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Stransky ML, Cobb L, Menon N, Barnard E, Belfleur C, Scahill L, Kuhn J. Reinvigorating the Promise of the National Database for Autism Research (NDAR) to Advance Autism Knowledge. J Autism Dev Disord 2025; 55:385-389. [PMID: 39556299 DOI: 10.1007/s10803-024-06641-7] [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] [Accepted: 10/30/2024] [Indexed: 11/19/2024]
Abstract
The National Institute of Mental Health created the National Database for Autism Research (NDAR) to accelerate autism knowledge through data sharing and collaboration. However, our experience using NDAR reveals systematic challenges across several aspects of data submission, selection, management, and analysis that limit utility of this resource. We describe our NDAR experience in an ongoing project examining autism intervention outcomes among marginalized racial, ethnic, and gender groups. For this study, we planned to gather data from NDAR to conduct an individual participant data meta-analysis. Eighteen studies met inclusion criteria and reported data on participants at more than one point in time on the Vineland Adaptive Behavior Scales (Vineland) and the Autism Diagnostic Observation Schedule (ADOS). The difficulties with submitting, selecting, downloading, and managing data from NDAR posed limitations on data availability and analysis. Of the 3,850 unique participants in the selected studies, data at multiple time points were available for 312 participants on the Vineland and 278 on the ADOS. No participants had data on all assessment domains. To accelerate autism research via data sharing and collaboration with NDAR necessitates improving the processes for submitting, selecting, and managing data.
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Affiliation(s)
- Michelle L Stransky
- Center for the Urban Child and Healthy Family, Boston Medical Center, 801 Albany St, Boston, MA, 02119, USA.
- Department of Pediatrics, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA.
| | - Laneva Cobb
- Marcus Autism Center, Children's Healthcare of Atlanta, Atlanta, GA, USA
| | - Nina Menon
- Department of Pediatrics, Boston Medical Center, Boston, MA, USA
| | - Emily Barnard
- Department of Pediatrics, Boston Medical Center, Boston, MA, USA
| | - Cynthia Belfleur
- Marcus Autism Center, Children's Healthcare of Atlanta, Atlanta, GA, USA
- Morehouse School of Medicine, Atlanta, GA, USA
| | - Lawrence Scahill
- Marcus Autism Center, Children's Healthcare of Atlanta, Atlanta, GA, USA
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA
| | - Jocelyn Kuhn
- Marcus Autism Center, Children's Healthcare of Atlanta, Atlanta, GA, USA
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA
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Al-Beltagi M, Saeed NK, Bediwy AS, Bediwy EA, Elbeltagi R. Decoding the genetic landscape of autism: A comprehensive review. World J Clin Pediatr 2024; 13:98468. [PMID: 39350903 PMCID: PMC11438927 DOI: 10.5409/wjcp.v13.i3.98468] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/26/2024] [Revised: 07/29/2024] [Accepted: 08/01/2024] [Indexed: 08/30/2024] Open
Abstract
BACKGROUND Autism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized by heterogeneous symptoms and genetic underpinnings. Recent advancements in genetic and epigenetic research have provided insights into the intricate mechanisms contributing to ASD, influencing both diagnosis and therapeutic strategies. AIM To explore the genetic architecture of ASD, elucidate mechanistic insights into genetic mutations, and examine gene-environment interactions. METHODS A comprehensive systematic review was conducted, integrating findings from studies on genetic variations, epigenetic mechanisms (such as DNA methylation and histone modifications), and emerging technologies [including Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-Cas9 and single-cell RNA sequencing]. Relevant articles were identified through systematic searches of databases such as PubMed and Google Scholar. RESULTS Genetic studies have identified numerous risk genes and mutations associated with ASD, yet many cases remain unexplained by known factors, suggesting undiscovered genetic components. Mechanistic insights into how these genetic mutations impact neural development and brain connectivity are still evolving. Epigenetic modifications, particularly DNA methylation and non-coding RNAs, also play significant roles in ASD pathogenesis. Emerging technologies like CRISPR-Cas9 and advanced bioinformatics are advancing our understanding by enabling precise genetic editing and analysis of complex genomic data. CONCLUSION Continued research into the genetic and epigenetic underpinnings of ASD is crucial for developing personalized and effective treatments. Collaborative efforts integrating multidisciplinary expertise and international collaborations are essential to address the complexity of ASD and translate genetic discoveries into clinical practice. Addressing unresolved questions and ethical considerations surrounding genetic research will pave the way for improved diagnostic tools and targeted therapies, ultimately enhancing outcomes for individuals affected by ASD.
