metallothioneins are cysteine-rich proteins involved in the buffering of excess heavy metals, both essential (Cu and Zn) and nonessential (Cd, Ag, and Hg). S. cerevisiae has two innate metallothioneins, Cup1 and Crs5, intensively investigated. Additionally, S. cerevisiae served as a host for the heterologous expression of a variety of metallothioneins from different species. This review focuses on the technological implications of expressing metallothioneins in yeast and on the possibility to use these transgenic cells in heavy metal-related biotechnologies: bioremediation, recovery of rare metals, or obtaining clonable tags for protein imaging

Calcium and Cell Response to Heavy Metals: Can Yeast Provide an Answer?

Despite constant efforts to maintain a clean environment, heavy metal pollution continues to raise challenges to the industrialized world. Exposure to heavy metals is detrimental to living organisms, and it is of utmost importance that cells find rapid and efficient ways to respond to and eventually adapt to surplus metals for survival under severe stress. This chapter focuses on the attempts done so far to elucidate the calcium-mediated response to heavy metal stress using the model organism Saccharomyces cerevisiae. The possibilities to record the transient elevations of calcium within yeast cells concomitantly with the heavy metal exposure are presented, and the limitations imposed by interference between calcium and heavy metals are discussed

Obsessive–compulsive traits in children and adolescents with Asperger syndrome

The objective of this study is to examine the occurrence and characteristic features of obsessive–compulsive behaviours in children and adolescents with Asperger syndrome (AS), with respect to a matched obsessive compulsive disorder group (OCD) and a typically developing control group (CG). For this purpose, 60 subjects (20 OCD; 18 AS; 22 CG), aged 8–15 years, matched for age, gender and IQ were compared. AS and OCD patients were diagnosed according to the DSM-IV-TR criteria. The Autism Diagnostic Interview-Revised and the Autism Diagnostic Observation Schedule were used to assist in the AS diagnosis; the WISC-R was administered to assess IQ. Obsessive and compulsive symptoms were evaluated by using the Children’s Yale-Brown Obsessive-Compulsive Scale (CY-BOCS). None of the AS children received a formal diagnosis of OCD. The AS group presented significantly higher frequencies of Hoarding obsessions and Repeating, Ordering and Hoarding compulsions compared to CG. The OCD group, in turn, reported significantly higher frequencies of Contamination and Aggressive obsessions and Checking compulsions compared to both the AS group and CG. As expected, the OCD group displayed a higher severity of symptoms (Moderate level of severity) than did the AS group (Mild level of severity). Finally, in our sample, neither the OCD group nor the AS group demonstrated a completely full awareness of the intrusive, unreasonable and distressing nature of symptoms, and the level of insight did not differ between the OCD group and CG, although an absence of insight was observed in the AS group. Children with AS showed higher frequencies of obsessive and compulsive symptoms than did typically developing children, and these features seem to cluster around Hoarding behaviours. Additionally, different patterns of symptoms emerged between the OCD and AS groups. Finally, in our sample, the level of insight was poor in both the OCD and the AS children. Further research should be conducted to better understand the characteristics of repetitive thoughts and behaviours in autism spectrum disorders, and to clarify the underlying neurobiological basis of these symptoms

Quantitative Checklist for Autism in Toddlers (Q-CHAT). A population screening study with follow-up: the case for multiple time-point screening for autism.

