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Dakopolos A, Glassman D, Scott H, Bass M, Hessl D. iBehavior-a preliminary proof of concept study of a smartphone-based tool for the assessment of behavior change in neurodevelopmental disabilities. Front Psychol 2023; 14:1217821. [PMID: 37920743 PMCID: PMC10619652 DOI: 10.3389/fpsyg.2023.1217821] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Accepted: 10/04/2023] [Indexed: 11/04/2023] Open
Abstract
Purpose The purpose of the present study was to describe the content and function of iBehavior, a smartphone-based caregiver-report electronic ecological momentary assessment (eEMA) tool developed to assess and track behavior change in people with intellectual and developmental disabilities (IDDs), and to examine its preliminary validity. Methods Ten parents of children (ages of 5-17 years) with IDDs (n = 7 with fragile X syndrome; n = 3 with Down syndrome) rated their child's behavior (aggression and irritability, avoidant and fearful behavior, restricted and repetitive behavior and interests, and social initiation) using iBehavior once daily for 14 days. At the conclusion of the 14-day observation period, parents completed traditional rating scales as validation measures, as well as a user feedback survey. Results Across the 140 possible observations, 8 were skipped, leading to a 94% response rate over 10 participants' observation periods. Participants also completed 100% of items for each of their logged observations. Parent ratings using iBehavior showed emerging evidence of convergent validity among domains with traditional rating scales including the Behavior Rating Inventory of Executive Function 2 (BRIEF-2), and Aberrant Behavior Checklist-Community (ABC-C). iBehavior was feasible in the sample, and parent feedback indicated high overall satisfaction. Conclusion Results of the present pilot study indicate successful implementation and preliminary feasibility and validity of an eEMA tool for use as a behavioral outcome measure in IDDs.
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Affiliation(s)
- Andrew Dakopolos
- MIND Institute, University of California Davis Health, Sacramento, CA, United States
- Department of Psychiatry and Behavioral Sciences, University of California Davis School of Medicine, Sacramento, CA, United States
| | - Dana Glassman
- MIND Institute, University of California Davis Health, Sacramento, CA, United States
- Department of Psychiatry and Behavioral Sciences, University of California Davis School of Medicine, Sacramento, CA, United States
| | - Haleigh Scott
- Department of Psychiatry and Behavioral Sciences, UC Davis MIND Institute, Sacramento, CA, United States
| | - Michael Bass
- Fienberg School of Medicine, Northwestern University, Chicago, IL, United States
| | - David Hessl
- MIND Institute, University of California Davis Health, Sacramento, CA, United States
- Department of Psychiatry and Behavioral Sciences, University of California Davis School of Medicine, Sacramento, CA, United States
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Wathen JK, Jagannatha S, Ness S, Bangerter A, Pandina G. A platform trial approach to proof-of-concept (POC) studies in autism spectrum disorder: Autism spectrum POC initiative (ASPI). Contemp Clin Trials Commun 2023; 32:101061. [PMID: 36949847 PMCID: PMC10025278 DOI: 10.1016/j.conctc.2023.101061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Revised: 11/29/2022] [Accepted: 01/14/2023] [Indexed: 01/18/2023] Open
Abstract
Background Over the past decade, autism spectrum disorder (ASD) research has blossomed, and multiple clinical trials have tested potential interventions, with varying results and no clear demonstration of efficacy. Lack of clarity concerning appropriate biological mechanisms to target and lack of sensitive, objective tools to identify subgroups and measure symptom changes have hampered the efforts to develop treatments. A platform trial for proof-of-concept studies in ASD could help address these issues. A major goal of a platform trial is to find the best treatment in the most expeditious manner, by simultaneously investigating multiple treatments, using specialized statistical tools for allocation and analysis. We describe the setup of a platform trial and perform simulations to evaluate the operating characteristics under several scenarios. We use the Autism Behavior Inventory (ABI), a psychometrically validated web-based rating scale to measure the change in ASD core and associated symptoms. Methods Detailed description of the setup, conduct, and decision-making rules of a platform trial are explained. Simulations of a virtual platform trial for several scenarios are performed to compare operating characteristics. The success and futility criteria for treatments are based on a Bayesian posterior probability model. Results Overall, simulation results show the potential gain in terms of statistical properties especially for improved decision-making ability, while careful planning is needed due to the complexities of a platform trial. Conclusions Autism research, shaped particularly by its heterogeneity, may benefit from the platform trial approach for POC clinical studies.
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Affiliation(s)
| | - Shyla Jagannatha
- Corresponding author. Janssen Research & Development, LLC 1125 Trenton-Harbourton Road Titusville NJ 08560, USA.
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Qiu M, Li Y, Na K, Qi Z, Ma S, Zhou H, Xu X, Li J, Xu K, Wang X, Han Y. A Novel Multiple Risk Score Model for Prediction of Long-Term Ischemic Risk in Patients With Coronary Artery Disease Undergoing Percutaneous Coronary Intervention: Insights From the I-LOVE-IT 2 Trial. Front Cardiovasc Med 2022; 8:756379. [PMID: 35096990 PMCID: PMC8793781 DOI: 10.3389/fcvm.2021.756379] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Accepted: 12/06/2021] [Indexed: 11/13/2022] Open
Abstract
Backgrounds: A plug-and-play standardized algorithm to identify the ischemic risk in patients with coronary artery disease (CAD) undergoing percutaneous coronary intervention (PCI) could play a valuable step to help a wide spectrum of clinic workers. This study intended to investigate the ability to use the accumulation of multiple clinical routine risk scores to predict long-term ischemic events in patients with CAD undergoing PCI.Methods: This was a secondary analysis of the I-LOVE-IT 2 (Evaluate Safety and Effectiveness of the Tivoli drug-eluting stent (DES) and the Firebird DES for Treatment of Coronary Revascularization) trial, which was a prospective, multicenter, and randomized study. The Global Registry for Acute Coronary Events (GRACE), baseline Synergy Between Percutaneous Coronary Intervention with Taxus and Cardiac Surgery (SYNTAX), residual SYNTAX, and age, creatinine, and ejection fraction (ACEF) score were calculated in all patients. Risk stratification was based on the number of these four scores that met the established thresholds for the ischemic risk. The primary end point was ischemic events at 48 months, defined as the composite of cardiac death, nonfatal myocardial infarction, stroke, or definite/probable stent thrombosis (ST).Results: The 48-month ischemic events had a significant trend for higher event rates (from 6.61 to 16.93%) with an incremental number of risk scores presenting the higher ischemic risk from 0 to ≥3 (p trend < 0.001). In addition, the categories were associated with increased risk for all components of ischemic events, including cardiac death (from 1.36 to 3.15%), myocardial infarction (MI) (from 3.31 to 9.84%), stroke (3.31 to 6.10%), definite/probable ST (from 0.58 to 1.97%), and all-cause mortality (from 2.14 to 6.30%) (all p trend < 0.05). The net reclassification index after combined with four risk scores was 12.5% (5.3–20.0%), 9.4% (2.0–16.8%), 12.1% (4.5–19.7%), and 10.7% (3.3–18.1%), which offered statistically significant improvement in the performance, compared with SYNTAX, residual SYNTAX, ACEF, and GRACE score, respectively.Conclusion: The novel multiple risk score model was significantly associated with the risk of long-term ischemic events in these patients with an increment of scores. A meaningful improvement to predict adverse outcomes when multiple risk scores were applied to risk stratification.
