Faculty Bibliography

Reports an error in "Subcortical brain volume differences in participants with attention deficit hyperactivity disorder in children and adults: A cross-sectional mega-analysis" by Martine Hoogman, Janita Bralten, Derrek P. Hibar, Maarten Mennes, Marcel P. Zwiers, Lizanne S. J. Schweren, Kimm J. E. van Hulzen, Sarah E. Medland, Elena Shumskaya, Neda Jahanshad, Patrick de Zeeuw, Eszter Szekely, Gustavo Sudre, Thomas Wolfers, Alberdingk M. H. Onnink, Janneke T. Dammers, Jeanette C. Mostert, Yolanda Vives-Gilabert, Gregor Kohls, Eileen Oberwelland, Jochen Seitz, Martin Schulte-Ruther, Sara Ambrosino, Alysa E. Doyle, Marie F. Hovik, Margaretha Dramsdahl, Leanne Tamm, Theo G. M. van Erp, Anders Dale, Andrew Schork, Annette Conzelmann, Kathrin Zierhut, Ramona Baur, Hazel McCarthy, Yuliya N. Yoncheva, Ana Cubillo, Kaylita Chantiluke, Mitul A. Mehta, Yannis Paloyelis, Sarah Hohmann, Sarah Baumeister, Ivanei Bramati, Paulo Mattos, Fernanda Tovar-Moll, Pamela Douglas, Tobias Banaschewski, Daniel Brandeis, Jonna Kuntsi, Philip Asherson, Katya Rubia, Clare Kelly, Adriana Di Martino, Michael P. Milham, Francisco X. Castellanos, Thomas Frodl, Mariam Zentis, Klaus-Peter Lesch, Andreas Reif, Paul Pauli, Terry L. Jernigan, Jan Haavik, Kerstin J. Plessen, Astri J. Lundervold, Kenneth Hugdahl, Larry J. Seidman, Joseph Biederman, Nanda Rommelse, Dirk J. Heslenfeld, Catharina A. Hartman, Pieter J. Hoekstra, Jaap Oosterlaan, Georg von Polier, Kerstin Konrad, Oscar Vilarroya, Josep Antoni Ramos-Quiroga, Joan Carles Soliva, Sarah Durston, Jan K. Buitelaar, Stephen V. Faraone, Philip Shaw, Paul M. Thompson and Barbara Franke (The Lancet Psychiatry, 2017[Apr], Vol 4[4], 310-319). In the original article, there were some errors. Corrections are present in the erratum. (The abstract of the original article appeared in record 2017-14573-025).

Perceived social support (PSS) has been related to physical and mental well-being in typically developing individuals, but systematic characterizations of PSS in autism spectrum disorder (ASD) are limited. We compared self-report ratings of the multidimensional scale of PSS (MSPSS) among age- and IQ-matched groups of adults (18-58 years) with cognitively high-functioning ASD (N = 41), or attention-deficit/hyperactivity disorder (ADHD; N = 69), and neurotypical controls (NC; N = 69). Accompanying group comparisons, we used machine learning random forest (RF) analyses to explore predictors among a range of psychopathological and socio-emotional variables. Relative to both ADHD and NC, adults with ASD showed lower MSPSS ratings, specifically for the friends subscale (MSPSS-f). Across ASD and ADHD, interindividual differences in autism severity, affective empathy, symptoms of anxiety related to social interactions, hyperactivity/impulsivity, and somatization best predicted MSPSS-f. These relationships did not differ between clinical groups. While group comparisons demonstrated greater impairment in individuals with ASD, analyzing individuals' characteristics revealed cross-diagnoses similarities in regard to their MSPSS-f relationships. This is consistent with the Research Domain Criteria framework, supporting a trans-diagnostic approach as on the path toward "precision medicine." Autism Res 2017. (c) 2017 International Society for Autism Research, Wiley Periodicals, Inc.

