1. Buckley AW, Rodriguez AJ, Jennison K, Buckley J, Thurm A, Sato S, Swedo S. {{Rapid eye movement sleep percentage in children with autism compared with children with developmental delay and typical development}}. {Arch Pediatr Adolesc Med} (Nov);164(11):1032-1037.
OBJECTIVE: To compare objective polysomnographic parameters between 3 cohorts: children with autism, typical development, and developmental delay without autism. DESIGN: Overnight polysomnographic recordings were scored for sleep architecture according to American Academy of Sleep Medicine criteria by a board-certified sleep medicine specialist blind to diagnosis for studies collected between July 2006 and September 2009. SETTING: Subjects were evaluated in the pediatric ward in the Clinical Research Center of the National Institutes of Health. PARTICIPANTS: First 60 consecutive children with autism, 15 with typical development, and 13 with developmental delay matched for nonverbal IQ to the autism group, ranging in age from 2 to 13 years, selected without regard to the presence or absence of sleep problem behavior. MAIN OUTCOME MEASURES: Total sleep time, latencies to non-rapid eye movement (REM) and REM sleep, and percentages of total sleep time for stages 1 and 2 sleep, slow-wave sleep, and REM sleep. RESULTS: There were no differences between the typical vs developmental delay groups. Comparison of children with autism vs typical children revealed shorter total sleep time (P = .004), greater slow-wave sleep percentage (P = .001), and much smaller REM sleep percentage (14.5% vs 22.6%; P < .001). Comparison of children with autism vs children with developmental delay revealed shorter total sleep time (P = .001), greater stage 1 sleep percentage (P < .001), greater slow-wave sleep percentage (P < .001), and much less REM sleep percentage (14.5% v 25%; P < .001). CONCLUSION: A relative deficiency of REM sleep may indicate an abnormality in neural organization in young children with autism that is not directly associated with or related to inherent intellectual disability but may serve as a window into understanding core neurotransmitter abnormalities unique to this disorder.
2. Canitano R, Scandurra V. {{Psychopharmacology in autism: An update}}. {Prog Neuropsychopharmacol Biol Psychiatry} (Oct 26)
Autism spectrum disorders are characterized by impairment in social reciprocity, disturbances in language and communication, restricted interests and repetitive behaviors of various types, as defined by the DSM-IV. The neurobiological bases of these disorders are poorly understood, although several abnormalities have been found. Pharmacotherapy in autism spectrum disorders lacks a solid, reliable neurobiological basis and at present it is mainly directed at the so-called associated behavioral symptoms, with limited relevance to core symptoms. Atypical neuroleptics, especially risperidone, have been shown to be useful in the treatment of behavioral symptoms in autism. Recent trials with SSRIs did not show remarkable results, in spite of their promising potential role. Attention deficit and hyperactivity disorder medications may be useful for counteracting the additional features of hyperactivity and short attention span. Antiepileptics have shown promising results but there are no specific indications for them as of yet. Research is now directed at evaluating novel treatments and combined behavioral and pharmacologic treatments, since behavioural interventions are the mainstay of the early treatment of autism. An update of currently available pharmacological treatments is provided.
3. Derosier ME, Swick DC, Davis NO, McMillen JS, Matthews R. {{The Efficacy of a Social Skills Group Intervention for Improving Social Behaviors in Children with High Functioning Autism Spectrum Disorders}}. {J Autism Dev Disord} (Nov 2)
4. Estes A, Rivera V, Bryan M, Cali P, Dawson G. {{Discrepancies Between Academic Achievement and Intellectual Ability in Higher-Functioning School-Aged Children with Autism Spectrum Disorder}}. {J Autism Dev Disord} (Nov 2)
5. Ganz JB, Lashley E, Rispoli MJ. {{Non-responsiveness to intervention: Children with autism spectrum disorders who do not rapidly respond to communication interventions}}. {Dev Neurorehabil} (Oct 31)
Objective: Providing a detailed description of two participants who failed to acquire functional communication skills following a verbal modelling intervention and Picture Exchange Communication System (PECS) training. Methods: Single-case research; Independent verbal requests, imitated verbal requests, word approximations and independent picture requests were assessed in a toddler and a pre-schooler with autism before and during two interventions. Results: Although both participants used some vocalizations over the course of the study, experimental control was not demonstrated and the participants did not acquire a functional communication system prior to the cessation of intervention. Conclusions: Future research should include additional, detailed reports that provide insight to why some children with autism do not respond to particular communication interventions and should investigate the pairing of particular child characteristics with targeted interventions.