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Affiliation(s)
- Mohammed Al-Beltagi
- Department of Pediatric, Faculty of Medicine, Tanta University, Alghrabia, Tanta 31511, Egypt
- Department of Pediatric, University Medical Center, King Abdulla Medical City, Arabian Gulf University, Manama 26671, Bahrain
| | - Nermin Kamal Saeed
- Medical Microbiology Section, Department of Pathology, Salmaniya Medical Complex, Ministry of Health, Kingdom of Bahrain, Manama 12, Bahrain
- Medical Microbiology Section, Department of Pathology, Irish Royal College of Surgeon, Muharraq, Busaiteen 15503, Bahrain
| | - Adel Salah Bediwy
- Department of Pulmonology, Faculty of Medicine, Tanta University, Alghrabia, Tanta 31527, Egypt
- Department of Pulmonology, University Medical Center, King Abdulla Medical City, Arabian Gulf University, Manama 26671, Bahrain
| | - Eman A Bediwy
- Internal Medicine, Faculty of Medicine, Tanta University, Algharbia, Tanta 31527, Egypt
| | - Reem Elbeltagi
- Department of Medicine, The Royal College of Surgeons in Ireland-Bahrain, Muharraq, Busiateen 15503, Bahrain
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Anderson JT, Roth JD, Rosenau KA, Dwyer PS, Kuo AA, Martinez-Agosto JA. Enhancing multi-site autism research through the development of a collaborative data platform. Autism Res 2024; 17:1322-1327. [PMID: 38794841 DOI: 10.1002/aur.3167] [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: 11/16/2023] [Accepted: 05/02/2024] [Indexed: 05/26/2024]
Abstract
Data repositories, particularly those storing data on vulnerable populations, increasingly need to carefully consider not only what data is being collected, but how it will be used. As such, the Autism Intervention Research Network on Physical Health (AIR-P) has created the Infrastructure for Collaborative Research (ICR) to establish standards on data collection practices in Autism repositories. The ICR will strive to encourage inter-site collaboration, amplify autistic voices, and widen accessibility to data. The ICR is staged as a three-tiered framework consisting of (1) a request for proposals system, (2) a REDCap-based data repository, and (3) public data dashboards to display aggregate de-identified data. Coupled with a review process including autistic and non-autistic researchers, this framework aims to propel the implementation of equitable autism research, enhance standardization within and between studies, and boost transparency and dissemination of findings. In addition, the inclusion of a contact registry that study participants can opt into creates the base for a robust participant pool. As such, researchers can leverage the platform to identify, reach, and distribute electronic materials to a greater proportion of potential participants who likely fall within their eligibility criteria. By incorporating practices that promote effective communication between researchers and participants, the ICR can facilitate research that is both considerate of and a benefit to autistic people.
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Affiliation(s)
- Jeffrey T Anderson
- Department of Medicine, University of California, Los Angeles, California, USA
| | - Jeffrey D Roth
- Department of Medicine, University of California, Los Angeles, California, USA
| | - Kashia A Rosenau
- Department of Medicine, University of California, Los Angeles, California, USA
| | - Patrick S Dwyer
- Department of Psychology, University of California, Los Angeles, California, USA
- Olga Tennison Autism Research Centre, School of Psychology and Public Health, La Trobe University, Bundoora, Victoria, Australia
| | - Alice A Kuo
- Department of Medicine, University of California, Los Angeles, California, USA
- Department of Pediatrics, University of California, Los Angeles, California, USA
| | - Julian A Martinez-Agosto
- Department of Pediatrics, University of California, Los Angeles, California, USA
- Department of Human Genetics, University of California, Los Angeles, California, USA
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Rippon G. Differently different?: A commentary on the emerging social cognitive neuroscience of female autism. Biol Sex Differ 2024; 15:49. [PMID: 38872228 PMCID: PMC11177439 DOI: 10.1186/s13293-024-00621-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Accepted: 05/23/2024] [Indexed: 06/15/2024] Open
Abstract