The second iteration of the Autism Brain Imaging Data Exchange (ABIDE II) aims to enhance the scope of brain connectomics research in Autism Spectrum Disorder (ASD). Consistent with the initial ABIDE effort (ABIDE I), that released 1112 datasets in 2012, this new multisite open-data resource is an aggregate of resting state functional magnetic resonance imaging (MRI) and corresponding structural MRI and phenotypic datasets. ABIDE II includes datasets from an additional 487 individuals with ASD and 557 controls previously collected across 16 international institutions. The combination of ABIDE I and ABIDE II provides investigators with 2156 unique cross-sectional datasets allowing selection of samples for discovery and/or replication. This sample size can also facilitate the identification of neurobiological subgroups, as well as preliminary examinations of sex differences in ASD. Additionally, ABIDE II includes a range of psychiatric variables to inform our understanding of the neural correlates of co-occurring psychopathology; 284 diffusion imaging datasets are also included. It is anticipated that these enhancements will contribute to unraveling key sources of ASD heterogeneity.

Recent advances in neuroimaging have offered a rich array of structural and functional markers to probe the organization of regional and large-scale brain networks. The current chapter provides a brief introduction into these techniques and overviews their contribution to the understanding of autism spectrum disorder (ASD), a neurodevelopmental condition associated with atypical social cognition, language function, and repetitive behaviors/interests. While it is generally recognized that ASD relates to structural and functional network anomalies, the extent and overall pattern of reported findings have been rather heterogeneous. Indeed, while several attempts have been made to label the main neuroimaging phenotype of ASD (e.g., 'early brain overgrowth hypothesis', 'amygdala theory', 'disconnectivity hypothesis'), none of these frameworks has been without controversy. Methodological sources of inconsistent results may include differences in subject inclusion criteria, variability in image processing, and analysis methodology. However, inconsistencies may also relate to high heterogeneity across the autism spectrum itself. It, therefore, remains to be investigated whether a consistent imaging phenotype that adequately describes the entire autism spectrum can, in fact, be established. On the other hand, as previous findings clearly emphasize the value of neuroimaging in identifying atypical brain morphology, function, and connectivity, they ultimately support its high potential to identify biologically and clinically relevant endophenotypes.

Objectives: We present initial empirical work examining neural markers of social communicative impairment characteristic of ASD across children with ASD and ADHD. Increasing evidence indicates that autistic traits (AT) are present in a substantial group of children with ADHD. These children do not meet diagnostic criteria for ASD, present higher functional impairment, or pose a challenge for recognition and treatment. To date, it is unknown whether AT in ADHD and ASD represent similar neurobiological dysfunctions. Methods: To address this question, we examined resting-state fMRI data from children with ADHD (mean age 9.5 +/- 1.6 years), identified as ADHD with AT (ADHD+AT; N = 45), or without ADHD (ADHD-AT; N = 57) per parent responses on the Social Responsiveness Scale. We conducted seed-based connectivity analyses of the right fusiform face area (FFA). After removal of nuisance signals (24-Friston motion parameters, cerebral spinal fluid, and white matter masks), we extracted the residual mean time series for the FFA seed. We then ran between-group analysis using random effect models [covariate: age, motion, subjects, whole-brain intrinsic functional connectivity (iFC) average]. Gaussian random field theory corrected for multiple comparisons (Z > 2.3, p < 0.05). Results: Children with ADHD+AT had weaker iFC between the right FFA and left rostral anterior cingulate cortex (ACC). Secondary analyses with agematched children with ASD (N = 57) showed a hypoconnectivity iFC pattern similar to ADHD+AT. Conclusions: These initial findings highlight a circuit involving two core hubs of the social brain: the FFA subserving face recognition and the ACC subserving "mentalizing." Weaker iFC between these nodes characterized children with AT regardless of their DSM-based diagnosis, illustrating the use of eschewing extreme comparisons for the identification of potential biomarkers specific to and shared across psychiatric conditions

