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Keehn B, Monahan P, Enneking B, Ryan T, Swigonski N, McNally Keehn R. Eye-Tracking Biomarkers and Autism Diagnosis in Primary Care. JAMA Netw Open 2024; 7:e2411190. [PMID: 38743420 PMCID: PMC11094561 DOI: 10.1001/jamanetworkopen.2024.11190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Accepted: 03/12/2024] [Indexed: 05/16/2024] Open
Abstract
Importance Finding effective and scalable solutions to address diagnostic delays and disparities in autism is a public health imperative. Approaches that integrate eye-tracking biomarkers into tiered community-based models of autism evaluation hold promise for addressing this problem. Objective To determine whether a battery of eye-tracking biomarkers can reliably differentiate young children with and without autism in a community-referred sample collected during clinical evaluation in the primary care setting and to evaluate whether combining eye-tracking biomarkers with primary care practitioner (PCP) diagnosis and diagnostic certainty is associated with diagnostic outcome. Design, Setting, and Participants Early Autism Evaluation (EAE) Hub system PCPs referred a consecutive sample of children to this prospective diagnostic study for blinded eye-tracking index test and follow-up expert evaluation from June 7, 2019, to September 23, 2022. Participants included 146 children (aged 14-48 months) consecutively referred by 7 EAE Hubs. Of 154 children enrolled, 146 provided usable data for at least 1 eye-tracking measure. Main Outcomes and Measures The primary outcomes were sensitivity and specificity of a composite eye-tracking (ie, index) test, which was a consolidated measure based on significant eye-tracking indices, compared with reference standard expert clinical autism diagnosis. Secondary outcome measures were sensitivity and specificity of an integrated approach using an index test and PCP diagnosis and certainty. Results Among 146 children (mean [SD] age, 2.6 [0.6] years; 104 [71%] male; 21 [14%] Hispanic or Latine and 96 [66%] non-Latine White; 102 [70%] with a reference standard autism diagnosis), 113 (77%) had concordant autism outcomes between the index (composite biomarker) and reference outcomes, with 77.5% sensitivity (95% CI, 68.4%-84.5%) and 77.3% specificity (95% CI, 63.0%-87.2%). When index diagnosis was based on the combination of a composite biomarker, PCP diagnosis, and diagnostic certainty, outcomes were concordant with reference standard for 114 of 127 cases (90%) with a sensitivity of 90.7% (95% CI, 83.3%-95.0%) and a specificity of 86.7% (95% CI, 70.3%-94.7%). Conclusions and Relevance In this prospective diagnostic study, a composite eye-tracking biomarker was associated with a best-estimate clinical diagnosis of autism, and an integrated diagnostic model including PCP diagnosis and diagnostic certainty demonstrated improved sensitivity and specificity. These findings suggest that equipping PCPs with a multimethod diagnostic approach has the potential to substantially improve access to timely, accurate diagnosis in local communities.
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Affiliation(s)
- Brandon Keehn
- Department of Speech, Language, and Hearing Sciences, Purdue University, West Lafayette, Indiana
- Department of Psychological Sciences, Purdue University, West Lafayette, Indiana
| | - Patrick Monahan
- Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis
| | - Brett Enneking
- Department of Pediatrics, Indiana University School of Medicine, Indianapolis
| | - Tybytha Ryan
- Department of Pediatrics, Indiana University School of Medicine, Indianapolis
| | - Nancy Swigonski
- Department of Pediatrics, Indiana University School of Medicine, Indianapolis
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Bouman A, Geelen JM, Kummeling J, Schenck A, van der Zwan YG, Klein WM, Kleefstra T. Growth, body composition, and endocrine-metabolic profiles of individuals with Kleefstra syndrome provide directions for clinical management and translational studies. Am J Med Genet A 2024; 194:e63472. [PMID: 38155610 DOI: 10.1002/ajmg.a.63472] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Revised: 10/17/2023] [Accepted: 10/27/2023] [Indexed: 12/30/2023]
Abstract
Mendelian neurodevelopmental disorders caused by variants in genes encoding chromatin modification can be categorized as Mendelian disorders of the epigenetic machinery (MDEMs). These disorders have significant overlap in molecular pathways and phenotypes including intellectual disability, short stature, and obesity. Among the MDEMs is Kleefstra syndrome (KLFS), which is caused by haploinsufficiency of EHMT1. Preclinical studies have identified metabolic dysregulation and obesity in KLFS models, but proper clinical translation lacks. In this study, we aim to delineate growth, body composition, and endocrine-metabolic characteristics in a total of 62 individuals with KLFS. Our results revealed a high prevalence of childhood-onset overweight/obesity (60%; 28/47) with disproportionately high body fat percentage, which aligns perfectly with previous preclinical studies. Short stature was common (33%), likely due to advanced skeletal maturation. Endocrine-metabolic investigations showed thyroid dysregulation (22%; 9/41), elevated triglycerides, and decreased blood ammonia levels. Moreover, hand radiographs identified decreased bone mineralization (57%; 8/14) and negative ulnar variance (71%; 10/14). Our findings indicate a high (cardio)metabolic risk in KLFS. Therefore, we recommend monitoring of weight and endocrine-metabolic profile. Supporting a healthy lifestyle and screening of bone mineralization is advised. Our comprehensive results support translational research and contribute to a better understanding of MDEM-associated phenotypes.
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Affiliation(s)
- Arianne Bouman
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Joyce M Geelen
- Department of Pediatrics, Developmental and Genetic Pediatrics, Amalia Children's Hospital, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Joost Kummeling
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Annette Schenck
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Yvonne G van der Zwan
- Department of Pediatrics, Pediatric Endocrinology, Amalia Children's Hospital, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Willemijn M Klein
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Tjitske Kleefstra
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Clinical Genetics, Erasmus MC, Rotterdam, The Netherlands
- Center of Excellence for Neuropsychiatry, Vincent van Gogh Institute for Psychiatry, Venray, The Netherlands
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3
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Guo X, Yu J, Quan C, Xiao J, Wang J, Zhang B, Hao X, Wu X, Liang J. The effect of N-methyl-D-aspartate receptor antagonists on the mismatch negativity of event-related potentials and its regulatory factors: A systematic review and meta-analysis. J Psychiatr Res 2024; 172:210-220. [PMID: 38402843 DOI: 10.1016/j.jpsychires.2024.02.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Revised: 01/28/2024] [Accepted: 02/01/2024] [Indexed: 02/27/2024]
Abstract
This study investigates the influence of N-methyl-D-aspartate receptor (NMDAR) antagonists on the mismatch negativity (MMN) components of event-related potentials (ERPs) in healthy subjects and explores whether NMDAR antagonists have different effects on MMN components under different types of antagonists, drug dosages, and deviant stimuli. We conducted a comprehensive literature search of PubMed, EMBASE, and the Cochrane Library from inception to August 1, 2023 for studies comparing the MMN components between the NMDAR antagonist intervention group and the control group (or baseline). All statistical analyses were performed using Stata version 12.0 software. Sixteen articles were included in the systematic review: 13 articles were included in the meta-analysis of MMN amplitudes, and seven articles were included in the meta-analysis of MMN latencies. The pooled analysis showed that NMDAR antagonists reduced MMN amplitudes [SMD (95% CI) = 0.32 (0.16, 0.47), P < 0.01, I2 = 47.3%, p < 0.01] and prolonged MMN latencies [SMD (95% CI) = 0.31 (0.13, 0.49), P = 0.16, I2 = 28.3%, p < 0.01]. The type of antagonist drug regulates the effect of NMDAR antagonists on MMN amplitudes. Different antagonists, doses of antagonists, and types of deviant stimuli can also have different effects on MMN. These findings indicate a correlation between NMDAR and MMN, which may provide a foundation for the application of ERP-MMN in the early identification of NMDAR encephalitis.
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Affiliation(s)
- Xin Guo
- Department of Pediatric Neurology, The First Hospital of Jilin University, Changchun, 130021, China; Jilin Provincial Key Laboratory of Pediatric Neurology, Changchun, 130021, China.
| | - Jieyang Yu
- Department of Pediatric Neurology, The First Hospital of Jilin University, Changchun, 130021, China; Jilin Provincial Key Laboratory of Pediatric Neurology, Changchun, 130021, China.
| | - Chunhua Quan
- Central Laboratory, The Affiliated Hospital of Yanbian University, Juzi-St., No.1327, Yanji, 133000, China.
| | - Jinyu Xiao
- Department of Pediatric Neurology, The First Hospital of Jilin University, Changchun, 130021, China; Jilin Provincial Key Laboratory of Pediatric Neurology, Changchun, 130021, China.
| | - Jiangtao Wang
- Department of Pediatric Neurology, The First Hospital of Jilin University, Changchun, 130021, China; Jilin Provincial Key Laboratory of Pediatric Neurology, Changchun, 130021, China.
| | - Bo Zhang
- Department of Pediatric Neurology, The First Hospital of Jilin University, Changchun, 130021, China; Jilin Provincial Key Laboratory of Pediatric Neurology, Changchun, 130021, China.
| | - Xiaosheng Hao
- Department of Pediatric Neurology, The First Hospital of Jilin University, Changchun, 130021, China; Jilin Provincial Key Laboratory of Pediatric Neurology, Changchun, 130021, China.
| | - Xuemei Wu
- Department of Pediatric Neurology, The First Hospital of Jilin University, Changchun, 130021, China; Jilin Provincial Key Laboratory of Pediatric Neurology, Changchun, 130021, China.
| | - Jianmin Liang
- Department of Pediatric Neurology, The First Hospital of Jilin University, Changchun, 130021, China; Jilin Provincial Key Laboratory of Pediatric Neurology, Changchun, 130021, China.
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Goikolea-Vives A, Fernandes C, Thomas MSC, Thornton C, Stolp HB. Sex-specific behavioural deficits in adulthood following acute activation of the GABAA receptor in the neonatal mouse. Dev Neurosci 2024:000536641. [PMID: 38325353 DOI: 10.1159/000536641] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Accepted: 01/26/2024] [Indexed: 02/09/2024] Open
Abstract
INTRODUCTION Sex differences exist in the prevalence of neurodevelopmental disorders (NDDs). Part of the aetiology of NDDs has been proposed to be alterations in the balance between excitatory and inhibitory neurotransmission, leading to the question of whether males and females respond differently to altered neurotransmitter balance. We investigated whether pharmacological alteration of GABAA signalling in early development results in sex-dependent changes in adult behaviours associated with NDDs. METHODS Male and female C57BL/6J mice received intraperitoneal injections of 0.5mg/kg muscimol or saline on postnatal days (P) 3-5 and were subjected to behavioural testing, specifically open field, light dark box, marble burying, sucralose preference, social interaction and olfactory habituation/dishabituation tests between P60-90. RESULTS Early postnatal administration of muscimol resulted in reduced anxiety in the light dark box test in both male and female adult mice. Muscimol reduced sucralose preference in males, but not females, whereas female mice showed reduced social behaviours. Regional alterations in cortical thickness were observed in the weeks following GABAA receptor activation, pointing to an evolving structural difference in the brain underlying adult behaviour. CONCLUSIONS We conclude that activation of the GABAA receptor in the first week of life resulted in long-lasting changes in a range of behaviours in adulthood following altered neurodevelopment. Sex of the individual affected the nature and severity of these abnormalities, explaining part of the varied pathophysiology and neurodevelopmental diagnosis that derive from excitatory/inhibitory imbalance.
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Neo WS, Foti D, Keehn B, Kelleher B. Resting-state EEG power differences in autism spectrum disorder: a systematic review and meta-analysis. Transl Psychiatry 2023; 13:389. [PMID: 38097538 PMCID: PMC10721649 DOI: 10.1038/s41398-023-02681-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Revised: 11/23/2023] [Accepted: 11/27/2023] [Indexed: 12/17/2023] Open
Abstract
Narrative reviews have described various resting-state EEG power differences in autism across all five canonical frequency bands, with increased power for low and high frequencies and reduced power for middle frequencies. However, these differences have yet to be quantified using effect sizes and probed robustly for consistency, which are critical next steps for clinical translation. Following PRISMA guidelines, we conducted a systematic review of published and gray literature on resting-state EEG power in autism. We performed 10 meta-analyses to synthesize and quantify differences in absolute and relative resting-state delta, theta, alpha, beta, and gamma EEG power in autism. We also conducted moderator analyses to determine whether demographic characteristics, methodological details, and risk-of-bias indicators might account for heterogeneous study effect sizes. Our literature search and study selection processes yielded 41 studies involving 1,246 autistic and 1,455 neurotypical individuals. Meta-analytic models of 135 effect sizes demonstrated that autistic individuals exhibited reduced relative alpha (g = -0.35) and increased gamma (absolute: g = 0.37, relative: g = 1.06) power, but similar delta (absolute: g = 0.06, relative: g = 0.10), theta (absolute: g = -0.03, relative: g = -0.15), absolute alpha (g = -0.17), and beta (absolute: g = 0.01, relative: g = 0.08) power. Substantial heterogeneity in effect sizes was observed across all absolute (I2: 36.1-81.9%) and relative (I2: 64.6-84.4%) frequency bands. Moderator analyses revealed that age, biological sex, IQ, referencing scheme, epoch duration, and use of gold-standard autism diagnostic instruments did not moderate study effect sizes. In contrast, resting-state paradigm type (eyes-closed versus eyes-open) moderated absolute beta, relative delta, and relative alpha power effect sizes, and resting-state recording duration moderated relative alpha power effect sizes. These findings support further investigation of resting-state alpha and gamma power as potential biomarkers for autism.
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Affiliation(s)
- Wei Siong Neo
- Department of Psychological Sciences, Purdue University, West Lafayette, IN, USA.
| | - Dan Foti
- Department of Psychological Sciences, Purdue University, West Lafayette, IN, USA
| | - Brandon Keehn
- Department of Psychological Sciences, Purdue University, West Lafayette, IN, USA
- Department of Speech, Language, and Hearing Sciences, Purdue University, West Lafayette, IN, USA
| | - Bridgette Kelleher
- Department of Psychological Sciences, Purdue University, West Lafayette, IN, USA
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6
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Aydin Ü, Cañigueral R, Tye C, McLoughlin G. Face processing in young adults with autism and ADHD: An event related potentials study. Front Psychiatry 2023; 14:1080681. [PMID: 36998627 PMCID: PMC10043418 DOI: 10.3389/fpsyt.2023.1080681] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Accepted: 02/14/2023] [Indexed: 03/18/2023] Open
Abstract
Background Atypicalities in perception and interpretation of faces and emotional facial expressions have been reported in both autism and attention-deficit/hyperactivity disorder (ADHD) during childhood and adulthood. Investigation of face processing during young adulthood (18 to 25 years), a transition period to full-fledged adulthood, could provide important information on the adult outcomes of autism and ADHD. Methods In this study, we investigated event-related potentials (ERPs) related to visual face processing in autism, ADHD, and co-occurring autism and ADHD in a large sample of young adults (N = 566). The groups were based on the Diagnostic Interview for ADHD in Adults 2.0 (DIVA-2) and the Autism Diagnostic Observation Schedule-2 (ADOS-2). We analyzed ERPs from two passive viewing tasks previously used in childhood investigations: (1) upright and inverted faces with direct or averted gaze; (2) faces expressing different emotions. Results Across both tasks, we consistently found lower amplitude and longer latency of N170 in participants with autism compared to those without. Longer P1 latencies and smaller P3 amplitudes in response to emotional expressions and longer P3 latencies for upright faces were also characteristic to the autistic group. Those with ADHD had longer N170 latencies, specific to the face-gaze task. Individuals with both autism and ADHD showed additional alterations in gaze modulation and a lack of the face inversion effect indexed by a delayed N170. Conclusion Alterations in N170 for autistic young adults is largely consistent with studies on autistic adults, and some studies in autistic children. These findings suggest that there are identifiable and measurable socio-functional atypicalities in young adults with autism.
