1. Ann Gernsbacher M, Dawson M, Goldsmith HH. {{Three Reasons Not to Believe in an Autism Epidemic}}. {Curr Dir Psychol Sci};2005 (Apr);14(2):55-58.
According to some lay groups, the nation is experiencing an autism epidemic-a rapid escalation in the prevalence of autism for unknown reasons. However, no sound scientific evidence indicates that the increasing number of diagnosed cases of autism arises from anything other than purposely broadened diagnostic criteria, coupled with deliberately greater public awareness and intentionally improved case finding. Why is the public perception so disconnected from the scientific evidence? In this article we review three primary sources of misunderstanding: lack of awareness about the changing diagnostic criteria, uncritical acceptance of a conclusion illogically drawn in a California-based study, and inattention to a crucial feature of the « child count » data reported annually by the U.S. Department of Education.
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2. Correia C, Oliveira G, Vicente AM. {{Protein Interaction Networks Reveal Novel Autism Risk Genes within GWAS Statistical Noise}}. {PLoS One};2014;9(11):e112399.
Genome-wide association studies (GWAS) for Autism Spectrum Disorder (ASD) thus far met limited success in the identification of common risk variants, consistent with the notion that variants with small individual effects cannot be detected individually in single SNP analysis. To further capture disease risk gene information from ASD association studies, we applied a network-based strategy to the Autism Genome Project (AGP) and the Autism Genetics Resource Exchange GWAS datasets, combining family-based association data with Human Protein-Protein interaction (PPI) data. Our analysis showed that autism-associated proteins at higher than conventional levels of significance (P<0.1) directly interact more than random expectation and are involved in a limited number of interconnected biological processes, indicating that they are functionally related. The functionally coherent networks generated by this approach contain ASD-relevant disease biology, as demonstrated by an improved positive predictive value and sensitivity in retrieving known ASD candidate genes relative to the top associated genes from either GWAS, as well as a higher gene overlap between the two ASD datasets. Analysis of the intersection between the networks obtained from the two ASD GWAS and six unrelated disease datasets identified fourteen genes exclusively present in the ASD networks. These are mostly novel genes involved in abnormal nervous system phenotypes in animal models, and in fundamental biological processes previously implicated in ASD, such as axon guidance, cell adhesion or cytoskeleton organization. Overall, our results highlighted novel susceptibility genes previously hidden within GWAS statistical « noise » that warrant further analysis for causal variants.
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3. El-Ansary A, Al-Ayadhi L. {{GABAergic/glutamatergic imbalance relative to excessive neuroinflammation in autism spectrum disorders}}. {J Neuroinflammation};2014 (Nov 19);11(1):189.
BackgroundAutism spectrum disorder (ASD) is characterized by three core behavioral domains: social deficits, impaired communication, and repetitive behaviors. Glutamatergic/GABAergic imbalance has been found in various preclinical models of ASD. Additionally, autoimmunity immune dysfunction, and neuroinflammation are also considered as etiological mechanisms of this disorder. This study aimed to elucidate the relationship between glutamatergic/ GABAergic imbalance and neuroinflammation as two recently-discovered autism-related etiological mechanisms.MethodsTwenty autistic patients aged 3 to 15 years and 19 age- and gender-matched healthy controls were included in this study. The plasma levels of glutamate, GABA and glutamate/GABA ratio as markers of excitotoxicity together with TNF- inverted question mark, IL-6, IFN- inverted question mark and IFI16 as markers of neuroinflammation were determined in both groups.ResultsAutistic patients exhibited glutamate excitotoxicity based on a much higher glutamate concentration in the autistic patients than in the control subjects. Unexpectedly higher GABA and lower glutamate/GABA levels were recorded in autistic patients compared to control subjects. TNF- inverted question mark and IL-6 were significantly lower, whereas IFN- inverted question mark and IFI16 were remarkably higher in the autistic patients than in the control subjects.ConclusionMultiple regression analysis revealed associations between reduced GABA level, neuroinflammation and glutamate excitotoxicity. This study indicates that autism is a developmental synaptic disorder showing imbalance in GABAergic and glutamatergic synapses as a consequence of neuroinflammation.
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4. Gernsbacher MA, Stevenson JL, Khandakar S, Goldsmith HH. {{Autistics’ Atypical Joint Attention: Policy Implications and Empirical Nuance}}. {Child Dev Perspect};2008 (Apr);2(1):49-52.
Burack and Russo (2008) applaud our approach to understanding autistics’ atypical joint attention (Gernsbacher, Stevenson, Khandakar, & Goldsmith, 2008) but express some concerns about the evidence we drew upon to support our thesis. In response, we underscore the empirical nuance of our thesis-that autistics’ atypical manifestations of joint attention arise from their atypical resistance to distraction, atypical parallel perception, and atypical execution of volitional actions. We recap how our hypothesis derives from fresh interpretations, well-replicated findings, and underlying mechanisms.
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5. Gillespie-Lynch K, Kapp SK, Shane-Simpson C, Smith DS, Hutman T. {{Intersections Between the Autism Spectrum and the Internet: Perceived Benefits and Preferred Functions of Computer-Mediated Communication}}. {Intellect Dev Disabil};2014 (Dec);52(6):456-469.
Abstract An online survey compared the perceived benefits and preferred functions of computer-mediated communication of participants with (N = 291) and without ASD (N = 311). Participants with autism spectrum disorder (ASD) perceived benefits of computer-mediated communication in terms of increased comprehension and control over communication, access to similar others, and the opportunity to express their true selves. They enjoyed using the Internet to meet others more, and to maintain connections with friends and family less, than did participants without ASD. People with ASD enjoyed aspects of computer-mediated communication that may be associated with special interests or advocacy, such as blogging, more than did participants without ASD. This study suggests that people with ASD may use the Internet in qualitatively different ways from those without ASD. Suggestions for interventions are discussed.