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Affiliation(s)
- Miaohan Qiu
- Second Affiliated Hospital of Dalian Medical University, Dalian, China
- The Department of Cardiology, General Hospital of Northern Theater Command, Shenyang, China
| | - Yi Li
- The Department of Cardiology, General Hospital of Northern Theater Command, Shenyang, China
| | - Kun Na
- The Department of Cardiology, General Hospital of Northern Theater Command, Shenyang, China
- Postgraduate College, Shenyang Pharmaceutical University, Shenyang, China
| | - Zizhao Qi
- The Department of Cardiology, General Hospital of Northern Theater Command, Shenyang, China
- Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Sicong Ma
- The Department of Cardiology, General Hospital of Northern Theater Command, Shenyang, China
- The Second Hospital of Jilin University, Changchun, China
| | - He Zhou
- The Department of Cardiology, General Hospital of Northern Theater Command, Shenyang, China
- Postgraduate College, Liaoning University of Traditional Chinese Medicine, Shenyang, China
| | - Xiaoming Xu
- The Department of Cardiology, General Hospital of Northern Theater Command, Shenyang, China
| | - Jing Li
- The Department of Cardiology, General Hospital of Northern Theater Command, Shenyang, China
- Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Kai Xu
- The Department of Cardiology, General Hospital of Northern Theater Command, Shenyang, China
| | - Xiaozeng Wang
- The Department of Cardiology, General Hospital of Northern Theater Command, Shenyang, China
| | - Yaling Han
- The Department of Cardiology, General Hospital of Northern Theater Command, Shenyang, China
- *Correspondence: Yaling Han
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Park Y, Go TH, Hong SH, Kim SH, Han JH, Kang Y, Kang DR. Digital Biomarkers in Living Labs for Vulnerable and Susceptible Individuals: An Integrative Literature Review. Yonsei Med J 2022; 63:S43-S55. [PMID: 35040605 PMCID: PMC8790590 DOI: 10.3349/ymj.2022.63.s43] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 10/26/2021] [Accepted: 10/27/2021] [Indexed: 11/27/2022] Open
Abstract
PURPOSE The study aimed to identify which digital biomarkers are collected and which specific devices are used according to vulnerable and susceptible individual characteristics in a living-lab setting. MATERIALS AND METHODS A literature search, screening, and appraisal process was implemented using the Web of Science, Pubmed, and Embase databases. The search query included a combination of terms related to "digital biomarkers," "devices that collect digital biomarkers," and "vulnerable and susceptible groups." After the screening and appraisal process, a total of 37 relevant articles were obtained. RESULTS In elderly people, the main digital biomarkers measured were values related to physical activity. Most of the studies used sensors. The articles targeting children aimed to predict diseases, and most of them used devices that are simple and can induce some interest, such as wearable device-based smart toys. In those who were disabled, digital biomarkers that measured location-based movement for the purpose of diagnosing disabilities were widely used, and most were measured by easy-to-use devices that did not require detailed explanations. In the disadvantaged, digital biomarkers related to health promotion were measured, and various wearable devices, such as smart bands and headbands were used depending on the purpose and target. CONCLUSION As the digital biomarkers and devices that collect them vary depending on the characteristics of study subjects, researchers should pay attention not only to the purpose of the study but also the characteristics of study subjects when collecting and analyzing digital biomarkers from living labs.
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Affiliation(s)
- YouHyun Park
- Department of Biostatistics, Yonsei University Wonju College of Medicine, Wonju, Korea
| | - Tae-Hwa Go
- Department of Biostatistics, Yonsei University Wonju College of Medicine, Wonju, Korea
| | - Se Hwa Hong
- Department of Biostatistics, Yonsei University Wonju College of Medicine, Wonju, Korea
| | - Sung Hwa Kim
- Department of Biostatistics, Yonsei University Wonju College of Medicine, Wonju, Korea
| | - Jae Hun Han
- Department of Biostatistics, Yonsei University Wonju College of Medicine, Wonju, Korea
| | | | - Dae Ryong Kang
- Department of Biostatistics, Yonsei University Wonju College of Medicine, Wonju, Korea
- Department of Precision Medicine and Biostatistics, Yonsei University Wonju College of Medicine, Wonju, Korea.
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Kaliukhovich DA, Manyakov NV, Bangerter A, Pandina G. Context Modulates Attention to Faces in Dynamic Social Scenes in Children and Adults with Autism Spectrum Disorder. J Autism Dev Disord 2021; 52:4219-4232. [PMID: 34623583 PMCID: PMC9508054 DOI: 10.1007/s10803-021-05279-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/04/2021] [Indexed: 11/28/2022]
Abstract
Individuals with autism spectrum disorder (ASD) have been found to view social scenes differently compared to typically developing (TD) peers, but results can vary depending on context and age. We used eye-tracking in children and adults (age 6-63) to assess allocation of visual attention in a dynamic social orientation paradigm previously used only in younger children. The ASD group (n = 94) looked less at the actor's face compared to TD (n = 38) when they were engaged in activity (mean percentage of looking time, ASD = 30.7% vs TD = 34.9%; Cohen's d = 0.56; p value < 0.03) or looking at a moving toy (24.5% vs 33.2%; d = 0.65; p value < 0.001). Findings indicate that there are qualitative differences in allocation of visual attention to social stimuli across ages in ASD.ClinicalTrials.gov identifier: NCT02668991.
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Affiliation(s)
| | | | | | - Gahan Pandina
- Janssen Research & Development, LLC, Titusville, NJ, USA
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6
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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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Armstrong C, Marsh ED. Electrophysiological Biomarkers in Genetic Epilepsies. Neurotherapeutics 2021; 18:1458-1467. [PMID: 34642905 PMCID: PMC8609056 DOI: 10.1007/s13311-021-01132-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/27/2021] [Indexed: 02/04/2023] Open
Abstract
Precision treatments for epilepsy targeting the underlying genetic diagnoses are becoming a reality. Historically, the goal of epilepsy treatments was to reduce seizure frequency. In the era of precision medicine, however, outcomes such as prevention of epilepsy progression or even improvements in cognitive functions are both aspirational targets for any intervention. Developing methods, both in clinical trial design and in novel endpoints, will be necessary for measuring, not only seizures, but also the other neurodevelopmental outcomes that are predicted to be targeted by precision treatments. Biomarkers that quantitatively measure disease progression or network level changes are needed to allow for unbiased measurements of the effects of any gene-level treatments. Here, we discuss some of the promising electrophysiological biomarkers that may be of use in clinical trials of precision therapies, as well as the difficulties in implementing them.
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Affiliation(s)
- Caren Armstrong
- Division of Neurology and Pediatric Epilepsy Program, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Eric D Marsh
- Division of Neurology and Pediatric Epilepsy Program, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
- Department of Pediatrics and Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA.
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Exploring Social Biomarkers in High-Functioning Adults with Autism and Asperger's Versus Healthy Controls: A Cross-Sectional Analysis. J Autism Dev Disord 2021; 50:4412-4430. [PMID: 32279223 PMCID: PMC7677266 DOI: 10.1007/s10803-020-04493-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Biomarkers for autism spectrum disorder (ASD) are lacking but would facilitate drug development for the core deficits of the disorder. We evaluated markers proposed for characterization of differences in social communication and interaction in adults with ASD versus healthy controls (HC) for utility as biomarkers. Data pooled from an observational study and baseline data from a placebo-controlled study were analyzed. Between-group differences were observed in eye-tracking tasks for activity monitoring, biomotion, human activity preference, composite score (p = 0.0001-0.037) and pupillometry (various tasks, p = 0.017-0.05). Impaired olfaction was more common in the ASD sample versus HC (p = 0.018). Our preliminary results suggest the potential use for stratification and response sub-analyses outcome-prediction of specific eye-tracking tasks, pupillometry and olfaction tests in ASD trials.
