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Aydin Ü, Cañigueral R, Tye C, McLoughlin G. Face processing in young adults with autism and ADHD: An event related potentials study. Front Psychiatry 2023; 14:1080681. [PMID: 36998627 PMCID: PMC10043418 DOI: 10.3389/fpsyt.2023.1080681] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Accepted: 02/14/2023] [Indexed: 03/18/2023] Open
Abstract
Background Atypicalities in perception and interpretation of faces and emotional facial expressions have been reported in both autism and attention-deficit/hyperactivity disorder (ADHD) during childhood and adulthood. Investigation of face processing during young adulthood (18 to 25 years), a transition period to full-fledged adulthood, could provide important information on the adult outcomes of autism and ADHD. Methods In this study, we investigated event-related potentials (ERPs) related to visual face processing in autism, ADHD, and co-occurring autism and ADHD in a large sample of young adults (N = 566). The groups were based on the Diagnostic Interview for ADHD in Adults 2.0 (DIVA-2) and the Autism Diagnostic Observation Schedule-2 (ADOS-2). We analyzed ERPs from two passive viewing tasks previously used in childhood investigations: (1) upright and inverted faces with direct or averted gaze; (2) faces expressing different emotions. Results Across both tasks, we consistently found lower amplitude and longer latency of N170 in participants with autism compared to those without. Longer P1 latencies and smaller P3 amplitudes in response to emotional expressions and longer P3 latencies for upright faces were also characteristic to the autistic group. Those with ADHD had longer N170 latencies, specific to the face-gaze task. Individuals with both autism and ADHD showed additional alterations in gaze modulation and a lack of the face inversion effect indexed by a delayed N170. Conclusion Alterations in N170 for autistic young adults is largely consistent with studies on autistic adults, and some studies in autistic children. These findings suggest that there are identifiable and measurable socio-functional atypicalities in young adults with autism.
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Affiliation(s)
- Ümit Aydin
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
- School of Psychology and Clinical Language Sciences, University of Reading, Reading, United Kingdom
| | - Roser Cañigueral
- Department of Clinical, Educational and Health Psychology, University College London, London, United Kingdom
| | - Charlotte Tye
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
- Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Gráinne McLoughlin
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
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2
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Aydin Ü, Capp SJ, Tye C, Colvert E, Lau‐Zhu A, Rijsdijk F, Palmer J, McLoughlin G. Quality of life, functional impairment and continuous performance task event‐related potentials (ERPs) in young adults with ADHD and autism: A twin study. JCPP ADVANCES 2022. [DOI: 10.1002/jcv2.12090] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Affiliation(s)
- Ümit Aydin
- Social, Genetic & Developmental Psychiatry Centre Institute of Psychiatry, Psychology & Neuroscience King's College London London UK
| | - Simone J. Capp
- Social, Genetic & Developmental Psychiatry Centre Institute of Psychiatry, Psychology & Neuroscience King's College London London UK
| | - Charlotte Tye
- Department of Child and Adolescent Psychiatry Institute of Psychiatry, Psychology & Neuroscience King's College London London UK
- Department of Psychology Institute of Psychiatry, Psychology & Neuroscience King's College London London UK
| | - Emma Colvert
- Social, Genetic & Developmental Psychiatry Centre Institute of Psychiatry, Psychology & Neuroscience King's College London London UK
| | - Alex Lau‐Zhu
- Social, Genetic & Developmental Psychiatry Centre Institute of Psychiatry, Psychology & Neuroscience King's College London London UK
- Oxford Institute for Clinical Psychology Training and Research Medical Sciences Division University of Oxford Oxford UK
| | - Frühling Rijsdijk
- Social, Genetic & Developmental Psychiatry Centre Institute of Psychiatry, Psychology & Neuroscience King's College London London UK
- Psychology Department Faculty of Social Sciences Anton de Kom University Paramaribo Suriname
| | - Jason Palmer
- Endowed Research Department of Clinical Neuroengineering Global Center for Medical Engineering and Informatics Osaka University Suita Japan
| | - Gráinne McLoughlin
- Social, Genetic & Developmental Psychiatry Centre Institute of Psychiatry, Psychology & Neuroscience King's College London London UK
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3
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The Interactive Effect of Genetic and Epigenetic Variations in FKBP5 and ApoE Genes on Anxiety and Brain EEG Parameters. Genes (Basel) 2022; 13:genes13020164. [PMID: 35205209 PMCID: PMC8872390 DOI: 10.3390/genes13020164] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2021] [Revised: 01/11/2022] [Accepted: 01/13/2022] [Indexed: 02/04/2023] Open
Abstract
FKBP51 is a key stress-responsive regulator of the hypothalamic–pituitary–adrenal axis. To elucidate the contribution of rs1360780 FKBP5 C/T alleles to aging and longevity, we genotyped FKBP5 in a cohort of 800 non-demented and Alzheimer’s disease (AD) subjects of different age, taking into account the allele state of ApoE ε4, the major risk factor for AD. Furthermore, we searched for the association of FKBP5 with subcohorts of non-demented subjects evaluated for anxiety and resting-state quantitative EEG characteristics, associated with cognitive, emotional, and functional brain activities. We observed that increased state anxiety scores depend on the combination of the FKBP5 and ApoE genotypes and on the DNA methylation state of the FKBP5 promoter and ApoE genotype. We also found a significant gender-dependent correlation between FKBP5 promoter methylation and alpha-, delta-, and theta-rhythms. Analysis of the FKBP5 expression in an independent cohort revealed a significant upregulation of FKBP5 in females versus males. Our data suggest a synergistic effect of the stress-associated (FKBP5) and neurodegeneration-associated (ApoE) gene alleles on anxiety and the gender-dependent effect of FKBP5 on neurophysiological brain activity.
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4
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Wallace J, Yahia-Cherif L, Gitton C, Hugueville L, Lemaréchal JD, Selmaoui B. Human resting-state EEG and radiofrequency GSM mobile phone exposure: the impact of the individual alpha frequency. Int J Radiat Biol 2021; 98:986-995. [PMID: 34797205 DOI: 10.1080/09553002.2021.2009146] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
PURPOSE With the extensive use of mobile phone (MP), several studies have been realized to investigate the effects of radiofrequency electromagnetic fields (RF-EMF) exposure on brain activity at rest via electroencephalography (EEG), and the most consistent effect has been seen on the alpha band power spectral density (PSD). However, some studies reported an increase or a decrease of the PSD, while others showed no effect. It has been suggested that these differences might partly be due to a variability of the physiological state of the brain between subjects. So, the aim of this study was to investigate the alpha band modulation, exploring the impact of the alpha band frequency ranges applied in the PSD analysis. MATERIALS AND METHODS Twenty-one healthy volunteers took part to the study with a double-blind, randomized and counterbalanced crossover design, during which eyes-open (EO) and eyes-closed (EC) resting-state EEG was recorded. The exposure system was a sham or a real GSM (global system for mobile) 900 MHz MP (pulse modulated at 217 Hz, mean power of 250 mW and 2 W peak, with a maximum specific absorption rate of 0.70 W/kg on 1 g tissue). The experimental protocol presented a baseline recording phase without MP exposure, an exposure phase during which the exposure system was placed against the left ear, and the post-exposure phase without MP. EEG data from baseline and exposure phases were analyzed and PSD was computed for the alpha band in the fixed range of 8-12 Hz and for the individual alpha band frequency range (IAF). RESULTS Results showed a trend in decrease or increase of EEG power of both alpha oscillations during exposure in relation to EC and EO recording conditions, respectively, but not reaching statistical significance. Findings did not provide evidence for a different sensitivity to RF-EMF MP related to individual variability in the frequency of the alpha band. CONCLUSION In conclusion, these results did not show alpha band activity modulation during resting-state under RF-EMF. It might be argued the need of a delay after the exposure in order to appreciate an EEG spectral power modulation related to RF-EMF exposure.
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Affiliation(s)
- Jasmina Wallace
- Department of Experimental Toxicology and Modeling (TEAM), Institut National de l'Environnement Industriel et des Risques (INERIS), Verneuil-en-Halatte, France.,PériTox Laboratory, UMR-I 01 INERIS, Université de Picardie Jules Verne, Amiens, France.,Department of Biological Radiation Effect, Emergent Risk Technologies Unit, French Armed Forces Biomedical Research Institute (IRBA), Bretigny-sur-Orge, France
| | - Lydia Yahia-Cherif
- Centre De NeuroImagerie De Recherche (CENIR), Institut du Cerveau et de la Moelle épinière (ICM), Paris, France.,Inserm U 1127, CNRS UMR 7225, Sorbonne Université, Institut du Cerveau et de la Moelle épinière (ICM), Paris, France
| | - Christophe Gitton
- Centre De NeuroImagerie De Recherche (CENIR), Institut du Cerveau et de la Moelle épinière (ICM), Paris, France.,Inserm U 1127, CNRS UMR 7225, Sorbonne Université, Institut du Cerveau et de la Moelle épinière (ICM), Paris, France
| | - Laurent Hugueville
- Centre De NeuroImagerie De Recherche (CENIR), Institut du Cerveau et de la Moelle épinière (ICM), Paris, France.,Inserm U 1127, CNRS UMR 7225, Sorbonne Université, Institut du Cerveau et de la Moelle épinière (ICM), Paris, France
| | - Jean-Didier Lemaréchal
- Centre De NeuroImagerie De Recherche (CENIR), Institut du Cerveau et de la Moelle épinière (ICM), Paris, France.,Inserm U 1127, CNRS UMR 7225, Sorbonne Université, Institut du Cerveau et de la Moelle épinière (ICM), Paris, France
| | - Brahim Selmaoui
- Department of Experimental Toxicology and Modeling (TEAM), Institut National de l'Environnement Industriel et des Risques (INERIS), Verneuil-en-Halatte, France.,PériTox Laboratory, UMR-I 01 INERIS, Université de Picardie Jules Verne, Amiens, France
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5
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Smit DJA, Andreassen OA, Boomsma DI, Burwell SJ, Chorlian DB, de Geus EJC, Elvsåshagen T, Gordon RL, Harper J, Hegerl U, Hensch T, Iacono WG, Jawinski P, Jönsson EG, Luykx JJ, Magne CL, Malone SM, Medland SE, Meyers JL, Moberget T, Porjesz B, Sander C, Sisodiya SM, Thompson PM, van Beijsterveldt CEM, van Dellen E, Via M, Wright MJ. Large-scale collaboration in ENIGMA-EEG: A perspective on the meta-analytic approach to link neurological and psychiatric liability genes to electrophysiological brain activity. Brain Behav 2021; 11:e02188. [PMID: 34291596 PMCID: PMC8413828 DOI: 10.1002/brb3.2188] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Revised: 03/12/2021] [Accepted: 04/30/2021] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND AND PURPOSE The ENIGMA-EEG working group was established to enable large-scale international collaborations among cohorts that investigate the genetics of brain function measured with electroencephalography (EEG). In this perspective, we will discuss why analyzing the genetics of functional brain activity may be crucial for understanding how neurological and psychiatric liability genes affect the brain. METHODS We summarize how we have performed our currently largest genome-wide association study of oscillatory brain activity in EEG recordings by meta-analyzing the results across five participating cohorts, resulting in the first genome-wide significant hits for oscillatory brain function located in/near genes that were previously associated with psychiatric disorders. We describe how we have tackled methodological issues surrounding genetic meta-analysis of EEG features. We discuss the importance of harmonizing EEG signal processing, cleaning, and feature extraction. Finally, we explain our selection of EEG features currently being investigated, including the temporal dynamics of oscillations and the connectivity network based on synchronization of oscillations. RESULTS We present data that show how to perform systematic quality control and evaluate how choices in reference electrode and montage affect individual differences in EEG parameters. CONCLUSION The long list of potential challenges to our large-scale meta-analytic approach requires extensive effort and organization between participating cohorts; however, our perspective shows that these challenges are surmountable. Our perspective argues that elucidating the genetic of EEG oscillatory activity is a worthwhile effort in order to elucidate the pathway from gene to disease liability.