Autism is a neurodevelopmental condition, behaviourally identified, which is generally characterised by social communication differences, and restrictive and repetitive patterns of behaviour and interests. It has long been claimed that it is more common in males. This observed preponderance of males in autistic populations has served as a focussing framework in all spheres of autism-related issues, from recognition and diagnosis through to theoretical models and research agendas. One related issue is the near total absence of females in key research areas. For example, this paper reports a review of over 120 brain-imaging studies of social brain processes in autism that reveals that nearly 70% only included male participants or minimal numbers (just one or two) of females. Authors of such studies very rarely report that their cohorts are virtually female-free and discuss their findings as though applicable to all autistic individuals. The absence of females can be linked to exclusionary consequences of autism diagnostic procedures, which have mainly been developed on male-only cohorts. There is clear evidence that disproportionately large numbers of females do not meet diagnostic criteria and are then excluded from ongoing autism research. Another issue is a long-standing assumption that the female autism phenotype is broadly equivalent to that of the male autism phenotype. Thus, models derived from male-based studies could be applicable to females. However, it is now emerging that certain patterns of social behaviour may be very different in females. This includes a specific type of social behaviour called camouflaging or masking, linked to attempts to disguise autistic characteristics. With respect to research in the field of sex/gender cognitive neuroscience, there is emerging evidence of female differences in patterns of connectivity and/or activation in the social brain that are at odds with those reported in previous, male-only studies. Decades of research have excluded or overlooked females on the autistic spectrum, resulting in the construction of inaccurate and misleading cognitive neuroscience models, and missed opportunities to explore the brain bases of this highly complex condition. A note of warning needs to be sounded about inferences drawn from past research, but if future research addresses this problem of male bias, then a deeper understanding of autism as a whole, as well as in previously overlooked females, will start to emerge.
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Affiliation(s)
- Gina Rippon
- Emeritus of Cognitive NeuroImaging, Institute of Health and Neurodevelopment, College of Health and Life Sciences, Aston University, Birmingham, B4 7ET, UK.
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Camilleri LJ, Maras K, Brosnan M. Effective digital support for autism: digital social stories. Front Psychiatry 2024; 14:1272157. [PMID: 38234364 PMCID: PMC10791792 DOI: 10.3389/fpsyt.2023.1272157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Accepted: 11/29/2023] [Indexed: 01/19/2024] Open
Abstract
Social Stories™ is one of the most popular interventions for autistic children and has been researched extensively. However, effectiveness data has been gathered mainly through single-participant designs which generate outcomes which can lack generalizability and social validity. Stories Online For Autism (SOFA) is a digital application which supports the development and delivery of Social Stories in a real-world setting and has the potential to contribute toward furthering (1) Social Stories research and (2) research on digital applications for autism by gathering large data sets from multiple participants. Three data sets (N = 856) were gathered through the SOFA app and were analyzed to investigate three key variables: What predicted closeness-to-goal of the Social Stories (as rated by an adult/parent/guardian, n = 568); the child's comprehension of the Social Stories (assessed by story comprehension questions, n = 127); and the child's rating of the enjoyability of the Social Stories (n = 161). A merged data set then investigated correlations between these three key variables. Age range (≤15), gender, autism diagnosis, and the child's level of language understanding were the potential predictors for these three key variables. Regression analysis indicated that parental closeness-to-goal ratings for their children were highest for children who were younger and more verbal. Regression analysis also indicated that older children scored higher in comprehension assessment, and autistic children rated the Social Stories as more enjoyable. Closeness-to-goal, comprehension scores and enjoyment ratings did not significantly correlate with each other. This is the largest study of Social Stories effectiveness, which was enabled through the collection of data through a digital app from multiple participants. The results indicate that digital social stories are particularly effective for younger verbal children. While this was the case for all children, it was particularly true for autistic children and female (and gender-diverse) children. For the first time, the gathering of large digital data sets has highlighted that while digital Social Stories can be effective for autistic males, they can be more effective for autistic females and gender-diverse autistic individuals. Thus, the SOFA app can support the investigation of the factors which influence Social Stories outcomes that are generalizable and with high social validity.
