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Molloy CJ, Cooke J, Gatford NJF, Rivera-Olvera A, Avazzadeh S, Homberg JR, Grandjean J, Fernandes C, Shen S, Loth E, Srivastava DP, Gallagher L. Bridging the translational gap: what can synaptopathies tell us about autism? Front Mol Neurosci 2023; 16:1191323. [PMID: 37441676 PMCID: PMC10333541 DOI: 10.3389/fnmol.2023.1191323] [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: 03/21/2023] [Accepted: 05/24/2023] [Indexed: 07/15/2023] Open
Abstract
Multiple molecular pathways and cellular processes have been implicated in the neurobiology of autism and other neurodevelopmental conditions. There is a current focus on synaptic gene conditions, or synaptopathies, which refer to clinical conditions associated with rare genetic variants disrupting genes involved in synaptic biology. Synaptopathies are commonly associated with autism and developmental delay and may be associated with a range of other neuropsychiatric outcomes. Altered synaptic biology is suggested by both preclinical and clinical studies in autism based on evidence of differences in early brain structural development and altered glutamatergic and GABAergic neurotransmission potentially perturbing excitatory and inhibitory balance. This review focusses on the NRXN-NLGN-SHANK pathway, which is implicated in the synaptic assembly, trans-synaptic signalling, and synaptic functioning. We provide an overview of the insights from preclinical molecular studies of the pathway. Concentrating on NRXN1 deletion and SHANK3 mutations, we discuss emerging understanding of cellular processes and electrophysiology from induced pluripotent stem cells (iPSC) models derived from individuals with synaptopathies, neuroimaging and behavioural findings in animal models of Nrxn1 and Shank3 synaptic gene conditions, and key findings regarding autism features, brain and behavioural phenotypes from human clinical studies of synaptopathies. The identification of molecular-based biomarkers from preclinical models aims to advance the development of targeted therapeutic treatments. However, it remains challenging to translate preclinical animal models and iPSC studies to interpret human brain development and autism features. We discuss the existing challenges in preclinical and clinical synaptopathy research, and potential solutions to align methodologies across preclinical and clinical research. Bridging the translational gap between preclinical and clinical studies will be necessary to understand biological mechanisms, to identify targeted therapies, and ultimately to progress towards personalised approaches for complex neurodevelopmental conditions such as autism.
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Affiliation(s)
- Ciara J. Molloy
- Department of Psychiatry, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Jennifer Cooke
- Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Nicholas J. F. Gatford
- Kavli Institute for Nanoscience Discovery, Nuffield Department of Clinical Neurosciences, University of Oxford, Medical Sciences Division, Oxford, United Kingdom
| | - Alejandro Rivera-Olvera
- Donders Institute for Brain, Cognition, and Behaviour, Radboud University Medical Centre, Nijmegen, Netherlands
| | - Sahar Avazzadeh
- Physiology and Cellular Physiology Research Laboratory, CÚRAM SFI Centre for Research in Medical Devices, School of Medicine, Human Biology Building, University of Galway, Galway, Ireland
| | - Judith R. Homberg
- Donders Institute for Brain, Cognition, and Behaviour, Radboud University Medical Centre, Nijmegen, Netherlands
| | - Joanes Grandjean
- Physiology and Cellular Physiology Research Laboratory, CÚRAM SFI Centre for Research in Medical Devices, School of Medicine, Human Biology Building, University of Galway, Galway, Ireland
- Department of Medical Imaging, Radboud University Medical Centre, Nijmegen, Netherlands
| | - Cathy Fernandes
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Sanbing Shen
- Regenerative Medicine Institute, School of Medicine, University of Galway, Galway, Ireland
- FutureNeuro, The SFI Research Centre for Chronic and Rare Neurological Diseases, Royal College of Surgeons, Dublin, Ireland
| | - Eva Loth
- Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Deepak P. Srivastava
- MRC Centre for Neurodevelopmental Disorders, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Louise Gallagher
- Department of Psychiatry, School of Medicine, Trinity College Dublin, Dublin, Ireland
- The Hospital for SickKids, Toronto, ON, Canada
- The Peter Gilgan Centre for Research and Learning, SickKids Research Institute, Toronto, ON, Canada
- The Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
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Davis P, Takach K, Maski K, Levin A. A circuit-level biomarker of Rett syndrome based on ectopic phase-amplitude coupling during slow-wave-sleep. Cereb Cortex 2023; 33:2559-2572. [PMID: 35640651 DOI: 10.1093/cercor/bhac226] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Revised: 05/01/2022] [Accepted: 05/02/2022] [Indexed: 11/13/2022] Open