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Affiliation(s)
- Dirk J A Smit
- Department of Psychiatry, Amsterdam Neuroscience, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Ole A Andreassen
- Norwegian Centre for Mental Disorders Research (NORMENT), Oslo University Hospital, Oslo, Norway.,Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Scott J Burwell
- Department of Psychology, Minnesota Center for Twin and Family Research, University of Minnesota, Minneapolis, MN, USA.,Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA
| | - David B Chorlian
- Henri Begleiter Neurodynamics Laboratory, Department of Psychiatry, Downstate Health Sciences University, Brooklyn, NY, USA
| | - Eco J C de Geus
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Torbjørn Elvsåshagen
- Norwegian Centre for Mental Disorders Research (NORMENT), Oslo University Hospital, Oslo, Norway.,Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,Department of Neurology, Oslo University Hospital, Oslo, Norway
| | - Reyna L Gordon
- Department of Otolaryngology, Vanderbilt University Medical Center, Nashville, TN, USA.,Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA.,Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA
| | - Jeremy Harper
- Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA
| | - Ulrich Hegerl
- Department of Psychiatry, Psychosomatics, and Psychotherapy, Goethe Universität Frankfurt am Main, Frankfurt, Germany
| | - Tilman Hensch
- Department of Psychiatry and Psychotherapy, University of Leipzig Medical Center, Leipzig, Germany.,LIFE - Leipzig Research Center for Civilization Diseases, Universität Leipzig, Leipzig, Germany.,IU International University, Erfurt, Germany
| | - William G Iacono
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Philippe Jawinski
- LIFE - Leipzig Research Center for Civilization Diseases, Universität Leipzig, Leipzig, Germany.,Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Erik G Jönsson
- TOP-Norment, Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,Department of Clinical Neuroscience, Centre for Psychiatric Research, Karolinska Institutet & Stockholm Health Care Services, Stockholm Region, Stockholm, Sweden
| | - Jurjen J Luykx
- Department of Psychiatry, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.,Department of Translational Neuroscience, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.,Outpatient Second Opinion Clinic, GGNet Mental Health, Apeldoorn, The Netherlands
| | - Cyrille L Magne
- Psychology Department, Middle Tennessee State University, Murfreesboro, TN, USA.,Literacy Studies Ph.D. Program, Middle Tennessee State University, Mufreesboro, TN, USA
| | - Stephen M Malone
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Sarah E Medland
- QIMR Berghofer Medical Research Institute, Herston, QLD, Australia
| | - Jacquelyn L Meyers
- Henri Begleiter Neurodynamics Laboratory, Department of Psychiatry, Downstate Health Sciences University, Brooklyn, NY, USA.,Department of Psychiatry, State University of New York Downstate Health Sciences University, Brooklyn, NY, USA
| | - Torgeir Moberget
- Department of Psychiatry, Amsterdam Neuroscience, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.,Department of Psychology, Faculty of Social Sciences, University of Oslo, Oslo, Norway
| | - Bernice Porjesz
- Henri Begleiter Neurodynamics Laboratory, Department of Psychiatry, Downstate Health Sciences University, Brooklyn, NY, USA
| | - Christian Sander
- Department of Psychiatry and Psychotherapy, University of Leipzig Medical Center, Leipzig, Germany
| | - Sanjay M Sisodiya
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK.,Chalfont Centre for Epilepsy, Chalfont-St-Peter, UK
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | | | - Edwin van Dellen
- Department of Psychiatry, Department of Intensive Care Medicine, Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Marc Via
- Brainlab-Cognitive Neuroscience Research Group, Department of Clinical Psychology and Psychobiology, and Institute of Neurosciences (UBNeuro), Universitat de Barcelona, Barcelona, Spain.,Institut de Recerca Sant Joan de Déu (IRSJD), Esplugues de Llobregat, Spain
| | - Margaret J Wright
- Queensland Brain Institute, University of Queensland, Brisbane, QLD, Australia.,Centre for Advanced Imaging, University of Queensland, Brisbane, QLD, Australia
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6
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Harper J, Liu M, Malone SM, McGue M, Iacono WG, Vrieze SI. Using multivariate endophenotypes to identify psychophysiological mechanisms associated with polygenic scores for substance use, schizophrenia, and education attainment. Psychol Med 2021; 52:1-11. [PMID: 33731234 PMCID: PMC8448784 DOI: 10.1017/s0033291721000763] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/16/2020] [Revised: 02/16/2021] [Accepted: 02/17/2021] [Indexed: 11/29/2022]
Abstract
BACKGROUND To better characterize brain-based mechanisms of polygenic liability for psychopathology and psychological traits, we extended our previous report (Liu et al. Psychophysiological endophenotypes to characterize mechanisms of known schizophrenia genetic loci. Psychological Medicine, 2017), focused solely on schizophrenia, to test the association between multivariate psychophysiological candidate endophenotypes (including novel measures of θ/δ oscillatory activity) and a range of polygenic scores (PGSs), namely alcohol/cannabis/nicotine use, an updated schizophrenia PGS (containing 52 more genome-wide significant loci than the PGS used in our previous report) and educational attainment. METHOD A large community-based twin/family sample (N = 4893) was genome-wide genotyped and imputed. PGSs were constructed for alcohol use, regular smoking initiation, lifetime cannabis use, schizophrenia, and educational attainment. Eleven endophenotypes were assessed: visual oddball task event-related electroencephalogram (EEG) measures (target-related parietal P3 amplitude, frontal θ, and parietal δ energy/inter-trial phase clustering), band-limited resting-state EEG power, antisaccade error rate. Principal component analysis exploited covariation among endophenotypes to extract a smaller number of meaningful dimensions/components for statistical analysis. RESULTS Endophenotypes were heritable. PGSs showed expected intercorrelations (e.g. schizophrenia PGS correlated positively with alcohol/nicotine/cannabis PGSs). Schizophrenia PGS was negatively associated with an event-related P3/δ component [β = -0.032, nonparametric bootstrap 95% confidence interval (CI) -0.059 to -0.003]. A prefrontal control component (event-related θ/antisaccade errors) was negatively associated with alcohol (β = -0.034, 95% CI -0.063 to -0.006) and regular smoking PGSs (β = -0.032, 95% CI -0.061 to -0.005) and positively associated with educational attainment PGS (β = 0.031, 95% CI 0.003-0.058). CONCLUSIONS Evidence suggests that multivariate endophenotypes of decision-making (P3/δ) and cognitive/attentional control (θ/antisaccade error) relate to alcohol/nicotine, schizophrenia, and educational attainment PGSs and represent promising targets for future research.
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Affiliation(s)
- Jeremy Harper
- Department of Psychiatry & Behavioral Sciences, University of Minnesota, Twin Cities, MN, USA
| | - Mengzhen Liu
- Department of Psychology, University of Minnesota, Twin Cities, MN, USA
| | - Stephen M. Malone
- Department of Psychology, University of Minnesota, Twin Cities, MN, USA
| | - Matt McGue
- Department of Psychology, University of Minnesota, Twin Cities, MN, USA
| | - William G. Iacono
- Department of Psychology, University of Minnesota, Twin Cities, MN, USA
| | - Scott I. Vrieze
- Department of Psychology, University of Minnesota, Twin Cities, MN, USA
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7
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Rebelo MÂ, Gómez C, Gomes I, Poza J, Martins S, Maturana-Candelas A, Ruiz-Gómez SJ, Durães L, Sousa P, Figueruelo M, Rodríguez M, Pita C, Arenas M, Álvarez L, Hornero R, Pinto N, Lopes AM. Genome-Wide Scan for Five Brain Oscillatory Phenotypes Identifies a New QTL Associated with Theta EEG Band. Brain Sci 2020; 10:brainsci10110870. [PMID: 33218114 PMCID: PMC7698967 DOI: 10.3390/brainsci10110870] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Revised: 11/06/2020] [Accepted: 11/10/2020] [Indexed: 11/17/2022] Open
Abstract
Brain waves, measured by electroencephalography (EEG), are a powerful tool in the investigation of neurophysiological traits and a noninvasive and cost-effective alternative in the diagnostic of some neurological diseases. In order to identify novel Quantitative Trait Loci (QTLs) for brain wave relative power (RP), we collected resting state EEG data in five frequency bands (δ, θ, α, β1, and β2) and genome-wide data in a cohort of 105 patients with late onset Alzheimer’s disease (LOAD), 41 individuals with mild cognitive impairment and 45 controls from Iberia, correcting for disease status. One novel association was found with an interesting candidate for a role in brain wave biology, CLEC16A (C-type lectin domain family 16), with a variant at this locus passing the adjusted genome-wide significance threshold after Bonferroni correction. This finding reinforces the importance of immune regulation in brain function. Additionally, at a significance cutoff value of 5 × 10−6, 18 independent association signals were detected. These signals comprise brain expression Quantitative Loci (eQTLs) in caudate basal ganglia, spinal cord, anterior cingulate cortex and hypothalamus, as well as chromatin interactions in adult and fetal cortex, neural progenitor cells and hippocampus. Moreover, in the set of genes showing signals of association with brain wave RP in our dataset, there is an overrepresentation of loci previously associated with neurological traits and pathologies, evidencing the pleiotropy of the genetic variation modulating brain function.