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Affiliation(s)
- Ümit Aydin
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
- School of Psychology and Clinical Language Sciences, University of Reading, Reading, United Kingdom
| | - Roser Cañigueral
- Department of Clinical, Educational and Health Psychology, University College London, London, United Kingdom
| | - Charlotte Tye
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
- Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Gráinne McLoughlin
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
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Mintz Hemed N, Melosh NA. An integrated perspective for the diagnosis and therapy of neurodevelopmental disorders - From an engineering point of view. Adv Drug Deliv Rev 2023; 194:114723. [PMID: 36746077 DOI: 10.1016/j.addr.2023.114723] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Revised: 12/14/2022] [Accepted: 01/29/2023] [Indexed: 02/05/2023]
Abstract
Neurodevelopmental disorders (NDDs) are complex conditions with largely unknown pathophysiology. While many NDD symptoms are familiar, the cause of these disorders remains unclear and may involve a combination of genetic, biological, psychosocial, and environmental risk factors. Current diagnosis relies heavily on behaviorally defined criteria, which may be biased by the clinical team's professional and cultural expectations, thus a push for new biological-based biomarkers for NDDs diagnosis is underway. Emerging new research technologies offer an unprecedented view into the electrical, chemical, and physiological activity in the brain and with further development in humans may provide clinically relevant diagnoses. These could also be extended to new treatment options, which can start to address the underlying physiological issues. When combined with current speech, language, occupational therapy, and pharmacological treatment these could greatly improve patient outcomes. The current review will discuss the latest technologies that are being used or may be used for NDDs diagnosis and treatment. The aim is to provide an inspiring and forward-looking view for future research in the field.
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Affiliation(s)
- Nofar Mintz Hemed
- Department of Materials Science and Engineering, Stanford University, Stanford, CA 94305, USA.
| | - Nicholas A Melosh
- Department of Materials Science and Engineering, Stanford University, Stanford, CA 94305, USA
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8
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Loth E. Does the current state of biomarker discovery in autism reflect the limits of reductionism in precision medicine? Suggestions for an integrative approach that considers dynamic mechanisms between brain, body, and the social environment. Front Psychiatry 2023; 14:1085445. [PMID: 36911126 PMCID: PMC9992810 DOI: 10.3389/fpsyt.2023.1085445] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 01/23/2023] [Indexed: 02/24/2023] Open
Abstract
Over the past decade, precision medicine has become one of the most influential approaches in biomedical research to improve early detection, diagnosis, and prognosis of clinical conditions and develop mechanism-based therapies tailored to individual characteristics using biomarkers. This perspective article first reviews the origins and concept of precision medicine approaches to autism and summarises recent findings from the first "generation" of biomarker studies. Multi-disciplinary research initiatives created substantially larger, comprehensively characterised cohorts, shifted the focus from group-comparisons to individual variability and subgroups, increased methodological rigour and advanced analytic innovations. However, although several candidate markers with probabilistic value have been identified, separate efforts to divide autism by molecular, brain structural/functional or cognitive markers have not identified a validated diagnostic subgroup. Conversely, studies of specific monogenic subgroups revealed substantial variability in biology and behaviour. The second part discusses both conceptual and methodological factors in these findings. It is argued that the predominant reductionist approach, which seeks to parse complex issues into simpler, more tractable units, let us to neglect the interactions between brain and body, and divorce individuals from their social environment. The third part draws on insights from systems biology, developmental psychology and neurodiversity approaches to outline an integrative approach that considers the dynamic interaction between biological (brain, body) and social mechanisms (stress, stigma) to understanding the origins of autistic features in particular conditions and contexts. This requires 1) closer collaboration with autistic people to increase face validity of concepts and methodologies; (2) development of measures/technologies that enable repeat assessment of social and biological factors in different (naturalistic) conditions and contexts, (3) new analytic methods to study (simulate) these interactions (including emergent properties), and (4) cross-condition designs to understand which mechanisms are transdiagnostic or specific for particular autistic sub-populations. Tailored support may entail both creating more favourable conditions in the social environment and interventions for some autistic people to increase well-being.
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Affiliation(s)
- Eva Loth
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
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Levy EJ, Foss-Feig J, Isenstein EL, Srihari V, Anticevic A, Naples AJ, McPartland JC. Electrophysiological Studies of Reception of Facial Communication in Autism Spectrum Disorder and Schizophrenia. REVIEW JOURNAL OF AUTISM AND DEVELOPMENTAL DISORDERS 2022; 9:521-554. [PMID: 36568688 PMCID: PMC9783109 DOI: 10.1007/s40489-021-00260-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Accepted: 04/22/2021] [Indexed: 12/30/2022]
Abstract
Autism spectrum disorder (ASD) and schizophrenia spectrum disorders (SZ) are characterized by difficulty with social cognition and atypical reception of facial communication - a key area in the Research Domain Criteria framework. To identify areas of overlap and dissociation between ASD and SZ, we review studies of event-related potentials (ERP) to faces across ASD and SZ populations, focusing on ERPs implicated in social perception: P100, N170, N250, and P300. There were many inconsistent findings across studies; however, replication was strongest for delayed N170 latency in ASD and attenuated N170 amplitude in SZ. These results highlight the challenges of replicating research findings in heterogeneous clinical populations and the need for transdiagnostic research that continuously quantifies behavior and neural activity across neurodevelopmental disorders.
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Affiliation(s)
| | - Jennifer Foss-Feig
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai
- Seaver Autism Center, Icahn School of Medicine at Mount Sinai
| | | | - Vinod Srihari
- Department of Psychiatry, Yale University School of Medicine
| | - Alan Anticevic
- Department of Psychiatry, Yale University School of Medicine
- Department of Psychology, Yale University
- Division of Neurogenetics, Neurocomputation, and Neuroimaging, Yale University School of Medicine
| | - Adam J. Naples
- Yale Child Study Center, Yale University School of Medicine
| | - James C. McPartland
- Department of Psychology, Yale University
- Yale Child Study Center, Yale University School of Medicine
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Lopes LT, Rodrigues JM, Baccarin C, Oliveira K, Abreu M, Ribeiro V, Anastácio ZC, Machado JP. Autism Spectrum as an Etiologic Systemic Disorder: A Protocol for an Umbrella Review. Healthcare (Basel) 2022; 10:healthcare10112200. [PMID: 36360541 PMCID: PMC9690003 DOI: 10.3390/healthcare10112200] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Revised: 10/29/2022] [Accepted: 10/31/2022] [Indexed: 11/06/2022] Open
Abstract
Autism spectrum disorder (ASD) is the most common neurodevelopmental disorder with a huge prevalence increasing every year (1/44 children). Still diagnosed as a mental disorder, the last 10 years of research found possible causes, risks, genetics, environmental triggers, epigenetics, metabolic, immunological, and neurophysiological unbalances as relevant aetiology. Umbrella methodology is the highest level of scientific evidence, designed to support clinical and political decisions. A literature search for autism aetiology, pathophysiology, or causes, conducted in the last 10 years, at PubMed, Embase, Cochrane, Scopus, and the Web of Science, resulted in six umbrella reviews. Nevertheless, only one quantitative analysis reported risk factors and biomarkers but excluded genetics, experiments on animal models, and post-mortem studies. We grouped ASD’s multi-factorial causes and risks into five etiological categories: genetic, epigenetic, organic, psychogenic, and environmental. Findings suggest that autism might be evaluated as a systemic disorder instead of only through the lens of mental and behavioural. The overview implications of included studies will be qualitatively analysed under ROBIS and GRADE tools. This umbrella review can provide a rational basis for a new urgent health policy to develop better and adequate integrated care services for ASD. The methodological protocol has the register CRD42022348586 at PROSPERO.
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Affiliation(s)
- Lara Teixeira Lopes
- Institute of Biomedical Sciences, University of Porto, 4099-030 Porto, Portugal
- Center of BioSciences in Integrative Health, 4200-355 Porto, Portugal
- Correspondence:
| | | | - Celeste Baccarin
- Center of BioSciences in Integrative Health, 4200-355 Porto, Portugal
| | - Kevin Oliveira
- Center of BioSciences in Integrative Health, 4200-355 Porto, Portugal
| | - Manuela Abreu
- Center of BioSciences in Integrative Health, 4200-355 Porto, Portugal
| | - Victor Ribeiro
- Center of BioSciences in Integrative Health, 4200-355 Porto, Portugal
| | - Zélia Caçador Anastácio
- Research Center on Child Studies, Institute of Education, University of Minho, 4804-533 Braga, Portugal
| | - Jorge Pereira Machado
- Institute of Biomedical Sciences, University of Porto, 4099-030 Porto, Portugal
- Center of BioSciences in Integrative Health, 4200-355 Porto, Portugal
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Horien C, Floris DL, Greene AS, Noble S, Rolison M, Tejavibulya L, O'Connor D, McPartland JC, Scheinost D, Chawarska K, Lake EMR, Constable RT. Functional Connectome-Based Predictive Modeling in Autism. Biol Psychiatry 2022; 92:626-642. [PMID: 35690495 PMCID: PMC10948028 DOI: 10.1016/j.biopsych.2022.04.008] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Revised: 04/14/2022] [Accepted: 04/17/2022] [Indexed: 01/08/2023]
Abstract
Autism is a heterogeneous neurodevelopmental condition, and functional magnetic resonance imaging-based studies have helped advance our understanding of its effects on brain network activity. We review how predictive modeling, using measures of functional connectivity and symptoms, has helped reveal key insights into this condition. We discuss how different prediction frameworks can further our understanding of the brain-based features that underlie complex autism symptomatology and consider how predictive models may be used in clinical settings. Throughout, we highlight aspects of study interpretation, such as data decay and sampling biases, that require consideration within the context of this condition. We close by suggesting exciting future directions for predictive modeling in autism.
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Affiliation(s)
- Corey Horien
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, Connecticut; MD-PhD Program, Yale School of Medicine, New Haven, Connecticut.
| | - Dorothea L Floris
- Methods of Plasticity Research, Department of Psychology, University of Zürich, Zurich, Switzerland; Donders Center for Brain, Cognition and Behavior, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Abigail S Greene
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, Connecticut; MD-PhD Program, Yale School of Medicine, New Haven, Connecticut
| | - Stephanie Noble
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut
| | - Max Rolison
- Yale Child Study Center, New Haven, Connecticut
| | - Link Tejavibulya
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, Connecticut
| | - David O'Connor
- Department of Biomedical Engineering, Yale University, New Haven, Connecticut
| | - James C McPartland
- Department of Psychology, Yale University, New Haven, Connecticut; Yale Child Study Center, New Haven, Connecticut
| | - Dustin Scheinost
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, Connecticut; Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut; Department of Biomedical Engineering, Yale University, New Haven, Connecticut; Department of Statistics and Data Science, Yale University, New Haven, Connecticut; Yale Child Study Center, New Haven, Connecticut
| | - Katarzyna Chawarska
- Department of Pediatrics, Yale School of Medicine, New Haven, Connecticut; Department of Statistics and Data Science, Yale University, New Haven, Connecticut; Yale Child Study Center, New Haven, Connecticut
| | - Evelyn M R Lake
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut
| | - R Todd Constable
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, Connecticut; Department of Neurosurgery, Yale School of Medicine, New Haven, Connecticut; Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut; Department of Biomedical Engineering, Yale University, New Haven, Connecticut.
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12
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Mason L, Moessnang C, Chatham C, Ham L, Tillmann J, Dumas G, Ellis C, Leblond CS, Cliquet F, Bourgeron T, Beckmann C, Charman T, Oakley B, Banaschewski T, Meyer-Lindenberg A, Baron-Cohen S, Bölte S, Buitelaar JK, Durston S, Loth E, Oranje B, Persico A, Dell'Acqua F, Ecker C, Johnson MH, Murphy D, Jones EJH. Stratifying the autistic phenotype using electrophysiological indices of social perception. Sci Transl Med 2022; 14:eabf8987. [PMID: 35976994 DOI: 10.1126/scitranslmed.abf8987] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by difficulties in social communication, but also great heterogeneity. To offer individualized medicine approaches, we need to better target interventions by stratifying autistic people into subgroups with different biological profiles and/or prognoses. We sought to validate neural responses to faces as a potential stratification factor in ASD by measuring neural (electroencephalography) responses to faces (critical in social interaction) in N = 436 children and adults with and without ASD. The speed of early-stage face processing (N170 latency) was on average slower in ASD than in age-matched controls. In addition, N170 latency was associated with responses to faces in the fusiform gyrus, measured with functional magnetic resonance imaging, and polygenic scores for ASD. Within the ASD group, N170 latency predicted change in adaptive socialization skills over an 18-month follow-up period; data-driven clustering identified a subgroup with slower brain responses and poor social prognosis. Use of a distributional data-driven cutoff was associated with predicted improvements of power in simulated clinical trials targeting social functioning. Together, the data provide converging evidence for the utility of the N170 as a stratification factor to identify biologically and prognostically defined subgroups in ASD.
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Affiliation(s)
- Luke Mason
- Centre for Brain and Cognitive Development, Birkbeck, University of London, WC1E 7HX, London, UK
| | - Carolin Moessnang
- Department of Child and Adolescent Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, 68159 Mannheim, Germany
| | | | - Lindsay Ham
- F. Hoffmann-La Roche Ltd., Grenzacherstrasse 124, 4070 Basel, Switzerland
| | - Julian Tillmann
- Institute of Psychiatry, Psychology and Neuroscience, King's College, London, London, UK
| | - Guillaume Dumas
- Human Genetics and Cognitive Functions, Institut Pasteur, UMR3571 CNRS, Université de Paris, 75015 Paris, France.,Precision Psychiatry and Social Physiology laboratory, CHU Sainte-Justine Research Center, Department of Psychiatry, University of Montreal, H3T 1C5 Quebec, Canada
| | - Claire Ellis
- Institute of Psychiatry, Psychology and Neuroscience, King's College, London, London, UK
| | - Claire S Leblond
- Human Genetics and Cognitive Functions, Institut Pasteur, UMR3571 CNRS, Université de Paris, 75015 Paris, France
| | - Freddy Cliquet
- Human Genetics and Cognitive Functions, Institut Pasteur, UMR3571 CNRS, Université de Paris, 75015 Paris, France
| | - Thomas Bourgeron
- Human Genetics and Cognitive Functions, Institut Pasteur, UMR3571 CNRS, Université de Paris, 75015 Paris, France
| | - Christian Beckmann
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behavior, Radboudumc, 6525 EN Nijmegen, Netherlands
| | - Tony Charman
- Institute of Psychiatry, Psychology and Neuroscience, King's College, London, London, UK
| | - Beth Oakley
- Institute of Psychiatry, Psychology and Neuroscience, King's College, London, London, UK
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, 68159 Mannheim, Germany
| | - Andreas Meyer-Lindenberg
- Department of Child and Adolescent Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, 68159 Mannheim, Germany
| | - Simon Baron-Cohen
- Department of Psychology, University of Cambridge, CB2 3EB Cambridge, UK
| | - Sven Bölte
- Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research Child and Adolescent Psychiatry, Stockholm Health Care Services, Region Stockholm, Stockholm 171 77, Sweden
| | - Jan K Buitelaar
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behavior, Radboudumc, 6525 EN Nijmegen, Netherlands
| | - Sarah Durston
- NICHE-lab, Department of Psychiatry, Brain Center of University Medical Center Utrecht, 3584 CX Utrecht, Netherlands
| | - Eva Loth
- Institute of Psychiatry, Psychology and Neuroscience, King's College, London, London, UK
| | - Bob Oranje
- NICHE-lab, Department of Psychiatry, Brain Center of University Medical Center Utrecht, 3584 CX Utrecht, Netherlands
| | | | - Flavio Dell'Acqua
- Institute of Psychiatry, Psychology and Neuroscience, King's College, London, London, UK
| | - Christine Ecker
- Curtin Autism Research Group, School of Occupational Therapy, Social Work and Speech Pathology, Curtin University, Perth, Western Australia 6102, Australia
| | - Mark H Johnson
- Centre for Brain and Cognitive Development, Birkbeck, University of London, WC1E 7HX, London, UK.,Department of Psychology, University of Cambridge, CB2 3EB Cambridge, UK
| | - Declan Murphy
- Institute of Psychiatry, Psychology and Neuroscience, King's College, London, London, UK
| | - Emily J H Jones
- Centre for Brain and Cognitive Development, Birkbeck, University of London, WC1E 7HX, London, UK
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13
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Le Floch P, Li Q, Lin Z, Zhao S, Liu R, Tasnim K, Jiang H, Liu J. Stretchable Mesh Nanoelectronics for 3D Single-Cell Chronic Electrophysiology from Developing Brain Organoids. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2022; 34:e2106829. [PMID: 35014735 PMCID: PMC8930507 DOI: 10.1002/adma.202106829] [Citation(s) in RCA: 35] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/29/2021] [Revised: 12/26/2021] [Indexed: 05/13/2023]
Abstract
Human induced pluripotent stem cell derived brain organoids have shown great potential for studies of human brain development and neurological disorders. However, quantifying the evolution of the electrical properties of brain organoids during development is currently limited by the measurement techniques, which cannot provide long-term stable 3D bioelectrical interfaces with developing brain organoids. Here, a cyborg brain organoid platform is reported, in which "tissue-like" stretchable mesh nanoelectronics are designed to match the mechanical properties of brain organoids and to be folded by the organogenetic process of progenitor or stem cells, distributing stretchable electrode arrays across the 3D organoids. The tissue-wide integrated stretchable electrode arrays show no interruption to brain organoid development, adapt to the volume and morphological changes during brain organoid organogenesis, and provide long-term stable electrical contacts with neurons within brain organoids during development. The seamless and noninvasive coupling of electrodes to neurons enables long-term stable, continuous recording and captures the emergence of single-cell action potentials from early-stage brain organoid development.