Abstract
Rett syndrome (RTT) is a neurodevelopmental disorder characterized by loss of purposeful hand use and spoken language following an initial period of normal development. Although much is known about the genetic and molecular underpinnings of RTT, less is known about the circuit-level etiopathology. Coupling of oscillations during slow-wave-sleep (SWS) underlies important neurocognitive processes in adulthood, yet its emergence has yet to be described in early typical development (TD) or in RTT. We therefore addressed these unknowns by describing SWS cross-frequency coupling in both RTT and early TD using a retrospective study design. We found that in TD, phase-amplitude coupling (PAC) during SWS was dominated by coupling of slow-wave (0.5-2 Hz) phase to theta amplitude (5-8 Hz, "SW:T") as well as slow-wave to spindle-range (12-15 Hz, "SW:S"). Coupling exhibited characteristic vertex-prominent spatial topography, which emerged during an early developmental window. This topography failed to develop in patients with RTT due to persistent ectopic coupling. Furthermore, we found that subtypes of RTT exhibit distinct PAC topographic profiles, and that ectopic PAC correlates with clinical severity. These findings suggest that altered PAC dynamics and spatial organization during SWS may underlie the circuit-level pathophysiology of RTT and suggest that ectopic coupling may contribute to RTT pathogenesis.
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Affiliation(s)
- Patrick Davis
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, United States
| | - Kyle Takach
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, United States
- Division of Developmental Medicine, Department of Pediatrics, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, United States
| | - Kiran Maski
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, United States
| | - April Levin
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, United States
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Loth E. Does the current state of biomarker discovery in autism reflect the limits of reductionism in precision medicine? Suggestions for an integrative approach that considers dynamic mechanisms between brain, body, and the social environment. Front Psychiatry 2023; 14:1085445. [PMID: 36911126 PMCID: PMC9992810 DOI: 10.3389/fpsyt.2023.1085445] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 01/23/2023] [Indexed: 02/24/2023] Open
Abstract
Over the past decade, precision medicine has become one of the most influential approaches in biomedical research to improve early detection, diagnosis, and prognosis of clinical conditions and develop mechanism-based therapies tailored to individual characteristics using biomarkers. This perspective article first reviews the origins and concept of precision medicine approaches to autism and summarises recent findings from the first "generation" of biomarker studies. Multi-disciplinary research initiatives created substantially larger, comprehensively characterised cohorts, shifted the focus from group-comparisons to individual variability and subgroups, increased methodological rigour and advanced analytic innovations. However, although several candidate markers with probabilistic value have been identified, separate efforts to divide autism by molecular, brain structural/functional or cognitive markers have not identified a validated diagnostic subgroup. Conversely, studies of specific monogenic subgroups revealed substantial variability in biology and behaviour. The second part discusses both conceptual and methodological factors in these findings. It is argued that the predominant reductionist approach, which seeks to parse complex issues into simpler, more tractable units, let us to neglect the interactions between brain and body, and divorce individuals from their social environment. The third part draws on insights from systems biology, developmental psychology and neurodiversity approaches to outline an integrative approach that considers the dynamic interaction between biological (brain, body) and social mechanisms (stress, stigma) to understanding the origins of autistic features in particular conditions and contexts. This requires 1) closer collaboration with autistic people to increase face validity of concepts and methodologies; (2) development of measures/technologies that enable repeat assessment of social and biological factors in different (naturalistic) conditions and contexts, (3) new analytic methods to study (simulate) these interactions (including emergent properties), and (4) cross-condition designs to understand which mechanisms are transdiagnostic or specific for particular autistic sub-populations. Tailored support may entail both creating more favourable conditions in the social environment and interventions for some autistic people to increase well-being.
