- Email: [email protected]
2.7 Everyone Likes Candi: Data Sharing and Neuroinformatics to Address Big Data Questions
INSTITUTES 2.6 — 3.0
using rTMS have examined resting-state connectivity biomarker approaches for MDD. Emerging data suggest that high-frequency rTMS treatments may modulate frontostriatal connectivity. Other recent efforts have identified a resting-state biotype, which may predict responsiveness to rTMS therapy for MDD. Although data from future adolescent studies may diverge from adults, these initial efforts will inform future study design. Existing studies with magnetic resonance spectroscopy suggest that successful rTMS in adolescent depression may potentiate cortical glutamate neurotransmission. Conclusions: Prior studies suggest that rTMS will play an important role as a neurophysiological probe and therapeutic intervention in future research. Synergistic research with neuroimaging modalities holds the promise of enhancing the efficacy of therapeutic rTMS and informing developmental neuroscience. Ideal future study designs with rTMS and neuroimaging will concurrently address both of these broad goals.
DDD, IMAGS, NM Supported by Pfizer ASPIRE Grant WS1976243, Assurex, Neuronetics, the Brain and Behavior Research Foundation, the Mayo Clinic Foundation, and NIMH Grant K23 MH100266 http://dx.doi.org/10.1016/j.jaac.2017.07.518
2.6 USING BRAIN-BASED MECHANISMS TO INFORM NOVEL TREATMENTS FOR SEVERE IRRITABILITY Ellen Leibenluft, MD, National Institute of Mental Health, [email protected]; Katharina Kircanski, PhD, National Institute of Mental Health, [email protected]; Joel Stoddard, MD, MAS, University of Colorado Denver, [email protected]; Argyris Stringaris, MD, PhD, National Institute of Health, [email protected]; Daniel S. Pine, MD, National Institute of Mental Health, daniel.pine@ nih.gov; Melissa A. Brotman, PhD, National Institute of Mental Health, [email protected] Objectives: Brain-based research can guide the development of novel treatments for severe irritability, as operationalized in DSM-5 classification of disruptive mood dysregulation disorder (DMDD). This presentation will describe two such treatments: interpretation bias training (IBT) and an exposure-based CBT for frustration, accompanied by parent training. Methods: Studies using standardized behavioral paradigms and fMRI were used to test the hypothesis that irritability in youth is associated with aberrant responses to frustration (including decreased threshold, increased amplitude, and increased duration of the emotional response) and aberrant approach responses to threat. This translational model for irritability further posits specific deficits relevant to aberrant reward processing, including deficits in the content and process of instrumental learning, and increased sensitivity to reward omission. Results: With regard to aberrant responses to threat, research indicates that, relative to healthy youth, those with DMDD are more likely to view ambiguous faces as angry rather than happy. Furthermore, one clinical trial demonstrated that computer-based training designed to rectify this interpretation bias was effective in decreasing aggression in youth at risk for criminal behavior. We have demonstrated that such training can shift perceptions in youth with DMDD and are now conducting a randomized clinical trial to test whether such shifts are associated with decreased irritability. The new CBT treatment posits that parent training can be used to alter the child’s deficits in instrumental learning secondary to suboptimal reinforcers in the home environment and that exposing children to frustrating situations in a graded fashion will, through extinction learning, allow them to develop increased tolerance for frustration and more adaptive coping strategies. For both studies, fMRI studies pre- and posttreatment will test whether the hypothesized brain mechanisms mediate clinical response. Conclusions: Translational neuroscience research can suggest new avenues to address the dearth of evidence-based treatment for the common and impairing clinical presentation of severe irritability in children.
CBT, IMAGS, IMD http://dx.doi.org/10.1016/j.jaac.2017.07.519
S138
www.jaacap.org
2.7 EVERYONE LIKES CANDI: DATA SHARING AND NEUROINFORMATICS TO ADDRESS BIG DATA QUESTIONS Jean A. Frazier, MD, UMass Medical School, Jean.Frazier@ umassmed.edu; Steve Hodge, MA, UMass Medical School, [email protected]; Jean-Baptiste Poline, PhD, Helen Wills Neuroscience Institute, [email protected]; Christian Haselgrove, BA, UMass Medical School, Christian. [email protected]; David Cochran, MD, PhD, UMass Medical School, [email protected]; David Kennedy, PhD, UMass Medical School, David. [email protected] Objectives: A substantial amount of neuroimaging data are now being shared that will allow us to answer important questions, thanks to efforts by the NIH Pediatric Database (PEDS); Autism Brain Data Exchange (ABIDE); and Pediatric Imaging, Neurocognition and Genetics (PING). We will discuss the use of these shared resources and ways to use them to answer important questions. For example, in typical development, do multiple sources of developmental data tell us the same things about the developmental trajectory and sex effects? Methods: By use of these shared data resources and a specific structural analysis workflow (Freesurfer), we can ask for a given statistical model if there is consistency of effect. As an example structure that lets us examine some specific questions in this data, we explore the total hippocampus volume in these datasets. Results: Our first analysis looks at the sex effect of the total hippocampus volume across three datasets: PING, PEDS, and ABIDE, including 95% confidence limits for the model [total hippocampus volume w sex + age + sex age + total cerebral volume (TCV) + site]. Neither PEDS (N w 300) nor ABIDE (N w 400) indicates a significant gender effect, whereas the sex effect is significant and seen to be w3% in the PING (N w 1,200) dataset. Using the PING data, where we have access to the most complete set of behavioral and demographic factors, we generate 32 model permutations that include the following factors: age, sex, site, socioeconomic status (SES), genetic ancestry factors, and intracranial volume (ICV). Accounting for ICV greatly reduces the magnitude of the sex effect that is over and above the allometric scaling of total brain. All of these sex effects are significant, and despite being lower in magnitude, the models that include ICV show an increase in R2 from w0.25 to w0.40, indicating a better overall fit to the data. Conclusions: These results demonstrate that, even before considering the subtle modulations caused by diagnostic effects of child mental health disorders, careful attention to data model and data sources is needed to definitely document developmental factors in brain-imaging data.
