Search Results (8)

This case report was conducted by searching for the following keywords on PubMed: High Functioning Autism, Autism Spectrum Disorder, cariprazine, aripiprazole, partial agonist antipsychotic, DRD2/DRD3. High Functioning Autism (HFA) is a neurodevelopmental disorder characterized by the core symptoms of autism spectrum disorder (ASD) with average intellectual abilities, behavioral symptoms such as irritability, hyperactivity, aggressiveness and mood symptoms. HFA is not a term used in the Diagnostic and Statistical Manual of mental disorders (DSM), but it is commonly used to identify patients diagnosed with Autistic Disorder (AD) or Pervasive Developmental Disorder-Not Otherwise Specified (PDD-NOS) with average or above average intellectual abilities. Several factors are involved in HFA development, including environmental and genetic factors. In particular, over the last several decades, dopaminergic signaling system dysfunction has been highlighted as being responsible for behavioral patterns. Nowadays, symptoms of ASD lack a specific pharmacological treatment. The only medications approved by the Food and Drug Administration (FDA) for symptoms associated with ASD, in particular the irritability, are risperidone and aripiprazole. According to the hypothesis that dopamine receptor DRD2 and DRD3 might be involved in impulsive behavior, stereotypy, repetitive behaviors and language impairment, cariprazine could be a therapeutic option. This molecule is primarily characterized by DRD3 partial agonism and serotonin 5-HT1A partial agonism, with a lower ability to activate DRD2 than other third-generation antipsychotics, such as aripiprazole. We have reported here a case study of treatment of HFA with cariprazine. Full article

(1) Background: The study deepens the diagnosis of “pervasive developmental disorder not otherwise specified” (PDD-NOS), a subthreshold diagnosis introduced in DSM-IV and then absorbed into the broader spectrum disorder of autism in DSM 5. The presence of people still attributed with a diagnosis of PDD-NOS can cause confusion in the understanding of this disorder, which is no longer present in the current diagnostic system. This review aims to gain a deeper understanding of the characteristics and boundaries of diagnosis, its use within the scientific community, and the long-term stability of that diagnosis. (2) Methods: The Prisma method was used to carry out the literature review; the scientific papers were selected using scientific search engines, including SCOPUS, PUBMED, and PsychINFO. Twenty-three articles were finally selected, and a meticulous reading was carried out in relation to the research questions. (3) Results: Four cross-cutting categories were identified: (1) diagnosis; (2) differential diagnosis; (3) prognosis; and (4) comorbidity. (4) Conclusions: Limits have emerged regarding the consistency, sensitivity, and the stability of PDD-NOS. The inclusion of this diagnosis within the broader autism spectrum disorder category coined in DSM-5 appears applicable. Full article

Molecular biology combined with genomics can be a powerful tool for developing potential intervention strategies for improving outcomes in children with autism spectrum disorders (ASD). Monogenic etiologies rarely cause autism. Instead, ASD is more frequently due to many polygenic contributing factors interacting with each other, combined with the epigenetic effects of diet, lifestyle, and environment. One limitation of genomics has been identifying ways of responding to each identified gene variant to translate the information to something clinically useful. This paper will illustrate how understanding the function of a gene and the effects of a reported variant on a molecular level can be used to develop actionable and targeted potential interventions for a gene variant or combinations of variants. For illustrative purposes, this communication highlights a specific genomic variant, SHANK3. The steps involved in developing molecularly genomically targeted actionable interventions will be demonstrated. Cases will be shared to support the efficacy of this strategy and to show how clinicians utilized these targeted interventions to improve ASD-related symptoms significantly. The presented approach demonstrates the utility of genomics as a part of clinical decision-making. Full article