ObjectiveThis is a prospective population screening study for autism in toddlers aged 18-30 months old using the Quantitative Checklist for Autism in Toddlers (Q-CHAT), with follow-up at age 4.DesignObservational study.SettingLuton, Bedfordshire and Cambridgeshire in the UK.Participants13 070 toddlers registered on the Child Health Surveillance Database between March 2008 and April 2009, with follow-up at age 4; 3770 (29%) were screened for autism at 18-30 months using the Q-CHAT and the Childhood Autism Spectrum Test (CAST) at follow-up at age 4.InterventionsA stratified sample across the Q-CHAT score distribution was invited for diagnostic assessment (phase 1). The 4-year follow-up included the CAST and the Checklist for Referral (CFR). All with CAST ≥15, phase 1 diagnostic assessment or with developmental concerns on the CFR were invited for diagnostic assessment (phase 2). Standardised diagnostic assessment at both time-points was conducted to establish the test accuracy of the Q-CHAT.Main outcome measuresConsensus diagnostic outcome at phase 1 and phase 2.ResultsAt phase 1, 3770 Q-CHATs were returned (29% response) and 121 undertook diagnostic assessment, of whom 11 met the criteria for autism. All 11 screened positive on the Q-CHAT. The positive predictive value (PPV) at a cut-point of 39 was 17% (95% CI 8% to 31%). At phase 2, 2005 of 3472 CASTs and CFRs were returned (58% response). 159 underwent diagnostic assessment, including 82 assessed in phase 1. All children meeting the criteria for autism identified via the Q-CHAT at phase 1 also met the criteria at phase 2. The PPV was 28% (95% CI 15% to 46%) after phase 1 and phase 2.ConclusionsThe Q-CHAT can be used at 18-30 months to identify autism and enable accelerated referral for diagnostic assessment. The low PPV suggests that for every true positive there would, however, be ~4-5 false positives. At follow-up, new cases were identified, illustrating the need for continued surveillance and rescreening at multiple time-points using developmentally sensitive instruments. Not all children who later receive a diagnosis of autism are detectable during the toddler period

Optical manipulation of Saccharomyces cerevisiae cells reveals that green light protection against UV irradiation is favored by low Ca2+ and requires intact UPR pathway

AbstractOptical manipulation of Saccharomyces cerevisiae cells with high density green photons conferred protection against the deleterious effects of UV radiation. Combining chemical screening with UV irradiation of yeast cells, it was noted that the high density green photons relied on the presence of intact unfolded protein response (UPR) pathway to exert their protective effect and that the low Ca2+ conditions boosted the effect. UPR chemical inducers tunicamycin, dithiotreitol and calcium chelators augmented the green light effect in a synergic action against UV-induced damage. Photo-manipulation of cells was a critical factor since the maximum protection was achieved only when cells were pre-exposed to green light

An Ecological Visual Exploration Tool to Support the Analysis of Visual Processing Pathways in Children with Autism Spectrum Disorders

Recent improvements in the field of assistive technologies have led to innovative solutions aiming at increasing the capabilities of people with disability, helping them in daily activities with applications that span from cognitive impairments to developmental disabilities. In particular, in the case of Autism Spectrum Disorder (ASD), the need to obtain active feedback in order to extract subsequently meaningful data becomes of fundamental importance. In this work, a study about the possibility of understanding the visual exploration in children with ASD is presented. In order to obtain an automatic evaluation, an algorithm for free (i.e., without constraints, nor using additional hardware, infrared (IR) light sources or other intrusive methods) gaze estimation is employed. Furthermore, no initial calibration is required. It allows the user to freely rotate the head in the field of view of the sensor, and it is insensitive to the presence of eyeglasses, hats or particular hairstyles. These relaxations of the constraints make this technique particularly suitable to be used in the critical context of autism, where the child is certainly not inclined to employ invasive devices, nor to collaborate during calibration procedures.The evaluation of children’s gaze trajectories through the proposed solution is presented for the purpose of an Early Start Denver Model (ESDM) program built on the child’s spontaneous interests and game choice delivered in a natural setting

Quantitative Checklist for Autism in Toddlers (Q-CHAT). A population screening study with follow-up: the case for multiple time-point screening for autism