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Affiliation(s)
- Miguel Ângelo Rebelo
- IPATIMUP—Instituto de Patologia e Imunologia Molecular da Universidade do Porto, 4200-135 Porto, Portugal; (M.Â.R.); (I.G.); (S.M.); (A.M.L.)
- I3S—Instituto de Investigação e Inovação em Saúde, Universidade do Porto, 4200-135 Porto, Portugal
| | - Carlos Gómez
- Grupo de Ingeniería Biomédica, Universidad de Valladolid, 47011 Valladolid, Spain; (J.P.); (A.M.-C.); (S.J.R.-G.); (R.H.)
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), 47011 Valladolid, Spain
- Correspondence: (C.G.); (N.P.)
| | - Iva Gomes
- IPATIMUP—Instituto de Patologia e Imunologia Molecular da Universidade do Porto, 4200-135 Porto, Portugal; (M.Â.R.); (I.G.); (S.M.); (A.M.L.)
- I3S—Instituto de Investigação e Inovação em Saúde, Universidade do Porto, 4200-135 Porto, Portugal
| | - Jesús Poza
- Grupo de Ingeniería Biomédica, Universidad de Valladolid, 47011 Valladolid, Spain; (J.P.); (A.M.-C.); (S.J.R.-G.); (R.H.)
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), 47011 Valladolid, Spain
- Instituto de Investigación en Matemáticas (IMUVA), Universidad de Valladolid, 47011 Valladolid, Spain
| | - Sandra Martins
- IPATIMUP—Instituto de Patologia e Imunologia Molecular da Universidade do Porto, 4200-135 Porto, Portugal; (M.Â.R.); (I.G.); (S.M.); (A.M.L.)
- I3S—Instituto de Investigação e Inovação em Saúde, Universidade do Porto, 4200-135 Porto, Portugal
| | - Aarón Maturana-Candelas
- Grupo de Ingeniería Biomédica, Universidad de Valladolid, 47011 Valladolid, Spain; (J.P.); (A.M.-C.); (S.J.R.-G.); (R.H.)
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), 47011 Valladolid, Spain
| | - Saúl J. Ruiz-Gómez
- Grupo de Ingeniería Biomédica, Universidad de Valladolid, 47011 Valladolid, Spain; (J.P.); (A.M.-C.); (S.J.R.-G.); (R.H.)
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), 47011 Valladolid, Spain
| | - Luis Durães
- Associação Portuguesa de Familiares e Amigos de Doentes de Alzheimer, Delegação Norte, 4455-301 Lavra, Portugal; (L.D.); (P.S.)
| | - Patrícia Sousa
- Associação Portuguesa de Familiares e Amigos de Doentes de Alzheimer, Delegação Norte, 4455-301 Lavra, Portugal; (L.D.); (P.S.)
| | - Manuel Figueruelo
- Asociación de Familiares y Amigos de Enfermos de Alzheimer y otras demencias de Zamora, 49021 Zamora, Spain; (M.F.); (M.R.); (C.P.)
| | - María Rodríguez
- Asociación de Familiares y Amigos de Enfermos de Alzheimer y otras demencias de Zamora, 49021 Zamora, Spain; (M.F.); (M.R.); (C.P.)
| | - Carmen Pita
- Asociación de Familiares y Amigos de Enfermos de Alzheimer y otras demencias de Zamora, 49021 Zamora, Spain; (M.F.); (M.R.); (C.P.)
| | - Miguel Arenas
- Department of Biochemistry, Genetics and Immunology, University of Vigo, 36310 Vigo, Spain;
| | | | - Roberto Hornero
- Grupo de Ingeniería Biomédica, Universidad de Valladolid, 47011 Valladolid, Spain; (J.P.); (A.M.-C.); (S.J.R.-G.); (R.H.)
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), 47011 Valladolid, Spain
- Instituto de Investigación en Matemáticas (IMUVA), Universidad de Valladolid, 47011 Valladolid, Spain
| | - Nádia Pinto
- IPATIMUP—Instituto de Patologia e Imunologia Molecular da Universidade do Porto, 4200-135 Porto, Portugal; (M.Â.R.); (I.G.); (S.M.); (A.M.L.)
- I3S—Instituto de Investigação e Inovação em Saúde, Universidade do Porto, 4200-135 Porto, Portugal
- Centro de Matemática da, Universidade do Porto, 4169-007 Porto, Portugal
- Correspondence: (C.G.); (N.P.)
| | - Alexandra M. Lopes
- IPATIMUP—Instituto de Patologia e Imunologia Molecular da Universidade do Porto, 4200-135 Porto, Portugal; (M.Â.R.); (I.G.); (S.M.); (A.M.L.)
- I3S—Instituto de Investigação e Inovação em Saúde, Universidade do Porto, 4200-135 Porto, Portugal
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8
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Hart B, Guindani M, Malone S, Fiecas M. A nonparametric Bayesian model for estimating spectral densities of resting-state EEG twin data. Biometrics 2020; 78:313-323. [PMID: 33058149 DOI: 10.1111/biom.13393] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2019] [Revised: 09/16/2020] [Accepted: 10/05/2020] [Indexed: 11/27/2022]
Abstract
Electroencephalography (EEG) is a noninvasive neuroimaging modality that captures electrical brain activity many times per second. We seek to estimate power spectra from EEG data that ware gathered for 557 adolescent twin pairs through the Minnesota Twin Family Study (MTFS). Typically, spectral analysis methods treat time series from each subject separately, and independent spectral densities are fit to each time series. Since the EEG data were collected on twins, it is reasonable to assume that the time series have similar underlying characteristics, so borrowing information across subjects can significantly improve estimation. We propose a Nested Bernstein Dirichlet prior model to estimate the power spectrum of the EEG signal for each subject by smoothing periodograms within and across subjects while requiring minimal user input to tuning parameters. Furthermore, we leverage the MTFS twin study design to estimate the heritability of EEG power spectra with the hopes of establishing new endophenotypes. Through simulation studies designed to mimic the MTFS, we show our method out-performs a set of other popular methods.
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Affiliation(s)
- Brian Hart
- Division of Biostatistics, University of Minnesota, Minneapolis, Minnesota, USA
| | - Michele Guindani
- Department of Statistics, University of California Irvine, Irvine, California, USA
| | - Stephen Malone
- Department of Psychology, University of Minnesota, Minneapolis, Minnesota, USA
| | - Mark Fiecas
- Division of Biostatistics, University of Minnesota, Minneapolis, Minnesota, USA
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9
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Rogala J, Kublik E, Krauz R, Wróbel A. Resting-state EEG activity predicts frontoparietal network reconfiguration and improved attentional performance. Sci Rep 2020; 10:5064. [PMID: 32193502 PMCID: PMC7081192 DOI: 10.1038/s41598-020-61866-7] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2019] [Accepted: 03/05/2020] [Indexed: 12/21/2022] Open
Abstract
Mounting evidence indicates that resting-state EEG activity is related to various cognitive functions. To trace physiological underpinnings of this relationship, we investigated EEG and behavioral performance of 36 healthy adults recorded at rest and during visual attention tasks: visual search and gun shooting. All measures were repeated two months later to determine stability of the results. Correlation analyses revealed that within the range of 2–45 Hz, at rest, beta-2 band power correlated with the strength of frontoparietal connectivity and behavioral performance in both sessions. Participants with lower global beta-2 resting-state power (gB2rest) showed weaker frontoparietal connectivity and greater capacity for its modifications, as indicated by changes in phase correlations of the EEG signals. At the same time shorter reaction times and improved shooting accuracy were found, in both test and retest, in participants with low gB2rest compared to higher gB2rest values. We posit that weak frontoparietal connectivity permits flexible network reconfigurations required for improved performance in everyday tasks.
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Affiliation(s)
- Jacek Rogala
- Bioimaging Research Center, World Hearing Center, Institute of Physiology and Pathology of Hearing, Mokra 17 street, Kajetany, 05-830, Nadarzyn, Poland.
