1
|
Silver BB, Brooks A, Gerrish K, Tokar EJ. Isolation and Characterization of Cell-Free DNA from Cerebral Organoids. Int J Mol Sci 2024; 25:5522. [PMID: 38791569 PMCID: PMC11121789 DOI: 10.3390/ijms25105522] [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: 04/23/2024] [Revised: 05/09/2024] [Accepted: 05/13/2024] [Indexed: 05/26/2024] Open
Abstract
Early detection of neurological conditions is critical for timely diagnosis and treatment. Identifying cellular-level changes is essential for implementing therapeutic interventions prior to symptomatic disease onset. However, monitoring brain tissue directly through biopsies is invasive and poses a high risk. Bodily fluids such as blood or cerebrospinal fluid contain information in many forms, including proteins and nucleic acids. In particular, cell-free DNA (cfDNA) has potential as a versatile neurological biomarker. Yet, our knowledge of cfDNA released by brain tissue and how cfDNA changes in response to deleterious events within the brain is incomplete. Mapping changes in cfDNA to specific cellular events is difficult in vivo, wherein many tissues contribute to circulating cfDNA. Organoids are tractable systems for examining specific changes consistently in a human background. However, few studies have investigated cfDNA released from organoids. Here, we examined cfDNA isolated from cerebral organoids. We found that cerebral organoids release quantities of cfDNA sufficient for downstream analysis with droplet-digital PCR and whole-genome sequencing. Further, gene ontology analysis of genes aligning with sequenced cfDNA fragments revealed associations with terms related to neurodevelopment and autism spectrum disorder. We conclude that cerebral organoids hold promise as tools for the discovery of cfDNA biomarkers related to neurodevelopmental and neurological disorders.
Collapse
Affiliation(s)
- Brian B. Silver
- Mechanistic Toxicology Branch, Division of Translational Toxicology, National Institute of Environmental Health Sciences, Research Triangle Park, Durham, NC 27709, USA
- Molecular Genomics Core, Division of Intramural Research, National Institute of Environmental Health Sciences, Research Triangle Park, Durham, NC 27709, USA;
| | - Ashley Brooks
- Biostatistics and Computational Biology Branch, Division of Intramural Research, National Institute of Environmental Health Sciences, Research Triangle Park, Durham, NC 27709, USA;
| | - Kevin Gerrish
- Molecular Genomics Core, Division of Intramural Research, National Institute of Environmental Health Sciences, Research Triangle Park, Durham, NC 27709, USA;
| | - Erik J. Tokar
- Mechanistic Toxicology Branch, Division of Translational Toxicology, National Institute of Environmental Health Sciences, Research Triangle Park, Durham, NC 27709, USA
| |
Collapse
|
2
|
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.
Collapse
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
| | | |
Collapse
|
3
|
Karadogan ZN, Tanir Y, Karayagmurlu A, Kucukgergin C, Coskun M. Higher Levels of Galectin-1 and Galectin-3 in Young Subjects with Autism Spectrum Disorder Compared to Unaffected Siblings and Healthy Controls. CLINICAL PSYCHOPHARMACOLOGY AND NEUROSCIENCE : THE OFFICIAL SCIENTIFIC JOURNAL OF THE KOREAN COLLEGE OF NEUROPSYCHOPHARMACOLOGY 2023; 21:749-757. [PMID: 37859448 PMCID: PMC10591161 DOI: 10.9758/cpn.23.1052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Revised: 03/03/2023] [Accepted: 03/18/2023] [Indexed: 10/21/2023]
Abstract
Objective : Despite being highly genetic, the etiology of autism spectrum disorder (ASD), has not yet been clarified. Recent research has focused on the role of neuroinflammation and immune system dysfunction in the pathophysiology of neurodevelopmental disorders including ASD. Galectin-1 and galactin-3 are considered among the biomarkers of neuroinflammation and there has been recent reports on the potential role of galectins in the etiology of neurodevelopmental disorders. However, there has been no study examining the relationship between ASD and galectin levels. Methods : Current study aimed to investigate galectin-1 and galectin-3 serum levels in young subjects with ASD comparing with their unaffected siblings and healthy controls. Results : We found significantly higher levels of galectin-1 in case group compared to both unaffected siblings and healthy controls, and higher levels of galectin-3 in case group compared to healthy controls. However, there was no significant association between galectin-1 and galectin-3 levels with the severity of ASD. Conclusion : Findings of our study may support neuroinflammation hypothesis in the etiology of ASD and the potential role of galectin-1 and galectin-3 as biomarkers.