Funder: Autism Research TrustFunder: National Lottery Community Fund; FundRef: http://dx.doi.org/10.13039/501100013529Funder: Collaboration for Leadership in Applied Health Research and Care (CLAHRC)Objective: This is a prospective population screening study for autism in toddlers aged 18–30 months old using the Quantitative Checklist for Autism in Toddlers (Q-CHAT), with follow-up at age 4. Design: Observational study. Setting: Luton, Bedfordshire and Cambridgeshire in the UK. Participants: 13 070 toddlers registered on the Child Health Surveillance Database between March 2008 and April 2009, with follow-up at age 4; 3770 (29%) were screened for autism at 18–30 months using the Q-CHAT and the Childhood Autism Spectrum Test (CAST) at follow-up at age 4. Interventions: A stratified sample across the Q-CHAT score distribution was invited for diagnostic assessment (phase 1). The 4-year follow-up included the CAST and the Checklist for Referral (CFR). All with CAST ≥15, phase 1 diagnostic assessment or with developmental concerns on the CFR were invited for diagnostic assessment (phase 2). Standardised diagnostic assessment at both time-points was conducted to establish the test accuracy of the Q-CHAT. Main outcome measures: Consensus diagnostic outcome at phase 1 and phase 2. Results: At phase 1, 3770 Q-CHATs were returned (29% response) and 121 undertook diagnostic assessment, of whom 11 met the criteria for autism. All 11 screened positive on the Q-CHAT. The positive predictive value (PPV) at a cut-point of 39 was 17% (95% CI 8% to 31%). At phase 2, 2005 of 3472 CASTs and CFRs were returned (58% response). 159 underwent diagnostic assessment, including 82 assessed in phase 1. All children meeting the criteria for autism identified via the Q-CHAT at phase 1 also met the criteria at phase 2. The PPV was 28% (95% CI 15% to 46%) after phase 1 and phase 2. Conclusions: The Q-CHAT can be used at 18–30 months to identify autism and enable accelerated referral for diagnostic assessment. The low PPV suggests that for every true positive there would, however, be ~4–5 false positives. At follow-up, new cases were identified, illustrating the need for continued surveillance and rescreening at multiple time-points using developmentally sensitive instruments. Not all children who later receive a diagnosis of autism are detectable during the toddler period

Molecular Sex Differences in Human Serum

Background: Sex is an important factor in the prevalence, incidence, progression, and response to treatment of many medical conditions, including autoimmune and cardiovascular diseases and psychiatric conditions. Identification of molecular differences between typical males and females can provide a valuable basis for exploring conditions differentially affected by sex. Methodology/Principal Findings: Using multiplexed immunoassays, we analyzed 174 serum molecules in 9 independent cohorts of typical individuals, comprising 196 males and 196 females. Sex differences in analyte levels were quantified using a meta-analysis approach and put into biological context using k-means to generate clusters of analytes with distinct biological functions. Natural sex differences were established in these analyte groups and these were applied to illustrate sexually dimorphic analyte expression in a cohort of 22 males and 22 females with Asperger syndrome. Reproducible sex differences were found in the levels of 77 analytes in serum of typical controls, and these comprised clusters of molecules enriched with distinct biological functions. Analytes involved in fatty acid oxidation/hormone regulation, immune cell growth and activation, and cell death were found at higher levels in females, and analytes involved in immune cell chemotaxis and other indistinct functions were higher in males. Comparison of these naturally occurring sex differences against a cohort of people with Asperger syndrome indicated that a cluster of analytes that had functions related to fatty acid oxidation/hormone regulation was associated with sex and the occurren

Validation of the Quantitative Checklist for Autism in Toddlers in an Italian Clinical Sample of Young Children With Autism and Other Developmental Disorders.

Background: The Quantitative Checklist for Autism in Toddlers (Q-CHAT) is parent-report screening questionnaire for detecting threshold and sub-threshold autistic features in toddlers. The Q-CHAT is a dimensional measure normally distributed in the general population sample and is able to differentiate between a group of children with a diagnosis of autism and unselected toddlers. Objectives: We aim to investigate the psychometric properties, score distribution, and external validity of the Q-CHAT in an Italian clinical sample of young children with autism versus children with developmental delay and typically developing children. Method: N = 126 typically developing children (TD), n = 139 children with autism, and n = 50 children presenting developmental delay (DD) were administered the Q-CHAT. Standardized measures of cognitive functions, language, and behaviors were also obtained. Results: The Q-CHAT scores were normally distributed and demonstrated adequate internal consistency and good item to total score correlations. The mean Q-CHAT score in the autism group was significantly higher than those found in the DD sample and TD children. No difference on the mean Q-CHAT score between DD and TD children was found. The accuracy of the Q-CHAT to discriminate between autism and TD was very good. Two different cut-points (27 and 31, respectively) maximized sensitivity and specificity for autism versus TD and DD, respectively. Finally, higher Q-CHAT scores were correlated with lower language and social communication skills. Conclusions: In clinical settings, the Q-CHAT demonstrated good psychometric properties and external validity to discriminate autism children not just from children with typical development but also from children with developmental delay