6. Hamza RT, Hewedi DH, Ismail MA. {{Basal and Adrenocorticotropic Hormone Stimulated Plasma Cortisol Levels among Egyptian Autistic Children:Relation to Disease Severity}}. {Ital J Pediatr} (Oct 30);36(1):71.
ABSTRACT: BACKGROUND: Autism is a disorder of early childhood characterized by social impairment, communication abnormalities and stereotyped behaviors. The hypothalamo-pituitary-adrenocortical (HPA) axis deserves special attention, since it is the basis for emotions and social interactions that are affected in autism. Aim To assess basal and stimulated plasma cortisol, and adrenocorticotropic hormone(ACTH) levels in autistic children and their relationship to disease characteristics. METHODS: Fifty autistic children were studied in comparison to 50 healthy age-, sex- and pubertal stage- matched children. All subjects were subjected to clinical evaluation and measurement of plasma cortisol (basal and stimulated) and ACTH. In addition, electroencephalography (EEG) and intelligence quotient (IQ) assessment were done for all autistic children. RESULTS: Sixteen% of autistic patients had high ACTH, 10% had low basal cortisol and 10% did not show adequate cortisol response to ACTH stimulation. Autistic patients had lower basal (p=0.032) and stimulated cortisol (p=0.04) and higher ACTH (p=0.01) than controls. Childhood Autism Rating Scale (CARS) score correlated positively with ACTH (r=0.71, p=0.02) and negatively with each of basal (r=-0.64, p=0.04) and stimulated cortisol (r= -0.88, p<0.001). Hormonal profile did not differ in relation to EEG abnormalities, IQ and self- aggressive symptoms. CONCLUSIONS: The observed hormonal changes may be due to a dysfunction in the HPA axis in autistic individuals. Further studies are warranted regarding the role of HPA axis dysfunction in the pathogenesis of autism.
7. Hoeft F, Walter E, Lightbody AA, Hazlett HC, Chang C, Piven J, Reiss AL. {{Neuroanatomical Differences in Toddler Boys With Fragile X Syndrome and Idiopathic Autism}}. {Arch Gen Psychiatry} (Nov 1)
CONTEXT: Autism is an etiologically heterogeneous neurodevelopmental disorder for which there is no known unifying etiology or pathogenesis. Many conditions of atypical development can lead to autism, including fragile X syndrome (FXS), which is presently the most common known single-gene cause of autism. OBJECTIVE: To examine whole-brain morphometric patterns that discriminate young boys with FXS from those with idiopathic autism (iAUT) as well as control participants. DESIGN: Cross-sectional, in vivo neuroimaging study. SETTING: Academic medical centers. Patients Young boys (n = 165; aged 1.57-4.15 years) diagnosed as having FXS or iAUT as well as typically developing and idiopathic developmentally delayed controls. MAIN OUTCOME MEASURES: Univariate voxel-based morphometric analyses, voxel-based morphometric multivariate pattern classification (linear support vector machine), and clustering analyses (self-organizing map). RESULTS: We found that frontal and temporal gray and white matter regions often implicated in social cognition, including the medial prefrontal cortex, orbitofrontal cortex, superior temporal region, temporal pole, amygdala, insula, and dorsal cingulum, were aberrant in FXS and iAUT as compared with controls. However, these differences were in opposite directions for FXS and iAUT relative to controls; in general, greater volume was seen in iAUT compared with controls, who in turn had greater volume than FXS. Multivariate analysis showed that the overall pattern of brain structure in iAUT generally resembled that of the controls more than FXS, both with and without AUT. CONCLUSIONS: Our findings demonstrate that FXS and iAUT are associated with distinct neuroanatomical patterns, further underscoring the neurobiological heterogeneity of iAUT.
8. Kanne SM, Gerber AJ, Quirmbach LM, Sparrow SS, Cicchetti DV, Saulnier CA. {{The Role of Adaptive Behavior in Autism Spectrum Disorders: Implications for Functional Outcome}}. {J Autism Dev Disord} (Nov 2)
9. Kendler KS. {{Advances in our understanding of genetic risk factors for autism spectrum disorders}}. {Am J Psychiatry} (Nov);167(11):1291-1293.