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Pandina G, Ness S, Trudeau J, Stringer S, Knoble N, Lenderking WR, Bangerter A. Qualitative evaluation of the Autism Behavior Inventory: use of cognitive interviewing to establish validity of a caregiver report scale for autism spectrum disorder. Health Qual Life Outcomes 2021; 19:26. [PMID: 33472654 PMCID: PMC7819236 DOI: 10.1186/s12955-020-01665-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Accepted: 12/30/2020] [Indexed: 11/10/2022] Open
Abstract
PURPOSE The Autism Behavior Inventory (ABI) is an observer-reported outcome scale measuring core and associated features of autism spectrum disorder (ASD). Extensive scale development (reported elsewhere) took place, in alignment with the Food and Drug Administration's patient-reported outcome guidance, to address the need for instruments to measure change and severity of ASD symptoms. METHODS Cognitive interviewing was used to confirm understanding and content validity of the scale prior to its use in clinical trials. Respondents were caregivers of individuals with ASD (N = 50). Interviews used a hybrid of the "think-aloud" and verbal probing approach to assess ABI's content validity and participant understanding of the instrument, including: item clarity and relevance; item interpretation; appropriateness of response scales; and clarity of instructions. Audio-recordings of the interviews were transcribed for qualitative data analysis. The scale was revised based on participant feedback and tested in a second round of interviews (round 1 N = 38, round 2 N = 12). RESULTS In total, 67/70 items reached ≥ 90% understandability across participants. Caregivers were able to select an appropriate response from the options available and reported finding the examples helpful. Based on participant feedback, instructions were simplified, 8 items were removed, and 10 items were reworded. The final revised 62-item scale was presented in round 2, where caregivers reported readily understanding the instructions, response options, and 61/62 items reached ≥ 90% understandability. CONCLUSIONS Cognitive interviews with caregivers of a diverse sample of individuals with ASD confirm the content validity and relevance of the ABI to assess core and associated symptoms of ASD.
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Affiliation(s)
- Gahan Pandina
- Department of Neuroscience, Janssen Research & Development, LLC, Pennington, NJ, 08534, USA.
| | - Seth Ness
- Department of Neuroscience, Janssen Research & Development, LLC, Titusville, NJ, USA
| | - Jeremiah Trudeau
- Department of Patient Reported Outcomes, Janssen Global Services, Raritan, NJ, USA
| | - Sonja Stringer
- Evidera, Pharmaceutical Product Development, LLC, Bethesda, MD, USA
| | - Naomi Knoble
- Evidera, Pharmaceutical Product Development, LLC, Bethesda, MD, USA
| | | | - Abigail Bangerter
- Department of Neuroscience, Janssen Research & Development, LLC, Titusville, NJ, USA
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Pandina G, Ring RH, Bangerter A, Ness S. Current Approaches to the Pharmacologic Treatment of Core Symptoms Across the Lifespan of Autism Spectrum Disorder. Psychiatr Clin North Am 2020; 43:629-645. [PMID: 33126999 DOI: 10.1016/j.psc.2020.08.003] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
There are no approved medications for autism spectrum disorder (ASD) core symptoms. However, given the significant clinical need, children and adults with ASD are prescribed medication off label for core or associated conditions, sometimes based on limited evidence for effectiveness. Recent developments in the understanding of biologic basis of ASD have led to novel targets with potential to impact core symptoms, and several clinical trials are underway. Heterogeneity in course of development, co-occurring conditions, and age-related treatment response variability hampers study outcomes. Novel measures and approaches to ASD clinical trial design will help in development of effective pharmacologic treatments.
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Affiliation(s)
- Gahan Pandina
- Janssen Research & Development, LLC, 1125 Trenton Harbouron Road, Titusville, NJ 08560, USA.
| | | | - Abigail Bangerter
- Janssen Research & Development, LLC, 1125 Trenton Harbouron Road, Titusville, NJ 08560, USA
| | - Seth Ness
- Janssen Research & Development, LLC, 1125 Trenton Harbouron Road, Titusville, NJ 08560, USA
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Kaliukhovich DA, Manyakov NV, Bangerter A, Ness S, Skalkin A, Goodwin MS, Dawson G, Hendren RL, Leventhal B, Hudac CM, Bradshaw J, Shic F, Pandina G. Social attention to activities in children and adults with autism spectrum disorder: effects of context and age. Mol Autism 2020; 11:79. [PMID: 33076994 PMCID: PMC7574440 DOI: 10.1186/s13229-020-00388-5] [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: 02/04/2020] [Accepted: 10/01/2020] [Indexed: 11/10/2022] Open
Abstract
Background Diminished visual monitoring of faces and activities of others is an early feature of autism spectrum disorder (ASD). It is uncertain whether deficits in activity monitoring, identified using a homogeneous set of stimuli, persist throughout the lifespan in ASD, and thus, whether they could serve as a biological indicator (“biomarker”) of ASD. We investigated differences in visual attention during activity monitoring in children and adult participants with autism compared to a control group of participants without autism. Methods Eye movements of participants with autism (n = 122; mean age [SD] = 14.5 [8.0] years) and typically developing (TD) controls (n = 40, age = 16.4 [13.3] years) were recorded while they viewed a series of videos depicting two female actors conversing while interacting with their hands over a shared task. Actors either continuously focused their gaze on each other’s face (mutual gaze) or on the shared activity area (shared focus). Mean percentage looking time was computed for the activity area, actors’ heads, and their bodies. Results Compared to TD participants, participants with ASD looked longer at the activity area (mean % looking time: 58.5% vs. 53.8%, p < 0.005) but less at the heads (15.2% vs. 23.7%, p < 0.0001). Additionally, within-group differences in looking time were observed between the mutual gaze and shared focus conditions in both participants without ASD (activity: Δ = − 6.4%, p < 0.004; heads: Δ = + 3.5%, p < 0.02) and participants with ASD (bodies: Δ = + 1.6%, p < 0.002). Limitations The TD participants were not as well characterized as the participants with ASD. Inclusion criteria regarding the cognitive ability [intelligence quotient (IQ) > 60] limited the ability to include individuals with substantial intellectual disability. Conclusions Differences in attention to faces could constitute a feature discriminative between individuals with and without ASD across the lifespan, whereas between-group differences in looking at activities may shift with development. These findings may have applications in the search for underlying biological indicators specific to ASD. Trial registration ClinicalTrials.gov identifier NCT02668991.