Collapse
Affiliation(s)
| | - Yasar Tanir
- Departments of Child and Adolescent Psychiatry, Istanbul Medical Faculty, Istanbul University, Istanbul, Turkey
| | - Ali Karayagmurlu
- Departments of Child and Adolescent Psychiatry, Istanbul Medical Faculty, Istanbul University, Istanbul, Turkey
| | - Canan Kucukgergin
- Departments of Medical Biochemistry, Istanbul Medical Faculty, Istanbul University, Istanbul, Turkey
| | - Murat Coskun
- Departments of Child and Adolescent Psychiatry, Istanbul Medical Faculty, Istanbul University, Istanbul, Turkey
| |
Collapse
|
4
|
Smith AM, Donley ELR, Ney DM, Amaral DG, Burrier RE, Natowicz MR. Metabolomic biomarkers in autism: identification of complex dysregulations of cellular bioenergetics. Front Psychiatry 2023; 14:1249578. [PMID: 37928922 PMCID: PMC10622772 DOI: 10.3389/fpsyt.2023.1249578] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Accepted: 08/30/2023] [Indexed: 11/07/2023] Open
Abstract
Autism Spectrum Disorder (ASD or autism) is a phenotypically and etiologically heterogeneous condition. Identifying biomarkers of clinically significant metabolic subtypes of autism could improve understanding of its underlying pathophysiology and potentially lead to more targeted interventions. We hypothesized that the application of metabolite-based biomarker techniques using decision thresholds derived from quantitative measurements could identify autism-associated subpopulations. Metabolomic profiling was carried out in a case-control study of 499 autistic and 209 typically developing (TYP) children, ages 18-48 months, enrolled in the Children's Autism Metabolome Project (CAMP; ClinicalTrials.gov Identifier: NCT02548442). Fifty-four metabolites, associated with amino acid, organic acid, acylcarnitine and purine metabolism as well as microbiome-associated metabolites, were quantified using liquid chromatography-tandem mass spectrometry. Using quantitative thresholds, the concentrations of 4 metabolites and 149 ratios of metabolites were identified as biomarkers, each identifying subpopulations of 4.5-11% of the CAMP autistic population. A subset of 42 biomarkers could identify CAMP autistic individuals with 72% sensitivity and 90% specificity. Many participants were identified by several metabolic biomarkers. Using hierarchical clustering, 30 clusters of biomarkers were created based on participants' biomarker profiles. Metabolic changes associated with the clusters suggest that altered regulation of cellular metabolism, especially of mitochondrial bioenergetics, were common metabolic phenotypes in this cohort of autistic participants. Autism severity and cognitive and developmental impairment were associated with increased lactate, many lactate containing ratios, and the number of biomarker clusters a participant displayed. These studies provide evidence that metabolic phenotyping is feasible and that defined autistic subgroups can lead to enhanced understanding of the underlying pathophysiology and potentially suggest pathways for targeted metabolic treatments.