| | - Ewa Kublik
- Instytut Biologii Doświadczalnej im. Marcelego Nenckiego, 3 Pasteur Street, 02-093, Warsaw, Poland
| | - Rafał Krauz
- Military University of Technology, Physical Education, 3 gen, Sylwestra Kaliskiego street, 00-908, Warsaw, Poland
| | - Andrzej Wróbel
- Instytut Biologii Doświadczalnej im. Marcelego Nenckiego, 3 Pasteur Street, 02-093, Warsaw, Poland.,Department of Epistemology, Institute of Philosophy, University of Warsaw, 3 Krakowskie Przedmiescie street, 00-927, Warszawa, Poland
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10
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Jawinski P, Kirsten H, Sander C, Spada J, Ulke C, Huang J, Burkhardt R, Scholz M, Hensch T, Hegerl U. Human brain arousal in the resting state: a genome-wide association study. Mol Psychiatry 2019; 24:1599-1609. [PMID: 29703947 DOI: 10.1038/s41380-018-0052-2] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2017] [Revised: 01/22/2018] [Accepted: 02/19/2018] [Indexed: 12/20/2022]
Abstract
Arousal affects cognition, emotion, and behavior and has been implicated in the etiology of psychiatric disorders. Although environmental conditions substantially contribute to the level of arousal, stable interindividual characteristics are well-established and a genetic basis has been suggested. Here we investigated the molecular genetics of brain arousal in the resting state by conducting a genome-wide association study (GWAS). We selected N = 1877 participants from the population-based LIFE-Adult cohort. Participants underwent a 20-min eyes-closed resting state EEG, which was analyzed using the computerized VIGALL 2.1 (Vigilance Algorithm Leipzig). At the SNP-level, GWAS analyses revealed no genome-wide significant locus (p < 5E-8), although seven loci were suggestive (p < 1E-6). The strongest hit was an expression quantitative trait locus (eQTL) of TMEM159 (lead-SNP: rs79472635, p = 5.49E-8). Importantly, at the gene-level, GWAS analyses revealed significant evidence for TMEM159 (p = 0.013, Bonferroni-corrected). By mapping our SNPs to the GWAS results from the Psychiatric Genomics Consortium, we found that all corresponding markers of TMEM159 showed nominally significant associations with Major Depressive Disorder (MDD; 0.006 ≤ p ≤ 0.011). More specifically, variants associated with high arousal levels have previously been linked to an increased risk for MDD. In line with this, the MetaXcan database suggests increased expression levels of TMEM159 in MDD, as well as Autism Spectrum Disorder, and Alzheimer's Disease. Furthermore, our pathway analyses provided evidence for a role of sodium/calcium exchangers in resting state arousal. In conclusion, the present GWAS identifies TMEM159 as a novel candidate gene which may modulate the risk for psychiatric disorders through arousal mechanisms. Our results also encourage the elaboration of the previously reported interrelations between ion-channel modulators, sleep-wake behavior, and psychiatric disorders.
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Affiliation(s)
- Philippe Jawinski
- LIFE - Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany. .,Department of Psychiatry and Psychotherapy, University Hospital Leipzig, Leipzig, Germany. .,Depression Research Centre, German Depression Foundation, Leipzig, Germany.
| | - Holger Kirsten
- LIFE - Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany.,Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany.,Fraunhofer Institute for Cell Therapy and Immunology, Leipzig, Germany
| | - Christian Sander
- LIFE - Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany.,Department of Psychiatry and Psychotherapy, University Hospital Leipzig, Leipzig, Germany.,Depression Research Centre, German Depression Foundation, Leipzig, Germany
| | - Janek Spada
- LIFE - Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany.,Depression Research Centre, German Depression Foundation, Leipzig, Germany
| | - Christine Ulke
- LIFE - Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany.,Depression Research Centre, German Depression Foundation, Leipzig, Germany
| | - Jue Huang
- Department of Psychiatry and Psychotherapy, University Hospital Leipzig, Leipzig, Germany
| | - Ralph Burkhardt
- LIFE - Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany.,Institute of Laboratory Medicine, Clinical Chemistry and Molecular Diagnostics, University Hospital Leipzig, Leipzig, Germany
| | - Markus Scholz
- LIFE - Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany.,Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany
| | - Tilman Hensch
- LIFE - Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany.,Department of Psychiatry and Psychotherapy, University Hospital Leipzig, Leipzig, Germany
| | - Ulrich Hegerl
- LIFE - Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany.,Department of Psychiatry and Psychotherapy, University Hospital Leipzig, Leipzig, Germany.,Depression Research Centre, German Depression Foundation, Leipzig, Germany
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11
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Leppäaho E, Renvall H, Salmela E, Kere J, Salmelin R, Kaski S. Discovering heritable modes of MEG spectral power. Hum Brain Mapp 2019; 40:1391-1402. [PMID: 30600573 PMCID: PMC6590382 DOI: 10.1002/hbm.24454] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2018] [Revised: 09/27/2018] [Accepted: 10/19/2018] [Indexed: 12/14/2022] Open
Abstract
Brain structure and many brain functions are known to be genetically controlled, but direct links between neuroimaging measures and their underlying cellular-level determinants remain largely undiscovered. Here, we adopt a novel computational method for examining potential similarities in high-dimensional brain imaging data between siblings. We examine oscillatory brain activity measured with magnetoencephalography (MEG) in 201 healthy siblings and apply Bayesian reduced-rank regression to extract a low-dimensional representation of familial features in the participants' spectral power structure. Our results show that the structure of the overall spectral power at 1-90 Hz is a highly conspicuous feature that not only relates siblings to each other but also has very high consistency within participants' own data, irrespective of the exact experimental state of the participant. The analysis is extended by seeking genetic associations for low-dimensional descriptions of the oscillatory brain activity. The observed variability in the MEG spectral power structure was associated with SDK1 (sidekick cell adhesion molecule 1) and suggestively with several other genes that function, for example, in brain development. The current results highlight the potential of sophisticated computational methods in combining molecular and neuroimaging levels for exploring brain functions, even for high-dimensional data limited to a few hundred participants.
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Affiliation(s)
- Eemeli Leppäaho
- Department of Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Helsinki, Finland
| | - Hanna Renvall
- Department of Neuroscience and Biomedical Engineering, Aalto University, Helsinki, Finland.,Aalto NeuroImaging, Aalto University, Helsinki, Finland
| | - Elina Salmela
- Department of Biosciences, University of Helsinki, Helsinki, Finland
| | - Juha Kere
- Molecular Neurology Research Program, University of Helsinki, Folkhälsan Institute of Genetics, Helsinki, Finland.,Department of Biosciences and Nutrition, Karolinska Institutet, Huddinge, Sweden.,School of Basic and Medical Biosciences, King's College London, Guy's Hospital, London, United Kingdom
| | - Riitta Salmelin
- Department of Neuroscience and Biomedical Engineering, Aalto University, Helsinki, Finland.,Aalto NeuroImaging, Aalto University, Helsinki, Finland
| | - Samuel Kaski
- Department of Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Helsinki, Finland
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12
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Smit DJA, Wright MJ, Meyers JL, Martin NG, Ho YYW, Malone SM, Zhang J, Burwell SJ, Chorlian DB, de Geus EJC, Denys D, Hansell NK, Hottenga J, McGue M, van Beijsterveldt CEM, Jahanshad N, Thompson PM, Whelan CD, Medland SE, Porjesz B, Lacono WG, Boomsma DI. Genome-wide association analysis links multiple psychiatric liability genes to oscillatory brain activity. Hum Brain Mapp 2018; 39:4183-4195. [PMID: 29947131 PMCID: PMC6179948 DOI: 10.1002/hbm.24238] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2017] [Revised: 04/26/2018] [Accepted: 05/21/2018] [Indexed: 02/02/2023] Open
Abstract
Oscillatory activity is crucial for information processing in the brain, and has a long history as a biomarker for psychopathology. Variation in oscillatory activity is highly heritable, but current understanding of specific genetic influences remains limited. We performed the largest genome-wide association study to date of oscillatory power during eyes-closed resting electroencephalogram (EEG) across a range of frequencies (delta 1-3.75 Hz, theta 4-7.75 Hz, alpha 8-12.75 Hz, and beta 13-30 Hz) in 8,425 subjects. Additionally, we performed KGG positional gene-based analysis and brain-expression analyses. GABRA2-a known genetic marker for alcohol use disorder and epilepsy-significantly affected beta power, consistent with the known relation between GABAA interneuron activity and beta oscillations. Tissue-specific SNP-based imputation of gene-expression levels based on the GTEx database revealed that hippocampal GABRA2 expression may mediate this effect. Twenty-four genes at 3p21.1 were significant for alpha power (FDR q < .05). SNPs in this region were linked to expression of GLYCTK in hippocampal tissue, and GNL3 and ITIH4 in the frontal cortex-genes that were previously implicated in schizophrenia and bipolar disorder. In sum, we identified several novel genetic variants associated with oscillatory brain activity; furthermore, we replicated and advanced understanding of previously known genes associated with psychopathology (i.e., schizophrenia and alcohol use disorders). Importantly, these psychopathological liability genes affect brain functioning, linking the genes' expression to specific cortical/subcortical brain regions.
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Affiliation(s)
- Dirk J. A. Smit
- Psychiatry departmentAmsterdam Neuroscience, Academic Medical Center, University of AmsterdamThe Netherlands
| | - Margaret J. Wright
- Queensland Brain Institute, University of QueenslandBrisbaneAustralia
- Centre of Advanced Imaging, University QueenslandBrisbaneAustralia
| | - Jacquelyn L. Meyers
- Henri Begleiter Neurodynamics Lab., Department of PsychiatryState University of New York Downstate Medical CenterBrooklynNew York
| | | | | | | | - Jian Zhang
- Henri Begleiter Neurodynamics Lab., Department of PsychiatryState University of New York Downstate Medical CenterBrooklynNew York
| | - Scott J. Burwell
- Department of PsychologyUniversity of MinnesotaMinneapolisMinnesota
| | - David B. Chorlian
- Henri Begleiter Neurodynamics Lab., Department of PsychiatryState University of New York Downstate Medical CenterBrooklynNew York
| | - Eco J. C. de Geus
- Biological Psychology, Amsterdam Public Health research institute, Vrije Universiteit AmsterdamThe Netherlands
| | - Damiaan Denys
- Psychiatry departmentAmsterdam Neuroscience, Academic Medical Center, University of AmsterdamThe Netherlands
| | | | - Jouke‐Jan Hottenga
- Biological Psychology, Amsterdam Public Health research institute, Vrije Universiteit AmsterdamThe Netherlands
| | - Matt McGue
- Department of PsychologyUniversity of MinnesotaMinneapolisMinnesota
| | | | - Neda Jahanshad
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of University of Southern CaliforniaMarina del ReyCalifornia
| | - Paul M. Thompson
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of University of Southern CaliforniaMarina del ReyCalifornia
| | - Christopher D. Whelan
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of University of Southern CaliforniaMarina del ReyCalifornia
| | | | - Bernice Porjesz
- Henri Begleiter Neurodynamics Lab., Department of PsychiatryState University of New York Downstate Medical CenterBrooklynNew York
| | | | - Dorret I. Boomsma
- Biological Psychology, Amsterdam Public Health research institute, Vrije Universiteit AmsterdamThe Netherlands
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13
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Electrophysiological activity is associated with vulnerability of Internet addiction in non-clinical population. Addict Behav 2018; 84:33-39. [PMID: 29605758 DOI: 10.1016/j.addbeh.2018.03.025] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2018] [Revised: 03/21/2018] [Accepted: 03/22/2018] [Indexed: 12/13/2022]
Abstract
This study investigated the electrophysiological activity associated with vulnerability of problematic Internet use in non-clinical population. The resting EEG spectrum of alpha (8-13 Hz) rhythm was measured in 22 healthy subjects who have used the Internet for recreational purpose. The vulnerability of Internet addiction was assessed using Young's Internet Addiction Test (IAT) and Assessment for Computer and Internet Addiction-Screener (AICA-S) respectively. Depression and impulsivity were also measured with Beck Depression Inventory (BDI) and Barratt Impulsiveness Scale 11(BIS-11) respectively. The IAT was positively correlated with alpha power obtained during eyes closed (EC, r = 0.50, p = 0.02) but not during eyes open (EO). This was further supported by a negative correlation (r = -0.48, p = 0.02) between IAT scores and alpha desynchronization (EO-EC). These relationships remained significant following correction for multiple comparisons. Furthermore, The BDI score showed positive correlation with alpha asymmetry at mid-lateral (r = 0.54, p = 0.01) and mid-frontal (r = 0.46, p = 0.03) regions during EC, and at mid-frontal (r = 0.53, p = 0.01) region during EO. The current findings suggest that there are associations between neural activity and the vulnerability of problematic Internet use. Understanding of the neurobiological mechanisms underlying problematic Internet use would contribute to improved early intervention and treatment.