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Affiliation(s)
| | | | - Abigail Bangerter
- Janssen Research & Development, LLC, 1125 Trenton-Harbourton Road, Titusville, NJ, 08560, USA
| | - Seth Ness
- Janssen Research & Development, LLC, 1125 Trenton-Harbourton Road, Titusville, NJ, 08560, USA
| | - Andrew Skalkin
- Datagrok, INC, 1800 JFK Blvd Suite 300 PMB 90078, Philadelphia, PA, 19103, USA
| | - Matthew S Goodwin
- 312E Robinson Hall, Department of Health Sciences, Bouvé College of Health Sciences, Northeastern University, 360 Huntington Avenue, Boston, MA, 02115, USA
| | - Geraldine Dawson
- Duke Center for Autism and Brain Development and Duke Institute for Brain Sciences, Duke University School of Medicine, 2608 Erwin Road, Suite 30, Durham, NC, 27705, USA
| | - Robert L Hendren
- Benioff Children's Hospital, University of California, San Francisco, 401 Parnassus Avenue, Langley Porter, San Francisco, CA, 94143-0984, USA
| | - Bennett Leventhal
- Benioff Children's Hospital, University of California, San Francisco, 401 Parnassus Avenue, Langley Porter, San Francisco, CA, 94143-0984, USA
| | - Caitlin M Hudac
- Center for Youth Development and Intervention, University of Alabama, Box 870348, Tuscaloosa, AL, 35487-0348, USA
| | - Jessica Bradshaw
- Department of Psychology, University of South Carolina, 1512 Pendleton Street, Columbia, SC, 29201, USA
| | - Frederick Shic
- Department of Pediatrics, Seattle Children's Research Institute, Center for Child Health, Behavior and Development, University of Washington, 6200 NE 74th Street, Ste 110, Seattle, WA, 98115-8160, USA
| | - Gahan Pandina
- Janssen Research & Development, LLC, 1125 Trenton-Harbourton Road, Titusville, NJ, 08560, USA
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12
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Black MH, Milbourn B, Chen NTM, McGarry S, Wali F, Ho ASV, Lee M, Bölte S, Falkmer T, Girdler S. The use of wearable technology to measure and support abilities, disabilities and functional skills in autistic youth: a scoping review. Scand J Child Adolesc Psychiatr Psychol 2020; 8:48-69. [PMID: 33520778 PMCID: PMC7685500 DOI: 10.21307/sjcapp-2020-006] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022] Open
Abstract
Background: Wearable technology (WT) to measure and support social and non-social functioning in Autism Spectrum Disorder (ASD) has been a growing interest of researchers over the past decade. There is however limited understanding of the WTs currently available for autistic individuals, and how they measure functioning in this population. Objective: This scoping review explored the use of WTs for measuring and supporting abilities, disabilities and functional skills in autistic youth. Method: Four electronic databases were searched to identify literature investigating the use of WT in autistic youth, resulting in a total of 33 studies being reviewed. Descriptive and content analysis was conducted, with studies subsequently mapped to the ASD International Classification of Functioning, Disability and Health Core-sets and the ICF Child and Youth Version (ICF-CY). Results: Studies were predominately pilot studies for novel devices. WTs measured a range of physiological and behavioural functions to objectively measure stereotypical motor movements, social function, communication, and emotion regulation in autistic youth in the context of a range of environments and activities. Conclusions: While this review raises promising prospects for the use of WTs for autistic youth, the current evidence is limited and requires further investigation.
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Affiliation(s)
- Melissa H Black
- School of Occupational Therapy, Social Work and Speech Pathology, Curtin University, Perth, Western Australia.,Curtin Autism Research Group, Curtin University, Perth, Western Australia
| | - Benjamin Milbourn
- School of Occupational Therapy, Social Work and Speech Pathology, Curtin University, Perth, Western Australia.,Curtin Autism Research Group, Curtin University, Perth, Western Australia
| | - Nigel T M Chen
- School of Occupational Therapy, Social Work and Speech Pathology, Curtin University, Perth, Western Australia.,Curtin Autism Research Group, Curtin University, Perth, Western Australia
| | - Sarah McGarry
- School of Occupational Therapy, Social Work and Speech Pathology, Curtin University, Perth, Western Australia
| | - Fatema Wali
- School of Occupational Therapy, Social Work and Speech Pathology, Curtin University, Perth, Western Australia
| | - Armilda S V Ho
- School of Occupational Therapy, Social Work and Speech Pathology, Curtin University, Perth, Western Australia
| | - Mika Lee
- School of Occupational Therapy, Social Work and Speech Pathology, Curtin University, Perth, Western Australia
| | - Sven Bölte
- School of Occupational Therapy, Social Work and Speech Pathology, Curtin University, Perth, Western Australia.,Curtin Autism Research Group, Curtin University, Perth, Western Australia.,Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research; Dep. of Women's and Children's Health, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden.,Child and Adolescent Psychiatry, Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
| | - Torbjorn Falkmer
- School of Occupational Therapy, Social Work and Speech Pathology, Curtin University, Perth, Western Australia.,Curtin Autism Research Group, Curtin University, Perth, Western Australia.,Pain and Rehabilitation Centre, Dep. of Medical and Health Sciences, Linkoping University, Linkoping, Sweden
| | - Sonya Girdler
- School of Occupational Therapy, Social Work and Speech Pathology, Curtin University, Perth, Western Australia.,Curtin Autism Research Group, Curtin University, Perth, Western Australia
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13
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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: 12] [Impact Index Per Article: 3.0] [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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14
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Bangerter A, Chatterjee M, Manfredonia J, Manyakov NV, Ness S, Boice MA, Skalkin A, Goodwin MS, Dawson G, Hendren R, Leventhal B, Shic F, Pandina G. Automated recognition of spontaneous facial expression in individuals with autism spectrum disorder: parsing response variability. Mol Autism 2020; 11:31. [PMID: 32393350 PMCID: PMC7212683 DOI: 10.1186/s13229-020-00327-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2019] [Accepted: 03/10/2020] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Reduction or differences in facial expression are a core diagnostic feature of autism spectrum disorder (ASD), yet evidence regarding the extent of this discrepancy is limited and inconsistent. Use of automated facial expression detection technology enables accurate and efficient tracking of facial expressions that has potential to identify individual response differences. METHODS Children and adults with ASD (N = 124) and typically developing (TD, N = 41) were shown short clips of "funny videos." Using automated facial analysis software, we investigated differences between ASD and TD groups and within the ASD group in evidence of facial action unit (AU) activation related to the expression of positive facial expression, in particular, a smile. RESULTS Individuals with ASD on average showed less evidence of facial AUs (AU12, AU6) relating to positive facial expression, compared to the TD group (p < .05, r = - 0.17). Using Gaussian mixture model for clustering, we identified two distinct distributions within the ASD group, which were then compared to the TD group. One subgroup (n = 35), termed "over-responsive," expressed more intense positive facial expressions in response to the videos than the TD group (p < .001, r = 0.31). The second subgroup (n = 89), ("under-responsive"), displayed fewer, less intense positive facial expressions in response to videos than the TD group (p < .001; r = - 0.36). The over-responsive subgroup differed from the under-responsive subgroup in age and caregiver-reported impulsivity (p < .05, r = 0.21). Reduced expression in the under-responsive, but not the over-responsive group, was related to caregiver-reported social withdrawal (p < .01, r = - 0.3). LIMITATIONS This exploratory study does not account for multiple comparisons, and future work will have to ascertain the strength and reproducibility of all results. Reduced displays of positive facial expressions do not mean individuals with ASD do not experience positive emotions. CONCLUSIONS Individuals with ASD differed from the TD group in their facial expressions of positive emotion in response to "funny videos." Identification of subgroups based on response may help in parsing heterogeneity in ASD and enable targeting of treatment based on subtypes. TRIAL REGISTRATION ClinicalTrials.gov, NCT02299700. Registration date: November 24, 2014.