Collapse
Affiliation(s)
- Alan M. Smith
- Stemina Biomarker Discovery, Inc, Madison, WI, United States
| | | | - Denise M. Ney
- Department of Nutritional Sciences, University of Wisconsin-Madison, Madison, WI, United States
| | - David G. Amaral
- Department of Psychiatry and Behavioral Sciences, The MIND Institute, University of California, Davis, Davis, CA, United States
| | | | - Marvin R. Natowicz
- Pathology and Laboratory Medicine, Genomic Medicine, Neurological and Pediatrics Institutes, Cleveland Clinic, Cleveland, OH, United States
| |
Collapse
|
5
|
Tobe R, Zhu Y, Gleissl T, Rossomanno S, Veenstra-VanderWeele J, Smith J, Hollander E. Predictors of placebo response in three large clinical trials of the V1a receptor antagonist balovaptan in autism spectrum disorder. Neuropsychopharmacology 2023:10.1038/s41386-023-01573-9. [PMID: 37045991 PMCID: PMC10267133 DOI: 10.1038/s41386-023-01573-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Revised: 03/16/2023] [Accepted: 03/21/2023] [Indexed: 04/14/2023]
Abstract
High rates of placebo response are increasingly implicated in failed autism spectrum disorder (ASD) clinical trials. Despite this, there are limited investigations of placebo response in ASD. We sought to identify baseline predictors of placebo response and quantify their influence on clinical scales of interest for three harmonized randomized clinical trials of balovaptan, a V1a receptor antagonist. We employed a two-step approach to identify predictors of placebo response on the Vineland-II two-domain composite (2DC) (primary outcome and a caregiver measure) and Clinical Global Impression (CGI) scale (secondary outcome and a clinician measure). The initial candidate predictor set of variables pertained to participant-level, site-specific, and protocol-related factors. Step 1 aimed to identify influential predictors of placebo response using Least Absolute Shrinkage and Selection Operator (LASSO) regression, while Step 2 quantified the influence of predictors via linear regression. Results were validated through statistical bootstrapping approaches with 500 replications of the analysis dataset. The pooled participant-level dataset included individuals with ASD aged 5 to 62 years (mean age 21 [SD 10]), among which 263 and 172 participants received placebo at Weeks 12 and 24, respectively. Although no influential predictors were identified for CGI, findings for Vineland-II 2DC are robust and informative. Decreased placebo response was predicted by higher baseline Vineland-II 2DC (i.e., more advanced adaptive function), longer trial duration, and European (vs United States) sites, while increased placebo response was predicted by commercial (vs academic) sites, attention deficit hyperactivity disorder and depression. Identification of these factors may be useful in anticipating and mitigating placebo response in drug development efforts in ASD and across developmental and psychiatric conditions.
Collapse
Affiliation(s)
- Russell Tobe
- Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
| | - Yajing Zhu
- F. Hoffmann-La Roche Ltd., Welwyn Garden City, UK
| | | | | | - Jeremy Veenstra-VanderWeele
- Department of Psychiatry, Columbia University, New York, NY, USA
- New York State Psychiatric Institute, New York, NY, USA
| | - Janice Smith
- F. Hoffmann-La Roche Ltd., Welwyn Garden City, UK
| | - Eric Hollander
- Department of Psychiatry and Behavioral Sciences and Albert Einstein College of Medicine, New York, NY, USA
| |
Collapse
|
6
|
Martínez-Lorca M, Gómez Fernández D. Rendimiento de los estímulos visuales en el diagnóstico del TEA por Eye Tracking: Revisión Sistemática. REVISTA DE INVESTIGACIÓN EN LOGOPEDIA 2023. [DOI: 10.5209/rlog.83937] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/11/2023] Open
Abstract
El eye-tracking es una herramienta diagnóstica que tiene como fin el estudio del comportamiento de la mirada a través del escaneo de ojos para observar el seguimiento ocular, cómo se distribuye la mirada y la precisión de los movimientos oculares. Este sistema se ha utilizado con niños/as del Trastorno del Espectro Autista. El objetivo de esta revisión sistemática ha sido analizar el rendimiento de los estímulos visuales en el diagnóstico del TEA por método eye tracking. Para ello, se siguió la metodología PRISMA, realizando una búsqueda en las bases de datos PubMed, Science Direct y Scopus, así como, Reseach Gate. Se seleccionaron 22 artículos que cumplían los criterios de inclusión con experimentos unifactoriales, experimentales factoriales y cuasiexperimentales. Todos los experimentos han tenido un grupo control compuesto de muestra con participantes con desarrollo normotípico y de un grupo de caso compuesto de muestra con participantes TEA. Esta revisión sintetiza en tres categorías en base a las características del estímulo usado en el diagnóstico (estímulos sociales, no sociales y por confrontación), el análisis del rendimiento de los estímulos visuales, de manera que los estímulos sociales y los estímulos por confrontación van a ser eficaces para establecer un diagnóstico preciso de TEA puesto que permiten realizar un cribado de ambos grupos y establecer un riesgo temprano del trastorno.