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Affiliation(s)
- Louis John Camilleri
- Centre for Applied Autism Research (CAAR), University of Bath, Bath, United Kingdom
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Nishimura Y, Kurosawa K. Analysis of Gene-Environment Interactions Related to Developmental Disorders. Front Pharmacol 2022; 13:863664. [PMID: 35370658 PMCID: PMC8969575 DOI: 10.3389/fphar.2022.863664] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Accepted: 03/03/2022] [Indexed: 11/21/2022] Open
Abstract
Various genetic and environmental factors are associated with developmental disorders (DDs). It has been suggested that interaction between genetic and environmental factors (G × E) is involved in the etiology of DDs. There are two major approaches to analyze the interaction: genome-wide and candidate gene-based approaches. In this mini-review, we demonstrate how these approaches can be applied to reveal the G × E related to DDs focusing on zebrafish and mouse models. We also discuss novel approaches to analyze the G × E associated with DDs.
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Affiliation(s)
- Yuhei Nishimura
- Department of Integrative Pharmacology, Mie University Graduate School of Medicine, Tsu, Japan
| | - Kenji Kurosawa
- Division of Medical Genetics, Kanagawa Children’s Medical Center, Yokohama, Japan
- Department of Clinical Dysmorphology, Mie University Graduate School of Medicine, Tsu, Japan
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Carress H, Lawson DJ, Elhaik E. Population genetic considerations for using biobanks as international resources in the pandemic era and beyond. BMC Genomics 2021; 22:351. [PMID: 34001009 PMCID: PMC8127217 DOI: 10.1186/s12864-021-07618-x] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2020] [Accepted: 04/14/2021] [Indexed: 12/11/2022] Open
Abstract
The past years have seen the rise of genomic biobanks and mega-scale meta-analysis of genomic data, which promises to reveal the genetic underpinnings of health and disease. However, the over-representation of Europeans in genomic studies not only limits the global understanding of disease risk but also inhibits viable research into the genomic differences between carriers and patients. Whilst the community has agreed that more diverse samples are required, it is not enough to blindly increase diversity; the diversity must be quantified, compared and annotated to lead to insight. Genetic annotations from separate biobanks need to be comparable and computable and to operate without access to raw data due to privacy concerns. Comparability is key both for regular research and to allow international comparison in response to pandemics. Here, we evaluate the appropriateness of the most common genomic tools used to depict population structure in a standardized and comparable manner. The end goal is to reduce the effects of confounding and learn from genuine variation in genetic effects on phenotypes across populations, which will improve the value of biobanks (locally and internationally), increase the accuracy of association analyses and inform developmental efforts.
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Affiliation(s)
- Hannah Carress
- Department of Animal and Plant Sciences, University of Sheffield, Sheffield, UK
| | - Daniel John Lawson
- School of Mathematics and Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Eran Elhaik
- Department of Animal and Plant Sciences, University of Sheffield, Sheffield, UK. .,Department of Biology, Lund University, Lund, Sweden.
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8
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Mezinska S, Gallagher L, Verbrugge M, Bunnik EM. Ethical issues in genomics research on neurodevelopmental disorders: a critical interpretive review. Hum Genomics 2021; 15:16. [PMID: 33712057 PMCID: PMC7953558 DOI: 10.1186/s40246-021-00317-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2020] [Accepted: 03/04/2021] [Indexed: 11/16/2022] Open
Abstract
Background Genomic research on neurodevelopmental disorders (NDDs), particularly involving minors, combines and amplifies existing research ethics issues for biomedical research. We performed a review of the literature on the ethical issues associated with genomic research involving children affected by NDDs as an aid to researchers to better anticipate and address ethical concerns. Results Qualitative thematic analysis of the included articles revealed themes in three main areas: research design and ethics review, inclusion of research participants, and communication of research results. Ethical issues known to be associated with genomic research in general, such as privacy risks and informed consent/assent, seem especially pressing for NDD participants because of their potentially decreased cognitive abilities, increased vulnerability, and stigma associated with mental health problems. Additionally, there are informational risks: learning genetic information about NDD may have psychological and social impact, not only for the research participant but also for family members. However, there are potential benefits associated with research participation, too: by enrolling in research, the participants may access genetic testing and thus increase their chances of receiving a (genetic) diagnosis for their neurodevelopmental symptoms, prognostic or predictive information about disease progression or the risk of concurrent future disorders. Based on the results of our review, we developed an ethics checklist for genomic research involving children affected by NDDs. Conclusions In setting up and designing genomic research efforts in NDD, researchers should partner with communities of persons with NDDs. Particular attention should be paid to preventing disproportional burdens of research participation of children with NDDs and their siblings, parents and other family members. Researchers should carefully tailor the information and informed consent procedures to avoid therapeutic and diagnostic misconception in NDD research. To better anticipate and address ethical issues in specific NDD studies, we suggest researchers to use the ethics checklist for genomic research involving children affected by NDDs presented in this paper. Supplementary Information The online version contains supplementary material available at 10.1186/s40246-021-00317-4.