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Affiliation(s)
- Eva Loth
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
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Armstrong C, Zavez A, Mulcahey PJ, Sogawa Y, Gotoff JM, Hagopian S, Minnick J, Marsh ED. Quantitative electroencephalographic analysis as a potential biomarker of response to treatment with cannabidiol. Epilepsy Res 2022; 185:106996. [PMID: 35963151 DOI: 10.1016/j.eplepsyres.2022.106996] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Revised: 07/26/2022] [Accepted: 08/04/2022] [Indexed: 02/03/2023]
Abstract
PURPOSE Pharmaceutical grade cannabidiol (CBD) is one of the newest anti-seizure medications for refractory epilepsy, and the effects of CBD on EEG have not been fully described. METHODS Patients enrolled in a CBD expanded access study had EEGs prior to and 12 weeks after initiation of CBD treatment for their refractory epilepsy. In addition to evaluating the clinical EEG reports, a nonbiased quantitative EEG (qEEG) analysis of background EEG was performed to determine whether consistent changes occur in the EEG in response to administration of CBD. RESULTS No significant qualitative changes were seen, nor changes in quantitative markers of EEG amplitude (RMS amplitude, standard deviation of the amplitude, skewness, or kurtosis), frequency (relative delta, theta, or alpha power), Spearman correlation, or coherence between brain regions. However, relative beta power and 1/f slope, a measure of signal noise increased with the addition of CBD. When patients were separated into responders and nonresponders based on seizure reduction with CBD, responders also had decreased Spearman correlation between the frontopolar and occipital regions after addition of CBD, suggesting that responders may have quantitatively improved EEG background organization after CBD initiation. The differences in beta and 1/f slope were also seen more robustly in CBD responders compared with nonresponders after CBD initiation. These differences disappeared when analyzing only patients not taking benzodiazepines, suggesting that the effect of CBD on seizures was related to the ability of the brain to further increase beta in response to CBD in patients already taking benzodiazepines. We noted that even before initiation of CBD, 1/f slope was also significantly different in responders compared to nonresponders. Therefore, to explore the baseline EEG in responders and nonresponders, we utilized a variable selection procedure to identify baseline EEG features that could predict whether a patient's seizures would improve with CBD. In the optimal multivariable logistic model, baseline coherence, Spearman correlation, and patient sex jointly predicted whether a patient in this cohort would respond to CBD (defined as a seizure reduction of 40% or greater) with 74% accuracy. This model performed less well on a data set of reduced duration and variability, highlighting the importance of real-world testing of any clinically relevant model. CONCLUSION These results suggest that there are subtle changes in certain metrics detected by qEEG even at baseline that may not be perceived during qualitative EEG analysis and that could be used in the future as a biomarker to predict a patient's clinical response to CBD administration. Development of such a predictive EEG biomarker, especially before the initiation of a medication trial, could reduce unnecessary ASM exposure and improve outcomes for patients with epilepsy facing new medication selection.
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Affiliation(s)
- Caren Armstrong
- Division of Neurology and Pediatric Epilepsy Program, Children's Hospital of Philadelphia, 3401 Civic Center Blvd., Philadelphia, PA 19104, USA
| | - Alexis Zavez
- Orphan Disease Center, Suite 1200, 125 S 31st St, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Patrick J Mulcahey
- Division of Neurology and Pediatric Epilepsy Program, Children's Hospital of Philadelphia, 3401 Civic Center Blvd., Philadelphia, PA 19104, USA
| | - Yoshimi Sogawa
- UPMC Children's Hospital of Pittsburgh, Pediatric Neurology 4401 Penn Avenue, Pittsburgh, PA 15224, USA
| | - Jill M Gotoff
- Geisinger Medical Center, 100 N Academy Avenue, Danville, PA 17822, USA
| | - Samantha Hagopian
- Division of Neurology and Pediatric Epilepsy Program, Children's Hospital of Philadelphia, 3401 Civic Center Blvd., Philadelphia, PA 19104, USA
| | - Jennie Minnick
- Division of Neurology and Pediatric Epilepsy Program, Children's Hospital of Philadelphia, 3401 Civic Center Blvd., Philadelphia, PA 19104, USA
| | - Eric D Marsh
- Division of Neurology and Pediatric Epilepsy Program, Children's Hospital of Philadelphia, 3401 Civic Center Blvd., Philadelphia, PA 19104, USA; Orphan Disease Center, Suite 1200, 125 S 31st St, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Departments of Pediatrics and Neurology, University of Pennsylvania Perelman School of Medicine, 3400 Spruce St, Philadelphia, PA 19104, USA.