Collapse
|
7
|
Hsiao JH, An J, Hui VKS, Zheng Y, Chan AB. Understanding the role of eye movement consistency in face recognition and autism through integrating deep neural networks and hidden Markov models. NPJ SCIENCE OF LEARNING 2022; 7:28. [PMID: 36284113 PMCID: PMC9596700 DOI: 10.1038/s41539-022-00139-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Accepted: 08/31/2022] [Indexed: 06/16/2023]
Abstract
Greater eyes-focused eye movement pattern during face recognition is associated with better performance in adults but not in children. We test the hypothesis that higher eye movement consistency across trials, instead of a greater eyes-focused pattern, predicts better performance in children since it reflects capacity in developing visual routines. We first simulated visual routine development through combining deep neural network and hidden Markov model that jointly learn perceptual representations and eye movement strategies for face recognition. The model accounted for the advantage of eyes-focused pattern in adults, and predicted that in children (partially trained models) consistency but not pattern of eye movements predicted recognition performance. This result was then verified with data from typically developing children. In addition, lower eye movement consistency in children was associated with autism diagnosis, particularly autistic traits in social skills. Thus, children's face recognition involves visual routine development through social exposure, indexed by eye movement consistency.
Collapse
Affiliation(s)
- Janet H Hsiao
- Department of Psychology, University of Hong Kong, Hong Kong SAR, China.
- The State Key Laboratory of Brain and Cognitive Sciences, University of Hong Kong, Hong Kong SAR, China.
- The Institute of Data Science, University of Hong Kong, Hong Kong SAR, China.
| | - Jeehye An
- Department of Psychology, University of Hong Kong, Hong Kong SAR, China
| | | | - Yueyuan Zheng
- Department of Psychology, University of Hong Kong, Hong Kong SAR, China
| | - Antoni B Chan
- Department of Computer Science, City University of Hong Kong, Hong Kong SAR, China
| |
Collapse
|
8
|
Jacob S, Anagnostou E, Hollander E, Jou R, McNamara N, Sikich L, Tobe R, Murphy D, McCracken J, Ashford E, Chatham C, Clinch S, Smith J, Sanders K, Murtagh L, Noeldeke J, Veenstra-VanderWeele J. Large multicenter randomized trials in autism: key insights gained from the balovaptan clinical development program. Mol Autism 2022; 13:25. [PMID: 35690870 PMCID: PMC9188723 DOI: 10.1186/s13229-022-00505-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Accepted: 05/31/2022] [Indexed: 12/02/2022] Open
Abstract
BACKGROUND Autism spectrum disorder (ASD) is a common and heterogeneous neurodevelopmental condition that is characterized by the core symptoms of social communication difficulties and restricted and repetitive behaviors. At present, there is an unmet medical need for therapies to ameliorate these core symptoms in order to improve quality of life of autistic individuals. However, several challenges are currently faced by the ASD community relating to the development of pharmacotherapies, namely in the conduct of clinical trials. Balovaptan is a V1a receptor antagonist that has been investigated to improve social communication difficulties in individuals with ASD. In this viewpoint, we draw upon our recent first-hand experiences of the balovaptan clinical development program to describe current challenges of ASD trials. DISCUSSION POINTS The balovaptan trials were conducted in a wide age range of individuals with ASD with the added complexities associated with international trials. When summarizing all three randomized trials of balovaptan, a placebo response was observed across several outcome measures. Placebo response was predicted by greater baseline symptom severity, online recruitment of participants, and less experienced or non-academic trial sites. We also highlight challenges relating to selection of outcome measures in ASD, the impact of baseline characteristics, and the role of expectation bias in influencing trial results. CONCLUSION Taken together, the balovaptan clinical development program has advanced our understanding of the key challenges facing ASD treatment research. The insights gained can be used to inform and improve the design of future clinical trials with the collective aim of developing efficacious therapies to support individuals with ASD.