Background: Autism spectrum disorder (ASD) is a chronic and persistent pervasive developmental disorder (PDD) whose characteristic deficit is represented by social difficulties, semantic–pragmatic alterations and a limited, unusual and repetitive pattern of interests and behaviors. Specifically, individuals with high-functioning autism (HFA) frequently exhibit associated internalizing symptoms that are not part of the diagnostic criteria but which, nonetheless, tend to impair daily functioning. In this study, we investigated how some forms of treatment could be useful in subjects with HFA who display internalizing symptoms. Theoretical background relates to standard cognitive therapy (SCT) and rational education training with mindfulness (M-ERE). Methods: In this study, we investigated how some forms of treatment could be useful in subjects with HFA and internalizing symptoms, focusing on standard cognitive therapy (SCT) and mindfulness associated with emotional rational education training (M-ERE). We selected two groups of HFA patients with significant internalizing symptoms and performed two different forms of treatment for six months: SCT and M-ERE. The aim of the study was to verify the effectiveness of an M-ERE protocol with respect to anxious and depressive symptoms in subjects with HFA. Furthermore, we wanted to compare the results obtained with this combined treatment with those obtained in HFA subjects treated with SCT. Results: Our analyses showed an improvement in the internalizing symptoms (especially those related to the anxiety dimension) of the group that followed a treatment based on mindfulness and rational emotional education for 6 months compared to the group that had instead performed a 6-month treatment based on the SCT. Conclusions: Our hypotheses were supported by the results, which highlighted the efficacy of mindfulness-based interventions in the treatment of internalizing symptoms in adolescents with HFA, and specifically showed that an M-ERE intervention appears more effective in managing anxiety compared to treatment with SCT and appears to be equally effective in the management of depressive symptoms. Not only was the M-ERE treatment effective for the management of anxious and depressive symptoms in subjects with HFA, but the efficacy for the management of anxious symptoms was greater than the SCT treatment. Full article

The functional connectivity (FC) patterns of resting-state functional magnetic resonance imaging (rs-fMRI) play an essential role in the development of autism spectrum disorders (ASD) classification models. There are available methods in literature that have used FC patterns as inputs for binary classification models, but the results barely reach an accuracy of 80%. Additionally, the generalizability across multiple sites of the models has not been investigated. Due to the lack of ASD subtypes identification model, the multi-class classification is proposed in the present study. This study aims to develop automated identification of autism spectrum disorder (ASD) subtypes using convolutional neural networks (CNN) using dynamic FC as its inputs. The rs-fMRI dataset used in this study consists of 144 individuals from 8 independent sites, labeled based on three ASD subtypes, namely autistic disorder (ASD), Asperger’s disorder (APD), and pervasive developmental disorder not otherwise specified (PDD-NOS). The blood-oxygen-level-dependent (BOLD) signals from 116 brain nodes of automated anatomical labeling (AAL) atlas are used, where the top-ranked node is determined based on one-way analysis of variance (ANOVA) of the power spectral density (PSD) values. Based on the statistical analysis of the PSD values of 3-level ASD and normal control (NC), putamen_R is obtained as the top-ranked node and used for the wavelet coherence computation. With good resolution in time and frequency domain, scalograms of wavelet coherence between the top-ranked node and the rest of the nodes are used as dynamic FC feature input to the convolutional neural networks (CNN). The dynamic FC patterns of wavelet coherence scalogram represent phase synchronization between the pairs of BOLD signals. Classification algorithms are developed using CNN and the wavelet coherence scalograms for binary and multi-class identification were trained and tested using cross-validation and leave-one-out techniques. Results of binary classification (ASD vs. NC) and multi-class classification (ASD vs. APD vs. PDD-NOS vs. NC) yielded, respectively, 89.8% accuracy and 82.1% macro-average accuracy, respectively. Findings from this study have illustrated the good potential of wavelet coherence technique in representing dynamic FC between brain nodes and open possibilities for its application in computer aided diagnosis of other neuropsychiatric disorders, such as depression or schizophrenia. Full article