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Affiliation(s)
- S Mezinska
- Faculty of Medicine and Institute of Clinical and Preventive Medicine, University of Latvia, Jelgavas Str.3, Riga, LV-1004, Latvia.
| | - L Gallagher
- Discipline of Psychiatry, School of Medicine, Trinity College Dublin, Dublin, Ireland.,Trinity Translational Medicine Institute, St. James Hospital, Dublin 8, Ireland
| | - M Verbrugge
- Department of Medical Ethics, Philosophy and History of Medicine, Erasmus MC, University Medical Centre Rotterdam, PO Box 2400, Rotterdam, 3000, CA, The Netherlands
| | - E M Bunnik
- Department of Medical Ethics, Philosophy and History of Medicine, Erasmus MC, University Medical Centre Rotterdam, PO Box 2400, Rotterdam, 3000, CA, The Netherlands
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Reilly J, Gallagher L, Leader G, Shen S. Coupling of autism genes to tissue-wide expression and dysfunction of synapse, calcium signalling and transcriptional regulation. PLoS One 2020; 15:e0242773. [PMID: 33338084 PMCID: PMC7748153 DOI: 10.1371/journal.pone.0242773] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Accepted: 11/09/2020] [Indexed: 12/11/2022] Open
Abstract
Autism Spectrum Disorder (ASD) is a heterogeneous disorder that is often accompanied with many co-morbidities. Recent genetic studies have identified various pathways from hundreds of candidate risk genes with varying levels of association to ASD. However, it is unknown which pathways are specific to the core symptoms or which are shared by the co-morbidities. We hypothesised that critical ASD candidates should appear widely across different scoring systems, and that comorbidity pathways should be constituted by genes expressed in the relevant tissues. We analysed the Simons Foundation for Autism Research Initiative (SFARI) database and four independently published scoring systems and identified 292 overlapping genes. We examined their mRNA expression using the Genotype-Tissue Expression (GTEx) database and validated protein expression levels using the human protein atlas (HPA) dataset. This led to clustering of the overlapping ASD genes into 2 groups; one with 91 genes primarily expressed in the central nervous system (CNS geneset) and another with 201 genes expressed in both CNS and peripheral tissues (CNS+PT geneset). Bioinformatic analyses showed a high enrichment of CNS development and synaptic transmission in the CNS geneset, and an enrichment of synapse, chromatin remodelling, gene regulation and endocrine signalling in the CNS+PT geneset. Calcium signalling and the glutamatergic synapse were found to be highly interconnected among pathways in the combined geneset. Our analyses demonstrate that 2/3 of ASD genes are expressed beyond the brain, which may impact peripheral function and involve in ASD co-morbidities, and relevant pathways may be explored for the treatment of ASD co-morbidities.