Collapse
Affiliation(s)
- Suma Jacob
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA.
| | - Evdokia Anagnostou
- Holland Bloorview Kids Rehabilitation Hospital, University of Toronto, Toronto, ON, Canada
| | - Eric Hollander
- Department of Psychiatry and Behavioral Sciences, Albert Einstein College of Medicine, New York, NY, USA
| | - Roger Jou
- Child Study Center, Yale School of Medicine, New Haven, CT, USA
| | - Nora McNamara
- Department of Psychiatry, University Hospitals, Cleveland, OH, USA
| | - Linmarie Sikich
- Department of Psychiatry and Behavioral Sciences, Duke Clinical Research Institute, Duke University School of Medicine, Durham, NC, USA
| | - Russell Tobe
- Nathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA
| | | | - James McCracken
- David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | | | | | | | - Janice Smith
- F. Hoffmann-La Roche Ltd, Welwyn Garden City, UK
| | - Kevin Sanders
- F. Hoffmann-La Roche Ltd, Genentech, South San Francisco, CA, USA
| | | | | | | |
Collapse
|
9
|
Assessment of the Autism Spectrum Disorder Based on Machine Learning and Social Visual Attention: A Systematic Review. J Autism Dev Disord 2021; 52:2187-2202. [PMID: 34101081 PMCID: PMC9021060 DOI: 10.1007/s10803-021-05106-5] [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: 05/21/2021] [Indexed: 10/25/2022]
Abstract
The assessment of autism spectrum disorder (ASD) is based on semi-structured procedures addressed to children and caregivers. Such methods rely on the evaluation of behavioural symptoms rather than on the objective evaluation of psychophysiological underpinnings. Advances in research provided evidence of modern procedures for the early assessment of ASD, involving both machine learning (ML) techniques and biomarkers, as eye movements (EM) towards social stimuli. This systematic review provides a comprehensive discussion of 11 papers regarding the early assessment of ASD based on ML techniques and children's social visual attention (SVA). Evidences suggest ML as a relevant technique for the early assessment of ASD, which might represent a valid biomarker-based procedure to objectively make diagnosis. Limitations and future directions are discussed.
Collapse
|
10
|
Kaliukhovich DA, Manyakov NV, Bangerter A, Ness S, Skalkin A, Boice M, Goodwin MS, Dawson G, Hendren R, Leventhal B, Shic F, Pandina G. Visual Preference for Biological Motion in Children and Adults with Autism Spectrum Disorder: An Eye-Tracking Study. J Autism Dev Disord 2021; 51:2369-2380. [PMID: 32951157 PMCID: PMC8189980 DOI: 10.1007/s10803-020-04707-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2022]
Abstract
Participants with autism spectrum disorder (ASD) (n = 121, mean [SD] age: 14.6 [8.0] years) and typically developing (TD) controls (n = 40, 16.4 [13.3] years) were presented with a series of videos representing biological motion on one side of a computer monitor screen and non-biological motion on the other, while their eye movements were recorded. As predicted, participants with ASD spent less overall time looking at presented stimuli than TD participants (P < 10-3) and showed less preference for biological motion (P < 10-5). Participants with ASD also had greater average latencies than TD participants of the first fixation on both biological (P < 0.01) and non-biological motion (P < 0.02). Findings suggest that individuals with ASD differ from TD individuals on multiple properties of eye movements and biological motion preference.
