1. Cheng H, Dharmadhikari AV, Varland S, Ma N, Domingo D, Kleyner R, Rope AF, Yoon M, Stray-Pedersen A, Posey JE, Crews SR, Eldomery MK, Akdemir ZC, Lewis AM, Sutton VR, Rosenfeld JA, Conboy E, Agre K, Xia F, Walkiewicz M, Longoni M, High FA, van Slegtenhorst MA, Mancini GMS, Finnila CR, van Haeringen A, den Hollander N, Ruivenkamp C, Naidu S, Mahida S, Palmer EE, Murray L, Lim D, Jayakar P, Parker MJ, Giusto S, Stracuzzi E, Romano C, Beighley JS, Bernier RA, Kury S, Nizon M, Corbett MA, Shaw M, Gardner A, Barnett C, Armstrong R, Kassahn KS, Van Dijck A, Vandeweyer G, Kleefstra T, Schieving J, Jongmans MJ, de Vries BBA, Pfundt R, Kerr B, Rojas SK, Boycott KM, Person R, Willaert R, Eichler EE, Kooy RF, Yang Y, Wu JC, Lupski JR, Arnesen T, Cooper GM, Chung WK, Gecz J, Stessman HAF, Meng L, Lyon GJ. {{Truncating Variants in NAA15 Are Associated with Variable Levels of Intellectual Disability, Autism Spectrum Disorder, and Congenital Anomalies}}. {Am J Hum Genet};2018 (Apr 9)
N-alpha-acetylation is a common co-translational protein modification that is essential for normal cell function in humans. We previously identified the genetic basis of an X-linked infantile lethal Mendelian disorder involving a c.109T>C (p.Ser37Pro) missense variant in NAA10, which encodes the catalytic subunit of the N-terminal acetyltransferase A (NatA) complex. The auxiliary subunit of the NatA complex, NAA15, is the dimeric binding partner for NAA10. Through a genotype-first approach with whole-exome or genome sequencing (WES/WGS) and targeted sequencing analysis, we identified and phenotypically characterized 38 individuals from 33 unrelated families with 25 different de novo or inherited, dominantly acting likely gene disrupting (LGD) variants in NAA15. Clinical features of affected individuals with LGD variants in NAA15 include variable levels of intellectual disability, delayed speech and motor milestones, and autism spectrum disorder. Additionally, mild craniofacial dysmorphology, congenital cardiac anomalies, and seizures are present in some subjects. RNA analysis in cell lines from two individuals showed degradation of the transcripts with LGD variants, probably as a result of nonsense-mediated decay. Functional assays in yeast confirmed a deleterious effect for two of the LGD variants in NAA15. Further supporting a mechanism of haploinsufficiency, individuals with copy-number variant (CNV) deletions involving NAA15 and surrounding genes can present with mild intellectual disability, mild dysmorphic features, motor delays, and decreased growth. We propose that defects in NatA-mediated N-terminal acetylation (NTA) lead to variable levels of neurodevelopmental disorders in humans, supporting the importance of the NatA complex in normal human development.
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2. Fluegge K. {{Music Therapy and Social Skills in Autism: Underlying Biological Mechanisms}}. {Adv Biomed Res};2018;7:57.