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6. Ledford JR, Wehby JH. {{Teaching Children with Autism in Small Groups with Students Who are At-Risk for Academic Problems: Effects on Academic and Social Behaviors}}. {J Autism Dev Disord};2014 (Nov 20)
Students with ASD are often taught in individual instructional arrangements, even when they receive educational services in inclusive settings. Providing intervention in small group arrangements may increase opportunities for social interactions, particularly when these opportunities are systematically planned. In this study, academic instruction was conducted in small groups consisting of one student with ASD and peers who were socially competent but at risk for academic failure. All students learned targeted academic behaviors and increased their use of targeted social behaviors during instructional sessions. Generalization of social behaviors to a less-structured context was variable. Results suggest that small group instruction may be a feasible and preferred alternative to individual instruction for students with ASD.
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7. Nair MK, Russell PS, George B, Prasanna GL, Bhaskaran D, Shankar SR, Singh Y. {{CDC Kerala 10: Diagnostic Accuracy of the Severity Scores for Childhood Autism Rating Scale in India}}. {Indian J Pediatr};2014 (Nov 20)
OBJECTIVE: To document the diagnostic accuracy of the Childhood Autism Scale (CARS) thresholds to identify mild, moderate and severe autism in India. METHODS: The CARS scores of 623 children, with and without autism were compared against the Diagnostic and Statistical Manual for Mental Disorders 4th edition (DSM-IV-TR) for ASD diagnosis and clinical consensus between two developmental paediatricians as the reference standard for autism severity using the Receiver operating characteristics (ROC) curve analyses and contingency tables. RESULTS: The CARS total score for mild, moderate and severe autism ranged from 30.5 to 35, 35.5-40 and >/=40.5 respectively in this study. The overall diagnostic accuracy of CARS total score in the mild range was moderate [AUC = 0.68 (95%CI = 0.62-0.88), z = 1.34; P = 0.18], moderate range was high [AUC = 0.90 (95%CI = 0.77-0.97), z = 8.62; P = 0.0001] and severe range was also high [AUC = 0.85 (95%CI = 0.77-0.90), z = 7.09; P = 0.0001]. CONCLUSIONS: There are validated severity scores for Childhood Autism Rating Scale for clinical and research use in India.
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8. Nyffeler J, Walitza S, Bobrowski E, Gundelfinger R, Grunblatt E. {{Association study in siblings and case-controls of serotonin- and oxytocin-related genes with high functioning autism}}. {J Mol Psychiatry};2014;2(1):1.
BACKGROUND: Autism spectrum disorder (ASD) is heritable and neurodevelopmental with unknown causes. The serotonergic and oxytocinergic systems are of interest in autism for several reasons: (i) Both systems are implicated in social behavior, and abnormal levels of serotonin and oxytocin have been found in people with ASD; (ii) treatment with selective serotonin reuptake inhibitors and oxytocin can yield improvements; and (iii) previous association studies have linked the serotonin transporter (SERT; SLC6A4), serotonin receptor 2A (HTR2A), and oxytocin receptor (OXTR) genes with ASD. We examined their association with high functioning autism (HFA) including siblings and their interaction. METHODS: In this association study with HFA children (IQ > 80), siblings, and controls, participants were genotyped for four single nucleotide polymorphisms (SNPs) in OXTR (rs2301261, rs53576, rs2254298, rs2268494) and one in HTR2A (rs6311) as well as the triallelic HTTLPR (SERT polymorphism). RESULTS: We identified a nominal significant association with HFA for the HTTLPR s allele (consisting of S and LG alleles) (p = .040; odds ratio (OR) = 1.697, 95% CI 1.191-2.204)). Four polymorphisms (HTTLPR, HTR2A rs6311, OXTR rs2254298 and rs53576) in combination conferred nominal significant risk for HFA with a genetic score of >/=4 (OR = 2.09, 95% CI 1.05-4.18, p = .037). The resulting area under the receiver operating characteristic curve was 0.595 (p = .033). CONCLUSIONS: Our findings, combined with those of previous reports, indicate that ASD, in particular HFA, is polygenetic rather than monogenetic and involves the serotonergic and oxytocin pathways, probably in combination with other factors.
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9. Scott HM, Havercamp SM. {{Race and Health Disparities in Adults With Intellectual and Developmental Disabilities Living in the United States}}. {Intellect Dev Disabil};2014 (Dec);52(6):409-418.
Abstract Research has documented disparities in health care and access for people with intellectual and developmental disabilities (IDD) and people in racial and ethnic minority groups. Though both populations are underserved, the additive impact of being both a member of a racial/ethnic minority and having IDD is largely unknown. This study uses data from a nationally representative survey to explore health service utilization among adults with IDD belonging to minority racial/ethnic groups compared to adults with IDD who are White. The results of this study indicated that racial/ethnic minority groups are disadvantaged in several essential areas of health care utilization and that Hispanic Americans are particularly underserved. Additional research is needed to identify and address the factors driving this difference.
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10. van Elst LT, Maier S, Fangmeier T, Endres D, Mueller GT, Nickel K, Ebert D, Lange T, Hennig J, Biscaldi M, Riedel A, Perlov E. {{Magnetic resonance spectroscopy comparing adults with high functioning autism and above average IQ}}. {Mol Psychiatry};2014 (Dec);19(12):1251.