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14
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Markovic A, Achermann P, Rusterholz T, Tarokh L. Heritability of Sleep EEG Topography in Adolescence: Results from a Longitudinal Twin Study. Sci Rep 2018; 8:7334. [PMID: 29743546 PMCID: PMC5943340 DOI: 10.1038/s41598-018-25590-7] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2018] [Accepted: 04/16/2018] [Indexed: 01/12/2023] Open
Abstract
The topographic distribution of sleep EEG power is a reflection of brain structure and function. The goal of this study was to examine the degree to which genes contribute to sleep EEG topography during adolescence, a period of brain restructuring and maturation. We recorded high-density sleep EEG in monozygotic (MZ; n = 28) and dizygotic (DZ; n = 22) adolescent twins (mean age = 13.2 ± 1.1 years) at two time points 6 months apart. The topographic distribution of normalized sleep EEG power was examined for the frequency bands delta (1-4.6 Hz) to gamma 2 (34.2-44 Hz) during NREM and REM sleep. We found highest heritability values in the beta band for NREM and REM sleep (0.44 ≤ h2 ≤ 0.57), while environmental factors shared amongst twin siblings accounted for the variance in the delta to sigma bands (0.59 ≤ c2 ≤ 0.83). Given that both genetic and environmental factors are reflected in sleep EEG topography, our results suggest that topography may provide a rich metric by which to understand brain function. Furthermore, the frequency specific parsing of the influence of genetic from environmental factors on topography suggests functionally distinct networks and reveals the mechanisms that shape these networks.
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Affiliation(s)
- Andjela Markovic
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Peter Achermann
- Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland
- Zurich Center for Integrative Human Physiology, University of Zurich, Zurich, Switzerland
- Zurich Center for Interdisciplinary Sleep Research, University of Zurich, Zurich, Switzerland
| | - Thomas Rusterholz
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
- Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland
| | - Leila Tarokh
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland.
- Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland.
- Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, RI, USA.
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15
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Corcoran AW, Alday PM, Schlesewsky M, Bornkessel-Schlesewsky I. Toward a reliable, automated method of individual alpha frequency (IAF) quantification. Psychophysiology 2018; 55:e13064. [PMID: 29357113 DOI: 10.1111/psyp.13064] [Citation(s) in RCA: 89] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2017] [Revised: 11/22/2017] [Accepted: 12/19/2017] [Indexed: 11/29/2022]
Abstract
Individual alpha frequency (IAF) is a promising electrophysiological marker of interindividual differences in cognitive function. IAF has been linked with trait-like differences in information processing and general intelligence, and provides an empirical basis for the definition of individualized frequency bands. Despite its widespread application, however, there is little consensus on the optimal method for estimating IAF, and many common approaches are prone to bias and inconsistency. Here, we describe an automated strategy for deriving two of the most prevalent IAF estimators in the literature: peak alpha frequency (PAF) and center of gravity (CoG). These indices are calculated from resting-state power spectra that have been smoothed using a Savitzky-Golay filter (SGF). We evaluate the performance characteristics of this analysis procedure in both empirical and simulated EEG data sets. Applying the SGF technique to resting-state data from n = 63 healthy adults furnished 61 PAF and 62 CoG estimates. The statistical properties of these estimates were consistent with previous reports. Simulation analyses revealed that the SGF routine was able to reliably extract target alpha components, even under relatively noisy spectral conditions. The routine consistently outperformed a simpler method of automated peak detection that did not involve spectral smoothing. The SGF technique is fast, open source, and available in two popular programming languages (MATLAB, Python), and thus can easily be integrated within the most popular M/EEG toolsets (EEGLAB, FieldTrip, MNE-Python). As such, it affords a convenient tool for improving the reliability and replicability of future IAF-related research.
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Affiliation(s)
- Andrew W Corcoran
- Cognition and Philosophy Laboratory, Monash University, Melbourne, Victoria, Australia.,Centre for Cognitive and Systems Neuroscience, University of South Australia, Adelaide, South Australia, Australia
| | - Phillip M Alday
- Centre for Cognitive and Systems Neuroscience, University of South Australia, Adelaide, South Australia, Australia.,Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Matthias Schlesewsky
- Centre for Cognitive and Systems Neuroscience, University of South Australia, Adelaide, South Australia, Australia
| | - Ina Bornkessel-Schlesewsky
- Centre for Cognitive and Systems Neuroscience, University of South Australia, Adelaide, South Australia, Australia
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16
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Meyers JL, Zhang J, Wang JC, Su J, Kuo SI, Kapoor M, Wetherill L, Bertelsen S, Lai D, Salvatore JE, Kamarajan C, Chorlian D, Agrawal A, Almasy L, Bauer L, Bucholz KK, Chan G, Hesselbrock V, Koganti L, Kramer J, Kuperman S, Manz N, Pandey A, Seay M, Scott D, Taylor RE, Dick DM, Edenberg HJ, Goate A, Foroud T, Porjesz B. An endophenotype approach to the genetics of alcohol dependence: a genome wide association study of fast beta EEG in families of African ancestry. Mol Psychiatry 2017; 22:1767-1775. [PMID: 28070124 PMCID: PMC5503794 DOI: 10.1038/mp.2016.239] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/17/2016] [Revised: 09/24/2016] [Accepted: 10/27/2016] [Indexed: 01/16/2023]
Abstract
Fast beta (20-28 Hz) electroencephalogram (EEG) oscillatory activity may be a useful endophenotype for studying the genetics of disorders characterized by neural hyperexcitability, including substance use disorders (SUDs). However, the genetic underpinnings of fast beta EEG have not previously been studied in a population of African-American ancestry (AA). In a sample of 2382 AA individuals from 482 families drawn from the Collaborative Study on the Genetics of Alcoholism (COGA), we performed a genome-wide association study (GWAS) on resting-state fast beta EEG power. To further characterize our genetic findings, we examined the functional and clinical/behavioral significance of GWAS variants. Ten correlated single-nucleotide polymorphisms (SNPs) (r2>0.9) located in an intergenic region on chromosome 3q26 were associated with fast beta EEG power at P<5 × 10-8. The most significantly associated SNP, rs11720469 (β: -0.124; P<4.5 × 10-9), is also an expression quantitative trait locus for BCHE (butyrylcholinesterase), expressed in thalamus tissue. Four of the genome-wide SNPs were also associated with Diagnostic and Statistical Manual of Mental Disorders Alcohol Dependence in COGA AA families, and two (rs13093097, rs7428372) were replicated in an independent AA sample (Gelernter et al.). Analyses in the AA adolescent/young adult (offspring from COGA families) subsample indicated association of rs11720469 with heavy episodic drinking (frequency of consuming 5+ drinks within 24 h). Converging findings presented in this study provide support for the role of genetic variants within 3q26 in neural and behavioral disinhibition. These novel genetic findings highlight the importance of including AA populations in genetics research on SUDs and the utility of the endophenotype approach in enhancing our understanding of mechanisms underlying addiction susceptibility.