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Affiliation(s)
- Paul Le Floch
- School of Engineering and Applied Sciences, Harvard University, Boston, MA 02134, USA
| | - Qiang Li
- School of Engineering and Applied Sciences, Harvard University, Boston, MA 02134, USA
| | - Zuwan Lin
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Siyuan Zhao
- School of Engineering and Applied Sciences, Harvard University, Boston, MA 02134, USA
| | - Ren Liu
- School of Engineering and Applied Sciences, Harvard University, Boston, MA 02134, USA
| | - Kazi Tasnim
- School of Engineering and Applied Sciences, Harvard University, Boston, MA 02134, USA
| | - Han Jiang
- School of Engineering and Applied Sciences, Harvard University, Boston, MA 02134, USA
| | - Jia Liu
- School of Engineering and Applied Sciences, Harvard University, Boston, MA 02134, USA
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14
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Saby JN, Mulcahey PJ, Zavez AE, Peters SU, Standridge SM, Swanson LC, Lieberman DN, Olson HE, Key AP, Percy AK, Neul JL, Nelson CA, Roberts TPL, Benke TA, Marsh ED. Electrophysiological biomarkers of brain function in CDKL5 deficiency disorder. Brain Commun 2022; 4:fcac197. [PMID: 35974796 PMCID: PMC9374482 DOI: 10.1093/braincomms/fcac197] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Revised: 05/05/2022] [Accepted: 08/02/2022] [Indexed: 11/14/2022] Open
Abstract
CDKL5 deficiency disorder is a debilitating developmental and epileptic encephalopathy for which no targeted treatment exists. A number of promising therapeutics are under development for CDKL5 deficiency disorder but a lack of validated biomarkers of brain function and clinical severity may limit the ability to objectively assess the efficacy of new treatments as they become available. To address this need, the current study quantified electrophysiological measures in individuals with CDKL5 deficiency disorder and the association between these parameters and clinical severity. Visual and auditory evoked potentials, as well as resting EEG, were acquired across 5 clinical sites from 26 individuals with CDKL5 deficiency disorder. Evoked potential and quantitative EEG features were calculated and compared with typically developing individuals in an age- and sex-matched cohort. Baseline and Year 1 data, when available, were analysed and the repeatability of the results was tested. Two clinician-completed severity scales were used for evaluating the clinical relevance of the electrophysiological parameters. Group-level comparisons revealed reduced visual evoked potential amplitude in CDKL5 deficiency disorder individuals versus typically developing individuals. There were no group differences in the latency of the visual evoked potentials or in the latency or amplitude of the auditory evoked potentials. Within the CDKL5 deficiency disorder group, auditory evoked potential amplitude correlated with disease severity at baseline as well as Year 1. Multiple quantitative EEG features differed between CDKL5 deficiency disorder and typically developing participants, including amplitude standard deviation, 1/f slope and global delta, theta, alpha and beta power. Several quantitative EEG features correlated with clinical severity, including amplitude skewness, theta/delta ratio and alpha/delta ratio. The theta/delta ratio was the overall strongest predictor of severity and also among the most repeatable qEEG measures from baseline to Year 1. Together, the present findings point to the utility of evoked potentials and quantitative EEG parameters as objective measures of brain function and disease severity in future clinical trials for CDKL5 deficiency disorder. The results also underscore the utility of the current methods, which could be similarly applied to the identification and validation of electrophysiological biomarkers of brain function for other developmental encephalopathies.
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Affiliation(s)
| | | | - Alexis E Zavez
- Orphan Disease Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Sarika U Peters
- Department of Pediatrics, Vanderbilt Kennedy Center, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Shannon M Standridge
- Cincinnati Children’s Hospital Medical Center, Division of Neurology and University of Cincinnati College of Medicine, Cincinnati, OH 45229, USA
| | - Lindsay C Swanson
- Department of Neurology, Boston Children’s Hospital, Boston, MA 02115, USA
| | - David N Lieberman
- Department of Neurology, Boston Children’s Hospital, Boston, MA 02115, USA
| | - Heather E Olson
- Department of Neurology, Boston Children’s Hospital, Boston, MA 02115, USA
| | - Alexandra P Key
- Department of Hearing and Speech Sciences, Vanderbilt Kennedy Center, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Alan K Percy
- Department of Pediatrics, University of Alabama at Birmingham, Birmingham, AL 35233, USA
| | - Jeffrey L Neul
- Department of Pediatrics, Vanderbilt Kennedy Center, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Charles A Nelson
- Laboratories of Cognitive Neuroscience, Boston Children’s Hospital, Boston, MA 02115, USA
- Department of Pediatrics, Harvard Medical School, Cambridge, MA 02115, USA
- Graduate School of Education, Harvard University, Cambridge, MA 02115, USA
| | - Timothy P L Roberts
- Division of Radiology Research, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Timothy A Benke
- Department of Pediatrics, University of Colorado School of Medicine and Children’s Hospital Colorado, Aurora, CO 80045, USA
- Department of Neurology, University of Colorado School of Medicine and Children’s Hospital Colorado, Aurora, CO 80045, USA
- Department of Pharmacology, University of Colorado School of Medicine and Children’s Hospital Colorado, Aurora, CO 80045, USA
- Department of Otolaryngology, University of Colorado School of Medicine and Children’s Hospital Colorado, Aurora, CO 80045, USA
| | - Eric D Marsh
- Correspondence to: Eric D. Marsh, MD Division of Child Neurology Abramson Research Building, Room 502E 3615 Civic Center Boulevard Philadelphia, PA 19104, USA E-mail:
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15
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Abstract
The search for biomarkers for autism spectrum disorder (henceforth autism) has received a lot of attention due to their potential clinical relevance. The clinical and aetiological heterogeneity of autism suggests the presence of subgroups. The lack of identification of a valid diagnostic biomarker for autism, and the inconsistencies seen in studies assessing differences between autism and typically developing control groups, may be partially explained by the vast heterogeneity observed in autism. The focus now is to better understand the clinical and biological heterogeneity and identify stratification biomarkers, which are measures that describe subgroups of individuals with shared biology. Using stratification approaches to assess treatment within pre-defined subgroups could clarify who may benefit from different treatments and therapies, and ultimately lead to more effective individualised treatment plans.
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16
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Loth E, Ahmad J, Chatham C, López B, Carter B, Crawley D, Oakley B, Hayward H, Cooke J, San José Cáceres A, Bzdok D, Jones E, Charman T, Beckmann C, Bourgeron T, Toro R, Buitelaar J, Murphy D, Dumas G. The meaning of significant mean group differences for biomarker discovery. PLoS Comput Biol 2021; 17:e1009477. [PMID: 34793435 PMCID: PMC8601419 DOI: 10.1371/journal.pcbi.1009477] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Abstract
Over the past decade, biomarker discovery has become a key goal in psychiatry to aid in the more reliable diagnosis and prognosis of heterogeneous psychiatric conditions and the development of tailored therapies. Nevertheless, the prevailing statistical approach is still the mean group comparison between "cases" and "controls," which tends to ignore within-group variability. In this educational article, we used empirical data simulations to investigate how effect size, sample size, and the shape of distributions impact the interpretation of mean group differences for biomarker discovery. We then applied these statistical criteria to evaluate biomarker discovery in one area of psychiatric research-autism research. Across the most influential areas of autism research, effect size estimates ranged from small (d = 0.21, anatomical structure) to medium (d = 0.36 electrophysiology, d = 0.5, eye-tracking) to large (d = 1.1 theory of mind). We show that in normal distributions, this translates to approximately 45% to 63% of cases performing within 1 standard deviation (SD) of the typical range, i.e., they do not have a deficit/atypicality in a statistical sense. For a measure to have diagnostic utility as defined by 80% sensitivity and 80% specificity, Cohen's d of 1.66 is required, with still 40% of cases falling within 1 SD. However, in both normal and nonnormal distributions, 1 (skewness) or 2 (platykurtic, bimodal) biologically plausible subgroups may exist despite small or even nonsignificant mean group differences. This conclusion drastically contrasts the way mean group differences are frequently reported. Over 95% of studies omitted the "on average" when summarising their findings in their abstracts ("autistic people have deficits in X"), which can be misleading as it implies that the group-level difference applies to all individuals in that group. We outline practical approaches and steps for researchers to explore mean group comparisons for the discovery of stratification biomarkers.
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Affiliation(s)
- Eva Loth
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
- Sackler Institute for Translational Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Jumana Ahmad
- Department of Psychology, Social Work and Counselling, Faculty of Education and Health, University of Greenwich, London, United Kingdom
| | - Chris Chatham
- Neuroscience & Rare Diseases, Pharma Research & Early Development, Roche Innovation Center New York, New York, United States of America
| | - Beatriz López
- Department of Psychology, Portsmouth University, Portsmouth, United Kingdom
| | - Ben Carter
- Department of Biostatistics, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Daisy Crawley
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Bethany Oakley
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Hannah Hayward
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Jennifer Cooke
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Antonia San José Cáceres
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
- Instituto de Investigación Sanitaria Gregorio Marañón, Departamento de Psiquiatría del Niño y del Adolescente, Hospital General Universitario Gregorio Marañón and Centro Investigación Biomédica en Red Salud Mental (CIBERSAM), Madrid, Spain
| | - Danilo Bzdok
- Department of Biomedical Engineering, McConnell Brain-Imaging Centre (BIC), Montreal Neurological Institute (MNI), Faculty of Medicine, McGill University, Montreal, Canada
- Canadian Institute for Advanced Research (CIFAR), Canada
- Mila–Quebec Artificial Intelligence Institute, Montreal, Canada
| | - Emily Jones
- Centre for Brain and Cognitive Development, Birkbeck, University of London, London, United Kingdom
| | - Tony Charman
- Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Christian Beckmann
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, the Netherlands
| | - Thomas Bourgeron
- Human Genetics and Cognitive Functions, Institut Pasteur, UMR3571 CNRS, Université de Paris, Paris, France
| | - Roberto Toro
- Human Genetics and Cognitive Functions, Institut Pasteur, UMR3571 CNRS, Université de Paris, Paris, France
| | - Jan Buitelaar
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, the Netherlands
| | - Declan Murphy
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
- Sackler Institute for Translational Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Guillaume Dumas
- Mila–Quebec Artificial Intelligence Institute, Montreal, Canada
- Human Genetics and Cognitive Functions, Institut Pasteur, UMR3571 CNRS, Université de Paris, Paris, France
- Precision Psychiatry and Social Physiology laboratory, CHU Sainte-Justine Research Center, Department of Psychiatry, University of Montreal, Quebec, Canada
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17
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Loth E. Are we ready for precision medicine for Autism? And who wants it? Eur Neuropsychopharmacol 2021; 48:32-33. [PMID: 33853744 DOI: 10.1016/j.euroneuro.2021.03.009] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Revised: 03/12/2021] [Accepted: 03/15/2021] [Indexed: 12/13/2022]
Affiliation(s)
- Eva Loth
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, United Kingdom.
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18
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Abstract
This commentary reflects on reasonable biomarker expectations in ASD by addressing three key questions: What is a biomarker? What is required for a biomarker in ASD? How can biomarkers be useful in ASD? In addressing these queries, a path forward emerges based on clear definition of the objective for any given ASD biomarker and evaluation of each biomarker relative to current best practices.
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19
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McCracken JT, Anagnostou E, Arango C, Dawson G, Farchione T, Mantua V, McPartland J, Murphy D, Pandina G, Veenstra-VanderWeele J. Drug development for Autism Spectrum Disorder (ASD): Progress, challenges, and future directions. Eur Neuropsychopharmacol 2021; 48:3-31. [PMID: 34158222 PMCID: PMC10062405 DOI: 10.1016/j.euroneuro.2021.05.010] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Revised: 05/13/2021] [Accepted: 05/18/2021] [Indexed: 12/11/2022]
Abstract
In 2017, facing lack of progress and failures encountered in targeted drug development for Autism Spectrum Disorder (ASD) and related neurodevelopmental disorders, the ISCTM with the ECNP created the ASD Working Group charged to identify barriers to progress and recommending research strategies for the field to gain traction. Working Group international academic, regulatory and industry representatives held multiple in-person meetings, teleconferences, and subgroup communications to gather a wide range of perspectives on lessons learned from extant studies, current challenges, and paths for fundamental advances in ASD therapeutics. This overview delineates the barriers identified, and outlines major goals for next generation biomedical intervention development in ASD. Current challenges for ASD research are many: heterogeneity, lack of validated biomarkers, need for improved endpoints, prioritizing molecular targets, comorbidities, and more. The Working Group emphasized cautious but unwavering optimism for therapeutic progress for ASD core features given advances in the basic neuroscience of ASD and related disorders. Leveraging genetic data, intermediate phenotypes, digital phenotyping, big database discovery, refined endpoints, and earlier intervention, the prospects for breakthrough treatments are substantial. Recommendations include new priorities for expanded research funding to overcome challenges in translational clinical ASD therapeutic research.
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Affiliation(s)
- James T McCracken
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA 90024, United States.
| | | | - Celso Arango
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Univesitario Gregorio Maranon, and School of Medicine, Universidad Complutense de Madrid, CIBERSAM, Madrid, Spain
| | - Geraldine Dawson
- Duke University Medical Center, Durham, North Carolina, United States
| | - Tiffany Farchione
- Food and Drug Administration, Silver Spring, Maryland, United States
| | - Valentina Mantua
- Food and Drug Administration, Silver Spring, Maryland, United States
| | | | - Declan Murphy
- Institute of Psychiatry, Psychology and Neuroscience, King's College De Crespigny Park, Denmark Hill, London SE5 8AF, United Kingdom
| | - Gahan Pandina
- Neuroscience Therapeutic Area, Janssen Research & Development, Pennington, New Jersey, United States
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20
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DeMayo MM, Pokorski I, Song YJC, Thapa R, Patel S, Ambarchi Z, Soligo D, Sadeli I, Thomas EE, Hickie IB, Guastella AJ. The Feasibility of Magnetic Resonance Imaging in a Non-Selective Comprehensive Clinical Trial in Pediatric Autism Spectrum Disorder. J Autism Dev Disord 2021; 52:1211-1222. [PMID: 33903957 DOI: 10.1007/s10803-021-05028-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/14/2021] [Indexed: 12/16/2022]
Abstract
There is an increasing interest in using magnetic resonance imaging (MRI) as a tool for precision medicine in autism spectrum disorder (ASD). This study investigated the feasibility of MRI scanning in a large comprehensive, inclusive and test heavy clinical trial for children (aged 3-12 years) with ASD, without functioning constraints for participation. Of the 71 participants enrolled who consented to the MRI, 24 participants (38%) successfully completed an MRI scan at baseline along with other assessments. This scanning followed a familiarization procedure at two preceding visits. At post-treatment, 21 participants successfully completed the MRI scan. This study highlights the challenge of completing MRI assessments in ASD populations when conducted as one of a number of tests in a clinical trial.