DAM, IMAGS, NEURODEV Supported by NIH-National Institute of Biomedical Imaging and Bioengineering Grant P41 EB019936 and NIH-NIMH Grant R01 MH083320 http://dx.doi.org/10.1016/j.jaac.2017.07.520
INSTITUTE 3 AUTISM SPECTRUM DISORDER: FROM CLINICAL PRACTICE TO CUTTING EDGE RESEARCH Alexander Kolevzon, MD, Icahn School of Medicine at Mount Sinai, [email protected] Objectives: The goal of this Institute is to provide an update on assessment and management of autism spectrum disorder (ASD) while placing emphasis on the advances in neuroscience and translational research. Attendees will gain knowledge on the impact that molecular genetics has in our understanding of the neurobiology of ASD and in the development of novel therapeutics Methods: Presentations are crafted to build on each other. Morning sessions will provide a comprehensive review of current practice parameters in the management of ASD; afternoon sessions will integrate cutting-edge research progress to inform management. Presenters will use a multimedia approach with videos and vignettes and illustrate clinical relevance throughout the Institute.
J OURNAL
OF THE
AMERICAN A CADEMY OF CHILD & ADOLESCENT P SYCHIATRY VOLUME 56 NUMBER 10S OCTOBER 2017
using rTMS have examined resting-state connectivity biomarker approaches for MDD. Emerging data suggest that high-frequency rTMS treatments may modulate frontostriatal connectivity. Other recent efforts have identified a resting-state biotype, which may predict responsiveness to rTMS therapy for MDD. Although data from future adolescent studies may diverge from adults, these initial efforts will inform future study design. Existing studies with magnetic resonance spectroscopy suggest that successful rTMS in adolescent depression may potentiate cortical glutamate neurotransmission. Conclusions: Prior studies suggest that rTMS will play an important role as a neurophysiological probe and therapeutic intervention in future research. Synergistic research with neuroimaging modalities holds the promise of enhancing the efficacy of therapeutic rTMS and informing developmental neuroscience. Ideal future study designs with rTMS and neuroimaging will concurrently address both of these broad goals.
DDD, IMAGS, NM Supported by Pfizer ASPIRE Grant WS1976243, Assurex, Neuronetics, the Brain and Behavior Research Foundation, the Mayo Clinic Foundation, and NIMH Grant K23 MH100266 http://dx.doi.org/10.1016/j.jaac.2017.07.518
2.6 USING BRAIN-BASED MECHANISMS TO INFORM NOVEL TREATMENTS FOR SEVERE IRRITABILITY Ellen Leibenluft, MD, National Institute of Mental Health, [email protected]; Katharina Kircanski, PhD, National Institute of Mental Health, [email protected]; Joel Stoddard, MD, MAS, University of Colorado Denver, [email protected]; Argyris Stringaris, MD, PhD, National Institute of Health, [email protected]; Daniel S. Pine, MD, National Institute of Mental Health, daniel.pine@ nih.gov; Melissa A. Brotman, PhD, National Institute of Mental Health, [email protected] Objectives: Brain-based research can guide the development of novel treatments for severe irritability, as operationalized in DSM-5 classification of disruptive mood dysregulation disorder (DMDD). This presentation will describe two such treatments: interpretation bias training (IBT) and an exposure-based CBT for frustration, accompanied by parent training. Methods: Studies using standardized behavioral paradigms and fMRI were used to test the hypothesis that irritability in youth is associated with aberrant responses to frustration (including decreased threshold, increased amplitude, and increased duration of the emotional response) and aberrant approach responses to threat. This translational model for irritability further posits specific deficits relevant to aberrant reward processing, including deficits in the content and process of instrumental learning, and increased sensitivity to reward omission. Results: With regard to aberrant responses to threat, research indicates that, relative to healthy youth, those with DMDD are more likely to view ambiguous faces as angry rather than happy. Furthermore, one clinical trial demonstrated that computer-based training designed to rectify this interpretation bias was effective in decreasing aggression in youth at risk for criminal behavior. We have demonstrated that such training can shift perceptions in youth with DMDD and are now conducting a randomized clinical trial to test whether such shifts are associated with decreased irritability. The new CBT treatment posits that parent training can be used to alter the child’s deficits in instrumental learning secondary to suboptimal reinforcers in the home environment and that exposing children to frustrating situations in a graded fashion will, through extinction learning, allow them to develop increased tolerance for frustration and more adaptive coping strategies. For both studies, fMRI studies pre- and posttreatment will test whether the hypothesized brain mechanisms mediate clinical response. Conclusions: Translational neuroscience research can suggest new avenues to address the dearth of evidence-based treatment for the common and impairing clinical presentation of severe irritability in children.