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Affiliation(s)
- J L Meyers
- Department of Psychiatry, State University of New York Downstate Medical Center, Brooklyn, NY, USA
| | - J Zhang
- Department of Psychiatry, State University of New York Downstate Medical Center, Brooklyn, NY, USA
| | - J C Wang
- Department of Neuroscience, Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - J Su
- Department of Psychology, Virginia Commonwealth University, Richmond, VA, USA
| | - S I Kuo
- Department of Psychology, Virginia Commonwealth University, Richmond, VA, USA
| | - M Kapoor
- Department of Neuroscience, Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - L Wetherill
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - S Bertelsen
- Department of Neuroscience, Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - D Lai
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - J E Salvatore
- Department of Psychology, Virginia Commonwealth University, Richmond, VA, USA
- Virginia Institute of Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - C Kamarajan
- Department of Psychiatry, State University of New York Downstate Medical Center, Brooklyn, NY, USA
| | - D Chorlian
- Department of Psychiatry, State University of New York Downstate Medical Center, Brooklyn, NY, USA
| | - A Agrawal
- Department of Psychiatry, Washington University School of Medicine in St Louis, St Louis, MO, USA
| | - L Almasy
- Department of Biomedical and Health Informatics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - L Bauer
- Department of Psychiatry, University of Connecticut School of Medicine, Farmington, CT, USA
| | - K K Bucholz
- Department of Psychiatry, Washington University School of Medicine in St Louis, St Louis, MO, USA
| | - G Chan
- Department of Psychiatry, University of Connecticut School of Medicine, Farmington, CT, USA
| | - V Hesselbrock
- Department of Psychiatry, University of Connecticut School of Medicine, Farmington, CT, USA
| | - L Koganti
- Department of Neuroscience, Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - J Kramer
- Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, IA, USA
| | - S Kuperman
- Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, IA, USA
| | - N Manz
- Department of Physics, The College of Wooster, Wooster, OH, USA
| | - A Pandey
- Department of Psychiatry, State University of New York Downstate Medical Center, Brooklyn, NY, USA
| | - M Seay
- Department of Psychiatry, State University of New York Downstate Medical Center, Brooklyn, NY, USA
| | - D Scott
- Collaborative Alcohol Research Center, Howard University College of Medicine, Washington, DC, USA
| | - R E Taylor
- Collaborative Alcohol Research Center, Howard University College of Medicine, Washington, DC, USA
| | - D M Dick
- Department of Psychology, Virginia Commonwealth University, Richmond, VA, USA
- Virginia Institute of Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - H J Edenberg
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - A Goate
- Department of Neuroscience, Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - T Foroud
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - B Porjesz
- Department of Psychiatry, State University of New York Downstate Medical Center, Brooklyn, NY, USA
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17
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Peng Q, Schork NJ, Wilhelmsen KC, Ehlers CL. Whole genome sequence association and ancestry-informed polygenic profile of EEG alpha in a Native American population. Am J Med Genet B Neuropsychiatr Genet 2017; 174:435-450. [PMID: 28436151 PMCID: PMC5435561 DOI: 10.1002/ajmg.b.32533] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/19/2016] [Accepted: 02/06/2017] [Indexed: 12/18/2022]
Abstract
EEG alpha activity is the dominant oscillation in most adult humans, is highly heritable, and has been associated with a number of cognitive functions. Two EEG phenotypes, low- and high-voltage alpha (LVA & HVA), have been demonstrated to have high heritabilities. They have different prevalence depending on a population's ancestral origins. In the present study we assessed the influence of ancestry admixture on EEG alpha power, and conducted a whole genome sequencing association analysis and an ancestry-informed polygenic study on those phenotypes in a Native American (NA) population that has a high prevalence of LVA. Seven common variants, in LD with each other upstream from gene ASIC2, reached genome-wide significance (p = 2 × 10-8 ) having a positive association with alpha voltage. They had lower minor allele frequencies in the NAs than in a global population sample. Overall correlations between lower degrees of NA (higher degree European) ancestry and HVA, and higher degrees of NA and LVA were also found. Additionally a rare-variant gene-based study identified gene TIA1 being negatively associated with LVA. Approximately 3% of SNPs exhibited a 15-fold enrichment that explained nearly half of the total SNP-heritability for EEG alpha. These regions showed the most significant anti-correlations between NA ancestry and alpha voltage, and were enriched for genes and pathways mediating cognitive functions. Our findings suggested that these regions likely harbor causal variants for HVA, and lacking of such variants could explain the high prevalence of LVA in this NA population, possibly illuminating the ancestral origin and genetic basis for EEG alpha.
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Affiliation(s)
- Qian Peng
- Department of Molecular and Cellular Neuroscience, The Scripps Research Institute, La Jolla, California 92037 USA
- Department of Human Biology, J. Craig Venter Institute, La Jolla, California 92037 USA
| | - Nicholas J. Schork
- Department of Human Biology, J. Craig Venter Institute, La Jolla, California 92037 USA
| | - Kirk C. Wilhelmsen
- Department of Genetics and Neurology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599 USA
| | - Cindy L. Ehlers
- Department of Molecular and Cellular Neuroscience, The Scripps Research Institute, La Jolla, California 92037 USA
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Meyers JL, Zhang J, Manz N, Rangaswamy M, Kamarajan C, Wetherill L, Chorlian DB, Kang SJ, Bauer L, Hesselbrock V, Kramer J, Kuperman S, Nurnberger JI, Tischfield J, Wang JC, Edenberg HJ, Goate A, Foroud T, Porjesz B. A genome wide association study of fast beta EEG in families of European ancestry. Int J Psychophysiol 2017; 115:74-85. [PMID: 28040410 PMCID: PMC5426060 DOI: 10.1016/j.ijpsycho.2016.12.008] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2015] [Revised: 12/08/2016] [Accepted: 12/15/2016] [Indexed: 11/25/2022]
Abstract
BACKGROUND Differences in fast beta (20-28Hz) electroencephalogram (EEG) oscillatory activity distinguish some individuals with psychiatric and substance use disorders, suggesting that it may be a useful endophenotype for studying the genetics of disorders characterized by neural hyper-excitability. Despite the high heritability estimates provided by twin and family studies, there have been relatively few genetic studies of beta EEG, and to date only one genetic association finding has replicated (i.e., GABRA2). METHOD In a sample of 1564 individuals from 117 families of European Ancestry (EA) drawn from the Collaborative Study on the Genetics of Alcoholism (COGA), we performed a Genome-Wide Association Study (GWAS) on resting-state fronto-central fast beta EEG power, adjusting regression models for family relatedness, age, sex, and ancestry. To further characterize genetic findings, we examined the functional and behavioral significance of GWAS findings. RESULTS Three intronic variants located within DSE (dermatan sulfate epimerase) on 6q22 were associated with fast beta EEG at a genome wide significant level (p<5×10-8). The most significant SNP was rs2252790 (p<2.6×10-8; MAF=0.36; β=0.135). rs2252790 is an eQTL for ROS1 expressed most robustly in the temporal cortex (p=1.2×10-6) and for DSE/TSPYL4 expressed most robustly in the hippocampus (p=7.3×10-4; β=0.29). Previous studies have indicated that DSE is involved in a network of genes integral to membrane organization; gene-based tests indicated that several variants within this network (i.e., DSE, ZEB2, RND3, MCTP1, and CTBP2) were also associated with beta EEG (empirical p<0.05), and of these genes, ZEB2 and CTBP2 were associated with DSM-V Alcohol Use Disorder (AUD; empirical p<0.05).' DISCUSSION In this sample of EA families enriched for AUDs, fast beta EEG is associated with variants within DSE on 6q22; the most significant SNP influences the mRNA expression of DSE and ROS1 in hippocampus and temporal cortex, brain regions important for beta EEG activity. Gene-based tests suggest evidence of association with related genes, ZEB2, RND3, MCTP1, CTBP2, and beta EEG. Converging data from GWAS, gene expression, and gene-networks presented in this study provide support for the role of genetic variants within DSE and related genes in neural hyperexcitability, and has highlighted two potential candidate genes for AUD and/or related neurological conditions: ZEB2 and CTBP2. However, results must be replicated in large, independent samples.
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Affiliation(s)
- Jacquelyn L Meyers
- Henri Begleiter Neurodynamics Laboratory, Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center, Brooklyn, NY, USA.
| | - Jian Zhang
- Henri Begleiter Neurodynamics Laboratory, Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center, Brooklyn, NY, USA
| | - Niklas Manz
- Henri Begleiter Neurodynamics Laboratory, Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center, Brooklyn, NY, USA; Department of Physics, College of Wooster, Wooster, OH, USA
| | | | - Chella Kamarajan
- Henri Begleiter Neurodynamics Laboratory, Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center, Brooklyn, NY, USA
| | - Leah Wetherill
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - David B Chorlian
- Henri Begleiter Neurodynamics Laboratory, Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center, Brooklyn, NY, USA
| | - Sun J Kang
- Albany Stratton VA Medical Center, Albany, NY, USA
| | - Lance Bauer
- University of Connecticut School of Medicine, Farmington, CT, USA
| | | | - John Kramer
- Department of Psychiatry, University of Iowa, Iowa City, IA, USA
| | - Samuel Kuperman
- Department of Psychiatry, University of Iowa, Iowa City, IA, USA
| | - John I Nurnberger
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | | | | | - Howard J Edenberg
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Alison Goate
- Icahn School of Medicine at Mt. Sinai, New York, NY, USA
| | - Tatiana Foroud
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Bernice Porjesz
- Henri Begleiter Neurodynamics Laboratory, Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center, Brooklyn, NY, USA
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Liu M, Malone SM, Vaidyanathan U, Keller MC, McGue M, Iacono WG, Vrieze SI. Psychophysiological endophenotypes to characterize mechanisms of known schizophrenia genetic loci. Psychol Med 2017; 47:1116-1125. [PMID: 27995817 PMCID: PMC5352523 DOI: 10.1017/s0033291716003184] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
BACKGROUND Endophenotypes are laboratory-based measures hypothesized to lie in the causal chain between genes and clinical disorder, and to serve as a more powerful way to identify genes associated with the disorder. One promise of endophenotypes is that they may assist in elucidating the neurobehavioral mechanisms by which an associated genetic polymorphism affects disorder risk in complex traits. We evaluated this promise by testing the extent to which variants discovered to be associated with schizophrenia through large-scale meta-analysis show associations with psychophysiological endophenotypes. METHOD We genome-wide genotyped and imputed 4905 individuals. Of these, 1837 were whole-genome-sequenced at 11× depth. In a community-based sample, we conducted targeted tests of variants within schizophrenia-associated loci, as well as genome-wide polygenic tests of association, with 17 psychophysiological endophenotypes including acoustic startle response and affective startle modulation, antisaccade, multiple frequencies of resting electroencephalogram (EEG), electrodermal activity and P300 event-related potential. RESULTS Using single variant tests and gene-based tests we found suggestive evidence for an association between contactin 4 (CNTN4) and antisaccade and P300. We were unable to find any other variant or gene within the 108 schizophrenia loci significantly associated with any of our 17 endophenotypes. Polygenic risk scores indexing genetic vulnerability to schizophrenia were not related to any of the psychophysiological endophenotypes after correction for multiple testing. CONCLUSIONS The results indicate significant difficulty in using psychophysiological endophenotypes to characterize the genetically influenced neurobehavioral mechanisms by which risk loci identified in genome-wide association studies affect disorder risk.