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Affiliation(s)
- Marilena M DeMayo
- Faculty of Medicine and Health, Brain and Mind Centre, Children's Hospital Westmead Clinical School, Autism Clinic for Translational Research, University of Sydney, 100 Mallett Street, Camperdown, NSW, 2050, Australia
| | - Izabella Pokorski
- Faculty of Medicine and Health, Brain and Mind Centre, Children's Hospital Westmead Clinical School, Autism Clinic for Translational Research, University of Sydney, 100 Mallett Street, Camperdown, NSW, 2050, Australia
| | - Yun J C Song
- Faculty of Medicine and Health, Brain and Mind Centre, Children's Hospital Westmead Clinical School, Autism Clinic for Translational Research, University of Sydney, 100 Mallett Street, Camperdown, NSW, 2050, Australia
| | - Rinku Thapa
- Faculty of Medicine and Health, Brain and Mind Centre, Children's Hospital Westmead Clinical School, Autism Clinic for Translational Research, University of Sydney, 100 Mallett Street, Camperdown, NSW, 2050, Australia
| | - Shrujna Patel
- Faculty of Medicine and Health, Brain and Mind Centre, Children's Hospital Westmead Clinical School, Autism Clinic for Translational Research, University of Sydney, 100 Mallett Street, Camperdown, NSW, 2050, Australia
| | - Zahava Ambarchi
- Faculty of Medicine and Health, Brain and Mind Centre, Children's Hospital Westmead Clinical School, Autism Clinic for Translational Research, University of Sydney, 100 Mallett Street, Camperdown, NSW, 2050, Australia
| | | | - Indra Sadeli
- Faculty of Medicine and Health, Brain and Mind Centre, Children's Hospital Westmead Clinical School, Autism Clinic for Translational Research, University of Sydney, 100 Mallett Street, Camperdown, NSW, 2050, Australia
| | - Emma E Thomas
- Faculty of Medicine and Health, Brain and Mind Centre, Children's Hospital Westmead Clinical School, Autism Clinic for Translational Research, University of Sydney, 100 Mallett Street, Camperdown, NSW, 2050, Australia
| | - Ian B Hickie
- Faculty of Medicine and Health, Brain and Mind Centre, Children's Hospital Westmead Clinical School, Autism Clinic for Translational Research, University of Sydney, 100 Mallett Street, Camperdown, NSW, 2050, Australia.,Faculty of Medicine and Health, Brain and Mind Centre, Central Clinical School, University of Sydney, 100 Mallett Street, Camperdown, NSW, 2050, Australia
| | - Adam J Guastella
- Faculty of Medicine and Health, Brain and Mind Centre, Children's Hospital Westmead Clinical School, Autism Clinic for Translational Research, University of Sydney, 100 Mallett Street, Camperdown, NSW, 2050, Australia.
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21
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Geurts HM, Agelink van Rentergem JA, Radhoe T, Torenvliet C, Van der Putten WJ, Groenman AP. Ageing and heterogeneity regarding autism spectrum conditions: a protocol paper of an accelerated longitudinal study. BMJ Open 2021; 11:e040943. [PMID: 33789848 PMCID: PMC8016100 DOI: 10.1136/bmjopen-2020-040943] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/01/2023] Open
Abstract
INTRODUCTION Autism spectrum conditions (ASC) develop early in life and are thought to last a lifetime. However, ASC research has two major knowledge gaps that hinder progression in understanding the concept of ASC and in providing proper support for autistic adults: (1) the majority of knowledge about ASC mainly stems from childhood studies so little is known about older autistic adults and (2) while it is broadly recognised that ASC is a heterogeneous condition, we do not yet understand the differences in trajectories leading to their future outcome. We aim to fill both knowledge gaps. METHODS AND ANALYSIS A multistage overlapping cohort design assessing (cognitive) ageing in ASC is designed to obtain an accelerated longitudinal data set. Data, including a multitude of questionnaires, diagnostics and cognitive tests, are collected over four waves within a 10-year time frame. This will provide information regarding actual changes in quality of life, co-occurring health conditions and cognition as well as the possibility to test external validity and temporal stability in newly formed behavioural subtypes. Participants consist of three groups of adults aged 20-90 years: (1) with a clinical diagnosis of ASC, (2) with a clinical diagnosis of attention deficit hyperactivity disorder (ADHD) but no ASC, (3) no ASC/ADHD (ie, comparison group). The sample size differs between waves and instruments. Detailed analysis plans will be preregistered in AsPredicted or at the Open Science Framework. ETHICS AND DISSEMINATION Ethical approval for this study was obtained from the ethical review board of the Department of Psychology of the University of Amsterdam (wave 1 2011-PN-1952 and 2013-PN-2668, wave 2 2015-BC-4270, waves 3 and 4 2018-BC-9285). In line with the funding policies of the grant organisation funding this study, future papers will be published open access.
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Affiliation(s)
- Hilde M Geurts
- Psychology, University of Amsterdam, Amsterdam, The Netherlands
- Leo Kannerhuis (Youz), Amsterdam, The Netherlands
| | | | - Tulsi Radhoe
- Psychology, University of Amsterdam, Amsterdam, The Netherlands
| | | | - Wikke J Van der Putten
- Psychology, University of Amsterdam, Amsterdam, The Netherlands
- Leo Kannerhuis (Youz), Amsterdam, The Netherlands
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22
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Parker TC, Crowley MJ, Naples AJ, Rolison MJ, Wu J, Trapani JA, McPartland JC. The N170 event-related potential reflects delayed neural response to faces when visual attention is directed to the eyes in youths with ASD. Autism Res 2021; 14:1347-1356. [PMID: 33749161 DOI: 10.1002/aur.2505] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Revised: 03/10/2021] [Accepted: 03/11/2021] [Indexed: 11/10/2022]
Abstract
Atypical neural response to faces is thought to contribute to social deficits in autism spectrum disorder (ASD). Compared to typically developing (TD) controls, individuals with ASD exhibit delayed brain responses to upright faces at a face-sensitive event-related potential (ERP), the N170. Given observed differences in patterns of visual attention to faces, it is not known whether slowed neural processing may simply reflect atypical looking to faces. The present study manipulated visual attention to facial features to examine whether directed attention to the eyes normalizes N170 latency in ASD. ERPs were recorded in 30 children and adolescents with ASD as well as 26 TD children and adolescents. Results replicated prior findings of shorter N170 latency to the eye region of the face in TD individuals. In contrast, those with ASD did not demonstrate modulation of N170 latency by point of regard to the face. Group differences in latency were most pronounced when attention was directed to the eyes. Results suggest that well-replicated findings of N170 delays in ASD do not simply reflect atypical patterns of visual engagement with experimental stimuli. These findings add to a body of evidence indicating that N170 delays are a promising marker of atypical neural response to social information in ASD. LAY SUMMARY: This study looks at how children's and adolescents' brains respond when looking at different parts of a face. Typically developing children and adolescents processed eyes faster than other parts of the face, whereas this pattern was not seen in ASD. Children and adolescents with ASD processed eyes more slowly than typically developing children. These findings suggest that observed inefficiencies in face processing in ASD are not simply reflective of failure to attend to the eyes.
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Affiliation(s)
- Termara C Parker
- Child Study Center, Yale School of Medicine, New Haven, Connecticut, USA
| | - Michael J Crowley
- Child Study Center, Yale School of Medicine, New Haven, Connecticut, USA
| | - Adam J Naples
- Child Study Center, Yale School of Medicine, New Haven, Connecticut, USA
| | - Max J Rolison
- Child Study Center, Yale School of Medicine, New Haven, Connecticut, USA
| | - Jia Wu
- Child Study Center, Yale School of Medicine, New Haven, Connecticut, USA
| | - Julie A Trapani
- Department of Psychology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - James C McPartland
- Child Study Center, Yale School of Medicine, New Haven, Connecticut, USA
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23
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Van der Donck S, Dzhelyova M, Vettori S, Mahdi SS, Claes P, Steyaert J, Boets B. Rapid neural categorization of angry and fearful faces is specifically impaired in boys with autism spectrum disorder. J Child Psychol Psychiatry 2020; 61:1019-1029. [PMID: 32003011 PMCID: PMC7496330 DOI: 10.1111/jcpp.13201] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 12/18/2019] [Indexed: 01/05/2023]
Abstract
BACKGROUND Difficulties with facial expression processing may be associated with the characteristic social impairments in individuals with autism spectrum disorder (ASD). Emotional face processing in ASD has been investigated in an abundance of behavioral and EEG studies, yielding, however, mixed and inconsistent results. METHODS We combined fast periodic visual stimulation (FPVS) with EEG to assess the neural sensitivity to implicitly detect briefly presented facial expressions among a stream of neutral faces, in 23 boys with ASD and 23 matched typically developing (TD) boys. Neutral faces with different identities were presented at 6 Hz, periodically interleaved with an expressive face (angry, fearful, happy, sad in separate sequences) every fifth image (i.e., 1.2 Hz oddball frequency). These distinguishable frequency tags for neutral and expressive stimuli allowed direct and objective quantification of the expression-categorization responses, needing only four sequences of 60 s of recording per condition. RESULTS Both groups show equal neural synchronization to the general face stimulation and similar neural responses to happy and sad faces. However, the ASD group displays significantly reduced responses to angry and fearful faces, compared to TD boys. At the individual subject level, these neural responses allow to predict membership of the ASD group with an accuracy of 87%. Whereas TD participants show a significantly lower sensitivity to sad faces than to the other expressions, ASD participants show an equally low sensitivity to all the expressions. CONCLUSIONS Our results indicate an emotion-specific processing deficit, instead of a general emotion-processing problem: Boys with ASD are less sensitive than TD boys to rapidly and implicitly detect angry and fearful faces. The implicit, fast, and straightforward nature of FPVS-EEG opens new perspectives for clinical diagnosis.
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Affiliation(s)
- Stephanie Van der Donck
- Department of NeurosciencesCenter for Developmental PsychiatryKU LeuvenLeuvenBelgium
- Leuven Autism Research (LAuRes)KU LeuvenLeuvenBelgium
| | - Milena Dzhelyova
- Institute of Research in Psychological SciencesInstitute of NeuroscienceUniversity of LouvainLouvain‐La‐NeuveBelgium
| | - Sofie Vettori
- Department of NeurosciencesCenter for Developmental PsychiatryKU LeuvenLeuvenBelgium
- Leuven Autism Research (LAuRes)KU LeuvenLeuvenBelgium
| | - Soha Sadat Mahdi
- Department of NeurosciencesCenter for Developmental PsychiatryKU LeuvenLeuvenBelgium
- Medical Imaging Research Center, MIRCUZ LeuvenLeuvenBelgium
| | - Peter Claes
- Medical Imaging Research Center, MIRCUZ LeuvenLeuvenBelgium
- Department of Electrical Engineering (ESAT/PSI)KU LeuvenLeuvenBelgium
- Department of Human GeneticsKU LeuvenLeuvenBelgium
| | - Jean Steyaert
- Department of NeurosciencesCenter for Developmental PsychiatryKU LeuvenLeuvenBelgium
- Leuven Autism Research (LAuRes)KU LeuvenLeuvenBelgium
| | - Bart Boets
- Department of NeurosciencesCenter for Developmental PsychiatryKU LeuvenLeuvenBelgium
- Leuven Autism Research (LAuRes)KU LeuvenLeuvenBelgium
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24
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Vargason T, Grivas G, Hollowood-Jones KL, Hahn J. Towards a Multivariate Biomarker-Based Diagnosis of Autism Spectrum Disorder: Review and Discussion of Recent Advancements. Semin Pediatr Neurol 2020; 34:100803. [PMID: 32446437 PMCID: PMC7248126 DOI: 10.1016/j.spen.2020.100803] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
An ever-evolving understanding of autism spectrum disorder (ASD) pathophysiology necessitates that diagnostic standards also evolve from being observation-based to include quantifiable clinical measurements. The multisystem nature of ASD motivates the use of multivariate methods of statistical analysis over common univariate approaches for discovering clinical biomarkers relevant to this goal. In addition to characterization of important behavioral patterns for improving current diagnostic instruments, multivariate analyses to date have allowed for thorough investigation of neuroimaging-based, genetic, and metabolic abnormalities in individuals with ASD. This review highlights current research using multivariate statistical analyses to quantify the value of these behavioral and physiological markers for ASD diagnosis. A detailed discussion of a blood-based diagnostic test for ASD using specific metabolite concentrations is also provided. The advancement of ASD biomarker research promises to provide earlier and more accurate diagnoses of the disorder.
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Affiliation(s)
- Troy Vargason
- Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY; Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, NY
| | - Genevieve Grivas
- Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY; Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, NY
| | - Kathryn L Hollowood-Jones
- Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY; Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, NY
| | - Juergen Hahn
- Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY; Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, NY; Department of Chemical and Biological Engineering, Rensselaer Polytechnic Institute, Troy, NY.
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25
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Early Motor Development Predicts Clinical Outcomes of Siblings at High-Risk for Autism: Insight from an Innovative Motion-Tracking Technology. Brain Sci 2020; 10:brainsci10060379. [PMID: 32560198 PMCID: PMC7349903 DOI: 10.3390/brainsci10060379] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Revised: 06/12/2020] [Accepted: 06/12/2020] [Indexed: 11/17/2022] Open
Abstract
Atypical motor patterns are potential early markers and predictors of later diagnosis of Autism Spectrum Disorder (ASD). This study aimed to investigate the early motor trajectories of infants at high-risk (HR) of ASD through MOVIDEA, a semi-automatic software developed to analyze 2D and 3D videos and provide objective kinematic features of their movements. MOVIDEA was developed within the Italian Network for early detection of Autism Spectrum Disorder (NIDA Network), which is currently coordinating the most extensive surveillance program for infants at risk for neurodevelopmental disorders (NDDs). MOVIDEA was applied to video recordings of 53 low-risk (LR; siblings of typically developing children) and 50 HR infants’ spontaneous movements collected at 10 days and 6, 12, 18, and 24 weeks. Participants were grouped based on their clinical outcome (18 HR received an NDD diagnosis, 32 HR and 53 LR were typically developing). Results revealed that early developmental trajectories of specific motor parameters were different in HR infants later diagnosed with NDDs from those of infants developing typically. Since MOVIDEA was useful in the association of quantitative measures with specific early motor patterns, it should be applied to the early detection of ASD/NDD markers.
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26
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Saby JN, Peters SU, Roberts TPL, Nelson CA, Marsh ED. Evoked Potentials and EEG Analysis in Rett Syndrome and Related Developmental Encephalopathies: Towards a Biomarker for Translational Research. Front Integr Neurosci 2020; 14:30. [PMID: 32547374 PMCID: PMC7271894 DOI: 10.3389/fnint.2020.00030] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2019] [Accepted: 05/04/2020] [Indexed: 12/17/2022] Open
Abstract
Rett syndrome is a debilitating neurodevelopmental disorder for which no disease-modifying treatment is available. Fortunately, advances in our understanding of the genetics and pathophysiology of Rett syndrome has led to the development of promising new therapeutics for the condition. Several of these therapeutics are currently being tested in clinical trials with others likely to progress to clinical trials in the coming years. The failure of recent clinical trials for Rett syndrome and other neurodevelopmental disorders has highlighted the need for electrophysiological or other objective biological markers of treatment response to support the success of clinical trials moving forward. The purpose of this review is to describe the existing studies of electroencephalography (EEG) and evoked potentials (EPs) in Rett syndrome and discuss the open questions that must be addressed before the field can adopt these measures as surrogate endpoints in clinical trials. In addition to summarizing the human work on Rett syndrome, we also describe relevant studies with animal models and the limited research that has been carried out on Rett-related disorders, particularly methyl-CpG binding protein 2 (MECP2) duplication syndrome, CDKL5 deficiency disorder, and FOXG1 disorder.
