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      Mechanisms underlying the EEG biomarker in Dup15q syndrome

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          Abstract

          Background

          Duplications of 15q11.2-q13.1 (Dup15q syndrome), including the paternally imprinted gene UBE3A and three nonimprinted gamma-aminobutyric acid type-A (GABA A) receptor genes, are highly penetrant for neurodevelopmental disorders such as autism spectrum disorder (ASD). To guide targeted treatments of Dup15q syndrome and other forms of ASD, biomarkers are needed that reflect molecular mechanisms of pathology. We recently described a beta EEG phenotype of Dup15q syndrome, but it remains unknown which specific genes drive this phenotype.

          Methods

          To test the hypothesis that UBE3A overexpression is not necessary for the beta EEG phenotype, we compared EEG from a reference cohort of children with Dup15q syndrome ( n = 27) to (1) the pharmacological effects of the GABA A modulator midazolam ( n = 12) on EEG from healthy adults, (2) EEG from typically developing (TD) children ( n = 14), and (3) EEG from two children with duplications of paternal 15q (i.e., the UBE3A-silenced allele).

          Results

          Peak beta power was significantly increased in the reference cohort relative to TD controls. Midazolam administration recapitulated the beta EEG phenotype in healthy adults with a similar peak frequency in central channels ( f = 23.0 Hz) as Dup15q syndrome ( f = 23.1 Hz). Both paternal Dup15q syndrome cases displayed beta power comparable to the reference cohort.

          Conclusions

          Our results suggest a critical role for GABAergic transmission in the Dup15q syndrome beta EEG phenotype, which cannot be explained by UBE3A dysfunction alone. If this mechanism is confirmed, the phenotype may be used as a marker of GABAergic pathology in clinical trials for Dup15q syndrome.

          Electronic supplementary material

          The online version of this article (10.1186/s13229-019-0280-6) contains supplementary material, which is available to authorized users.

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          Most cited references74

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            Advances in autism genetics: on the threshold of a new neurobiology.

            Autism is a heterogeneous syndrome defined by impairments in three core domains: social interaction, language and range of interests. Recent work has led to the identification of several autism susceptibility genes and an increased appreciation of the contribution of de novo and inherited copy number variation. Promising strategies are also being applied to identify common genetic risk variants. Systems biology approaches, including array-based expression profiling, are poised to provide additional insights into this group of disorders, in which heterogeneity, both genetic and phenotypic, is emerging as a dominant theme.
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              Removal of eye activity artifacts from visual event-related potentials in normal and clinical subjects.

              Electrical potentials produced by blinks and eye movements present serious problems for electroencephalographic (EEG) and event-related potential (ERP) data interpretation and analysis, particularly for analysis of data from some clinical populations. Often, all epochs contaminated by large eye artifacts are rejected as unusable, though this may prove unacceptable when blinks and eye movements occur frequently. Frontal channels are often used as reference signals to regress out eye artifacts, but inevitably portions of relevant EEG signals also appearing in EOG channels are thereby eliminated or mixed into other scalp channels. A generally applicable adaptive method for removing artifacts from EEG records based on blind source separation by independent component analysis (ICA) (Neural Computation 7 (1995) 1129; Neural Computation 10(8) (1998) 2103; Neural Computation 11(2) (1999) 606) overcomes these limitations. Results on EEG data collected from 28 normal controls and 22 clinical subjects performing a visual selective attention task show that ICA can be used to effectively detect, separate and remove ocular artifacts from even strongly contaminated EEG recordings. The results compare favorably to those obtained using rejection or regression methods. The ICA method can preserve ERP contributions from all of the recorded trials and all the recorded data channels, even when none of the single trials are artifact-free.
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                Author and article information

                Contributors
                joelfrohlich@gmail.com
                Journal
                Mol Autism
                Mol Autism
                Molecular Autism
                BioMed Central (London )
                2040-2392
                3 July 2019
                3 July 2019
                2019
                : 10
                : 29
                Affiliations
                [1 ]Roche Pharma Research and Early Development, Neuroscience, Ophthalmology and Rare Diseases, Roche Innovation Center Basel, Basel, Switzerland
                [2 ]ISNI 0000 0000 9632 6718, GRID grid.19006.3e, Center for Autism Research and Treatment, , University of California Los Angeles, Semel Institute for Neuroscience, ; Los Angeles, CA 90024 USA
                [3 ]ISNI 0000 0000 9632 6718, GRID grid.19006.3e, Department of Psychology, , University of California Los Angeles, ; 3423 Franz Hall, Los Angeles, CA 90095 USA
                [4 ]ISNI 0000 0004 0386 9246, GRID grid.267301.1, Departments of Neurology, Pediatrics and Anatomy & Neurobiology, , The University of Tennessee Health Science Center, ; 855 Monroe Ave., Link, Memphis, TN 415 USA
                [5 ]ISNI 0000 0000 9064 4811, GRID grid.63984.30, McGill University, , MUHC Research Institute, ; 5252, boul. de Maisonneuve Ouest, 3E.19, Montreal, QC H4A 3S5 Canada
                [6 ]ISNI 0000000419370394, GRID grid.208078.5, Genetics and Genome Sciences, , UConn Health, ; 400 Farmington Avenue, Farmington, CT 06030-6403 USA
                [7 ]ISNI 0000 0000 9632 6718, GRID grid.19006.3e, Department of Psychiatry and Biobehavioral Sciences and Department of Psychology, , University of California Los Angeles, ; Suite A7-460, 760 Westwood Plaza, Los Angeles, CA 90095 USA
                [8 ]ISNI 0000 0000 9632 6718, GRID grid.19006.3e, Department of Neurology and Psychiatry, , David Geffen School of Medicine, ; 710 Westwood Plaza, Los Angeles, CA 90095 USA
                [9 ]ISNI 0000 0001 2156 6853, GRID grid.42505.36, Leonard Davis School of Gerontology, , University of Southern California, ; 3715 McClintock Ave., Suite 228C, California, Los Angeles 90089 USA
                [10 ]ISNI 0000 0000 9632 6718, GRID grid.19006.3e, Department of Molecular and Medical Pharmacology, , David Geffen School of Medicine at UCLA, ; California, Los Angeles 90095 USA
                Author information
                http://orcid.org/0000-0001-8382-4344
                Article
                280
                10.1186/s13229-019-0280-6
                6609401
                31312421
                ebdb4f78-8b06-4d0c-9fab-734b6efb35a0
                © The Author(s). 2019

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 7 March 2019
                : 11 June 2019
                Funding
                Funded by: NIH
                Award ID: U54 HD87101
                Award Recipient :
                Funded by: NIH/NIMH
                Award ID: R01MH101198
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100002889, Foundation for Prader-Willi Research;
                Award ID: Grant #20160852
                Award Recipient :
                Funded by: Dup15q Alliance
                Award ID: 2014460
                Award Recipient :
                Funded by: Shainberg Neuroscience Fund
                Categories
                Research
                Custom metadata
                © The Author(s) 2019

                Neurosciences
                dup15q syndrome,gaba,ube3a,biomarkers,autism,eeg,neurodevelopmental disorders,gabra5,gabrb3,gabrg3
                Neurosciences
                dup15q syndrome, gaba, ube3a, biomarkers, autism, eeg, neurodevelopmental disorders, gabra5, gabrb3, gabrg3

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