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Electrophysiological and Behavioral Evidence for Hyper- and Hyposensitivity in Rare Genetic Syndromes Associated with Autism. Genes (Basel) 2022; 13:genes13040671. [PMID: 35456477 PMCID: PMC9027402 DOI: 10.3390/genes13040671] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Revised: 03/29/2022] [Accepted: 04/05/2022] [Indexed: 01/27/2023] Open
Abstract
Our study reviewed abnormalities in spontaneous, as well as event-related, brain activity in syndromes with a known genetic underpinning that are associated with autistic symptomatology. Based on behavioral and neurophysiological evidence, we tentatively subdivided the syndromes on primarily hyper-sensitive (Fragile X, Angelman) and hypo-sensitive (Phelan–McDermid, Rett, Tuberous Sclerosis, Neurofibromatosis 1), pointing to the way of segregation of heterogeneous idiopathic ASD, that includes both hyper-sensitive and hypo-sensitive individuals. This segmentation links abnormalities in different genes, such as FMR1, UBE3A, GABRB3, GABRA5, GABRG3, SHANK3, MECP2, TSC1, TSC2, and NF1, that are causative to the above-mentioned syndromes and associated with synaptic transmission and cell growth, as well as with translational and transcriptional regulation and with sensory sensitivity. Excitation/inhibition imbalance related to GABAergic signaling, and the interplay of tonic and phasic inhibition in different brain regions might underlie this relationship. However, more research is needed. As most genetic syndromes are very rare, future investigations in this field will benefit from multi-site collaboration with a common protocol for electrophysiological and event-related potential (EEG/ERP) research that should include an investigation into all modalities and stages of sensory processing, as well as potential biomarkers of GABAergic signaling (such as 40-Hz ASSR).
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Mariscal MG, Levin AR, Gabard-Durnam LJ, Xie W, Tager-Flusberg H, Nelson CA. EEG Phase-Amplitude Coupling Strength and Phase Preference: Association with Age over the First Three Years after Birth. eNeuro 2021; 8:ENEURO.0264-20.2021. [PMID: 34049989 PMCID: PMC8225408 DOI: 10.1523/eneuro.0264-20.2021] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Revised: 04/26/2021] [Accepted: 05/10/2021] [Indexed: 01/11/2023] Open
Abstract
Phase-amplitude coupling (PAC), the coupling of the phase of slower electrophysiological oscillations with the amplitude of faster oscillations, is thought to facilitate dynamic integration of neural activity in the brain. Although the brain undergoes dramatic change and development during the first few years of life, how PAC changes through this developmental period has not been extensively studied. Here, we examined PAC through electroencephalography (EEG) data collected during an awake, eyes-open EEG collection paradigm in 98 children between the ages of three months and three years. We employed non-parametric clustering methods to identify areas of significant PAC across a range of frequency pairs and electrode locations, and examined how PAC strength and phase preference develops in these areas. We found that PAC, primarily between the α-β and γ frequencies, was positively correlated with age from early infancy to early childhood (p = 2.035 × 10-6). Additionally, we found γ over anterior electrodes coupled with the rising phase of the α-β waveform, while γ over posterior electrodes coupled with the falling phase of the α-β waveform; this regionalized phase preference became more prominent with age. This opposing trend may reflect each region's specialization toward feedback or feedforward processing, respectively, suggesting opportunities for back translation in future studies.
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Affiliation(s)
- Michael G Mariscal
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115
| | - April R Levin
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115
| | - Laurel J Gabard-Durnam
- Division of Developmental Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA 02215
| | - Wanze Xie
- Division of Developmental Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA 02215
| | - Helen Tager-Flusberg
- Department of Psychological and Brain Sciences, Boston University, Boston, MA 02215
| | - Charles A Nelson
- Division of Developmental Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA 02215
- Harvard Graduate School of Education, Cambridge, MA 02138
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