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Affiliation(s)
- Jamie Reilly
- Regenerative Medicine Institute, School of Medicine, Biomedical Science Building, National University of Ireland (NUI) Galway, Galway, Ireland
- * E-mail: (JR); (SS)
| | - Louise Gallagher
- Discipline of Psychiatry, School of Medicine, Trinity College Dublin, Dublin, Ireland
- Trinity Translational Medicine Institute, Trinity Centre for Health Sciences—Trinity College Dublin, St. James’s Hospital, Dublin, Ireland
| | - Geraldine Leader
- Irish Centre for Autism and Neurodevelopmental Research (ICAN), Department of Psychology, National University of Ireland (NUI) Galway, Galway, Ireland
| | - Sanbing Shen
- Regenerative Medicine Institute, School of Medicine, Biomedical Science Building, National University of Ireland (NUI) Galway, Galway, Ireland
- FutureNeuro Research Centre, Royal College of Surgeons in Ireland (RCSI), Dublin, Ireland
- * E-mail: (JR); (SS)
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Hong SJ, Vogelstein JT, Gozzi A, Bernhardt BC, Yeo BTT, Milham MP, Di Martino A. Toward Neurosubtypes in Autism. Biol Psychiatry 2020; 88:111-128. [PMID: 32553193 DOI: 10.1016/j.biopsych.2020.03.022] [Citation(s) in RCA: 93] [Impact Index Per Article: 18.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/23/2019] [Revised: 03/25/2020] [Accepted: 03/28/2020] [Indexed: 12/22/2022]
Abstract
There is a consensus that substantial heterogeneity underlies the neurobiology of autism spectrum disorder (ASD). As such, it has become increasingly clear that a dissection of variation at the molecular, cellular, and brain network domains is a prerequisite for identifying biomarkers. Neuroimaging has been widely used to characterize atypical brain patterns in ASD, although findings have varied across studies. This is due, at least in part, to a failure to account for neurobiological heterogeneity. Here, we summarize emerging data-driven efforts to delineate more homogeneous ASD subgroups at the level of brain structure and function-that is, neurosubtyping. We break this pursuit into key methodological steps: the selection of diagnostic samples, neuroimaging features, algorithms, and validation approaches. Although preliminary and methodologically diverse, current studies generally agree that at least 2 to 4 distinct ASD neurosubtypes may exist. Their identification improved symptom prediction and diagnostic label accuracy above and beyond group average comparisons. Yet, this nascent literature has shed light onto challenges and gaps. These include 1) the need for wider and more deeply transdiagnostic samples collected while minimizing artifacts (e.g., head motion), 2) quantitative and unbiased methods for feature selection and multimodal fusion, 3) greater emphasis on algorithms' ability to capture hybrid dimensional and categorical models of ASD, and 4) systematic independent replications and validations that integrate different units of analyses across multiple scales. Solutions aimed to address these challenges and gaps are discussed for future avenues leading toward a comprehensive understanding of the mechanisms underlying ASD heterogeneity.
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Affiliation(s)
- Seok-Jun Hong
- Center for the Developing Brain, Child Mind Institute, New York
| | - Joshua T Vogelstein
- Department of Biomedical Engineering Institute for Computational Medicine, Kavli Neuroscience Discovery Institute, Johns Hopkins University, Baltimore, Maryland
| | - Alessandro Gozzi
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive Systems, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Boris C Bernhardt
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - B T Thomas Yeo
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, Massachusetts; Department of Electrical and Computer Engineering, Center for Sleep and Cognition, Clinical Imaging Research Centre, N.1 Institute for Health, National University of Singapore; NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore; Centre for Cognitive Neuroscience, Duke-NUS Medical School, Singapore
| | - Michael P Milham
- Center for the Developing Brain, Child Mind Institute, New York; Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute, Orangeburg, New York
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Lombardo MV, Lai MC, Baron-Cohen S. Big data approaches to decomposing heterogeneity across the autism spectrum. Mol Psychiatry 2019; 24:1435-1450. [PMID: 30617272 PMCID: PMC6754748 DOI: 10.1038/s41380-018-0321-0] [Citation(s) in RCA: 265] [Impact Index Per Article: 44.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/08/2018] [Revised: 10/30/2018] [Accepted: 11/12/2018] [Indexed: 12/27/2022]
Abstract
Autism is a diagnostic label based on behavior. While the diagnostic criteria attempt to maximize clinical consensus, it also masks a wide degree of heterogeneity between and within individuals at multiple levels of analysis. Understanding this multi-level heterogeneity is of high clinical and translational importance. Here we present organizing principles to frame research examining multi-level heterogeneity in autism. Theoretical concepts such as 'spectrum' or 'autisms' reflect non-mutually exclusive explanations regarding continuous/dimensional or categorical/qualitative variation between and within individuals. However, common practices of small sample size studies and case-control models are suboptimal for tackling heterogeneity. Big data are an important ingredient for furthering our understanding of heterogeneity in autism. In addition to being 'feature-rich', big data should be both 'broad' (i.e., large sample size) and 'deep' (i.e., multiple levels of data collected on the same individuals). These characteristics increase the likelihood that the study results are more generalizable and facilitate evaluation of the utility of different models of heterogeneity. A model's utility can be measured by its ability to explain clinically or mechanistically important phenomena, and also by explaining how variability manifests across different levels of analysis. The directionality for explaining variability across levels can be bottom-up or top-down, and should include the importance of development for characterizing changes within individuals. While progress can be made with 'supervised' models built upon a priori or theoretically predicted distinctions or dimensions of importance, it will become increasingly important to complement such work with unsupervised data-driven discoveries that leverage unknown and multivariate distinctions within big data. A better understanding of how to model heterogeneity between autistic people will facilitate progress towards precision medicine for symptoms that cause suffering, and person-centered support.