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Affiliation(s)
- M. Liu
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO, USA
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA
| | - S. M. Malone
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | | | - M. C. Keller
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO, USA
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA
| | - M. McGue
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - W. G. Iacono
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - S. I. Vrieze
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO, USA
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA
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Anokhin AP. The genetics of brain function and psychophysiology: An introduction to the special issue. Int J Psychophysiol 2017; 115:1-3. [PMID: 28259534 DOI: 10.1016/j.ijpsycho.2017.02.016] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
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Iacono WG, Malone SM, Vrieze SI. Endophenotype best practices. Int J Psychophysiol 2017; 111:115-144. [PMID: 27473600 PMCID: PMC5219856 DOI: 10.1016/j.ijpsycho.2016.07.516] [Citation(s) in RCA: 50] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2016] [Revised: 07/21/2016] [Accepted: 07/24/2016] [Indexed: 01/19/2023]
Abstract
This review examines the current state of electrophysiological endophenotype research and recommends best practices that are based on knowledge gleaned from the last decade of molecular genetic research with complex traits. Endophenotype research is being oversold for its potential to help discover psychopathology relevant genes using the types of small samples feasible for electrophysiological research. This is largely because the genetic architecture of endophenotypes appears to be very much like that of behavioral traits and disorders: they are complex, influenced by many variants (e.g., tens of thousands) within many genes, each contributing a very small effect. Out of over 40 electrophysiological endophenotypes covered by our review, only resting heart, a measure that has received scant advocacy as an endophenotype, emerges as an electrophysiological variable with verified associations with molecular genetic variants. To move the field forward, investigations designed to discover novel variants associated with endophenotypes will need extremely large samples best obtained by forming consortia and sharing data obtained from genome wide arrays. In addition, endophenotype research can benefit from successful molecular genetic studies of psychopathology by examining the degree to which these verified psychopathology-relevant variants are also associated with an endophenotype, and by using knowledge about the functional significance of these variants to generate new endophenotypes. Even without molecular genetic associations, endophenotypes still have value in studying the development of disorders in unaffected individuals at high genetic risk, constructing animal models, and gaining insight into neural mechanisms that are relevant to clinical disorder.
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22
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What can time-frequency and phase coherence measures tell us about the genetic basis of P3 amplitude? Int J Psychophysiol 2016; 115:40-56. [PMID: 27871913 DOI: 10.1016/j.ijpsycho.2016.11.008] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2015] [Revised: 10/26/2016] [Accepted: 11/08/2016] [Indexed: 11/21/2022]
Abstract
In a recent comprehensive investigation, we largely failed to identify significant genetic markers associated with P3 amplitude or to corroborate previous associations between P3 and specific single nucleotide polymorphisms (SNPs) or genes. In the present study we extended this line of investigation to examine time-frequency (TF) activity and intertrial phase coherence (ITPC) in the P3 time window, both of which are associated with P3 amplitude. Previous genome-wide research has reported associations between P3-related theta and delta activity and individual genetic variants. A large, population-based sample of 4211 subjects, comprising male and female adolescent twins and their parents, was genotyped for 527,828 single nucleotide polymorphisms (SNPs), from which over six million SNPs were accurately imputed. Heritability estimates were greater for TF energy than ITPC, whether based on biometric models or the combined influence of all measured SNPs (derived from genome-wide complex trait analysis). The magnitude of overlap in the specific SNPs associated with delta energy and ITPC and P3 amplitude was significant. A genome-wide analysis of all SNPs, accompanied by an analysis of approximately 17,600 genes, indicated a region of chromosome 2 around TEKT4 that was significantly associated with theta ITPC. Analysis of candidate SNPs and genes previously reported to be associated with P3 or related phenotypes yielded one association surviving correction for multiple tests: between theta energy and CRHR1. However, we did not obtain significant associations for SNPs implicated in previous genome-wide studies of TF measures. Identifying specific genetic variants associated with P3 amplitude remains a challenge.
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23
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Brain Networks and α-Oscillations: Structural and Functional Foundations of Cognitive Control. Trends Cogn Sci 2016; 20:805-817. [PMID: 27707588 DOI: 10.1016/j.tics.2016.09.004] [Citation(s) in RCA: 234] [Impact Index Per Article: 29.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2016] [Revised: 08/22/2016] [Accepted: 09/06/2016] [Indexed: 01/21/2023]
Abstract
The most salient electrical signal measured from the human brain is the α-rhythm, neural activity oscillating at ∼100ms intervals. Recent findings challenge the longstanding dogma of α-band oscillations as the signature of a passively idling brain state but diverge in terms of interpretation. Despite firm correlations with behavior, the mechanistic role of the α-rhythm in brain function remains debated. We suggest that three large-scale brain networks involved in different facets of top-down cognitive control differentially modulate α-oscillations, ranging from power within and synchrony between brain regions. Thereby, these networks selectively influence local signal processing, widespread information exchange, and ultimately perception and behavior.
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24
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Stephens DN, King SL, Lambert JJ, Belelli D, Duka T. GABAAreceptor subtype involvement in addictive behaviour. GENES BRAIN AND BEHAVIOR 2016; 16:149-184. [DOI: 10.1111/gbb.12321] [Citation(s) in RCA: 62] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/31/2016] [Revised: 07/19/2016] [Accepted: 08/15/2016] [Indexed: 12/17/2022]
Affiliation(s)
| | - S. L. King
- School of Psychology; University of Sussex; Brighton UK
| | - J. J. Lambert
- Division of Neuroscience; University of Dundee; Dundee UK
| | - D. Belelli
- Division of Neuroscience; University of Dundee; Dundee UK
| | - T. Duka
- School of Psychology; University of Sussex; Brighton UK
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25
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Burwell SJ, Malone SM, Iacono WG. One-year developmental stability and covariance among oddball, novelty, go/no-go, and flanker event-related potentials in adolescence: A monozygotic twin study. Psychophysiology 2016; 53:991-1007. [PMID: 26997525 DOI: 10.1111/psyp.12646] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2015] [Accepted: 02/19/2016] [Indexed: 01/14/2023]
Abstract
ERP measures may index genetic risk for psychopathology before disorder onset in adolescence, but little is known about their developmental rank-order stability during this period of significant brain maturation. We studied ERP stability in 48 pairs of identical twins (age 14-16 years) tested 1 year apart. Trial-averaged voltage waveforms were extracted from electroencephalographic recordings from oddball/novelty, go/no-go, and flanker tasks, and 16 amplitude measures were examined. Members of twin pairs were highly similar, whether based on ERP amplitude measures (intraclass correlation [ICC] median = .64, range = .44-.86) or three factor scores (all ICCs ≥ .69) derived from them. Stability was high overall, with 69% of the 16 individual measures generating stability coefficients exceeding .70 and all factor scores showing stability above .75. Measures from 10 difference waveforms calculated from paired conditions within tasks were also examined, and were associated with lower twin similarity (ICC median = .52, .38-.64) and developmental stability (only 30% exceeding .70). In a supplemental analysis, we found significant developmental stability for error-related negativity (range = .45-.55) and positivity (.56-.70) measures when average waveforms were based on one or more trials, and that these values were equivalent to those derived from averages using the current field recommendation, which requires six or more trials. Overall, we conclude that the studied brain measures are largely stable over 1 year of mid- to late adolescence, likely reflecting familial etiologic influences on brain functions pertaining to cognitive control and salience recognition.
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Affiliation(s)
- Scott J Burwell
- Department of Psychology, University of Minnesota, Minneapolis, Minnesota, USA
| | - Stephen M Malone
- Department of Psychology, University of Minnesota, Minneapolis, Minnesota, USA
| | - William G Iacono
- Department of Psychology, University of Minnesota, Minneapolis, Minnesota, USA
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Abstract
Endophenotypes are quantitative, heritable traits that may help to elucidate the pathophysiologic mechanisms underlying complex disease syndromes, such as schizophrenia. They can be assessed at numerous levels of analysis; here, we review electrophysiological endophenotypes that have shown promise in helping us understand schizophrenia from a more mechanistic point of view. For each endophenotype, we describe typical experimental procedures, reliability, heritability, and reported gene and neurobiological associations. We discuss recent findings regarding the genetic architecture of specific electrophysiological endophenotypes, as well as converging evidence from EEG studies implicating disrupted balance of glutamatergic signaling and GABAergic inhibition in the pathophysiology of schizophrenia. We conclude that refining the measurement of electrophysiological endophenotypes, expanding genetic association studies, and integrating data sets are important next steps for understanding the mechanisms that connect identified genetic risk loci for schizophrenia to the disease phenotype.
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Affiliation(s)
- Emily Owens
- Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA
| | - Peter Bachman
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA
| | - David C Glahn
- Olin Neuropsychiatric Research Center, Institute of Living, Hartford, CT,Department of Psychiatry, Yale University School of Medicine, New Haven, CT
| | - Carrie E Bearden
- Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA
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Yoon HH, Malone SM, Iacono WG. Longitudinal stability and predictive utility of the visual P3 response in adults with externalizing psychopathology. Psychophysiology 2015; 52:1632-45. [PMID: 26402396 DOI: 10.1111/psyp.12548] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2015] [Accepted: 07/20/2015] [Indexed: 12/18/2022]
Abstract
We determined whether time-domain P3 amplitude and time-frequency principal component (TF-PC) reductions could serve as stable and predictive developmental endophenotypes of externalizing psychopathology. Participants from the Minnesota Twin Family Study were assessed at age 17 and again at age 29 for lifetime externalizing (EXT) disorders. Comparisons of P3 amplitude and TF-PCs at delta and theta frequencies were made between EXT and unaffected comparison subjects. P3 amplitude and all five extracted TF-PCs were significantly reduced in those presenting lifetime EXT disorders at both ages 17 and 29 and showed substantial 12-year rank-order stability. P3 amplitude and delta TF-PCs measured at age 17 also predicted subsequent development of EXT by age 29, with every 1-microvolt decrease in age 17 amplitude associated with an approximately 5% increase in risk for an EXT diagnosis by age 29. Overall, results from this study further confirm that these P3-derived brain measures maintain their potential as putative EXT endophenotypes through the third decade of life.