Collapse
Affiliation(s)
- Dzmitry A. Kaliukhovich
- grid.419619.20000 0004 0623 0341Janssen Pharmaceutica NV, Turnhoutseweg 30, 2340 Beerse, Belgium
| | - Nikolay V. Manyakov
- grid.419619.20000 0004 0623 0341Janssen Pharmaceutica NV, Turnhoutseweg 30, 2340 Beerse, Belgium
| | - Abigail Bangerter
- grid.497530.c0000 0004 0389 4927Janssen Research & Development, LLC, 1125 Trenton-Harbourton Road, Titusville, NJ 08560 USA
| | - Seth Ness
- grid.497530.c0000 0004 0389 4927Janssen Research & Development, LLC, 1125 Trenton-Harbourton Road, Titusville, NJ 08560 USA
| | - Andrew Skalkin
- grid.497530.c0000 0004 0389 4927Janssen Research & Development, LLC, 1125 Trenton-Harbourton Road, Titusville, NJ 08560 USA ,Present Address: DataGrok, Inc., 1800 JFK Blvd Suite 300, PMB 90078, Philadelphia, PA 19103 USA
| | - Matthew Boice
- grid.497530.c0000 0004 0389 4927Janssen Research & Development, LLC, 1125 Trenton-Harbourton Road, Titusville, NJ 08560 USA
| | - Matthew S. Goodwin
- grid.261112.70000 0001 2173 3359Department of Health Sciences, Bouvé College of Health Sciences, Northeastern University, 312E Robinson Hall, 360 Huntington Avenue, Boston, MA 02115 USA
| | - Geraldine Dawson
- grid.26009.3d0000 0004 1936 7961Duke Center for Autism and Brain Development, Duke University School of Medicine, 2608 Erwin Road, Suite 30, Durham, NC 27705 USA
| | - Robert Hendren
- grid.34477.330000000122986657Present Address: Center for Child Health, Behavior and Development, Seattle Children’s Research Institute, Department of Pediatrics, University of Washington School of Medicine, 2001 8th Ave Suite #400, Seattle, WA 98121 USA
| | - Bennett Leventhal
- grid.266102.10000 0001 2297 6811Benioff Children’s Hospital, University of California, San Francisco, 401 Parnassus Ave, Langley Porter, San Francisco, CA 94143-0984 USA
| | - Frederick Shic
- grid.34477.330000000122986657Present Address: Center for Child Health, Behavior and Development, Seattle Children’s Research Institute, Department of Pediatrics, University of Washington School of Medicine, 2001 8th Ave Suite #400, Seattle, WA 98121 USA ,grid.47100.320000000419368710Yale Child Study Center, Yale University School of Medicine, New Haven, USA
| | - Gahan Pandina
- grid.497530.c0000 0004 0389 4927Janssen Research & Development, LLC, 1125 Trenton-Harbourton Road, Titusville, NJ 08560 USA
| |
Collapse
|
11
|
Sadria M, Karimi S, Layton AT. Network centrality analysis of eye-gaze data in autism spectrum disorder. Comput Biol Med 2019; 111:103332. [PMID: 31276943 DOI: 10.1016/j.compbiomed.2019.103332] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2019] [Revised: 06/17/2019] [Accepted: 06/17/2019] [Indexed: 01/14/2023]
Abstract
Individuals suffering from autism spectrum disorder (ASD) exhibit impaired social communication, the manifestations of which include abnormal eye contact and gaze. In this study, we first seek to characterize the spatial and temporal attributes of this atypical eye gaze. To achieve that goal, we analyze and compare eye-tracking data of ASD and typical development (TD) children. A fixation time analysis indicates that ASD children exhibit a distinct gaze pattern when looking at faces, spending significantly more time at the mouth and less at the eyes, compared with TD children. Another goal of this study is to identify an analytic approach that can better reveal differences between the face scanning patterns of ASD and TD children. Face scanning involves transitioning from one area of interest (AOI) to another and is not taken into account by the traditional fixation time analysis. Instead, we apply four network analysis approaches that measure the "importance" of a given AOI: degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality. Degree centrality and eignevector centrality yield statistically significant difference in the mouth and right eye, respectively, between the ASD and TD groups, whereas betweenness centrality reveals statistically significant between-group differences in four AOIs. Closeness centrality yields statistically meaningful differences in three AOIs, but those differences are negligible. Thus, our results suggest that betweenness centrality is the most effective network analysis approach in distinguishing the eye gaze patterns between ASD and TD children.