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Affiliation(s)
- Abigail Bangerter
- Neuroscience Therapeutic Area, Janssen Research & Development, Titusville, NJ USA
| | - Meenakshi Chatterjee
- Digital Phenotyping Group, Discovery Sciences, Janssen Research & Development, Spring House, PA USA
| | - Joseph Manfredonia
- Neuroscience Therapeutic Area, Janssen Research & Development, Titusville, NJ USA
| | - Nikolay V. Manyakov
- Digital Phenotyping Group, Discovery Sciences, Janssen Research & Development, Beerse, Belgium
| | - Seth Ness
- Neuroscience Therapeutic Area, Janssen Research & Development, Titusville, NJ USA
| | - Matthew A. Boice
- Neuroscience Therapeutic Area, Janssen Research & Development, Titusville, NJ USA
| | - Andrew Skalkin
- Neuroscience Therapeutic Area, Janssen Research & Development, Titusville, NJ USA
| | - Matthew S. Goodwin
- Bouvé College of Health Sciences, Northeastern University, Boston, MA USA
| | - Geraldine Dawson
- Department of Psychiatry and Behavioral Sciences, Duke Center for Autism and Brain Development, Duke Institute for Brain Sciences, Duke University, Durham, NC USA
| | - Robert Hendren
- Department of Psychiatry, School of Medicine, University of California, San Francisco, San Francisco, CA USA
| | - Bennett Leventhal
- Department of Psychiatry, School of Medicine, University of California, San Francisco, San Francisco, CA USA
| | - Frederick Shic
- Center for Child Health, Behavior and Development, Seattle Children’s Research Institute, Seattle, WA USA
- Department of Pediatrics, University of Washington, Seattle, WA USA
| | - Gahan Pandina
- Neuroscience Therapeutic Area, Janssen Research & Development, Titusville, NJ USA
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15
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McPartland JC, Bernier RA, Jeste SS, Dawson G, Nelson CA, Chawarska K, Earl R, Faja S, Johnson SP, Sikich L, Brandt CA, Dziura JD, Rozenblit L, Hellemann G, Levin AR, Murias M, Naples AJ, Platt ML, Sabatos-DeVito M, Shic F, Senturk D, Sugar CA, Webb SJ. The Autism Biomarkers Consortium for Clinical Trials (ABC-CT): Scientific Context, Study Design, and Progress Toward Biomarker Qualification. Front Integr Neurosci 2020; 14:16. [PMID: 32346363 PMCID: PMC7173348 DOI: 10.3389/fnint.2020.00016] [Citation(s) in RCA: 62] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2019] [Accepted: 03/10/2020] [Indexed: 12/19/2022] Open
Abstract
Clinical research in neurodevelopmental disorders remains reliant upon clinician and caregiver measures. Limitations of these approaches indicate a need for objective, quantitative, and reliable biomarkers to advance clinical research. Extant research suggests the potential utility of multiple candidate biomarkers; however, effective application of these markers in trials requires additional understanding of replicability, individual differences, and intra-individual stability over time. The Autism Biomarkers Consortium for Clinical Trials (ABC-CT) is a multi-site study designed to investigate a battery of electrophysiological (EEG) and eye-tracking (ET) indices as candidate biomarkers for autism spectrum disorder (ASD). The study complements published biomarker research through: inclusion of large, deeply phenotyped cohorts of children with ASD and typical development; a longitudinal design; a focus on well-evidenced candidate biomarkers harmonized with an independent sample; high levels of clinical, regulatory, technical, and statistical rigor; adoption of a governance structure incorporating diverse expertise in the ASD biomarker discovery and qualification process; prioritization of open science, including creation of a repository containing biomarker, clinical, and genetic data; and use of economical and scalable technologies that are applicable in developmental populations and those with special needs. The ABC-CT approach has yielded encouraging results, with one measure accepted into the FDA’s Biomarker Qualification Program to date. Through these advances, the ABC-CT and other biomarker studies in progress hold promise to deliver novel tools to improve clinical trials research in ASD.
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Affiliation(s)
| | - Raphael A Bernier
- Center for Child Health, Behavior and Development, Seattle Children's Research Institute, Seattle Children's Hospital, Seattle, WA, United States.,Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA, United States
| | - Shafali S Jeste
- University of California, Los Angeles, Los Angeles, CA, United States
| | - Geraldine Dawson
- Duke Center for Autism and Brain Development, Duke University, Durham, NC, United States
| | - Charles A Nelson
- Boston Children's Hospital and Harvard Medical School, Boston, MA, United States.,Harvard University, Boston, MA, United States
| | | | - Rachel Earl
- Center on Human Development and Disability, University of Washington, Seattle, WA, United States
| | - Susan Faja
- Boston Children's Hospital and Harvard Medical School, Boston, MA, United States.,Harvard University, Boston, MA, United States
| | - Scott P Johnson
- University of California, Los Angeles, Los Angeles, CA, United States
| | - Linmarie Sikich
- Duke Center for Autism and Brain Development, Duke University, Durham, NC, United States
| | | | | | | | - Gerhard Hellemann
- University of California, Los Angeles, Los Angeles, CA, United States
| | - April R Levin
- Boston Children's Hospital and Harvard Medical School, Boston, MA, United States.,Harvard University, Boston, MA, United States
| | | | - Adam J Naples
- Yale Child Study Center, New Haven, CT, United States
| | | | - Maura Sabatos-DeVito
- Duke Center for Autism and Brain Development, Duke University, Durham, NC, United States
| | - Frederick Shic
- Center for Child Health, Behavior and Development, Seattle Children's Research Institute, Seattle Children's Hospital, Seattle, WA, United States.,Department of Pediatrics, University of Washington School of Medicine, Seattle, WA, United States
| | - Damla Senturk
- University of California, Los Angeles, Los Angeles, CA, United States
| | - Catherine A Sugar
- University of California, Los Angeles, Los Angeles, CA, United States
| | - Sara J Webb
- Center for Child Health, Behavior and Development, Seattle Children's Research Institute, Seattle Children's Hospital, Seattle, WA, United States.,Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA, United States
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16
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Pandina G, Ring RH, Bangerter A, Ness S. Current Approaches to the Pharmacologic Treatment of Core Symptoms Across the Lifespan of Autism Spectrum Disorder. Child Adolesc Psychiatr Clin N Am 2020; 29:301-317. [PMID: 32169264 DOI: 10.1016/j.chc.2019.12.004] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
There are no approved medications for autism spectrum disorder (ASD) core symptoms. However, given the significant clinical need, children and adults with ASD are prescribed medication off label for core or associated conditions, sometimes based on limited evidence for effectiveness. Recent developments in the understanding of biologic basis of ASD have led to novel targets with potential to impact core symptoms, and several clinical trials are underway. Heterogeneity in course of development, co-occurring conditions, and age-related treatment response variability hampers study outcomes. Novel measures and approaches to ASD clinical trial design will help in development of effective pharmacologic treatments.
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Affiliation(s)
- Gahan Pandina
- Janssen Research & Development, LLC, 1125 Trenton Harbouron Road, Titusville, NJ 08560, USA.