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3. Guissart C, Latypova X, Rollier P, Khan TN, Stamberger H, McWalter K, Cho MT, Kjaergaard S, Weckhuysen S, Lesca G, Besnard T, Ounap K, Schema L, Chiocchetti AG, McDonald M, de Bellescize J, Vincent M, Van Esch H, Sattler S, Forghani I, Thiffault I, Freitag CM, Barbouth DS, Cadieux-Dion M, Willaert R, Guillen Sacoto MJ, Safina NP, Dubourg C, Grote L, Carre W, Saunders C, Pajusalu S, Farrow E, Boland A, Karlowicz DH, Deleuze JF, Wojcik MH, Pressman R, Isidor B, Vogels A, Van Paesschen W, Al-Gazali L, Al Shamsi AM, Claustres M, Pujol A, Sanders SJ, Rivier F, Leboucq N, Cogne B, Sasorith S, Sanlaville D, Retterer K, Odent S, Katsanis N, Bezieau S, Koenig M, Davis EE, Pasquier L, Kury S. {{Dual Molecular Effects of Dominant RORA Mutations Cause Two Variants of Syndromic Intellectual Disability with Either Autism or Cerebellar Ataxia}}. {Am J Hum Genet};2018 (Apr 10)
RORalpha, the RAR-related orphan nuclear receptor alpha, is essential for cerebellar development. The spontaneous mutant mouse staggerer, with an ataxic gait caused by neurodegeneration of cerebellar Purkinje cells, was discovered two decades ago to result from homozygous intragenic Rora deletions. However, RORA mutations were hitherto undocumented in humans. Through a multi-centric collaboration, we identified three copy-number variant deletions (two de novo and one dominantly inherited in three generations), one de novo disrupting duplication, and nine de novo point mutations (three truncating, one canonical splice site, and five missense mutations) involving RORA in 16 individuals from 13 families with variable neurodevelopmental delay and intellectual disability (ID)-associated autistic features, cerebellar ataxia, and epilepsy. Consistent with the human and mouse data, disruption of the D. rerio ortholog, roraa, causes significant reduction in the size of the developing cerebellum. Systematic in vivo complementation studies showed that, whereas wild-type human RORA mRNA could complement the cerebellar pathology, missense variants had two distinct pathogenic mechanisms of either haploinsufficiency or a dominant toxic effect according to their localization in the ligand-binding or DNA-binding domains, respectively. This dichotomous direction of effect is likely relevant to the phenotype in humans: individuals with loss-of-function variants leading to haploinsufficiency show ID with autistic features, while individuals with de novo dominant toxic variants present with ID, ataxia, and cerebellar atrophy. Our combined genetic and functional data highlight the complex mutational landscape at the human RORA locus and suggest that dual mutational effects likely determine phenotypic outcome.
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4. Hedley D, Uljarevic M, Foley KR, Richdale A, Trollor J. {{Risk and protective factors underlying depression and suicidal ideation in Autism Spectrum Disorder}}. {Depress Anxiety};2018 (Apr 16)
BACKGROUND: People with Autism Spectrum Disorder (ASD) are at significantly increased risk of suicidal thoughts and behavior. Given that social difficulties in ASD often lead to social isolation, which can in turn increase the risk for depression, this study examined loneliness and social support as potential risk and protective factors associated with depression and suicidal ideation. METHOD: The sample comprised 185 people (92 females) with ASD aged 14 to 80 years who were participating in a national survey. RESULTS: Forty-nine percent of participants returned scores in the clinical range for depression and 36% reported recent suicidal ideation. Females, comprising almost 50% of the sample, returned higher depression scores than males, however no differences were identified between males and females in terms of suicidal ideation. Regression analyses revealed that loneliness, satisfaction with social support, and ASD traits predicted depression scores. Satisfaction with social support predicted suicidal ideation, however, it was no longer a significant predictor after the effects of depression were taken into account. Path analysis showed that ASD trait severity was independently related to depression, that the effect of number of social supports on depression was mediated by loneliness and satisfaction with social support, and that effects of loneliness and satisfaction with social support on suicidal ideation were mediated by depression. The pattern of relationships was nearly identical for males and females. CONCLUSIONS: This study supports a model whereby loneliness and social support operate respectively as protective and risk factors for depression and suicidal ideation in ASD.
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5. Hennessey T, Andari E, Rainnie DG. {{RDoC-based categorization of amygdala functions and its implications in autism}}. {Neurosci Biobehav Rev};2018 (Apr 13)
Confusion endures as to the exact role of the amygdala in relation to autism. To help resolve this we turned to the NIMH’s Research Domain Criteria (RDoC) which provides a classification schema that identifies different categories of behaviors that can turn pathologic in mental health disorders, e.g. autism. While RDoC incorporates all the known neurobiological substrates for each domain, this review will focus primarily on the amygdala. We first consider the amygdala from an anatomical, historical, and developmental perspective. Next, we examine the different domains and constructs of RDoC that the amygdala is involved in: Negative Valence Systems, Positive Valence Systems, Cognitive Systems, Social Processes, and Arousal and Regulatory Systems. Then the evidence for a dysfunctional amygdala in autism is presented with a focus on alterations in development, prenatal valproic acid exposure as a model for ASD, and changes in the oxytocin system therein. Finally, a synthesis of RDoC, the amygdala, and autism is offered, emphasizing the task of disambiguation and suggestions for future research.