10. Kim JE, Lyoo IK, Estes AM, Renshaw PF, Shaw DW, Friedman SD, Kim DJ, Yoon SJ, Hwang J, Dager SR. {{Laterobasal amygdalar enlargement in 6- to 7-year-old children with autism spectrum disorder}}. {Arch Gen Psychiatry} (Nov);67(11):1187-1197.
CONTEXT: There is substantial imaging evidence for volumetric abnormalities of the amygdala in younger children with autism spectrum disorder (ASD). The amygdala can be divided into functionally distinct laterobasal, superficial, and centromedial subregions. To date, we are not aware of any in vivo reports specifically assessing subregional amygdalar abnormalities in individuals with ASD. OBJECTIVES: To evaluate alterations in subregional amygdalar morphology in children with ASD compared with typically developing (TD) children and to examine the relationships with ASD symptom severity. DESIGN: A cross-sectional study encompassing a narrow age range of children with ASD and age-matched TD children that evaluated magnetic resonance imaging-defined subregional morphology of the amygdala using a novel subregional analytic method. SETTING: Participants were recruited and clinically evaluated through the University of Washington Autism Center and imaged at the Diagnostic Imaging Sciences Center at the University of Washington. Imaging data were analyzed through the Brain Imaging Laboratory at the Seoul National University. PARTICIPANTS: Fifty-one children 6 to 7 years of age (ASD, n = 31 and TD, n = 20) were assessed using magnetic resonance imaging and behavioral measures. MAIN OUTCOME MEASURES: Volume and subregional measures of the amygdala and measures of social and communication functioning. RESULTS: The ASD group exhibited larger right and left amygdalae, by 12.7% and 11.0%, respectively, relative to the TD group. Subregional analysis revealed that the ASD group had enlarged laterobasal amygdalar subregions, relative to the TD group, after adjusting for age, sex, and hemispheric cerebral volume (P < .05, false discovery rate corrected and with clustered surface points >15). Exploratory analyses revealed that there were linear trends comparing a strictly defined subgroup of children with autistic disorder, who exhibited the greatest extent of laterobasal enlargement, followed by a subgroup of children with pervasive developmental disorder not otherwise specified and then the group of TD children (P for linear trend <.001). There were linear trends between enlargement of laterobasal subregions and lower levels of social and communication functioning (P < .001, P < .001, and P = .001 for 3 areas in the right laterobasal subregion; P < .001 for 1 area in the left laterobasal subregion). CONCLUSION: The current study demonstrates bilateral enlargement of laterobasal subregions of the amygdala in 6- to 7-year-old children with ASD and that subregional alterations are associated with deficits in social and communicative behavior.
11. Loth E, Gomez JC, Happe F. {{Do High-Functioning People with Autism Spectrum Disorder Spontaneously Use Event Knowledge to Selectively Attend to and Remember Context-Relevant Aspects in Scenes?}}. {J Autism Dev Disord} (Nov 2)
12. Matson JL, Hess JA, Kozlowski AM, Neal D. {{An examination of differences in symptom endorsements of autism spectrum disorders: A comparison between mothers and fathers}}. {Dev Neurorehabil} (Oct 31)
Objective: Best assessment practices for Autism Spectrum Disorders (ASD) incorporate both multimodal and multi-informant assessments. However, differences in symptoms reports from multiple informants can lead to diagnostic decision-making problems. Methods: Thus, the purpose of this paper was to examine differences in the reports of symptoms of ASD between parents (i.e. mothers and fathers) of children and adolescents that met research criteria for an ASD and additionally for a group of children that were typically-developing (n = 39). Results: There were differences in the number of symptoms endorsed between mothers and fathers. Conclusion: Implications of the current findings are discussed.
13. McAlonan GM, Li Q, Cheung C. {{The Timing and Specificity of Prenatal Immune Risk Factors for Autism Modeled in the Mouse and Relevance to Schizophrenia}}. {Neurosignals} (Nov 2)
14. Pardini M, Guida S, Gialloreti LE. {{Aripiprazole treatment for coprophagia in autistic disorder}}. {J Neuropsychiatry Clin Neurosci} (Fall);22(4):451s e433-451 e433.