| | | | - Abigail Bangerter
- Janssen Research & Development, LLC, 1125 Trenton Harbouron Road, Titusville, NJ 08560, USA
| | - Seth Ness
- Janssen Research & Development, LLC, 1125 Trenton Harbouron Road, Titusville, NJ 08560, USA
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17
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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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18
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19
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Sargsyan D, Jagannatha S, Manyakov NV, Skalkin A, Bangerter A, Ness S, Durham K, Amaratunga D, Cabrera J, Pandina G. Feature Selection With Weighted Importance Index in an Autism Spectrum Disorder Study. Stat Biopharm Res 2019. [DOI: 10.1080/19466315.2018.1537886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Affiliation(s)
- Davit Sargsyan
- Translational Medicine and Early Development Statistics, Janssen Research & Development, LLC, Spring House, PA
| | | | | | | | | | - Seth Ness
- Janssen Research & Development, LLC, Titusville, NJ
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20
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Jagannatha S, Sargsyan D, Manyakov NV, Skalkin A, Bangerter A, Ness S, Lewin D, Johnson K, Durham K, Pandina G. A Practical Application of Data Mining Methods to Build Predictive Models for Autism Spectrum Disorder Based on Biosensor Data From Janssen Autism Knowledge Engine (JAKE®). Stat Biopharm Res 2019. [DOI: 10.1080/19466315.2018.1527247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Affiliation(s)
| | | | | | | | | | - Seth Ness
- Janssen Research & Development, Teaneck, NJ
| | - David Lewin
- Janssen Research & Development, Titusville, NJ
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21
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Bangerter A, Manyakov NV, Lewin D, Boice M, Skalkin A, Jagannatha S, Chatterjee M, Dawson G, Goodwin MS, Hendren R, Leventhal B, Shic F, Ness S, Pandina G. Caregiver Daily Reporting of Symptoms in Autism Spectrum Disorder: Observational Study Using Web and Mobile Apps. JMIR Ment Health 2019; 6:e11365. [PMID: 30912762 PMCID: PMC6454343 DOI: 10.2196/11365] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/28/2018] [Revised: 12/05/2018] [Accepted: 12/31/2018] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND Currently, no medications are approved to treat core symptoms of autism spectrum disorder (ASD). One barrier to ASD medication development is the lack of validated outcome measures able to detect symptom change. Current ASD interventions are often evaluated using retrospective caregiver reports that describe general clinical presentation but often require recall of specific behaviors weeks after they occur, potentially reducing accuracy of the ratings. My JAKE, a mobile and Web-based mobile health (mHealth) app that is part of the Janssen Autism Knowledge Engine-a dynamically updated clinical research system-was designed to help caregivers of individuals with ASD to continuously log symptoms, record treatments, and track progress, to mitigate difficulties associated with retrospective reporting. OBJECTIVE My JAKE was deployed in an exploratory, noninterventional clinical trial to evaluate its utility and acceptability to monitor clinical outcomes in ASD. Hypotheses regarding relationships among daily tracking of symptoms, behavior, and retrospective caregiver reports were tested. METHODS Caregivers of individuals with ASD aged 6 years to adults (N=144) used the My JAKE app to make daily reports on their child's sleep quality, affect, and other self-selected specific behaviors across the 8- to 10-week observational study. The results were compared with commonly used paper-and-pencil scales acquired over a concurrent period at regular 4-week intervals. RESULTS Caregiver reporting of behaviors in real time was successfully captured by My JAKE. On average, caregivers made reports 2-3 days per week across the study period. Caregivers were positive about their use of the system, with over 50% indicating that they would like to use My JAKE to track behavior outside of a clinical trial. More positive average daily reporting of overall type of day was correlated with 4 weekly reports of lower caregiver burden made at 4-week intervals (r=-0.27, P=.006, n=88) and with ASD symptoms (r=-0.42, P<.001, n=112). CONCLUSIONS My JAKE reporting aligned with retrospective Web-based or paper-and-pencil scales. Use of mHealth apps, such as My JAKE, has the potential to increase the validity and accuracy of caregiver-reported outcomes and could be a useful way of identifying early changes in response to intervention. Such systems may also assist caregivers in tracking symptoms and behavior outside of a clinical trial, help with personalized goal setting, and monitoring of progress, which could collectively improve understanding of and quality of life for individuals with ASD and their families. TRIAL REGISTRATION ClinicalTrials.gov NCT02668991; https://clinicaltrials.gov/ct2/show/NCT02668991.
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Affiliation(s)
- Abigail Bangerter
- Neuroscience Therapeutic Area, Janssen Research & Development, LLC, Titusville, NJ, United States
| | - Nikolay V Manyakov
- Computational Biology, Discovery Sciences, Janssen Research & Development, Beerse, Belgium
| | - David Lewin
- Clinical Biostatistics, Janssen Research & Development, LLC, Titusville, NJ, United States
| | - Matthew Boice
- Neuroscience Therapeutic Area, Janssen Research & Development, LLC, Titusville, NJ, United States
| | - Andrew Skalkin
- Informatics, Janssen Research & Development, LLC, Spring House, PA, United States
| | - Shyla Jagannatha
- Statistical Decision Sciences, Janssen Research & Development, LLC, Titusville, NJ, United States
| | - Meenakshi Chatterjee
- Computational Biology, Discovery Sciences, Janssen Research & Development, LLC, Spring House, PA, United States
| | - Geraldine Dawson
- Duke Center for Autism and Brain Development, Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, United States
| | - Matthew S Goodwin
- Department of Health Sciences, Northeastern University, Boston, MA, United States
| | - Robert Hendren
- Department of Psychiatry, School of Medicine, University of California, San Francisco, San Francisco, CA, United States
| | - Bennett Leventhal
- Department of Psychiatry, School of Medicine, University of California, San Francisco, San Francisco, CA, United States
| | - Frederick Shic
- Center for Child Health, Behavior and Development, Seattle Children's Research Institute, Seattle, WA, United States
| | - Seth Ness
- Neuroscience Therapeutic Area, Janssen Research & Development, LLC, Titusville, NJ, United States
| | - Gahan Pandina
- Neuroscience Therapeutic Area, Janssen Research & Development, LLC, Titusville, NJ, United States
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22
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Automatic Recognition of Posed Facial Expression of Emotion in Individuals with Autism Spectrum Disorder. J Autism Dev Disord 2019; 49:279-293. [PMID: 30298462 DOI: 10.1007/s10803-018-3757-9] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
Facial expression is impaired in autism spectrum disorder (ASD), but rarely systematically studied. We focus on the ability of individuals with ASD to produce facial expressions of emotions in response to a verbal prompt. We used the Janssen Autism Knowledge Engine (JAKE®), including automated facial expression analysis software (FACET) to measure facial expressions in individuals with ASD (n = 144) and a typically developing (TD) comparison group (n = 41). Differences in ability to produce facial expressions were observed between ASD and TD groups, demonstrated by activation of facial action units (happy, scared, surprised, disgusted, but not angry or sad). Activation of facial action units correlated with parent-reported social communication skills. This approach has potential for diagnostic and response to intervention measures.Trial Registration NCT02299700.
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23
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Ness SL, Bangerter A, Manyakov NV, Lewin D, Boice M, Skalkin A, Jagannatha S, Chatterjee M, Dawson G, Goodwin MS, Hendren R, Leventhal B, Shic F, Frazier JA, Janvier Y, King BH, Miller JS, Smith CJ, Tobe RH, Pandina G. An Observational Study With the Janssen Autism Knowledge Engine (JAKE ®) in Individuals With Autism Spectrum Disorder. Front Neurosci 2019; 13:111. [PMID: 30872988 PMCID: PMC6402449 DOI: 10.3389/fnins.2019.00111] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2018] [Accepted: 01/30/2019] [Indexed: 11/13/2022] Open
Abstract
Objective: The Janssen Autism Knowledge Engine (JAKE®) is a clinical research outcomes assessment system developed to more sensitively measure treatment outcomes and identify subpopulations in autism spectrum disorder (ASD). Here we describe JAKE and present results from its digital phenotyping (My JAKE) and biosensor (JAKE Sense) components. Methods: An observational, non-interventional, prospective study of JAKE in children and adults with ASD was conducted at nine sites in the United States. Feedback on JAKE usability was obtained from caregivers. JAKE Sense included electroencephalography, eye tracking, electrocardiography, electrodermal activity, facial affect analysis, and actigraphy. Caregivers of individuals with ASD reported behaviors using My JAKE. Results from My JAKE and JAKE Sense were compared to traditional ASD symptom measures. Results: Individuals with ASD (N = 144) and a cohort of typically developing (TD) individuals (N = 41) participated in JAKE Sense. Most caregivers reported that overall use and utility of My JAKE was "easy" (69%, 74/108) or "very easy" (74%, 80/108). My JAKE could detect differences in ASD symptoms as measured by traditional methods. The majority of biosensors included in JAKE Sense captured sizable amounts of quality data (i.e., 93-100% of eye tracker, facial affect analysis, and electrocardiogram data was of good quality), demonstrated differences between TD and ASD individuals, and correlated with ASD symptom scales. No significant safety events were reported. Conclusions: My JAKE was viewed as easy or very easy to use by caregivers participating in research outside of a clinical study. My JAKE sensitively measured a broad range of ASD symptoms. JAKE Sense biosensors were well-tolerated. JAKE functioned well when used at clinical sites previously inexperienced with some of the technologies. Lessons from the study will optimize JAKE for use in clinical trials to assess ASD interventions. Additionally, because biosensors were able to detect features differentiating TD and ASD individuals, and also were correlated with standardized symptom scales, these measures could be explored as potential biomarkers for ASD and as endpoints in future clinical studies. Clinical Trial Registration: https://clinicaltrials.gov/ct2/show/NCT02668991 identifier: NCT02668991.