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Affiliation(s)
- Joni N. Saby
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children’s Hospital of Philadelphia, Philadelphia, PA, United States
| | - Sarika U. Peters
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Timothy P. L. Roberts
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children’s Hospital of Philadelphia, Philadelphia, PA, United States,Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States
| | - Charles A. Nelson
- Laboratories of Cognitive Neuroscience, Division of Developmental Medicine, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Eric D. Marsh
- Division of Neurology and Pediatrics, Children’s Hospital of Philadelphia, Philadelphia, PA, United States,Departments of Neurology and Pediatrics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States,*Correspondence: Eric D. Marsh
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27
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Wang Q, Chang J, Chawarska K. Atypical Value-Driven Selective Attention in Young Children With Autism Spectrum Disorder. JAMA Netw Open 2020; 3:e204928. [PMID: 32374399 PMCID: PMC7203607 DOI: 10.1001/jamanetworkopen.2020.4928] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/01/2019] [Accepted: 03/11/2020] [Indexed: 11/21/2022] Open
Abstract
Importance Enhanced selective attention toward nonsocial objects and impaired attention to social stimuli constitute key clinical features of autism spectrum disorder (ASD). Yet, the mechanisms associated with atypical selective attention in ASD are poorly understood, which limits the development of more effective interventions. In typically developing individuals, selective attention to social and nonsocial stimuli is associated with the informational value of the stimuli, which is typically learned over the course of repeated interactions with the stimuli. Objective To examine value learning (VL) of social and nonsocial stimuli and its association with selective attention in preschoolers with and without ASD. Design, Setting, and Participants This case-control study compared children with ASD vs children with developmental delay (DD) and children with typical development (TD) recruited between March 3, 2017, and June 13, 2018, at a university-based research laboratory. Participants were preschoolers with ASD, DD, or TD. Main Outcomes and Measures Procedure consisted of an eye-tracking gaze-contingent VL task involving social (faces) and nonsocial (fractals) stimuli and consisting of baseline, training, and choice test phases. Outcome measures were preferential attention to stimuli reinforced (high value) vs not reinforced (low value) during training. The hypotheses were stated before data collection. Results Included were 115 preschoolers with ASD (n = 48; mean [SD] age, 38.30 [15.55] months; 37 [77%] boys), DD (n = 31; mean [SD] age, 45.73 [19.49] months; 19 [61%] boys), or TD (n = 36; mean [SD] age, 36.53 [12.39] months; 22 [61%] boys). The groups did not differ in sex distribution; participants with ASD or TD had similar chronological age; and participants with ASD or DD had similar verbal IQ and nonverbal IQ. After training, the ASD group showed preference for the high-value nonsocial stimuli (mean proportion, 0.61 [95% CI, 0.56-0.65]; P < .001) but not for the high-value social stimuli (mean proportion, 0.51 [95% CI, 0.46-0.56]; P = .58). In contrast, the DD and TD groups demonstrated preference for the high-value social stimuli (DD mean proportion, 0.59 [95% CI, 0.54-0.64]; P = .001 and TD mean proportion, 0.57 [95% CI, 0.53-0.61]; P = .002) but not for the high-value nonsocial stimuli (DD mean proportion, 0.52 [95% CI, 0.44-0.59]; P = .64 and TD mean proportion, 0.50 [95% CI, 0.44-0.57]; P = .91). Controlling for age and nonverbal IQ, autism severity was positively correlated with enhanced learning in the nonsocial domain (r = 0.22; P = .03) and with poorer learning in the social domain (r = -0.26; P = .01). Conclusions and Relevance Increased attention to objects in preschoolers with ASD may be associated with enhanced VL in the nonsocial domain. When paired with poor VL in the social domain, enhanced value-driven attention to objects may play a formative role in the emergence of autism symptoms by altering attentional priorities and thus learning opportunities in affected children.
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Affiliation(s)
- Quan Wang
- Child Study Center, Yale School of Medicine, New Haven, Connecticut
- Key Laboratory of Spectral Imaging Technology, Key Laboratory of Biomedical Spectroscopy of Xi’an, Xi’an Institute of Optics and Precision Mechanics of Chinese Academy of Sciences
| | - Joseph Chang
- Child Study Center, Yale School of Medicine, New Haven, Connecticut
- Department of Statistics and Data Science, Yale University, New Haven, Connecticut
| | - Katarzyna Chawarska
- Child Study Center, Yale School of Medicine, New Haven, Connecticut
- Department of Statistics and Data Science, Yale University, New Haven, Connecticut
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28
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Levin AR, Naples AJ, Scheffler AW, Webb SJ, Shic F, Sugar CA, Murias M, Bernier RA, Chawarska K, Dawson G, Faja S, Jeste S, Nelson CA, McPartland JC, Şentürk D. Day-to-Day Test-Retest Reliability of EEG Profiles in Children With Autism Spectrum Disorder and Typical Development. Front Integr Neurosci 2020; 14:21. [PMID: 32425762 PMCID: PMC7204836 DOI: 10.3389/fnint.2020.00021] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2019] [Accepted: 03/23/2020] [Indexed: 01/11/2023] Open
Abstract
Biomarker development is currently a high priority in neurodevelopmental disorder research. For many types of biomarkers (particularly biomarkers of diagnosis), reliability over short periods is critically important. In the field of autism spectrum disorder (ASD), resting electroencephalography (EEG) power spectral densities (PSD) are well-studied for their potential as biomarkers. Classically, such data have been decomposed into pre-specified frequency bands (e.g., delta, theta, alpha, beta, and gamma). Recent technical advances, such as the Fitting Oscillations and One-Over-F (FOOOF) algorithm, allow for targeted characterization of the features that naturally emerge within an EEG PSD, permitting a more detailed characterization of the frequency band-agnostic shape of each individual's EEG PSD. Here, using two resting EEGs collected a median of 6 days apart from 22 children with ASD and 25 typically developing (TD) controls during the Feasibility Visit of the Autism Biomarkers Consortium for Clinical Trials, we estimate test-retest reliability based on the characterization of the PSD shape in two ways: (1) Using the FOOOF algorithm we estimate six parameters (offset, slope, number of peaks, and amplitude, center frequency and bandwidth of the largest alpha peak) that characterize the shape of the EEG PSD; and (2) using nonparametric functional data analyses, we decompose the shape of the EEG PSD into a reduced set of basis functions that characterize individual power spectrum shapes. We show that individuals exhibit idiosyncratic PSD signatures that are stable over recording sessions using both characterizations. Our data show that EEG activity from a brief 2-min recording provides an efficient window into characterizing brain activity at the single-subject level with desirable psychometric characteristics that persist across different analytical decomposition methods. This is a necessary step towards analytical validation of biomarkers based on the EEG PSD and provides insights into parameters of the PSD that offer short-term reliability (and thus promise as potential biomarkers of trait or diagnosis) vs. those that are more variable over the short term (and thus may index state or other rapidly dynamic measures of brain function). Future research should address the longer-term stability of the PSD, for purposes such as monitoring development or response to treatment.
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Affiliation(s)
- April R. Levin
- Department of Neurology, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Adam J. Naples
- Child Study Center, School of Medicine, Yale University, New Haven, CT, United States
| | - Aaron Wolfe Scheffler
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, United States
| | - Sara J. Webb
- Center for Child Health, Behavior, and Development, Seattle Children’s Research Institute, Seattle, WA, United States
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, United States
| | - Frederick Shic
- Center for Child Health, Behavior, and Development, Seattle Children’s Research Institute, Seattle, WA, United States
| | - Catherine A. Sugar
- Department of Biostatistics, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, United States
| | - Michael Murias
- Institute for Innovations in Developmental Sciences, Northwestern University, Chicago, IL, United States
| | - Raphael A. Bernier
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, United States
| | - Katarzyna Chawarska
- Child Study Center, School of Medicine, Yale University, New Haven, CT, United States
| | - Geraldine Dawson
- Duke Institute for Brain Sciences, Duke University, Durham, NC, United States
- Duke Center for Autism and Brain Development, Duke University, Durham, NC, United States
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, United States
| | - Susan Faja
- Laboratories of Cognitive Neuroscience, Division of Developmental Medicine, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Shafali Jeste
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, United States
| | - Charles A. Nelson
- Laboratories of Cognitive Neuroscience, Division of Developmental Medicine, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
| | - James C. McPartland
- Child Study Center, School of Medicine, Yale University, New Haven, CT, United States
| | - Damla Şentürk
- Department of Biostatistics, University of California, Los Angeles, Los Angeles, CA, United States
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Rolison MJ, Naples AJ, Rutherford HJV, McPartland JC. The Presence of Another Person Influences Oscillatory Cortical Dynamics During Dual Brain EEG Recording. Front Psychiatry 2020; 11:246. [PMID: 32362842 PMCID: PMC7180176 DOI: 10.3389/fpsyt.2020.00246] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/03/2019] [Accepted: 03/12/2020] [Indexed: 11/13/2022] Open
Abstract
Humans are innately social creatures and the social environment strongly influences brain development. As such, the human brain is primed for and sensitive to social information even in the absence of explicit task or instruction. In this study, we examined the influence of different levels of interpersonal proximity on resting state brain activity and its association with social cognition. We measured EEG in pairs of 13 typically developing (TD) adults seated in separate rooms, in the same room back-to-back, and in the same room facing each other. Interpersonal proximity modulated broadband EEG power from 4-55 Hz and individual differences in self-reported social cognition modulated these effects in the beta and gamma frequency bands. These findings provide novel insight into the influence of social environment on brain activity and its association with social cognition through dual-brain EEG recording and demonstrate the importance of using interactive methods to study the human brain.
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30
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Webb SJ, Shic F, Murias M, Sugar CA, Naples AJ, Barney E, Borland H, Hellemann G, Johnson S, Kim M, Levin AR, Sabatos-DeVito M, Santhosh M, Senturk D, Dziura J, Bernier RA, Chawarska K, Dawson G, Faja S, Jeste S, McPartland J. Biomarker Acquisition and Quality Control for Multi-Site Studies: The Autism Biomarkers Consortium for Clinical Trials. Front Integr Neurosci 2020; 13:71. [PMID: 32116579 PMCID: PMC7020808 DOI: 10.3389/fnint.2019.00071] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2019] [Accepted: 11/28/2019] [Indexed: 12/31/2022] Open
Abstract
The objective of the Autism Biomarkers Consortium for Clinical Trials (ABC-CT) is to evaluate a set of lab-based behavioral video tracking (VT), electroencephalography (EEG), and eye tracking (ET) measures for use in clinical trials with children with autism spectrum disorder (ASD). Within the larger organizational structure of the ABC-CT, the Data Acquisition and Analytic Core (DAAC) oversees the standardization of VT, EEG, and ET data acquisition, data processing, and data analysis. This includes designing and documenting data acquisition and analytic protocols and manuals; facilitating site training in acquisition; data acquisition quality control (QC); derivation and validation of dependent variables (DVs); and analytic deliverables including preparation of data for submission to the National Database for Autism Research (NDAR). To oversee consistent application of scientific standards and methodological rigor for data acquisition, processing, and analytics, we developed standard operating procedures that reflect the logistical needs of multi-site research, and the need for well-articulated, transparent processes that can be implemented in future clinical trials. This report details the methodology of the ABC-CT related to acquisition and QC in our Feasibility and Main Study phases. Based on our acquisition metrics from a preplanned interim analysis, we report high levels of acquisition success utilizing VT, EEG, and ET experiments in a relatively large sample of children with ASD and typical development (TD), with data acquired across multiple sites and use of a manualized training and acquisition protocol.
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Affiliation(s)
- Sara Jane Webb
- Center on Child Health, Behavior, and Development, Seattle Children’s Research Institute, Seattle, WA, United States
- Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA, United States
| | - Frederick Shic
- Center on Child Health, Behavior, and Development, Seattle Children’s Research Institute, Seattle, WA, United States
- Department of Pediatrics, University of Washington School of Medicine, Seattle, WA, United States
| | - Michael Murias
- Duke Center for Autism and Brain Development, Duke University, Durham, NC, United States
| | - Catherine A. Sugar
- Department of Biostatistics, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Statistics, University of California, Los Angeles, Los Angeles, CA, United States
| | - Adam J. Naples
- Yale Child Study Center, Yale University, New Haven, CT, United States
| | - Erin Barney
- Center on Child Health, Behavior, and Development, Seattle Children’s Research Institute, Seattle, WA, United States
| | - Heather Borland
- Center on Child Health, Behavior, and Development, Seattle Children’s Research Institute, Seattle, WA, United States
| | - Gerhard Hellemann
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, United States
| | - Scott Johnson
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, United States
| | - Minah Kim
- Center on Child Health, Behavior, and Development, Seattle Children’s Research Institute, Seattle, WA, United States
| | - April R. Levin
- Department of Neurology, Boston Children’s Hospital, Boston, MA, United States
- Harvard Medical School, Harvard University, Boston, MA, United States
| | - Maura Sabatos-DeVito
- Duke Center for Autism and Brain Development, Duke University, Durham, NC, United States
| | - Megha Santhosh
- Center on Child Health, Behavior, and Development, Seattle Children’s Research Institute, Seattle, WA, United States
| | - Damla Senturk
- Department of Biostatistics, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Statistics, University of California, Los Angeles, Los Angeles, CA, United States
| | - James Dziura
- Yale Child Study Center, Yale University, New Haven, CT, United States
| | - Raphael A. Bernier
- Center on Child Health, Behavior, and Development, Seattle Children’s Research Institute, Seattle, WA, United States
- Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA, United States
- Center on Human Development and Disability, University of Washington, Seattle, WA, United States
| | | | - Geraldine Dawson
- Duke Center for Autism and Brain Development, Duke University, Durham, NC, United States
| | - Susan Faja
- Harvard Medical School, Harvard University, Boston, MA, United States
- Department of Pediatrics, Boston Children’s Hospital, Boston, MA, United States
| | - Shafali Jeste
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Neurology, University of California, Los Angeles, Los Angeles, CA, United States
| | - James McPartland
- Yale Child Study Center, Yale University, New Haven, CT, United States
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31
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Light-Adapted Electroretinogram Differences in Autism Spectrum Disorder. J Autism Dev Disord 2020; 50:2874-2885. [DOI: 10.1007/s10803-020-04396-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
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32
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Multivariate Analysis of Plasma Metabolites in Children with Autism Spectrum Disorder and Gastrointestinal Symptoms Before and After Microbiota Transfer Therapy. Processes (Basel) 2019. [DOI: 10.3390/pr7110806] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023] Open
Abstract
Current diagnosis of autism spectrum disorder (ASD) is based on assessment of behavioral symptoms, although there is strong evidence that ASD affects multiple organ systems including the gastrointestinal (GI) tract. This study used Fisher discriminant analysis (FDA) to evaluate plasma metabolites from 18 children with ASD and chronic GI problems (ASD + GI cohort) and 20 typically developing (TD) children without GI problems (TD − GI cohort). Using three plasma metabolites that may represent three general groups of metabolic abnormalities, it was possible to distinguish the ASD + GI cohort from the TD − GI cohort with 94% sensitivity and 100% specificity after leave-one-out cross-validation. After the ASD + GI participants underwent Microbiota Transfer Therapy with significant improvement in GI and ASD-related symptoms, their metabolic profiles shifted significantly to become more similar to the TD − GI group, indicating potential utility of this combination of plasma metabolites as a biomarker for treatment efficacy. Two of the metabolites, sarcosine and inosine 5′-monophosphate, improved greatly after treatment. The third metabolite, tyramine O-sulfate, showed no change in median value, suggesting it and correlated metabolites to be a possible target for future therapies. Since it is unclear whether the observed differences are due to metabolic abnormalities associated with ASD or with GI symptoms (or contributions from both), future studies aiming to classify ASD should feature TD participants with GI symptoms and have larger sample sizes to improve confidence in the results.