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Affiliation(s)
- Michael V Lombardo
- Department of Psychology, University of Cyprus, Nicosia, Cyprus.
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK.
| | - Meng-Chuan Lai
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
- Centre for Addiction and Mental Health and The Hospital for Sick Children, Department of Psychiatry, University of Toronto, Toronto, ON, Canada
- Department of Psychiatry, National Taiwan University Hospital and College of Medicine, Taipei, Taiwan
| | - Simon Baron-Cohen
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
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Alvares GA, Dawson PA, Dissanayake C, Eapen V, Gratten J, Grove R, Henders A, Heussler H, Lawson L, Masi A, Raymond E, Rose F, Wallace L, Wray NR, Whitehouse AJO. Study protocol for the Australian autism biobank: an international resource to advance autism discovery research. BMC Pediatr 2018; 18:284. [PMID: 30149807 PMCID: PMC6112136 DOI: 10.1186/s12887-018-1255-z] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/14/2017] [Accepted: 08/15/2018] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND The phenotypic and genetic heterogeneity of autism spectrum disorder (ASD) presents considerable challenges in understanding etiological pathways, selecting effective therapies, providing genetic counselling, and predicting clinical outcomes. With advances in genetic and biological research alongside rapid-pace technological innovations, there is an increasing imperative to access large, representative, and diverse cohorts to advance knowledge of ASD. To date, there has not been any single collective effort towards a similar resource in Australia, which has its own unique ethnic and cultural diversity. The Australian Autism Biobank was initiated by the Cooperative Research Centre for Living with Autism (Autism CRC) to establish a large-scale repository of biological samples and detailed clinical information about children diagnosed with ASD to facilitate future discovery research. METHODS The primary group of participants were children with a confirmed diagnosis of ASD, aged between 2 and 17 years, recruited through four sites in Australia. No exclusion criteria regarding language level, cognitive ability, or comorbid conditions were applied to ensure a representative cohort was recruited. Both biological parents and siblings were invited to participate, along with children without a diagnosis of ASD, and children who had been queried for an ASD diagnosis but did not meet diagnostic criteria. All children completed cognitive assessments, with probands and parents completing additional assessments measuring ASD symptomatology. Parents completed questionnaires about their child's medical history and early development. Physical measurements and biological samples (blood, stool, urine, and hair) were collected from children, and physical measurements and blood samples were collected from parents. Samples were sent to a central processing site and placed into long-term storage. DISCUSSION The establishment of this biobank is a valuable international resource incorporating detailed clinical and biological information that will help accelerate the pace of ASD discovery research. Recruitment into this study has also supported the feasibility of large-scale biological sample collection in children diagnosed with ASD with comprehensive phenotyping across a wide range of ages, intellectual abilities, and levels of adaptive functioning. This biological and clinical resource will be open to data access requests from national and international researchers to support future discovery research that will benefit the autistic community.