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6. Pua EPK, Malpas CB, Bowden SC, Seal ML. {{Different brain networks underlying intelligence in autism spectrum disorders}}. {Hum Brain Mapp};2018 (Apr 17)
There has been sustained clinical and cognitive neuroscience research interest in how network correlates of brain-behavior relationships might be altered in Autism Spectrum Disorders (ASD) and other neurodevelopmental disorders. As previous work has mostly focused on adults, the nature of whole-brain connectivity networks underlying intelligence in pediatric cohorts with abnormal neurodevelopment requires further investigation. We used network-based statistics (NBS) to examine the association between resting-state functional Magnetic Resonance Imaging (fMRI) connectivity and fluid intelligence ability in male children (n = 50) with Autism Spectrum Disorders (ASD; M = 10.45, SD = 1.58 years and in controls (M = 10.38, SD = 0.96 years) matched on fluid intelligence performance, age and sex. Repeat analyses were performed in independent sites for validation and replication. Despite being equivalent on fluid intelligence ability to strictly matched neurotypical controls, boys with ASD displayed a subnetwork of significantly increased associations between functional connectivity and fluid intelligence. Between-group differences remained significant at higher edge thresholding, and results were validated in independent-site replication analyses in an equivalent age and sex-matched cohort with ASD. Regions consistently implicated in atypical connectivity correlates of fluid intelligence in ASD were the angular gyrus, posterior middle temporal gyrus, occipital and temporo-occipital regions. Development of fluid intelligence neural correlates in young ASD males is aberrant, with an increased strength in intrinsic connectivity association during childhood. Alterations in whole-brain network correlates of fluid intelligence in ASD may be a compensatory mechanism that allows equal task performance to neurotypical peers.
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7. Sen B, Borle NC, Greiner R, Brown MRG. {{A general prediction model for the detection of ADHD and Autism using structural and functional MRI}}. {PLoS One};2018;13(4):e0194856.
This work presents a novel method for learning a model that can diagnose Attention Deficit Hyperactivity Disorder (ADHD), as well as Autism, using structural texture and functional connectivity features obtained from 3-dimensional structural magnetic resonance imaging (MRI) and 4-dimensional resting-state functional magnetic resonance imaging (fMRI) scans of subjects. We explore a series of three learners: (1) The LeFMS learner first extracts features from the structural MRI images using the texture-based filters produced by a sparse autoencoder. These filters are then convolved with the original MRI image using an unsupervised convolutional network. The resulting features are used as input to a linear support vector machine (SVM) classifier. (2) The LeFMF learner produces a diagnostic model by first computing spatial non-stationary independent components of the fMRI scans, which it uses to decompose each subject’s fMRI scan into the time courses of these common spatial components. These features can then be used with a learner by themselves or in combination with other features to produce the model. Regardless of which approach is used, the final set of features are input to a linear support vector machine (SVM) classifier. (3) Finally, the overall LeFMSF learner uses the combined features obtained from the two feature extraction processes in (1) and (2) above as input to an SVM classifier, achieving an accuracy of 0.673 on the ADHD-200 holdout data and 0.643 on the ABIDE holdout data. Both of these results, obtained with the same LeFMSF framework, are the best known, over all hold-out accuracies on these datasets when only using imaging data-exceeding previously-published results by 0.012 for ADHD and 0.042 for Autism. Our results show that combining multi-modal features can yield good classification accuracy for diagnosis of ADHD and Autism, which is an important step towards computer-aided diagnosis of these psychiatric diseases and perhaps others as well.
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8. Smith IN, Thacker S, Jaini R, Eng C. {{Dynamics and Structural Stability Effects of Germline PTEN Mutations Associated with Cancer versus Autism Phenotypes}}. {J Biomol Struct Dyn};2018 (Apr 17):1-44.