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Affiliation(s)
- Henry H Yoon
- Department of Psychology, Augsburg College, Minneapolis, Minnesota, USA
| | - Stephen M Malone
- Department of Psychology, University of Minnesota, Twin Cities, Minneapolis, Minnesota, USA
| | - William G Iacono
- Department of Psychology, University of Minnesota, Twin Cities, Minneapolis, Minnesota, USA
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29
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Agrawal A, Bogdan R. Risky Business: Pathways to Progress in Biologically Informed Studies of Psychopathology. PSYCHOLOGICAL INQUIRY 2015; 26:231-238. [PMID: 27114696 DOI: 10.1080/1047840x.2015.1039930] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Affiliation(s)
- Arpana Agrawal
- Washington University School of Medicine, Department of Psychiatry, 660 S. Euclid, CB 8134, Saint Louis, MO 63110
| | - Ryan Bogdan
- Washington University in St. Louis, Department of Psychology, CB 1125, One Brookings Drive, Saint Louis, MO 63130
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Vaidyanathan U, Vrieze SI, Iacono WG. The Power of Theory, Research Design, and Transdisciplinary Integration in Moving Psychopathology Forward. PSYCHOLOGICAL INQUIRY 2015; 26:209-230. [PMID: 27030789 PMCID: PMC4809358 DOI: 10.1080/1047840x.2015.1015367] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
While the past few decades have seen much work in psychopathology research that has yielded provocative insights, relatively little progress has been made in understanding the etiology of mental disorders. We contend that this is due to an overreliance on statistics and technology with insufficient attention to adequacy of experimental design, a lack of integration of data across various domains of research, and testing of theoretical models using relatively weak study designs. We provide a conceptual discussion of these issues and follow with a concrete demonstration of our proposed solution. Using two different disorders - depression and substance use - as examples, we illustrate how we can evaluate competing theories regarding their etiology by integrating information from various domains including latent variable models, neurobiology, and quasi-experimental data such as twin and adoption studies, rather than relying on any single methodology alone. More broadly, we discuss the extent to which such integrative thinking allows for inferences about the etiology of mental disorders, rather than focusing on descriptive correlates alone. Greater scientific insight will require stringent tests of competing theories and a deeper conceptual understanding of the advantages and pitfalls of methodologies and criteria we use in our studies.
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Affiliation(s)
- Uma Vaidyanathan
- Department of Psychology, University of Minnesota, N218 Elliot Hall, 75 East River Road, Minneapolis, MN 55455
| | - Scott I Vrieze
- Institute for Behavioral Genetics, University of Colorado – Boulder, 1480 30 Street, Boulder, CO 80303
| | - William G. Iacono
- Department of Psychology, University of Minnesota, N218 Elliot Hall, 75 East River Road, Minneapolis, MN 55455
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The importance of endophenotypes in schizophrenia research. Schizophr Res 2015; 163:1-8. [PMID: 25795083 DOI: 10.1016/j.schres.2015.02.007] [Citation(s) in RCA: 50] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/19/2014] [Revised: 02/06/2015] [Accepted: 02/06/2015] [Indexed: 11/21/2022]
Abstract
Endophenotypes provide a powerful neurobiological platform from which we can understand the genomic and neural substrates of schizophrenia and other common complex neuropsychiatric disorders. The Consortium on the Genetics of Schizophrenia (COGS) has conducted multisite studies on carefully selected key neurocognitive and neurophysiological endophenotypes in 300 families (COGS-1) and then in a follow up multisite case-control study of 2471 subjects (COGS-2). Endophenotypes are neurobiologically informed quantitative measures that show deficits in probands and their first degree relatives. They are more amenable to statistical analysis than are "fuzzy" qualitative clinical traits or confoundingly heterogeneous diagnostic categories. Endophenotypes are also viewed as uniquely informative in traditional diagnosis-based as well as emerging NIMH Research Domain (RDoC) contexts, offering a bridge between the two approaches to psychopathology classification and research. Endo- or intermediate phenotypes are heritable, and in the COGS-1 cohort their level of heritability is in the same range as is the heritability of schizophrenia itself, using the same statistical methods and subjects to assess both. Because we can demonstrate endophenotypes link to both gene networks and neural circuits on the one hand and also to real-life function, endophenotypes provide a critically important bridge for "connecting the dots" between genes, cells, circuits, information processing, neurocognition and functional impairment and personalized treatment selection in schizophrenia patients. By connecting schizophrenia risk genes with neurobiologically informed endophenotypes, and via the use of association, linkage, sequencing, stem cell and other strategies, we can provide our field with new neurobiologically informed information in our efforts to understand and treat schizophrenia. Evolving views, data and new analytic strategies about schizophrenia risk, pathology and treatment are described in this Viewpoint and in the accompanying Special Issue reports.
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Vaidyanathan U, Malone SM, Donnelly JM, Hammer MA, Miller MB, McGue M, Iacono WG. Heritability and molecular genetic basis of antisaccade eye tracking error rate: a genome-wide association study. Psychophysiology 2014; 51:1272-84. [PMID: 25387707 PMCID: PMC4238043 DOI: 10.1111/psyp.12347] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Antisaccade deficits reflect abnormalities in executive function linked to various disorders including schizophrenia, externalizing psychopathology, and neurological conditions. We examined the genetic bases of antisaccade error in a sample of community-based twins and parents (N = 4,469). Biometric models showed that about half of the variance in the antisaccade response was due to genetic factors and half due to nonshared environmental factors. Molecular genetic analyses supported these results, showing that the heritability accounted for by common molecular genetic variants approximated biometric estimates. Genome-wide analyses revealed several SNPs as well as two genes-B3GNT7 and NCL-on Chromosome 2 associated with antisaccade error. SNPs and genes hypothesized to be associated with antisaccade error based on prior work, although generating some suggestive findings for MIR137, GRM8, and CACNG2, could not be confirmed.
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Affiliation(s)
- Uma Vaidyanathan
- Department of Psychology, University of Minnesota, Minneapolis, Minnesota, USA
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Iacono WG, Malone SM, Vaidyanathan U, Vrieze SI. Genome-wide scans of genetic variants for psychophysiological endophenotypes: a methodological overview. Psychophysiology 2014; 51:1207-24. [PMID: 25387703 PMCID: PMC4231489 DOI: 10.1111/psyp.12343] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
This article provides an introductory overview of the investigative strategy employed to evaluate the genetic basis of 17 endophenotypes examined as part of a 20-year data collection effort from the Minnesota Center for Twin and Family Research. Included are characterization of the study samples, descriptive statistics for key properties of the psychophysiological measures, and rationale behind the steps taken in the molecular genetic study design. The statistical approach included (a) biometric analysis of twin and family data, (b) heritability analysis using 527,829 single nucleotide polymorphisms (SNPs), (c) genome-wide association analysis of these SNPs and 17,601 autosomal genes, (d) follow-up analyses of candidate SNPs and genes hypothesized to have an association with each endophenotype, (e) rare variant analysis of nonsynonymous SNPs in the exome, and (f) whole genome sequencing association analysis using 27 million genetic variants. These methods were used in the accompanying empirical articles comprising this special issue, Genome-Wide Scans of Genetic Variants for Psychophysiological Endophenotypes.
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Affiliation(s)
- William G Iacono
- Department of Psychology, University of Minnesota, Minneapolis, Minnesota, USA
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Vrieze SI, Malone SM, Pankratz N, Vaidyanathan U, Miller MB, Kang HM, McGue M, Abecasis G, Iacono WG. Genetic associations of nonsynonymous exonic variants with psychophysiological endophenotypes. Psychophysiology 2014; 51:1300-8. [PMID: 25387709 PMCID: PMC4231532 DOI: 10.1111/psyp.12349] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
We mapped ∼85,000 rare nonsynonymous exonic single nucleotide polymorphisms (SNPs) to 17 psychophysiological endophenotypes in 4,905 individuals, including antisaccade eye movements, resting EEG, P300 amplitude, electrodermal activity, affect-modulated startle eye blink. Nonsynonymous SNPs are predicted to directly change or disrupt proteins encoded by genes and are expected to have significant biological consequences. Most such variants are rare, and new technologies can efficiently assay them on a large scale. We assayed 247,870 mostly rare SNPs on an Illumina exome array. Approximately 85,000 of the SNPs were polymorphic, rare (MAF < .05), and nonsynonymous. Single variant association tests identified a SNP in the PARD3 gene associated with theta resting EEG power. The sequence kernel association test, a gene-based test, identified a gene PNPLA7 associated with pleasant difference startle, the difference in startle magnitude between pleasant and neutral images. No other single nonsynonymous variant, or gene-based group of variants, was strongly associated with any endophenotype.
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Affiliation(s)
- Scott I. Vrieze
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA
| | - Stephen M. Malone
- Department of Psychology, University of Minnesota, Minneapolis, Minnesota, USA
| | - Nathan Pankratz
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, Minnesota, USA
| | - Uma Vaidyanathan
- Department of Psychology, University of Minnesota, Minneapolis, Minnesota, USA
| | - Michael B. Miller
- Department of Psychology, University of Minnesota, Minneapolis, Minnesota, USA
| | - Hyun Min Kang
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA
| | - Matt McGue
- Department of Psychology, University of Minnesota, Minneapolis, Minnesota, USA
| | - Gonçalo Abecasis
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA
| | - William G. Iacono
- Department of Psychology, University of Minnesota, Minneapolis, Minnesota, USA
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35
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Vrieze SI, Malone SM, Vaidyanathan U, Kwong A, Kang HM, Zhan X, Flickinger M, Irons D, Jun G, Locke AE, Pistis G, Porcu E, Levy S, Myers RM, Oetting W, McGue M, Abecasis G, Iacono WG. In search of rare variants: preliminary results from whole genome sequencing of 1,325 individuals with psychophysiological endophenotypes. Psychophysiology 2014; 51:1309-20. [PMID: 25387710 PMCID: PMC4231480 DOI: 10.1111/psyp.12350] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Whole genome sequencing was completed on 1,325 individuals from 602 families, identifying 27 million autosomal variants. Genetic association tests were conducted for those individuals who had been assessed for one or more of 17 endophenotypes (N range = 802-1,185). No significant associations were found. These 27 million variants were then imputed into the full sample of individuals with psychophysiological data (N range = 3,088-4,469) and again tested for associations with the 17 endophenotypes. No association was significant. Using a gene-based variable threshold burden test of nonsynonymous variants, we obtained five significant associations. These findings are preliminary and call for additional analysis of this rich sample. We argue that larger samples, alternative study designs, and additional bioinformatics approaches will be necessary to discover associations between these endophenotypes and genomic variation.
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Affiliation(s)
- Scott I Vrieze
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA
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Affiliation(s)
- Judith M. Ford
- San Francisco VA Medical Center; San Francisco California USA
- Department of Psychiatry; University of California; San Francisco (UCSF); San Francisco California USA
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