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Affiliation(s)
- Seth L. Ness
- Neuroscience Therapeutic Area, Janssen Research & Development, Titusville, FL, United States
| | - Abigail Bangerter
- Neuroscience Therapeutic Area, Janssen Research & Development, Titusville, FL, United States
| | - Nikolay V. Manyakov
- Computational Biology, Discovery Sciences, Janssen Research & Development, Beerse, Belgium
| | - David Lewin
- Statistically Speaking Consulting, LLC, Chicago, IL, United States
| | - Matthew Boice
- Neuroscience Therapeutic Area, Janssen Research & Development, Titusville, FL, United States
| | - Andrew Skalkin
- Informatics, Janssen Research & Development, Spring House, PA, United States
| | - Shyla Jagannatha
- Statistical Decision Sciences, Janssen Research & Development, Titusville, NJ, United States
| | - Meenakshi Chatterjee
- Computational Biology, Discovery Sciences, Janssen Research & Development, Spring House, PA, United States
| | - Geraldine Dawson
- Departments of Psychiatry and Behavioral Sciences, Duke Center for Autism and Brain Development, Duke University School of Medicine, Durham, NC, United States
| | - Matthew S. Goodwin
- Department of Health Sciences, Northeastern University, Boston, MA, United States
| | - Robert Hendren
- Department of Psychiatry, School of Medicine, University of California, San Francisco, San Francisco, CA, United States
| | - Bennett Leventhal
- Department of Psychiatry, School of Medicine, University of California, San Francisco, San Francisco, CA, United States
| | - Frederick Shic
- Center for Child Health, Behavior and Development, Seattle Children's Research Institute, Seattle, WA, United States
- Department of Pediatrics, University of Washington, Seattle, WA, United States
| | - Jean A. Frazier
- Eunice Kennedy Shriver Center and Department of Psychiatry, University of Massachusetts Medical School, Worcester, MA, United States
| | - Yvette Janvier
- Department of Developmental-Behavioral Pediatrics, Children's Specialized Hospital, Toms River, NJ, United States
| | - Bryan H. King
- Department of Psychiatry, School of Medicine, University of California, San Francisco, San Francisco, CA, United States
| | - Judith S. Miller
- Center for Autism Research, Perelman School of Medicine, Children's Hospital of Philadelphia, University of Pennsylvania, Philadelphia, PA, United States
| | | | - Russell H. Tobe
- Department of Outpatient Research, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY, United States
| | - Gahan Pandina
- Neuroscience Therapeutic Area, Janssen Research & Development, Pennington, NJ, United States
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Grabowski K, Rynkiewicz A, Lassalle A, Baron-Cohen S, Schuller B, Cummins N, Baird A, Podgórska-Bednarz J, Pieniążek A, Łucka I. Emotional expression in psychiatric conditions: New technology for clinicians. Psychiatry Clin Neurosci 2019; 73:50-62. [PMID: 30565801 DOI: 10.1111/pcn.12799] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/11/2017] [Revised: 09/24/2018] [Accepted: 11/11/2018] [Indexed: 12/24/2022]
Abstract
AIM Emotional expressions are one of the most widely studied topics in neuroscience, from both clinical and non-clinical perspectives. Atypical emotional expressions are seen in various psychiatric conditions, including schizophrenia, depression, and autism spectrum conditions. Understanding the basics of emotional expressions and recognition can be crucial for diagnostic and therapeutic procedures. Emotions can be expressed in the face, gesture, posture, voice, and behavior and affect physiological parameters, such as the heart rate or body temperature. With modern technology, clinicians can use a variety of tools ranging from sophisticated laboratory equipment to smartphones and web cameras. The aim of this paper is to review the currently used tools using modern technology and discuss their usefulness as well as possible future directions in emotional expression research and treatment strategies. METHODS The authors conducted a literature review in the PubMed, EBSCO, and SCOPUS databases, using the following key words: 'emotions,' 'emotional expression,' 'affective computing,' and 'autism.' The most relevant and up-to-date publications were identified and discussed. Search results were supplemented by the authors' own research in the field of emotional expression. RESULTS We present a critical review of the currently available technical diagnostic and therapeutic methods. The most important studies are summarized in a table. CONCLUSION Most of the currently available methods have not been adequately validated in clinical settings. They may be a great help in everyday practice; however, they need further testing. Future directions in this field include more virtual-reality-based and interactive interventions, as well as development and improvement of humanoid robots.
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Affiliation(s)
- Karol Grabowski
- Department of Psychiatry, Adult Psychiatry Clinic, Faculty of Medicine, Medical University of Gdansk, Gdansk, Poland
| | - Agnieszka Rynkiewicz
- Neurodevelopmental Disorders Research Lab, Institute of Experimental and Clinical Medicine, Faculty of Medicine, University of Rzeszow, Rzeszow, Poland.,Center for Diagnosis, Therapy and Education SPECTRUM ASC-MED, Gdansk & Rzeszow, Poland
| | - Amandine Lassalle
- Department of Psychology, Brain & Cognition, University of Amsterdam, Amsterdam, Netherlands
| | - Simon Baron-Cohen
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Björn Schuller
- Department of Computing, GLAM - Group on Language, Audio, and Music, Imperial College London, London, UK
| | - Nicholas Cummins
- Department of Computing, GLAM - Group on Language, Audio, and Music, Imperial College London, London, UK
| | - Alice Baird
- Embedded Intelligence for Health Care and Wellbeing, University of Augsburg, Augsburg, Germany
| | - Justyna Podgórska-Bednarz
- Institute of Physiotherapy, Faculty of Medicine, University of Rzeszow, Rzeszow, Poland.,Association for Children with Attention Deficit Hyperactivity Disorder in Rzeszow, Rzeszow, Poland
| | - Agata Pieniążek
- Institute of Physiotherapy, Faculty of Medicine, University of Rzeszow, Rzeszow, Poland.,SOLIS RADIUS Association for People with Disabilities and Autism Spectrum Disorders in Rzeszow, Rzeszow, Poland.,Medical Center for Children with Autism Spectrum Disorders in Rzeszow, Rzeszow, Poland
| | - Izabela Łucka
- Developmental Psychiatry, Psychotic and Geriatric Disorders Clinic, Department of Psychiatry, Faculty of Medicine, Medical University of Gdansk, Gdansk, Poland
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25
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Drozd HP, Karathanasis SF, Molosh AI, Lukkes JL, Clapp DW, Shekhar A. From bedside to bench and back: Translating ASD models. PROGRESS IN BRAIN RESEARCH 2018; 241:113-158. [PMID: 30447753 DOI: 10.1016/bs.pbr.2018.10.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Autism spectrum disorders (ASD) represent a heterogeneous group of disorders defined by deficits in social interaction/communication and restricted interests, behaviors, or activities. Models of ASD, developed based on clinical data and observations, are used in basic science, the "bench," to better understand the pathophysiology of ASD and provide therapeutic options for patients in the clinic, the "bedside." Translational medicine creates a bridge between the bench and bedside that allows for clinical and basic science discoveries to challenge one another to improve the opportunities to bring novel therapies to patients. From the clinical side, biomarker work is expanding our understanding of possible mechanisms of ASD through measures of behavior, genetics, imaging modalities, and serum markers. These biomarkers could help to subclassify patients with ASD in order to better target treatments to a more homogeneous groups of patients most likely to respond to a candidate therapy. In turn, basic science has been responding to developments in clinical evaluation by improving bench models to mechanistically and phenotypically recapitulate the ASD phenotypes observed in clinic. While genetic models are identifying novel therapeutics targets at the bench, the clinical efforts are making progress by defining better outcome measures that are most representative of meaningful patient responses. In this review, we discuss some of these challenges in translational research in ASD and strategies for the bench and bedside to bridge the gap to achieve better benefits to patients.