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Affiliation(s)
- Gail A. Alvares
- Cooperative Research Centre for Living with Autism (Autism CRC), Long Pocket, Brisbane, QLD Australia
- Telethon Kids Institute, University of Western Australia, Perth, WA Australia
| | - Paul A. Dawson
- Cooperative Research Centre for Living with Autism (Autism CRC), Long Pocket, Brisbane, QLD Australia
- Mater Research Institute, The University of Queensland, Brisbane, QLD Australia
| | - Cheryl Dissanayake
- Cooperative Research Centre for Living with Autism (Autism CRC), Long Pocket, Brisbane, QLD Australia
- Olga Tennison Autism Research Centre, La Trobe University, Melbourne, VIC Australia
| | - Valsamma Eapen
- Cooperative Research Centre for Living with Autism (Autism CRC), Long Pocket, Brisbane, QLD Australia
- School of Psychiatry, University of New South Wales, Sydney, NSW Australia
- Academic Unit of Child Psychiatry South West Sydney, Ingham Institute, Liverpool Hospital, Sydney, NSW Australia
| | - Jacob Gratten
- Cooperative Research Centre for Living with Autism (Autism CRC), Long Pocket, Brisbane, QLD Australia
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD Australia
| | - Rachel Grove
- Cooperative Research Centre for Living with Autism (Autism CRC), Long Pocket, Brisbane, QLD Australia
- School of Psychiatry, University of New South Wales, Sydney, NSW Australia
| | - Anjali Henders
- Cooperative Research Centre for Living with Autism (Autism CRC), Long Pocket, Brisbane, QLD Australia
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD Australia
| | - Helen Heussler
- Cooperative Research Centre for Living with Autism (Autism CRC), Long Pocket, Brisbane, QLD Australia
- Mater Research Institute, The University of Queensland, Brisbane, QLD Australia
| | - Lauren Lawson
- Cooperative Research Centre for Living with Autism (Autism CRC), Long Pocket, Brisbane, QLD Australia
- Olga Tennison Autism Research Centre, La Trobe University, Melbourne, VIC Australia
| | - Anne Masi
- Cooperative Research Centre for Living with Autism (Autism CRC), Long Pocket, Brisbane, QLD Australia
- School of Psychiatry, University of New South Wales, Sydney, NSW Australia
| | - Emma Raymond
- Cooperative Research Centre for Living with Autism (Autism CRC), Long Pocket, Brisbane, QLD Australia
- Wesley Medical Research, Brisbane, QLD Australia
| | - Felicity Rose
- Cooperative Research Centre for Living with Autism (Autism CRC), Long Pocket, Brisbane, QLD Australia
| | - Leanne Wallace
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD Australia
| | - Naomi R. Wray
- Cooperative Research Centre for Living with Autism (Autism CRC), Long Pocket, Brisbane, QLD Australia
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD Australia
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD Australia
| | - Andrew J. O. Whitehouse
- Cooperative Research Centre for Living with Autism (Autism CRC), Long Pocket, Brisbane, QLD Australia
- Telethon Kids Institute, University of Western Australia, Perth, WA Australia
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A Brain-Inspired Trust Management Model to Assure Security in a Cloud Based IoT Framework for Neuroscience Applications. Cognit Comput 2018. [DOI: 10.1007/s12559-018-9543-3] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Reilly J, Gallagher L, Chen JL, Leader G, Shen S. Bio-collections in autism research. Mol Autism 2017; 8:34. [PMID: 28702161 PMCID: PMC5504648 DOI: 10.1186/s13229-017-0154-8] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2017] [Accepted: 06/23/2017] [Indexed: 01/06/2023] Open
Abstract
Autism spectrum disorder (ASD) is a group of complex neurodevelopmental disorders with diverse clinical manifestations and symptoms. In the last 10 years, there have been significant advances in understanding the genetic basis for ASD, critically supported through the establishment of ASD bio-collections and application in research. Here, we summarise a selection of major ASD bio-collections and their associated findings. Collectively, these include mapping ASD candidate genes, assessing the nature and frequency of gene mutations and their association with ASD clinical subgroups, insights into related molecular pathways such as the synapses, chromatin remodelling, transcription and ASD-related brain regions. We also briefly review emerging studies on the use of induced pluripotent stem cells (iPSCs) to potentially model ASD in culture. These provide deeper insight into ASD progression during development and could generate human cell models for drug screening. Finally, we provide perspectives concerning the utilities of ASD bio-collections and limitations, and highlight considerations in setting up a new bio-collection for ASD research.
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Affiliation(s)
- Jamie Reilly
- Regenerative Medicine Institute, School of Medicine, BioMedical Sciences Building, National University of Ireland (NUI), Galway, Ireland
| | - Louise Gallagher
- Trinity Translational Medicine Institute and Department of Psychiatry, Trinity Centre for Health Sciences, St. James Hospital Street, Dublin 8, Ireland
| | - June L. Chen
- Department of Special Education, Faculty of Education, East China Normal University, Shanghai, 200062 China
| | - Geraldine Leader
- Irish Centre for Autism and Neurodevelopmental Research (ICAN), Department of Psychology, National University of Ireland Galway, University Road, Galway, Ireland
| | - Sanbing Shen
- Regenerative Medicine Institute, School of Medicine, BioMedical Sciences Building, National University of Ireland (NUI), Galway, Ireland
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