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33
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Van der Donck S, Dzhelyova M, Vettori S, Thielen H, Steyaert J, Rossion B, Boets B. Fast Periodic Visual Stimulation EEG Reveals Reduced Neural Sensitivity to Fearful Faces in Children with Autism. J Autism Dev Disord 2019; 49:4658-4673. [PMID: 31468275 PMCID: PMC6813754 DOI: 10.1007/s10803-019-04172-0] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
We objectively quantified the neural sensitivity of school-aged boys with and without autism spectrum disorder (ASD) to detect briefly presented fearful expressions by combining fast periodic visual stimulation with frequency-tagging electroencephalography. Images of neutral faces were presented at 6 Hz, periodically interleaved with fearful expressions at 1.2 Hz oddball rate. While both groups equally display the face inversion effect and mainly rely on information from the mouth to detect fearful expressions, boys with ASD generally show reduced neural responses to rapid changes in expression. At an individual level, fear discrimination responses predict clinical status with an 83% accuracy. This implicit and straightforward approach identifies subtle deficits that remain concealed in behavioral tasks, thereby opening new perspectives for clinical diagnosis.
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Affiliation(s)
- Stephanie Van der Donck
- Center for Developmental Psychiatry, Department of Neurosciences, KU Leuven, Leuven, Belgium.
- Leuven Autism Research (LAuRes), KU Leuven, Leuven, Belgium.
| | - Milena Dzhelyova
- Institute of Research in Psychological Sciences, Institute of Neuroscience, Université de Louvain, Louvain-La-Neuve, Belgium
| | - Sofie Vettori
- Center for Developmental Psychiatry, Department of Neurosciences, KU Leuven, Leuven, Belgium
- Leuven Autism Research (LAuRes), KU Leuven, Leuven, Belgium
| | - Hella Thielen
- Department of Brain and Cognition, KU Leuven, Leuven, Belgium
| | - Jean Steyaert
- Center for Developmental Psychiatry, Department of Neurosciences, KU Leuven, Leuven, Belgium
- Leuven Autism Research (LAuRes), KU Leuven, Leuven, Belgium
| | - Bruno Rossion
- Institute of Research in Psychological Sciences, Institute of Neuroscience, Université de Louvain, Louvain-La-Neuve, Belgium
- Université de Lorraine, CNRS, CRAN, Nancy, France
- Université de Lorraine, CHRU-Nancy, Service de Neurologie, Nancy, France
| | - Bart Boets
- Center for Developmental Psychiatry, Department of Neurosciences, KU Leuven, Leuven, Belgium
- Leuven Autism Research (LAuRes), KU Leuven, Leuven, Belgium
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34
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Ewen JB, Sweeney JA, Potter WZ. Conceptual, Regulatory and Strategic Imperatives in the Early Days of EEG-Based Biomarker Validation for Neurodevelopmental Disabilities. Front Integr Neurosci 2019; 13:45. [PMID: 31496945 PMCID: PMC6712089 DOI: 10.3389/fnint.2019.00045] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2019] [Accepted: 08/06/2019] [Indexed: 12/14/2022] Open
Abstract
Biological treatment development for syndromal neuropsychiatric conditions such as autism has seen slow progress for decades. Speeding drug discovery may result from the judicious development and application of biomarker measures of brain function to select patients for clinical trials, to confirm target engagement and to optimize drug dose. For neurodevelopmental disorders, electrophysiology (EEG) offers considerable promise because of its ability to monitor brain activity with high temporal resolution and its more ready application for pediatric populations relative to MRI. Here, we discuss conceptual/definitional issues related to biomarker development, discuss practical implementation issues, and suggest preliminary guidelines for validating EEG approaches as biomarkers with a context of use in neurodevelopmental disorder drug development.
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Affiliation(s)
- Joshua B. Ewen
- Department of Neurology and Developmental Medicine, Kennedy Krieger Institute, Baltimore, MD, United States
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- Department of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, MD, United States
| | - John A. Sweeney
- Department of Psychiatry, University of Cincinnati, Cincinnati, OH, United States
| | - William Z. Potter
- National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States
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35
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Bradshaw J, Shic F, Holden AN, Horowitz EJ, Barrett AC, German TC, Vernon TW. The Use of Eye Tracking as a Biomarker of Treatment Outcome in a Pilot Randomized Clinical Trial for Young Children with Autism. Autism Res 2019; 12:779-793. [PMID: 30891960 DOI: 10.1002/aur.2093] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2018] [Revised: 02/07/2019] [Accepted: 02/22/2019] [Indexed: 11/06/2022]
Abstract
There is a pressing need for objective, quantifiable outcome measures in intervention trials for children with autism spectrum disorder (ASD). The current study investigated the use of eye tracking as a biomarker of treatment response in the context of a pilot randomized clinical trial of treatment for young children with ASD. Participants included 28 children with ASD, aged 18-48 months, who were randomized to one of two conditions: Pivotal Response Intervention for Social Motivation (PRISM) or community treatment as usual (TAU). Eye-tracking and behavioral assessment of developmental functioning were administered at Time 1 (prior to randomization) and at Time 2 (after 6 months of intervention). Two well-established eye-tracking paradigms were used to measure social attention: social preference and face scanning. As a context for understanding relationships between social attention and developmental ability, we first examined how scanning patterns at Time 1 were associated with concurrent developmental functioning and compared to those of 23 age-matched typically developing (TD) children. Changes in scanning patterns from Time 1 to Time 2 were then compared between PRISM and TAU groups and associated with behavioral change over time. Results showed that the social preference paradigm differentiated children with ASD from TD children. In addition, attention during face scanning was associated with language and adaptive communication skills at Time 1 and change in language skills from Time 1 to Time 2. These findings highlight the importance of examining targeted biomarkers that measure unique aspects of child functioning and that are well-matched to proposed mechanisms of change. Autism Research 2019, 12: 779-793. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Biomarkers have the potential to provide important information about how and why early interventions effect positive change for young children with ASD. The current study suggests that eye-tracking measures of social attention can be used to track change in specific areas of development, such as language, and points to the need for targeted eye-tracking paradigms designed to measure specific behavioral changes. Such biomarkers could inform the development of optimal, individualized, and adaptive interventions for young children with ASD.
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Affiliation(s)
- Jessica Bradshaw
- Department of Psychology, University of South Carolina, Columbia, South Carolina
| | - Frederick Shic
- Center for Child Health, Behavior and Development, Seattle Children's Research Institute, Seattle, Washington.,Department of Pediatrics, University of Washington, Seattle, Washington
| | - Anahita N Holden
- Department of Counseling, Clinical, and School Psychology, University of California Santa Barbara, Santa Barbara, California
| | - Erin J Horowitz
- Department of Psychological and Brain Sciences, University of California Santa Barbara, Santa Barbara, California
| | - Amy C Barrett
- Department of Counseling, Clinical, and School Psychology, University of California Santa Barbara, Santa Barbara, California
| | - Tamsin C German
- Department of Psychological and Brain Sciences, University of California Santa Barbara, Santa Barbara, California
| | - Ty W Vernon
- Department of Counseling, Clinical, and School Psychology, University of California Santa Barbara, Santa Barbara, California
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36
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Kang E, McPartland JC, Keifer CM, Foss-Feig JH, Levy EJ, Lerner MD. Reply to: Can the N170 Be Used as an Electrophysiological Biomarker Indexing Face Processing Difficulties in Autism Spectrum Disorder? BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2019; 4:324-325. [PMID: 30391290 PMCID: PMC10026259 DOI: 10.1016/j.bpsc.2018.09.004] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/17/2018] [Accepted: 09/17/2018] [Indexed: 11/29/2022]
Affiliation(s)
- Erin Kang
- Department of Psychology, Stony Brook University, Stony Brook, New York.
| | - James C McPartland
- Yale Child Study Center, Yale University School of Medicine, New Haven, Connecticut
| | - Cara M Keifer
- Department of Psychology, Stony Brook University, Stony Brook, New York
| | | | - Emily J Levy
- Department of Biology, Duke University, Durham, North Carolina
| | - Matthew D Lerner
- Department of Psychology, Stony Brook University, Stony Brook, New York.
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37
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McPartland JC. Autism's existential crisis: a reflection on Livingston et al. (2018). J Child Psychol Psychiatry 2019; 60:111-113. [PMID: 30556607 DOI: 10.1111/jcpp.12989] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 09/05/2018] [Indexed: 11/30/2022]
Abstract
Livingston and colleagues present an empirical investigation of the compensatory framework describing the autism clinical phenotype as the sum of intrinsic neurocognitive deficits and compensatory mechanisms. This commentary highlights several methodologic features of the study that are pertinent to interpretation and reflects on the reduction of social behavior to cognitive processes. Taken together, the notion of compensation calls into question the validity and utility of the current behavioral diagnosis of autism.
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38
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Matta J, Zhao J, Ercal G, Obafemi-Ajayi T. Applications of node-based resilience graph theoretic framework to clustering autism spectrum disorders phenotypes. APPLIED NETWORK SCIENCE 2018; 3:38. [PMID: 30839816 PMCID: PMC6214326 DOI: 10.1007/s41109-018-0093-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/03/2018] [Accepted: 08/08/2018] [Indexed: 06/09/2023]
Abstract
With the growing ubiquity of data in network form, clustering in the context of a network, represented as a graph, has become increasingly important. Clustering is a very useful data exploratory machine learning tool that allows us to make better sense of heterogeneous data by grouping data with similar attributes based on some criteria. This paper investigates the application of a novel graph theoretic clustering method, Node-Based Resilience clustering (NBR-Clust), to address the heterogeneity of Autism Spectrum Disorder (ASD) and identify meaningful subgroups. The hypothesis is that analysis of these subgroups would reveal relevant biomarkers that would provide a better understanding of ASD phenotypic heterogeneity useful for further ASD studies. We address appropriate graph constructions suited for representing the ASD phenotype data. The sample population is drawn from a very large rigorous dataset: Simons Simplex Collection (SSC). Analysis of the results performed using graph quality measures, internal cluster validation measures, and clinical analysis outcome demonstrate the potential usefulness of resilience measure clustering for biomedical datasets. We also conduct feature extraction analysis to characterize relevant biomarkers that delineate the resulting subgroups. The optimal results obtained favored predominantly a 5-cluster configuration.
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Affiliation(s)
- John Matta
- Department of Computer Science, Southern Illinois University Edwardsville, Edwardsville, IL USA
| | - Junya Zhao
- Department of Computer Science, Missouri State University, Springfield, MO USA
| | - Gunes Ercal
- Department of Computer Science, Southern Illinois University Edwardsville, Edwardsville, IL USA
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39
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Bazelmans T, Jones EJH, Ghods S, Corrigan S, Toth K, Charman T, Webb SJ. Heart rate mean and variability as a biomarker for phenotypic variation in preschoolers with autism spectrum disorder. Autism Res 2018; 12:39-52. [PMID: 30114343 DOI: 10.1002/aur.1982] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2018] [Revised: 06/06/2018] [Accepted: 06/10/2018] [Indexed: 02/03/2023]
Abstract
Interest in autonomic arousal in autism spectrum disorder (ASD) is increasing; however, reliability of these measures in ASD is unknown, and previously reported associations with social and cognitive abilities are inconsistent. This study assesses heart rate (HR) and HR variability (HRV) in preschoolers with ASD or typical development (TD) while they passively watched naturalistic videos. Measurement reliability, group differences, and the relationship with social and cognitive abilities were evaluated. Seventy one ASD and 66 TD children (2-4 years) provided cardiac data from two sessions. Test-retest intraclass correlations of HR and HRV over a 3-week period were moderate to good in both groups. Groups did not differ in mean level of HR or HRV. Intra-individual variability of HR between video segments within a session was higher in the ASD group, but intraclass correlations of this metric were low. Higher HR related to better language skills in TD children, but not after accounting for age and nonverbal ability. Higher HRV related to better expressive and receptive language in ASD children after controlling for age and nonverbal ability. HR/HRV were not related to social or executive functioning skills and did not explain any additional variance in abilities at a 12-month follow-up visit. In summary, variation in language abilities is associated with HR in the TD group and HRV in the ASD group. While preliminary, these results are promising for consideration of autonomic control as a biomarker for individual differences in ASD and may help us understand the mechanisms that contribute to communication skills. Autism Research 2019, 12: 39-52. © 2018 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Cardiac activity, such as heart rate and heart rate variability, is linked to a wide range of psychological functions. This study shows that there is an association between heart rate and heart rate variability and language skills in young children with autism spectrum disorder (ASD). These results may help us understand what underlies individual differences in developmental abilities in young children with ASD.
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Affiliation(s)
- Tessel Bazelmans
- Psychology Department, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Emily J H Jones
- Centre for Brain and Cognitive Development, Birkbeck, University of London, London, UK.,Center for Child Health, Behavior & Development, Seattle Children's Research Institute, Seattle, Washington
| | - Sheila Ghods
- Center for Child Health, Behavior & Development, Seattle Children's Research Institute, Seattle, Washington.,Department of Psychiatry, University of California San Francisco, San Francisco, California
| | - Sarah Corrigan
- Center for Child Health, Behavior & Development, Seattle Children's Research Institute, Seattle, Washington
| | - Karen Toth
- Center for Child Health, Behavior & Development, Seattle Children's Research Institute, Seattle, Washington
| | - Tony Charman
- Psychology Department, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Sara J Webb
- Center for Child Health, Behavior & Development, Seattle Children's Research Institute, Seattle, Washington.,Department of Psychiatry & Behavioral Sciences, University of Washington, Seattle, Washington
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40
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Kang E, Keifer CM, Levy EJ, Foss-Feig JH, McPartland JC, Lerner MD. Atypicality of the N170 Event-Related Potential in Autism Spectrum Disorder: A Meta-analysis. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2018; 3:657-666. [PMID: 30092916 PMCID: PMC6089230 DOI: 10.1016/j.bpsc.2017.11.003] [Citation(s) in RCA: 51] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/26/2017] [Revised: 11/11/2017] [Accepted: 11/13/2017] [Indexed: 12/17/2022]
Abstract
BACKGROUND Autism spectrum disorder (ASD) is associated with impaired face processing. The N170 event-related potential (ERP) has been considered a promising neural marker of this impairment. However, no quantitative review to date has integrated the literature to assess whether the N170 response to faces in individuals with ASD differs from that of typically developing (TD) individuals. METHODS This meta-analysis examined the corpus of literature investigating difference in N170 response to faces in individuals with ASD and without ASD. Data from 23 studies (NASD = 374, NTD = 359) were reviewed. Meta-analysis was used to examine the effect size of the difference in N170 latency and amplitude among individuals with ASD and without ASD. Analyses were also conducted examining hemispheric differences, potential moderators, and publication bias. RESULTS On average, N170 latencies to faces were delayed in individuals with ASD, but amplitudes did not differ for individuals with ASD and TD individuals. Moderator analyses revealed that N170 amplitudes were smaller in magnitude in the ASD participants relative to the TD participants in adult samples and in those with higher cognitive ability. However, effects differed as a function of hemisphere of recording. No evidence of publication bias was found. CONCLUSIONS Atypicality of N170-particularly latency-to faces appears to be a specific biomarker of social-communicative dysfunction in ASD and may relate to differential developmental experiences and use of compensatory cognitive mechanisms. Future research should examine phenotypic differences that contribute to N170 heterogeneity, as well as specificity of N170 differences in ASD versus non-ASD clinical populations, and N170 malleability with treatment.