CBT, IMAGS, IMD http://dx.doi.org/10.1016/j.jaac.2017.07.519
S138
www.jaacap.org
2.7 EVERYONE LIKES CANDI: DATA SHARING AND NEUROINFORMATICS TO ADDRESS BIG DATA QUESTIONS Jean A. Frazier, MD, UMass Medical School, Jean.Frazier@ umassmed.edu; Steve Hodge, MA, UMass Medical School, [email protected]; Jean-Baptiste Poline, PhD, Helen Wills Neuroscience Institute, [email protected]; Christian Haselgrove, BA, UMass Medical School, Christian. [email protected]; David Cochran, MD, PhD, UMass Medical School, [email protected]; David Kennedy, PhD, UMass Medical School, David. [email protected] Objectives: A substantial amount of neuroimaging data are now being shared that will allow us to answer important questions, thanks to efforts by the NIH Pediatric Database (PEDS); Autism Brain Data Exchange (ABIDE); and Pediatric Imaging, Neurocognition and Genetics (PING). We will discuss the use of these shared resources and ways to use them to answer important questions. For example, in typical development, do multiple sources of developmental data tell us the same things about the developmental trajectory and sex effects? Methods: By use of these shared data resources and a specific structural analysis workflow (Freesurfer), we can ask for a given statistical model if there is consistency of effect. As an example structure that lets us examine some specific questions in this data, we explore the total hippocampus volume in these datasets. Results: Our first analysis looks at the sex effect of the total hippocampus volume across three datasets: PING, PEDS, and ABIDE, including 95% confidence limits for the model [total hippocampus volume w sex + age + sex age + total cerebral volume (TCV) + site]. Neither PEDS (N w 300) nor ABIDE (N w 400) indicates a significant gender effect, whereas the sex effect is significant and seen to be w3% in the PING (N w 1,200) dataset. Using the PING data, where we have access to the most complete set of behavioral and demographic factors, we generate 32 model permutations that include the following factors: age, sex, site, socioeconomic status (SES), genetic ancestry factors, and intracranial volume (ICV). Accounting for ICV greatly reduces the magnitude of the sex effect that is over and above the allometric scaling of total brain. All of these sex effects are significant, and despite being lower in magnitude, the models that include ICV show an increase in R2 from w0.25 to w0.40, indicating a better overall fit to the data. Conclusions: These results demonstrate that, even before considering the subtle modulations caused by diagnostic effects of child mental health disorders, careful attention to data model and data sources is needed to definitely document developmental factors in brain-imaging data.
DAM, IMAGS, NEURODEV Supported by NIH-National Institute of Biomedical Imaging and Bioengineering Grant P41 EB019936 and NIH-NIMH Grant R01 MH083320 http://dx.doi.org/10.1016/j.jaac.2017.07.520
INSTITUTE 3 AUTISM SPECTRUM DISORDER: FROM CLINICAL PRACTICE TO CUTTING EDGE RESEARCH Alexander Kolevzon, MD, Icahn School of Medicine at Mount Sinai, [email protected] Objectives: The goal of this Institute is to provide an update on assessment and management of autism spectrum disorder (ASD) while placing emphasis on the advances in neuroscience and translational research. Attendees will gain knowledge on the impact that molecular genetics has in our understanding of the neurobiology of ASD and in the development of novel therapeutics Methods: Presentations are crafted to build on each other. Morning sessions will provide a comprehensive review of current practice parameters in the management of ASD; afternoon sessions will integrate cutting-edge research progress to inform management. Presenters will use a multimedia approach with videos and vignettes and illustrate clinical relevance throughout the Institute.
J OURNAL
OF THE
AMERICAN A CADEMY OF CHILD & ADOLESCENT P SYCHIATRY VOLUME 56 NUMBER 10S OCTOBER 2017