A hypothesis testing case-control study evaluated concerns about the toxic effects of organic-mercury (Hg) exposure from thimerosal-containing (49.55% Hg by weight) vaccines on the risk of neurodevelopmental disorders (NDs). Automated medical records were examined to identify cases and controls enrolled from their date-of-birth (1991–2000) in the Vaccine Safety Datalink (VSD) project. ND cases were diagnosed with pervasive developmental disorder (PDD), specific developmental delay, tic disorder or hyperkinetic syndrome of childhood. In addition, putative non-thimerosal-related outcomes of febrile seizure, failure to thrive and cerebral degenerations were examined. The cumulative total dose of Hg exposure from thimerosal-containing hepatitis B vaccine (T-HBV) administered within the first six months of life was calculated. On a per microgram of organic-Hg basis, PDD (odds ratio (OR) = 1.054), specific developmental delay (OR = 1.035), tic disorder (OR = 1.034) and hyperkinetic syndrome of childhood (OR = 1.05) cases were significantly more likely than controls to receive increased organic-Hg exposure. By contrast, none of the non-thimerosal related outcomes were significantly more likely than the controls to have received increased organic-Hg exposure. Routine childhood vaccination may be an important public health tool to reduce infectious disease-associated morbidity/mortality, but the present study significantly associates organic-Hg exposure from T-HBV with an increased risk of an ND diagnosis. Full article

Autism is an etiologically heterogeneous developmental disorder for which the range of genetic investigations has expanded considerably over the past decade. Introduction of chromosomal microarray (CMA) to clinical practice has expanded the range of conditions which pediatricians are able to detect. This study reviewed the utilization, yield and cost of genetic investigations in a sample of children with pervasive developmental disorders (PDD) in an Australian metropolitan child development service. Six hundred and ninety eight patients with PDD were identified from the clinic population. One hundred and ten (15.7%) of the clinic population had undergone investigation with chromosomal microarray, 140 (20.0%) with karyotype (KT), and 167 (23.9%) with Fragile X testing (FRGX). Twelve (10.9%) CMA findings were reported, of which seven (6.3%) were felt to be the likely cause of the child’s clinical features. Five (3.5%) KT findings were reported, of which four (2.9%) were felt to be the likely cause of the child’s clinical features. Two patients (1.2%) were identified with Fragile X expansions. One fifth of the clinic’s recent PDD population had undergone testing with CMA. CMA appears to have increased the diagnostic yield of the genetic investigation of autism, in line with internationally reported levels. Number needed to test (NNT) and cost per incremental diagnosis, were also in line with internationally reported levels. Full article

Background: Despite the difficulties associated with establishing a diagnosis of a mental illness in persons with intellectual disability, most authors agree to say that those persons are at high risk of developing comorbid serious mental illness but the prevalence of psychiatric disorders in this population varies widely. The main reason for this variation lies in the difficulty to diagnose intellectual disability and psychiatric disorders at the same time. The aim of the present study is to investigate the association between severity of intellectual disability and prevalence of psychiatric and somatic disorders in an adult population with intellectual disability treated in the Psychiatric Unit of Mental Development (UPDM) in Geneva, Switzerland. Methods: The present study is based on the analysis of the medical record of all ambulatory patients of the UPDM treated in March 2008. This population presents at least a dual diagnosis of intellectual disability associated with psychiatric disorders. Results: Data show that 59.1% of the total sample has behavioural disorders and this percentage increases with severity of intellectual disability since it is higher in persons with severe and profound intellectual disability (79.7%). Furthermore, 48.2% of our sample has psychiatric disorders and this percentage is higher for persons with mild intellectual disability (59.5%). The most frequent psychiatric diagnosis associated to intellectual disability are pervasive developmental disorders (27.4%) and its prevalence is higher in the severe and profound intellectual disability level (66.1%), while schizophrenia and disorders of adult per - sonality are significantly more frequent in the mild intellectual disability level (20.4% and 23.0% respectively). Furthermore, 31% of the sample have somatic disorders and its prevalence is higher in persons with severe and profound in - tellectual disability (55.9%). Considering the total prevalence of all diagnoses, our results reveal that 65% of our sample have more than a dual diagnosis and that this is more frequent in persons with severe and profound intellectual disability (84.7%) compared to persons with mild intellec - tual disability (54.8%). Conclusions: The total prevalence of all psy - chiatric disorders decreases with severity of intellectual disability. These data are consistent with other studies, which found a lower prevalence of psychiatric disorders in participants with severe and profound intellectual disability. Our results also reveal that the total prevalence of all diagnoses increases with severity of intellectual disability, which is consistent with the literature since some authors underline the presence of multiple patho - logies associated with intellectual disability. In general, our results are encouraging and suggest a progress in defining more precise diagnostic methods. Full article