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Affiliation(s)
- Erin Kang
- Department of Psychology, Stony Brook University, Stony Brook, New York.
| | - Cara M Keifer
- Department of Psychology, Stony Brook University, Stony Brook, New York
| | - Emily J Levy
- Department of Biology, Duke University, Durham, North Carolina
| | | | | | - Matthew D Lerner
- Department of Psychology, Stony Brook University, Stony Brook, New York
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41
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Rolison MJ, Naples AJ, Rutherford HJV, McPartland JC. Modulation of reward in a live social context as revealed through interactive social neuroscience. Soc Neurosci 2018; 13:416-428. [PMID: 28586261 PMCID: PMC6072262 DOI: 10.1080/17470919.2017.1339635] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/16/2016] [Revised: 05/09/2017] [Indexed: 01/09/2023]
Abstract
Social neuroscience research investigating autism spectrum disorder (ASD) has yielded inconsistent findings, despite ASD being well-characterized by difficulties in social interaction and communication through behavioral observation. In particular, specific etiologies and functional and structural assays of the brain in autism have not been consistently identified. To date, most social neuroscience research has focused on a single person viewing static images. Research utilizing interactive social neuroscience featuring dual-brain recording offers great promise for the study of neurodevelopmental disabilities. Reward processing has been implicated in the pathology of ASD, yet mixed findings have brought uncertainty about the role reward processing deficits may play in ASD. The current study employed dual-brain EEG recording to examine reward processing during live interaction and its relation to autistic traits. Sixteen typically developing (TD) adults played a competitive treasure-hunt game against a computer and against a human partner. EEG results revealed enhanced neural sensitivity to reward outcome during live interaction with a human competitor. Further, individuals with higher levels of autistic traits demonstrated reduced sensitivity to reward outcome during live interaction. These findings provide novel insight into reward processing mechanisms associated with autistic traits, as well as support the necessary utility of interactive social neuroscience techniques to study developmental disorders.
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Affiliation(s)
- Max J Rolison
- a Child Study Center , Yale School of Medicine , New Haven , CT , USA
| | - Adam J Naples
- a Child Study Center , Yale School of Medicine , New Haven , CT , USA
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42
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Howsmon DP, Vargason T, Rubin RA, Delhey L, Tippett M, Rose S, Bennuri SC, Slattery JC, Melnyk S, James SJ, Frye RE, Hahn J. Multivariate techniques enable a biochemical classification of children with autism spectrum disorder versus typically-developing peers: A comparison and validation study. Bioeng Transl Med 2018; 3:156-165. [PMID: 30065970 PMCID: PMC6063877 DOI: 10.1002/btm2.10095] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2018] [Revised: 05/10/2018] [Accepted: 05/10/2018] [Indexed: 01/05/2023] Open
Abstract
Autism spectrum disorder (ASD) is a developmental disorder which is currently only diagnosed through behavioral testing. Impaired folate‐dependent one carbon metabolism (FOCM) and transsulfuration (TS) pathways have been implicated in ASD, and recently a study involving multivariate analysis based upon Fisher Discriminant Analysis returned very promising results for predicting an ASD diagnosis. This article takes another step toward the goal of developing a biochemical diagnostic for ASD by comparing five classification algorithms on existing data of FOCM/TS metabolites, and also validating the classification results with new data from an ASD cohort. The comparison results indicate a high sensitivity and specificity for the original data set and up to a 88% correct classification of the ASD cohort at an expected 5% misclassification rate for typically‐developing controls. These results form the foundation for the development of a biochemical test for ASD which promises to aid diagnosis of ASD and provide biochemical understanding of the disease, applicable to at least a subset of the ASD population.
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Affiliation(s)
- Daniel P Howsmon
- Dept. of Chemical & Biological Engineering Rensselaer Polytechnic Institute Troy NY 12180.,Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute Troy NY 12180
| | - Troy Vargason
- Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute Troy NY 12180.,Dept. of Biomedical Engineering Rensselaer Polytechnic Institute Troy NY 12180
| | | | - Leanna Delhey
- Arkansas Children's Research Institute Little Rock AR 72202.,Dept. of Pediatrics University of Arkansas for Medical Sciences Little Rock AR 72205
| | - Marie Tippett
- Arkansas Children's Research Institute Little Rock AR 72202.,Dept. of Pediatrics University of Arkansas for Medical Sciences Little Rock AR 72205
| | - Shannon Rose
- Arkansas Children's Research Institute Little Rock AR 72202.,Dept. of Pediatrics University of Arkansas for Medical Sciences Little Rock AR 72205
| | - Sirish C Bennuri
- Arkansas Children's Research Institute Little Rock AR 72202.,Dept. of Pediatrics University of Arkansas for Medical Sciences Little Rock AR 72205
| | - John C Slattery
- Dept. of Pediatrics University of Arkansas for Medical Sciences Little Rock AR 72205
| | - Stepan Melnyk
- Dept. of Pediatrics University of Arkansas for Medical Sciences Little Rock AR 72205
| | - S Jill James
- Dept. of Pediatrics University of Arkansas for Medical Sciences Little Rock AR 72205
| | - Richard E Frye
- Barrow Neurological Institute at Phoenix Children's Hospital, Phoenix, AZ 85013 and University of Arizona College of Medicine Phoenix AZ 85004
| | - Juergen Hahn
- Dept. of Chemical & Biological Engineering Rensselaer Polytechnic Institute Troy NY 12180.,Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute Troy NY 12180.,Dept. of Biomedical Engineering Rensselaer Polytechnic Institute Troy NY 12180
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43
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Bednarz HM, Kana RK. Advances, challenges, and promises in pediatric neuroimaging of neurodevelopmental disorders. Neurosci Biobehav Rev 2018; 90:50-69. [PMID: 29608989 DOI: 10.1016/j.neubiorev.2018.03.025] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2017] [Revised: 02/26/2018] [Accepted: 03/22/2018] [Indexed: 10/17/2022]
Abstract
Recent years have witnessed the proliferation of neuroimaging studies of neurodevelopmental disorders (NDDs), particularly of children with autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), and Tourette's syndrome (TS). Neuroimaging offers immense potential in understanding the biology of these disorders, and how it relates to clinical symptoms. Neuroimaging techniques, in the long run, may help identify neurobiological markers to assist clinical diagnosis and treatment. However, methodological challenges have affected the progress of clinical neuroimaging. This paper reviews the methodological challenges involved in imaging children with NDDs. Specific topics include correcting for head motion, normalization using pediatric brain templates, accounting for psychotropic medication use, delineating complex developmental trajectories, and overcoming smaller sample sizes. The potential of neuroimaging-based biomarkers and the utility of implementing neuroimaging in a clinical setting are also discussed. Data-sharing approaches, technological advances, and an increase in the number of longitudinal, prospective studies are recommended as future directions. Significant advances have been made already, and future decades will continue to see innovative progress in neuroimaging research endeavors of NDDs.
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Affiliation(s)
- Haley M Bednarz
- Department of Psychology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Rajesh K Kana
- Department of Psychology, University of Alabama at Birmingham, Birmingham, AL, USA.
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44
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Howsmon DP, Adams JB, Kruger U, Geis E, Gehn E, Hahn J. Erythrocyte fatty acid profiles in children are not predictive of autism spectrum disorder status: a case control study. Biomark Res 2018; 6:12. [PMID: 29568526 PMCID: PMC5853097 DOI: 10.1186/s40364-018-0125-z] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2017] [Accepted: 02/27/2018] [Indexed: 01/27/2023] Open
Abstract
Biomarkers promise biomolecular explanations as well as reliable diagnostics, stratification, and treatment strategies that have the potential to help mitigate the effects of disorders. While no reliable biomarker has yet been found for autism spectrum disorder (ASD), fatty acids have been investigated as potential biomarkers because of their association with brain development and neural functions. However, the ability of fatty acids to classify individuals with ASD from age/gender-matched neurotypical (NEU) peers has largely been ignored in favor of investigating population-level differences. Contrary to existing work, this classification task between ASD and NEU cohorts is the main focus of this work. The data presented herein suggest that fatty acids do not allow for classification at the individual level.
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Affiliation(s)
- Daniel P Howsmon
- 1Department of Chemical & Biological Engineering, Rensselaer Polytechnic Institute, 110 Eighth Street, Troy, 12180 NY USA.,2Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, 110 Eighth Street, Troy, 12180 NY USA.,5Willerson Center for Cardiovascular Modeling and Simulation, Institute for Computational Engineering and Sciences, University of Texas at Austin, Austin, 78712 TX USA
| | - James B Adams
- 3School for Engineering of Matter, Transport, and Energy, Arizona State University, PO Box: 876106, Tempe, 85281 AZ USA
| | - Uwe Kruger
- 4Department of Biomedical Engineering, Rensselaer Polytechnic Institute, 110 Eighth Street, Troy, 12180 NY USA
| | - Elizabeth Geis
- 3School for Engineering of Matter, Transport, and Energy, Arizona State University, PO Box: 876106, Tempe, 85281 AZ USA
| | - Eva Gehn
- 3School for Engineering of Matter, Transport, and Energy, Arizona State University, PO Box: 876106, Tempe, 85281 AZ USA
| | - Juergen Hahn
- 1Department of Chemical & Biological Engineering, Rensselaer Polytechnic Institute, 110 Eighth Street, Troy, 12180 NY USA.,2Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, 110 Eighth Street, Troy, 12180 NY USA.,4Department of Biomedical Engineering, Rensselaer Polytechnic Institute, 110 Eighth Street, Troy, 12180 NY USA
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Key AP. Psychophysiological biomarkers: Working around behavioral response limitations. Dev Neuropsychol 2018; 43:107-108. [PMID: 29384396 DOI: 10.1080/87565641.2018.1430803] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Affiliation(s)
- Alexandra P Key
- a Kennedy Center for Research on Human Development, Department of Hearing and Speech Sciences , Vanderbilt University Medical Center , Nashville , Tennessee , USA
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Foss-Feig JH, Stavropoulos KKM, McPartland JC, Wallace MT, Stone WL, Key AP. Electrophysiological response during auditory gap detection: Biomarker for sensory and communication alterations in autism spectrum disorder? Dev Neuropsychol 2018; 43:109-122. [PMID: 29436853 PMCID: PMC5972824 DOI: 10.1080/87565641.2017.1365869] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
Sensory symptoms, including auditory processing deficits, are common in autism spectrum disorder (ASD). Processing of temporal aspects of auditory input is understudied; yet, deficits in this domain could contribute to language-related impairments. In children with ASD and well-matched controls, this study examined electrophysiological response to silent gaps in auditory stimuli. Results revealed attenuated amplitude of the P2 event-related potential (ERP) component in ASD. The P2 amplitude reduction was also associated with sensory, language, and diagnostic features. These results suggest that neural response during auditory gap detection is a promising ASD biomarker that could be useful for stratifying subgroups and evaluating treatment response.
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Affiliation(s)
- Jennifer H Foss-Feig
- a Department of Psychiatry , Icahn School of Medicine at Mount Sinai Hospital , One Gustave Levy Place, New York , New York
- b Seaver Autism Center , Icahn School of Medicine at Mount Sinai Hospital , One Gustave Levy Place, New York , New York
| | | | - James C McPartland
- d Child Study Center , Yale University School of Medicine , New Haven , Connecticut
- e Department of Psychology , Yale University , New Haven , Connecticut
| | - Mark T Wallace
- f Department of Hearing and Speech Sciences , Vanderbilt University Medical Center , Nashville , Tennessee
- g Kennedy Center , Vanderbilt University Medical Center , Nashville , Tennessee
- h Department of Psychology , Vanderbilt University , Nashville , Tennessee
| | - Wendy L Stone
- i Department of Psychology , University of Washington , Seattle , Washington
| | - Alexandra P Key
- f Department of Hearing and Speech Sciences , Vanderbilt University Medical Center , Nashville , Tennessee
- g Kennedy Center , Vanderbilt University Medical Center , Nashville , Tennessee
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Abstract
Despite significant advances in understanding the biological bases of autism spectrum disorder (ASD), the field remains primarily reliant on observational and parent report measures of behavior to guide clinical practice, conduct research, and evaluate intervention outcomes. There is a critical need for objective measures to more sensitively and validly quantify risk for ASD, ASD symptomatology, and its change in clinical trials. To maximize public health impact, such biomarkers must be cost effective and utilize accessible and scalable technologies. This letter describes concerns specific to the development of clinically practicable biomarkers for ASD and approaches to optimize understanding of these biomarkers through development of large-scale consortia and clinical networks.
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Affiliation(s)
- James C McPartland
- Yale Child Study Center, 230 South Frontage Road, New Haven, CT, 06520, USA.
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Loth E, Charman T, Mason L, Tillmann J, Jones EJH, Wooldridge C, Ahmad J, Auyeung B, Brogna C, Ambrosino S, Banaschewski T, Baron-Cohen S, Baumeister S, Beckmann C, Brammer M, Brandeis D, Bölte S, Bourgeron T, Bours C, de Bruijn Y, Chakrabarti B, Crawley D, Cornelissen I, Acqua FD, Dumas G, Durston S, Ecker C, Faulkner J, Frouin V, Garces P, Goyard D, Hayward H, Ham LM, Hipp J, Holt RJ, Johnson MH, Isaksson J, Kundu P, Lai MC, D’ardhuy XL, Lombardo MV, Lythgoe DJ, Mandl R, Meyer-Lindenberg A, Moessnang C, Mueller N, O’Dwyer L, Oldehinkel M, Oranje B, Pandina G, Persico AM, Ruigrok ANV, Ruggeri B, Sabet J, Sacco R, Cáceres ASJ, Simonoff E, Toro R, Tost H, Waldman J, Williams SCR, Zwiers MP, Spooren W, Murphy DGM, Buitelaar JK. The EU-AIMS Longitudinal European Autism Project (LEAP): design and methodologies to identify and validate stratification biomarkers for autism spectrum disorders. Mol Autism 2017; 8:24. [PMID: 28649312 PMCID: PMC5481887 DOI: 10.1186/s13229-017-0146-8] [Citation(s) in RCA: 147] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2016] [Accepted: 05/19/2017] [Indexed: 01/05/2023] Open
Abstract
BACKGROUND The tremendous clinical and aetiological diversity among individuals with autism spectrum disorder (ASD) has been a major obstacle to the development of new treatments, as many may only be effective in particular subgroups. Precision medicine approaches aim to overcome this challenge by combining pathophysiologically based treatments with stratification biomarkers that predict which treatment may be most beneficial for particular individuals. However, so far, we have no single validated stratification biomarker for ASD. This may be due to the fact that most research studies primarily have focused on the identification of mean case-control differences, rather than within-group variability, and included small samples that were underpowered for stratification approaches. The EU-AIMS Longitudinal European Autism Project (LEAP) is to date the largest multi-centre, multi-disciplinary observational study worldwide that aims to identify and validate stratification biomarkers for ASD. METHODS LEAP includes 437 children and adults with ASD and 300 individuals with typical development or mild intellectual disability. Using an accelerated longitudinal design, each participant is comprehensively characterised in terms of clinical symptoms, comorbidities, functional outcomes, neurocognitive profile, brain structure and function, biochemical markers and genomics. In addition, 51 twin-pairs (of which 36 had one sibling with ASD) are included to identify genetic and environmental factors in phenotypic variability. RESULTS Here, we describe the demographic characteristics of the cohort, planned analytic stratification approaches, criteria and steps to validate candidate stratification markers, pre-registration procedures to increase transparency, standardisation and data robustness across all analyses, and share some 'lessons learnt'. A clinical characterisation of the cohort is given in the companion paper (Charman et al., accepted). CONCLUSION We expect that LEAP will enable us to confirm, reject and refine current hypotheses of neurocognitive/neurobiological abnormalities, identify biologically and clinically meaningful ASD subgroups, and help us map phenotypic heterogeneity to different aetiologies.