Objectives: Dramatic changes in typical brain organization occur during the first 5 years of life. There is a critical time window for the emergence of life- long pervasive psychiatric conditions, such as autism, and possibly for the initiation of processes resulting in later onset psychopathology. This presentation aims to provide an overview of the growing abilities of pediatric imaging to comprehensively map the development of neural circuitry (i.e., the connectome) in the early years of life and during the prenatal period. Implications for efforts to delineate typical from atypical development will be discussed. Methods: Dr. Adriana Di Martino will review recent methodological advances in functional and structural imaging for the developing connectome, including natural sleep MRI (for infants and toddlers/preschoolers) and fetal imaging. She will discuss the potential translational impact of these methodologies. Examples of possible uses in the future will be provided, which can range from identifying etiologic factors contributing to the development of mental illness to informing assessments of risk and prognosis. Current gaps and obstacles that need to be addressed also will be highlighted. Results: The audience will gain insight into the impact of recent technical and methodological advances on our ability to characterize early brain development in vivo. Furthermore, participants will learn of the short-term implications for our understanding of how abnormal patterns of brain connectivity emerge and potential long-term implications for translational pursuits (e.g., inform assessment of risk and prognosis). Finally, they will learn of the gaps and obstacles that must be addressed for these visions to be realized. Conclusions: Although brain connectomics has just begun to understand normative early developmental trajectories and their interfering factors, examples of its potential for translational impact are growing. As the field continues to overcome technical challenges, the potential for brain imaging to deliver clinically useful findings will continue to increase

Objectives: Organizational Skills Training (OST), is a 10-week psychosocial intervention found effective in improving organizational, time management, and planning (OTMP) skills in children with Attention-Deficit/Hyperactivity Disorder (ADHD). Little is known about the feasibility of identifying brain markers for treatment response. Using resting state fMRI (R-fMRI), we aimed to examine neuronal correlates of post-treatment change as a first step toward larger controlled studies of objective predictors of treatment response. Methods: We examined pre- and post-OST R-fMRI data of 15 children (12 males; mean age: 9+/-1 year) with ADHD and significant impairments in OTMP skills indexed by total scores on Children's Organizational Skills Scales-Parent (COSS-P) or Teacher (COSS-T). Our primary outcome measure was the change in COSS-P scores. As secondary summary outcome measure, we used prepost Z-score differences averaged across COSS-T, Homework Problems Checklist, Academic Progress Report and Academic Performance Rating scales. We selected a priori the intrinsic functional connectivity (iFC) of the dorsal anterior cingulate cortex (dACC), based on its role on cognitive control. Multivariate distance matrix regression (MDMR) analysis additionally allowed for whole-brain explorations. Follow-up iFC analyses were conducted on regions with significant within-subject post-OST differences by MDMR analysis. Results: COSS-P decreased significantly (t=7.1, p< 0.0001). In a cluster involving striatum bilaterally, dACC iFC decreased post-OST; these decreases were positively correlated with COSS-P improvements (r=.34, NS) and to improvements in the summary outcome (r=.63; p<0.03). MDMR analyses revealed iFC changes in the right medial and lateral precentral cortex. Followup seed-based iFC analyses of this region showed significant decreases in cortico-striatal iFC post-OST. Conclusions: Results support the feasibility of identifying changes in brain iFC after OST. Two distinct analysis converged on decreased corticosubcortical iFC post-treatment which related to change in clinical measures. As decreases in striato-cortical iFC characterize typical development, results suggest regionally-specific enhanced maturational effects of OST