15. Pearson B, Pobbe R, Defensor E, Oasay L, Bolivar V, Blanchard D, Blanchard R. {{Motor and cognitive stereotypies in the BTBR T+tf/J mouse model of autism}}. {Genes Brain Behav} (Oct 7)
The BTBR T+tf/J inbred mouse strain displays a variety of persistent phenotypic alterations similar to those exhibited in autism spectrum disorders. The unique genetic background of the BTBR strain is thought to underlie its lack of reciprocal social interactions, elevated repetitive self-directed grooming and restricted exploratory behaviors. In order to clarify the existence, range and mechanisms of abnormal repetitive behaviors within BTBR mice, we performed detailed analyses of the microstructure of self-grooming patterns and noted increased overall grooming, higher percentages of interruptions in grooming bouts and a concomitant decrease in the proportion of incorrect sequence transitions compared to C57BL/6J inbred mice. Analyses of active phase home cage behavior also revealed an increase in stereotypic bar-biting behavior in the BTBR strain relative to B6 mice. Finally, in a novel object investigation task, BTBR mice exhibited greater baseline preference for specific unfamiliar objects as well as more patterned sequences of sequential investigations of those items. These results suggest that the repetitive, stereotyped behavior patterns of BTBR mice are relatively pervasive and reflect both motor and cognitive mechanisms. Furthermore, other pre-clinical mouse models of autism spectrum disorders may benefit from these more detailed analyses of stereotypic behavior.
16. Quintero N, McIntyre LL. {{Sibling Adjustment and Maternal Well-Being: An Examination of Families With and Without a Child With an Autism Spectrum Disorder}}. {Focus Autism Other Dev Disabl} (Mar);25(1):37-46.
Differences in sibling social, behavioral, and academic adjustment and maternal well-being in families with (n = 20) and without (n = 23) a preschooler with autism spectrum disorder (ASD) were explored. Results are interpreted to suggest that mothers of children with autism report more daily hassles, life stress, and depression than mothers without a child with ASD. There were no significant differences in parent and teacher reports of older siblings’ social, behavioral, and academic adjustment in families with and without a child with ASD. Sibling behavioral adjustment was, however, significantly related to maternal well-being. Because families with children with ASD often experience more parenting stress and depression, siblings may be more vulnerable to the cumulative risks over time.
17. Varga S. {{Pretence, Social Cognition and Self-Knowledge in Autism}}. {Psychopathology} (Nov 2);44(1):46-52.
18. Vaz I. {{Improving the management of children with learning disability and autism spectrum disorder when they attend hospital}}. {Child Care Health Dev} (Nov);36(6):753-755.
19. Warren ZE, Sanders KB, Veenstra-Vanderweele J. {{Identity crisis involving body image in a young man with autism}}. {Am J Psychiatry} (Nov);167(11):1299-1303.
20. Weng SJ, Carrasco M, Swartz JR, Wiggins JL, Kurapati N, Liberzon I, Risi S, Lord C, Monk CS. {{Neural activation to emotional faces in adolescents with autism spectrum disorders}}. {J Child Psychol Psychiatry} (Oct 7)
Background: Autism spectrum disorders (ASD) involve a core deficit in social functioning and impairments in the ability to recognize face emotions. In an emotional faces task designed to constrain group differences in attention, the present study used functional MRI to characterize activation in the amygdala, ventral prefrontal cortex (vPFC), and striatum, three structures involved in socio-emotional processing in adolescents with ASD. Methods: Twenty-two adolescents with ASD and 20 healthy adolescents viewed facial expressions (happy, fearful, sad and neutral) that were briefly presented (250 ms) during functional MRI acquisition. To monitor attention, subjects pressed a button to identify the gender of each face. Results: The ASD group showed greater activation to the faces relative to the control group in the amygdala, vPFC and striatum. Follow-up analyses indicated that the ASD relative to control group showed greater activation in the amygdala, vPFC and striatum (p < .05 small volume corrected), particularly to sad faces. Moreover, in the ASD group, there was a negative correlation between developmental variables (age and pubertal status) and mean activation from the whole bilateral amygdala; younger adolescents showed greater activation than older adolescents. There were no group differences in accuracy or reaction time in the gender identification task. Conclusions: When group differences in attention to facial expressions were limited, adolescents with ASD showed greater activation in structures involved in socio-emotional processing.