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Affiliation(s)
- Eva Loth
- Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, De Crespigny Park, Denmark Hill, London, SE5 8AF UK
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, De Crespigny Park, Denmark Hill, London, SE5 8AF UK
| | - Tony Charman
- Clinical Child Psychology, Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, De Crespigny Park, Denmark Hill, London, SE5 8AF UK
| | - Luke Mason
- Centre for Brain and Cognitive Development, Birkbeck, University of London, Henry Wellcome Building, Malet Street, London, WC1E 7HX UK
| | - Julian Tillmann
- Clinical Child Psychology, Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, De Crespigny Park, Denmark Hill, London, SE5 8AF UK
| | - Emily J. H. Jones
- Centre for Brain and Cognitive Development, Birkbeck, University of London, Henry Wellcome Building, Malet Street, London, WC1E 7HX UK
| | - Caroline Wooldridge
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, De Crespigny Park, Denmark Hill, London, SE5 8AF UK
| | - Jumana Ahmad
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, De Crespigny Park, Denmark Hill, London, SE5 8AF UK
| | - Bonnie Auyeung
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Douglas House, 18b Trumpington Road, Cambridge, CB2 8AH UK
- Department of Psychology, The School of Philosophy, Psychology, and Language Sciences, University of Edinburgh, Dugald Stewart Building, 3 Charles Street, Edinburgh, EH8 9AD UK
| | - Claudia Brogna
- University Campus Bio-Medico, via Álvaro del Portillo, 21, Rome, Italy
| | - Sara Ambrosino
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Universiteitsweg 100, 3584 CG Utrecht, The Netherlands
| | - Tobias Banaschewski
- Child and Adolescent Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, J5, 68159 Mannheim, Germany
| | - Simon Baron-Cohen
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Douglas House, 18b Trumpington Road, Cambridge, CB2 8AH UK
| | - Sarah Baumeister
- Child and Adolescent Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, J5, 68159 Mannheim, Germany
| | - Christian Beckmann
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Kapittelweg 29, 6525 EN Nijmegen, The Netherlands
| | - Michael Brammer
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, De Crespigny Park, Denmark Hill, London, SE5 8AF UK
| | - Daniel Brandeis
- Child and Adolescent Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, J5, 68159 Mannheim, Germany
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric Hospital, University of Zürich, Neumünsterallee 9, 8032 Zürich, Switzerland
| | - Sven Bölte
- Center for Neurodevelopmental Disorders at Karolinska Institutet (KIND), Stockholm, Sweden
| | - Thomas Bourgeron
- Human Genetics and Cognitive Functions Unit, Institut Pasteur, 25 Rue du Docteur Roux, Paris, Cedex 15 France
| | - Carsten Bours
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Kapittelweg 29, 6525 EN Nijmegen, The Netherlands
| | - Yvette de Bruijn
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Kapittelweg 29, 6525 EN Nijmegen, The Netherlands
| | - Bhismadev Chakrabarti
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Douglas House, 18b Trumpington Road, Cambridge, CB2 8AH UK
- Centre for Autism, School of Psychology and Clinical Language Sciences, University of Reading, Whiteknights, Reading, RG6 6AL UK
| | - Daisy Crawley
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, De Crespigny Park, Denmark Hill, London, SE5 8AF UK
| | - Ineke Cornelissen
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Kapittelweg 29, 6525 EN Nijmegen, The Netherlands
| | - Flavio Dell’ Acqua
- Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, De Crespigny Park, Denmark Hill, London, SE5 8AF UK
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, De Crespigny Park, Denmark Hill, London, SE5 8AF UK
| | - Guillaume Dumas
- Human Genetics and Cognitive Functions Unit, Institut Pasteur, 25 Rue du Docteur Roux, Paris, Cedex 15 France
| | - Sarah Durston
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Universiteitsweg 100, 3584 CG Utrecht, The Netherlands
| | - Christine Ecker
- Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, De Crespigny Park, Denmark Hill, London, SE5 8AF UK
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Frankfurt am Main, Goethe University, Deutschordenstrasse 50, 60528 Frankfurt, Germany
| | - Jessica Faulkner
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, De Crespigny Park, Denmark Hill, London, SE5 8AF UK
| | - Vincent Frouin
- Neurospin Centre CEA, Saclay, 91191 Gif sur Yvette, France
| | - Pilar Garces
- Roche Pharma Research and Early Development, Neuroscience, Ophthalmology and Rare Diseases, Roche Innovation Center Basel, Grenzacherstrasse 124, B.001 N.667, CH-4070 Basel, Switzerland
| | - David Goyard
- Neurospin Centre CEA, Saclay, 91191 Gif sur Yvette, France
| | - Hannah Hayward
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, De Crespigny Park, Denmark Hill, London, SE5 8AF UK
| | - Lindsay M. Ham
- Regulatory Affairs, Product Development, F. Hoffmann-La Roche Pharmaceuticals, Grenzacherstrasse 124, CH-4070 Basel, Switzerland
| | - Joerg Hipp
- Roche Pharma Research and Early Development, Neuroscience, Ophthalmology and Rare Diseases, Roche Innovation Center Basel, Grenzacherstrasse 124, B.001 N.667, CH-4070 Basel, Switzerland
| | - Rosemary J. Holt
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Douglas House, 18b Trumpington Road, Cambridge, CB2 8AH UK
| | - Mark H. Johnson
- Centre for Brain and Cognitive Development, Birkbeck, University of London, Henry Wellcome Building, Malet Street, London, WC1E 7HX UK
| | - Johan Isaksson
- Center for Neurodevelopmental Disorders at Karolinska Institutet (KIND), Stockholm, Sweden
- Department of Neuroscience, Uppsala University, Uppsala, Sweden
| | - Prantik Kundu
- Department of Radiology, Icahn School of Medicine at Mount Sinai, NY, USA
| | - Meng-Chuan Lai
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Douglas House, 18b Trumpington Road, Cambridge, CB2 8AH UK
- Child and Youth Mental Health Collaborative, Centre for Addiction and Mental Health and The Hospital for Sick Children, Department of Psychiatry, University of Toronto, 80, Workman Way, Toronto, ON M6J 1H4 Canada
| | - Xavier Liogier D’ardhuy
- Roche Pharma Research and Early Development, Neuroscience, Ophthalmology and Rare Diseases, Roche Innovation Center Basel, Grenzacherstrasse 124, B.001 N.667, CH-4070 Basel, Switzerland
| | - Michael V. Lombardo
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Douglas House, 18b Trumpington Road, Cambridge, CB2 8AH UK
- Center for Applied Neuroscience, Department of Psychology, University of Cyprus, PO Box 20537, 1678 Nicosia, Cyprus
| | - David J. Lythgoe
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, De Crespigny Park, Denmark Hill, London, SE5 8AF UK
| | - René Mandl
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Universiteitsweg 100, 3584 CG Utrecht, The Netherlands
| | - Andreas Meyer-Lindenberg
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, 68159 Mannheim, Germany
| | - Carolin Moessnang
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, 68159 Mannheim, Germany
| | - Nico Mueller
- Child and Adolescent Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, J5, 68159 Mannheim, Germany
| | - Laurence O’Dwyer
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Kapittelweg 29, 6525 EN Nijmegen, The Netherlands
| | - Marianne Oldehinkel
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Kapittelweg 29, 6525 EN Nijmegen, The Netherlands
| | - Bob Oranje
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Universiteitsweg 100, 3584 CG Utrecht, The Netherlands
| | - Gahan Pandina
- Janssen Research & Development, 1125 Trenton Harbourton Road, Titusville, NJ 08560 USA
| | - Antonio M. Persico
- University Campus Bio-Medico, via Álvaro del Portillo, 21, Rome, Italy
- Child and Adolescent Neuropsychiatry Unit, Gaetano Martino University Hospital, University of Messina, Via Consolare Valeria 1, I-98125 Messina, Italy
| | - Amber N. V. Ruigrok
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Douglas House, 18b Trumpington Road, Cambridge, CB2 8AH UK
| | - Barbara Ruggeri
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, Denmark Hill, London, UK
| | - Jessica Sabet
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, De Crespigny Park, Denmark Hill, London, SE5 8AF UK
| | - Roberto Sacco
- University Campus Bio-Medico, via Álvaro del Portillo, 21, Rome, Italy
| | - Antonia San José Cáceres
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, De Crespigny Park, Denmark Hill, London, SE5 8AF UK
| | - Emily Simonoff
- Department of Child and Adolescent Psychiatry, Institute of Psychology, Psychiatry and Neuroscience, King’s College London, De Crespigny Park, Denmark Hill, London, SE5 8AF UK
| | - Roberto Toro
- Human Genetics and Cognitive Functions Unit, Institut Pasteur, 25 Rue du Docteur Roux, Paris, Cedex 15 France
| | - Heike Tost
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, 68159 Mannheim, Germany
| | - Jack Waldman
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Douglas House, 18b Trumpington Road, Cambridge, CB2 8AH UK
| | - Steve C. R. Williams
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, De Crespigny Park, Denmark Hill, London, SE5 8AF UK
| | - Marcel P. Zwiers
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Kapittelweg 29, 6525 EN Nijmegen, The Netherlands
| | - Will Spooren
- Roche Pharma Research and Early Development, Neuroscience, Ophthalmology and Rare Diseases, Roche Innovation Center Basel, Grenzacherstrasse 124, B.001 N.667, CH-4070 Basel, Switzerland
| | - Declan G. M. Murphy
- Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, De Crespigny Park, Denmark Hill, London, SE5 8AF UK
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, De Crespigny Park, Denmark Hill, London, SE5 8AF UK
| | - Jan K. Buitelaar
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Kapittelweg 29, 6525 EN Nijmegen, The Netherlands
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Dhamne SC, Silverman JL, Super CE, Lammers SHT, Hameed MQ, Modi ME, Copping NA, Pride MC, Smith DG, Rotenberg A, Crawley JN, Sahin M. Replicable in vivo physiological and behavioral phenotypes of the Shank3B null mutant mouse model of autism. Mol Autism 2017. [PMID: 28638591 PMCID: PMC5472997 DOI: 10.1186/s13229-017-0142-z] [Citation(s) in RCA: 103] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND Autism spectrum disorder (ASD) is a clinically and biologically heterogeneous condition characterized by social, repetitive, and sensory behavioral abnormalities. No treatments are approved for the core diagnostic symptoms of ASD. To enable the earliest stages of therapeutic discovery and development for ASD, robust and reproducible behavioral phenotypes and biological markers are essential to establish in preclinical animal models. The goal of this study was to identify electroencephalographic (EEG) and behavioral phenotypes that are replicable between independent cohorts in a mouse model of ASD. The larger goal of our strategy is to empower the preclinical biomedical ASD research field by generating robust and reproducible behavioral and physiological phenotypes in animal models of ASD, for the characterization of mechanistic underpinnings of ASD-relevant phenotypes, and to ensure reliability for the discovery of novel therapeutics. Genetic disruption of the SHANK3 gene, a scaffolding protein involved in the stability of the postsynaptic density in excitatory synapses, is thought to be responsible for a relatively large number of cases of ASD. Therefore, we have thoroughly characterized the robustness of ASD-relevant behavioral phenotypes in two cohorts, and for the first time quantified translational EEG activity in Shank3B null mutant mice. METHODS In vivo physiology and behavioral assays were conducted in two independently bred and tested full cohorts of Shank3B null mutant (Shank3B KO) and wildtype littermate control (WT) mice. EEG was recorded via wireless implanted telemeters for 7 days of baseline followed by 20 min of recording following pentylenetetrazol (PTZ) challenge. Behaviors relevant to the diagnostic and associated symptoms of ASD were tested on a battery of established behavioral tests. Assays were designed to reproduce and expand on the original behavioral characterization of Shank3B KO mice. Two or more corroborative tests were conducted within each behavioral domain, including social, repetitive, cognitive, anxiety-related, sensory, and motor categories of assays. RESULTS Relative to WT mice, Shank3B KO mice displayed a dramatic resistance to PTZ seizure induction and an enhancement of gamma band oscillatory EEG activity indicative of enhanced inhibitory tone. These findings replicated in two separate cohorts. Behaviorally, Shank3B KO mice exhibited repetitive grooming, deficits in aspects of reciprocal social interactions and vocalizations, and reduced open field activity, as well as variable deficits in sensory responses, anxiety-related behaviors, learning and memory. CONCLUSIONS Robust animal models and quantitative, replicable biomarkers of neural dysfunction are needed to decrease risk and enable successful drug discovery and development for ASD and other neurodevelopmental disorders. Complementary to the replicated behavioral phenotypes of the Shank3B mutant mouse is the new identification of a robust, translational in vivo neurophysiological phenotype. Our findings provide strong evidence for robustness and replicability of key translational phenotypes in Shank3B mutant mice and support the usefulness of this mouse model of ASD for therapeutic discovery.
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Affiliation(s)
- Sameer C Dhamne
- F.M. Kirby Neurobiology Center, Translational Neuroscience Center, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115 USA
| | - Jill L Silverman
- MIND Institute, Department of Psychiatry and Behavioral Sciences, University of California Davis School of Medicine, Sacramento, CA 95821 USA
| | - Chloe E Super
- F.M. Kirby Neurobiology Center, Translational Neuroscience Center, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115 USA
| | - Stephen H T Lammers
- F.M. Kirby Neurobiology Center, Translational Neuroscience Center, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115 USA
| | - Mustafa Q Hameed
- F.M. Kirby Neurobiology Center, Translational Neuroscience Center, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115 USA
| | - Meera E Modi
- F.M. Kirby Neurobiology Center, Translational Neuroscience Center, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115 USA
| | - Nycole A Copping
- MIND Institute, Department of Psychiatry and Behavioral Sciences, University of California Davis School of Medicine, Sacramento, CA 95821 USA
| | - Michael C Pride
- MIND Institute, Department of Psychiatry and Behavioral Sciences, University of California Davis School of Medicine, Sacramento, CA 95821 USA
| | - Daniel G Smith
- Autism Speaks, Inc., Boston, MA USA.,Present address: BlackThorn Therapeutics, Inc., Cambridge, MA USA
| | - Alexander Rotenberg
- F.M. Kirby Neurobiology Center, Translational Neuroscience Center, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115 USA
| | - Jacqueline N Crawley
- MIND Institute, Department of Psychiatry and Behavioral Sciences, University of California Davis School of Medicine, Sacramento, CA 95821 USA
| | - Mustafa Sahin
- F.M. Kirby Neurobiology Center, Translational Neuroscience Center, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115 USA
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50
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Arbaclofen in Children and Adolescents with Autism Spectrum Disorder: A Randomized, Controlled, Phase 2 Trial. Neuropsychopharmacology 2017; 42:1390-1398. [PMID: 27748740 PMCID: PMC5436109 DOI: 10.1038/npp.2016.237] [Citation(s) in RCA: 92] [Impact Index Per Article: 13.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/26/2016] [Revised: 10/05/2016] [Accepted: 10/12/2016] [Indexed: 12/11/2022]
Abstract
Several lines of emerging data point to an imbalance between neuronal excitation and inhibition in at least a subgroup of individuals with autism spectrum disorder (ASD), including in those with fragile X syndrome (FXS), one of the most common genetic syndromes within ASD. In animal models of FXS and of ASD, GABA-B agonists have improved both brain and behavioral phenotypes, including social behavior. A phase 2 randomized, placebo-controlled, crossover trial found that the GABA-B agonist arbaclofen improved social avoidance symptoms in FXS. A pilot open-label trial of arbaclofen suggested similar benefits in ASD. We therefore evaluated arbaclofen in a randomized, placebo-controlled, phase 2 study of 150 participants, aged 5-21 years, with ASD. No difference from placebo was detected on the primary outcome measure, the parent-rated Aberrant Behavior Checklist Social Withdrawal/Lethargy subscale. However, a specified secondary analysis found improvement on the clinician-rated Clinical Global Impression of Severity. An exploratory post hoc analysis of participants with a consistent rater across the trial revealed greater improvement in the Vineland Adaptive Behavior Scales II socialization domain in participants receiving arbaclofen. Affect lability (11%) and sedation (9%) were the most common adverse events. In this exploratory study, secondary analyses suggest that arbaclofen may have the potential to improve symptoms in some children with ASD, but further study will be needed to replicate and extend these initial findings.
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