Objectives: A growing literature indicates that caregiver-mediated social skills interventions increase social competence among children with autism; however, very little is known about the role of parent characteristics in treatment success. As an initial step toward closing this gap, we examined the following: 1) the feasibility of collecting measures of caregivers and children enrolled in these interventions in a clinic setting; and 2) the relationships between baseline measures of caregivers and their children. Methods: We enrolled 19 children with autism (15 males; mean age = 11 +/- 3 years) and 19 caregivers (one per child; 15 females; mean age = 48 +/- 8 years) in either the Program for the Education and Enrichment of Relational Skills (PEERS) or the Children's Friendship Training. The Social Responsiveness Scale, 2nd Edition parent report (SRS-2-P) and the Child Behavior Checklist (CBCL) parent report were used to index children's autism severity and their internalizing and externalizing symptoms of psychopathology. Parent autistic traits were assessed using the SRS-2 adult form (SRS-2-A), which were completed by their spouses. Parent-rated Positive Affect Index (PAI) assessed the quality of the parent-child relationship. We measured the relationship between child and caregiver characteristics using two-tailed bivariate correlations. Results: Relationship quality, as measured by the PAI, varied across families (mean age = 47 +/- 8 years). High relationship quality was correlated negatively with scores of the CBCL Externalizing Problems Scale (r = -0.69, P = 0.004) and several subscales that load onto this scale (e.g., aggressive behavior, r = -0.73, P = 0.002). The SRS-2-P scores indicated that children have clinically significant scores, whereas the SRS-2-A scores indicate their caregivers do not. There was no significant relationship between SRS-2-P and SRS-2-A scores (r = -0.03, P = 0.94) or PAI and SRS-2-P scores (r = -0.30, P = 0.40). Conclusions: Results indicate that it is feasible to collect caregiver and child data in the context of a clinic-based, caregiver-mediated intervention. Preliminary data underscore the relationship between caregiver-child relationship quality and externalizing behavioral challenges in children with autism. This relationship should be investigated as a potential mediator of treatment effects

BACKGROUND: Autism spectrum disorder (ASD) encompasses a complex manifestation of symptoms that include deficits in social interaction and repetitive or stereotyped interests and behaviors. In keeping with the increasing recognition of the dimensional characteristics of ASD symptoms and the categorical nature of a diagnosis, we sought to delineate the neural mechanisms of ASD symptoms based on the functional connectivity of four known neural networks (i.e., default mode network, dorsal attention network, salience network, and executive control network). METHODS: We leveraged an open data resource (Autism Brain Imaging Data Exchange) providing resting-state functional magnetic resonance imaging data sets from 90 boys with ASD and 95 typically developing boys. This data set also included the Social Responsiveness Scale as a dimensional measure of ASD traits. Seed-based functional connectivity was paired with linear regression to identify functional connectivity abnormalities associated with categorical effects of ASD diagnosis, dimensional effects of ASD-like behaviors, and their interaction. RESULTS: Our results revealed the existence of dimensional mechanisms of ASD uniquely affecting each network based on the presence of connectivity-behavioral relationships; these were independent of diagnostic category. However, we also found evidence of categorical differences (i.e., diagnostic group differences) in connectivity strength for each network as well as categorical differences in connectivity-behavioral relationships (i.e., diagnosis-by-behavior interactions), supporting the coexistence of categorical mechanisms of ASD. CONCLUSIONS: Our findings support a hybrid model for ASD characterization that includes a combination of categorical and dimensional brain mechanisms and provide a novel understanding of the neural underpinnings of ASD.

OBJECTIVES: Clinical neuroscience is increasingly turning to imaging the human brain for answers to a range of questions and challenges. To date, the majority of studies have focused on the neural basis of current psychiatric symptoms, which can facilitate the identification of neurobiological markers for diagnosis. However, the increasing availability and feasibility of using imaging modalities, such as diffusion imaging and resting-state fMRI, enable longitudinal mapping of brain development. This shift in the field is opening the possibility of identifying predictive markers of risk or prognosis, and also represents a critical missing element for efforts to promote personalized or individualized medicine in psychiatry (i.e., stratified psychiatry). METHODS: The present work provides a selective review of potentially high-yield populations for longitudinal examination with MRI, based upon our understanding of risk from epidemiologic studies and initial MRI findings. RESULTS: Our discussion is organized into three topic areas: (1) practical considerations for establishing temporal precedence in psychiatric research; (2) readiness of the field for conducting longitudinal MRI, particularly for neurodevelopmental questions; and (3) illustrations of high-yield populations and time windows for examination that can be used to rapidly generate meaningful and useful data. Particular emphasis is placed on the implementation of time-appropriate, developmentally informed longitudinal designs, capable of facilitating the identification of biomarkers predictive of risk and prognosis. CONCLUSIONS: Strategic longitudinal examination of the brain at-risk has the potential to bring the concepts of early intervention and prevention to psychiatry. (JINS, 2016, 22, 164-179).