Collapse
Affiliation(s)
- Mehrshad Sadria
- Department of Applied Mathematics, University of Waterloo, Waterloo, Ontario, N2L 3G1, Canada.
| | - Soroush Karimi
- Department of Physics, Shahid Beheshti University, G.C, Evin, Tehran, 19839, Iran
| | - Anita T Layton
- Department of Applied Mathematics, University of Waterloo, Waterloo, Ontario, N2L 3G1, Canada; Department of Biology and School of Pharmacy, University of Waterloo, Waterloo, Ontario, N2L 3G1, Canada
| |
Collapse
|
12
|
Zamanian Azodi M, Rezaei Tavirani M, Rezaei Tavirani M. Identification of the Key Genes of Autism Spectrum Disorder Through Protein-Protein Interaction Network. Galen Med J 2019; 8:e1367. [PMID: 34466502 PMCID: PMC8343959 DOI: 10.31661/gmj.v0i0.1367] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2018] [Revised: 10/09/2018] [Accepted: 11/17/2018] [Indexed: 12/01/2022] Open
Abstract
Background: Currently, the prevalence of autism spectrum disorder (ASD) is increasing, which widely spurs the interest in the molecular investigation. Thereby, a better understanding of the given disorder mechanisms is likely to be achieved. Bioinformatics suiting protein-protein interactions analysis via the application of high-throughput studies, such as protein array, is one of these achievements. Materials and Methods: The gene expression data from Gene Expression Omnibus (GEO) database were downloaded, and the expression profile of patients with developmental delay and autistic features were analyzed via Cytoscape and its relevant plug-ins. Results: Our findings indicated that EGFR, ACTB, RHOA, CALM1, MAPK1, and JUN genes as the hub-bottlenecks and their related terms could be important in ASD risk. In other words, any expression modification in these genes could trigger dysfunctions in the corresponding biological processes. Conclusion: We suggest that differentially expressed genes could be used as suitable targets for ASD after being validated.
Collapse
Affiliation(s)
- Mona Zamanian Azodi
- Proteomics Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Mostafa Rezaei Tavirani
- Proteomics Research Center, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Majid Rezaei Tavirani
- Faculty of Medicine, Iran University of Medical Sciences, Tehran, Iran
- Correspondence to: Majid Rezaei Tavirani, Faculty of Medicine, Iran University of Medical Sciences, Tehran, Iran Telephon Number: 09183420279 Email Address:
| |
Collapse
|
13
|
Eye-Tracking Research in Autism Spectrum Disorder: What Are We Measuring and for What Purposes? CURRENT DEVELOPMENTAL DISORDERS REPORTS 2019. [DOI: 10.1007/s40474-019-00158-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
|
14
|
Rush AJ. Biomarkers: Where Are We Going? FOCUS (AMERICAN PSYCHIATRIC PUBLISHING) 2018; 16:123. [PMID: 31975906 PMCID: PMC6526842 DOI: 10.1176/appi.focus.20180005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Affiliation(s)
- A John Rush
- Dr. Rush is professor emeritus, Duke-National University of Singapore, Singapore, and adjunct professor at the Department of Psychiatry, Duke University Medical School, Durham, North Carolina, and the Department of Psychiatry, Texas Tech University, Health Sciences Center, Permina Basin
| |
Collapse
|