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Affiliation(s)
- Hayley P Drozd
- Program in Medical Neurobiology, Stark Neurosciences Institute, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Sotirios F Karathanasis
- Program in Medical Neurobiology, Stark Neurosciences Institute, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Andrei I Molosh
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Jodi L Lukkes
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, United States
| | - D Wade Clapp
- Department of Pediatrics, Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN, United States; Department of Microbiology and Immunology, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Anantha Shekhar
- Program in Medical Neurobiology, Stark Neurosciences Institute, Indiana University School of Medicine, Indianapolis, IN, United States; Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, United States; Department of Pharmacology and Toxicology, Indiana University School of Medicine, Indianapolis, IN, United States; Indiana Clinical and Translation Sciences Institute, Indiana University School of Medicine, Indianapolis, IN, United States.
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26
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Manyakov NV, Bangerter A, Chatterjee M, Mason L, Ness S, Lewin D, Skalkin A, Boice M, Goodwin MS, Dawson G, Hendren R, Leventhal B, Shic F, Pandina G. Visual Exploration in Autism Spectrum Disorder: Exploring Age Differences and Dynamic Features Using Recurrence Quantification Analysis. Autism Res 2018; 11:1554-1566. [PMID: 30273450 DOI: 10.1002/aur.2021] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2018] [Revised: 08/01/2018] [Accepted: 08/16/2018] [Indexed: 01/17/2023]
Abstract
Eye-tracking studies have demonstrated that individuals with autism spectrum disorder sometimes show differences in attention and gaze patterns. This includes preference for certain nonsocial objects, heightened attention to detail, and more difficulty with attention shifting and disengagement, which may be associated with restricted and repetitive behaviors. This study utilized a visual exploration task and replicates findings of reduced number of objects explored and increased fixation duration on high autism interest objects in a large sample of individuals with autism spectrum disorder (n = 129, age 6-54 years) in comparison with a typically developing group. These findings correlated with parent-reported repetitive behaviors. Additionally, we applied recurrent quantification analysis to enable identification of new eye-tracking features, which accounted for temporal and spatial differences in viewing patterns. These new features were found to discriminate between autism spectrum disorder and typically developing groups and were correlated with parent-reported repetitive behaviors. Original and novel eye-tracking features identified by recurrent quantification analysis differed in their relationships to reported behaviors and were dependent on age. Trial Registration: NCT02299700. Autism Research 2018, 11: 1554-1566. © 2018 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Using eye-tracking technology and a visual exploration task, we showed that people with autism spectrum disorder (ASD) spend more time looking at particular kinds of objects, like trains and clocks, and look at fewer objects overall than people without ASD. Where people look and the order in which they look at objects were related to the restricted and repetitive behaviors reported by parents. Eye-tracking may be a useful addition to parent reports for measuring changes in behavior in individuals with ASD.
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Affiliation(s)
| | - Abigail Bangerter
- Janssen Research & Development, LLC, 1125 Trenton-Harbourton Road, Titusville, New Jersey, 08560
| | - Meenakshi Chatterjee
- Janssen Research & Development, LLC, PO Box 776, Welsh & McKean Roads, Spring House, Pennsylvania, 19477-0776
| | - Luke Mason
- Centre for Brain and Cognitive Development, Birkbeck, University of London, Malet Street WC1E 7HX, London, United Kingdom
| | - Seth Ness
- Janssen Research & Development, LLC, 1125 Trenton-Harbourton Road, Titusville, New Jersey, 08560
| | - David Lewin
- Janssen Research & Development, LLC, 1125 Trenton-Harbourton Road, Titusville, New Jersey, 08560
| | - Andrew Skalkin
- Janssen Research & Development, LLC, PO Box 776, Welsh & McKean Roads, Spring House, Pennsylvania, 19477-0776
| | - Matthew Boice
- Janssen Research & Development, LLC, 1125 Trenton-Harbourton Road, Titusville, New Jersey, 08560
| | - Matthew S Goodwin
- 312E Robinson Hall, Department of Health Sciences, Bouvé College of Health Sciences, Northeastern University, 360 Huntington Avenue, Boston, Massachusetts, 02115
| | - Geraldine Dawson
- Duke Center for Autism and Brain Development, Duke University School of Medicine, 2608 Erwin Road, Suite 30, Durham, North Carolina, 27705
| | - Robert Hendren
- Center for Child Health, Behavior and Development, Seattle Children's Research Institute, Department of Pediatrics, University of Washington, 2001 8th Ave Suite #400, Seattle, Washington, 98121
| | - Bennett Leventhal
- Benioff Children's Hospital, University of California, San Francisco, 401 Parnassus Ave, Langley Porter, San Francisco, California, 94143-0984
| | - Frederick Shic
- Center for Child Health, Behavior and Development, Seattle Children's Research Institute, Department of Pediatrics, University of Washington, Seattle, Washington
| | - Gahan Pandina
- Janssen Research & Development, LLC, 1125 Trenton-Harbourton Road, Titusville, New Jersey, 08560
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27
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Smartphone measures of day-to-day behavior changes in children with autism. NPJ Digit Med 2018; 1:34. [PMID: 31304316 PMCID: PMC6550261 DOI: 10.1038/s41746-018-0043-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2018] [Revised: 07/20/2018] [Accepted: 07/23/2018] [Indexed: 11/08/2022] Open
Abstract
Smartphones offer a flexible tool to collect data about mental health, but less is known about their effectiveness as a method to assess variability in children’s problem behaviors. Caregivers of children with autism completed daily questions about irritability, anxiety and mood delivered via smartphones across 8-weeks. Smartphone questions were consistent with subscales on standard caregiver questionnaires. Data collection from 7 to 10 days at the beginning and 7 to 10 days at the end of the study were sufficient to capture similar amounts of variance as daily data across 8-weeks. Other significant findings included effects of caregiver socioeconomic status and placebo-like effects from participation even though the study included no specific treatment. Nevertheless, single questions via smartphones collected over relatively brief periods reliably represent subdomains in standardized behavioral questionnaires, thereby decreasing burden on caregivers.
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