Individuals with germline mutations in the tumor suppressor gene phosphatase and tensin homolog (PTEN), irrespective of clinical presentation, are diagnosed with PTEN hamartoma tumor syndrome (PHTS). PHTS confers a high risk of breast, thyroid, and other cancers or autism spectrum disorder (ASD) with macrocephaly. It remains unclear why mutations in one gene can lead to seemingly disparate phenotypes. Thus, we sought to identify differences in ASD vs. cancer-associated germline PTEN missense mutations by investigating putative structural effects induced by each mutation. We utilized a theoretical computational approach combining in silico structural analysis and molecular dynamics (MD) to interrogate 17 selected mutations from our patient population: six mutations were observed in patients with ASD (only), six mutations in patients with PHTS-associated cancer (only), four mutations shared across both phenotypes, and one mutation with both ASD and cancer. We demonstrate structural stability changes where all six cancer-associated mutations showed a global decrease in structural stability and increased dynamics across the domain interface with a proclivity to unfold, mediating a closed (inactive) active site. In contrast, five of the six ASD-associated mutations showed localized destabilization that contribute to the partial opening of the active site. Our results lend insight into distinctive structural effects of germline PTEN mutations associated with PTEN-ASD vs. those associated with PTEN-cancer, potentially aiding in identification of the shared and separate molecular features that contribute to autism or cancer, thus, providing a deeper understanding of genotype-phenotype relationships for germline PTEN mutations.
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9. Tarquinio DC, Hou W, Neul JL, Berkmen GK, Drummond J, Aronoff E, Harris J, Lane JB, Kaufmann WE, Motil KJ, Glaze DG, Skinner SA, Percy AK. {{The course of awake breathing disturbances across the lifespan in Rett syndrome}}. {Brain Dev};2018 (Apr 12)
Rett syndrome (RTT), an X-linked dominant neurodevelopmental disorder caused by mutations in MECP2, is associated with a peculiar breathing disturbance exclusively during wakefulness that is distressing, and can even prompt emergency resuscitation. Through the RTT Natural History Study, we characterized cross sectional and longitudinal characteristics of awake breathing abnormalities in RTT and identified associated clinical features. Participants were recruited from 2006 to 2015, and cumulative lifetime prevalence of breathing dysfunction was determined using the Kaplan-Meier estimator. Risk factors were assessed using logistic regression. Of 1205 participants, 1185 had sufficient data for analysis, including 922 females with classic RTT, 778 of whom were followed longitudinally for up to 9.0years, for a total of 3944 person-years. Participants with classic or atypical severe RTT were more likely to have breathing dysfunction (nearly 100% over the lifespan) compared to those with atypical mild RTT (60-70%). Remission was common, lasting 1year on average, with 15% ending the study in terminal remission. Factors associated with higher odds of severe breathing dysfunction included poor gross and fine motor function, frequency of stereotypical hand movements, seizure frequency, prolonged corrected QT interval on EKG, and two quality of life metrics: caregiver concern about physical health and contracting illness. Factors associated with lower prevalence of severe breathing dysfunction included higher body mass index and head circumference Z-scores, advanced age, and severe scoliosis or contractures. Awake breathing dysfunction is common in RTT, more so than seizures, and is associated with function, quality of life and risk for cardiac dysrhythmia.
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10. Wiktor DM, Carroll JD. {{ASD Closure in Structural Heart Disease}}. {Curr Cardiol Rep};2018 (Apr 17);20(6):37.
PURPOSE OF REVIEW: While the safety and efficacy of percutaneous ASD closure has been established, new data have recently emerged regarding the negative impact of residual iatrogenic ASD (iASD) following left heart structural interventions. Additionally, new devices with potential advantages have recently been studied. We will review here the potential indications for closure of iASD along with new generation closure devices and potential late complications requiring long-term follow-up. RECENT FINDINGS: With the expansion of left-heart structural interventions and large-bore transseptal access, there has been growing experience gained with management of residual iASD. Some recently published reports have implicated residual iASD after these procedures as a potential source of diminished clinical outcomes and mortality. Additionally, recent trials investigating new generation closure devices as well as expanding knowledge regarding late complications of percutaneous ASD closure have been published. While percutaneous ASD closure is no longer a novel approach to managing septal defects, there are several contemporary issues related to residual iASD following large-bore transseptal access and new generation devices which serve as an impetus for this review. Ongoing attention to potential late complications and decreasing their incidence with ongoing study is clearly needed.
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11. Zu C, Gao Y, Munsell B, Kim M, Peng Z, Zhu Y, Gao W, Zhang D, Shen D, Wu G. {{Learning Subnetwork Biomarkers via Hypergraph for Classification of Autism Disease}}. {Proc Int Soc Magn Reson Med Sci Meet Exhib Int Soc Magn Reson Med Sci Meet Exhib};2017 (Apr);2017:1719.
