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Okpete UE, Byeon H. Challenges and prospects in bridging precision medicine and artificial intelligence in genomic psychiatric treatment. World J Psychiatry 2024; 14:1148-1164. [PMID: 39165556 PMCID: PMC11331387 DOI: 10.5498/wjp.v14.i8.1148] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/04/2024] [Revised: 06/13/2024] [Accepted: 07/09/2024] [Indexed: 08/12/2024] Open
Abstract
Precision medicine is transforming psychiatric treatment by tailoring personalized healthcare interventions based on clinical, genetic, environmental, and lifestyle factors to optimize medication management. This study investigates how artificial intelligence (AI) and machine learning (ML) can address key challenges in integrating pharmacogenomics (PGx) into psychiatric care. In this integration, AI analyzes vast genomic datasets to identify genetic markers linked to psychiatric conditions. AI-driven models integrating genomic, clinical, and demographic data demonstrated high accuracy in predicting treatment outcomes for major depressive disorder and bipolar disorder. This study also examines the pressing challenges and provides strategic directions for integrating AI and ML in genomic psychiatry, highlighting the importance of ethical considerations and the need for personalized treatment. Effective implementation of AI-driven clinical decision support systems within electronic health records is crucial for translating PGx into routine psychiatric care. Future research should focus on developing enhanced AI-driven predictive models, privacy-preserving data exchange, and robust informatics systems to optimize patient outcomes and advance precision medicine in psychiatry.
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Affiliation(s)
- Uchenna Esther Okpete
- Department of Digital Anti-aging Healthcare (BK21), Inje University, Gimhae 50834, South Korea
| | - Haewon Byeon
- Department of Digital Anti-aging Healthcare (BK21), Inje University, Gimhae 50834, South Korea
- Department of Medical Big Data, Inje University, Gimhae 50834, South Korea
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Xie YT, Yang YJ. Research fronts and researchers of World Journal of Psychiatry in 2023: A visualization and analysis of mapping knowledge domains. World J Psychiatry 2024; 14:1118-1126. [PMID: 39050206 PMCID: PMC11262920 DOI: 10.5498/wjp.v14.i7.1118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/03/2024] [Revised: 05/31/2024] [Accepted: 06/21/2024] [Indexed: 07/12/2024] Open
Abstract
BACKGROUND In the rapidly evolving landscape of psychiatric research, 2023 marked another year of significant progress globally, with the World Journal of Psychiatry (WJP) experiencing notable expansion and influence. AIM To conduct a comprehensive visualization and analysis of the articles published in the WJP throughout 2023. By delving into these publications, the aim is to determine the valuable insights that can illuminate pathways for future research endeavors in the field of psychiatry. METHODS A selection process led to the inclusion of 107 papers from the WJP published in 2023, forming the dataset for the analysis. Employing advanced visualization techniques, this study mapped the knowledge domains represented in these papers. RESULTS The findings revealed a prevalent focus on key topics such as depression, mental health, anxiety, schizophrenia, and the impact of coronavirus disease 2019. Additionally, through keyword clustering, it became evident that these papers were predominantly focused on exploring mental health disorders, depression, anxiety, schizophrenia, and related factors. Noteworthy contributions hailed authors in regions such as China, the United Kingdom, United States, and Turkey. Particularly, the paper garnered the highest number of citations, while the American Psychiatric Association was the most cited reference. CONCLUSION It is recommended that the WJP continue in its efforts to enhance the quality of papers published in the field of psychiatry. Additionally, there is a pressing need to delve into the potential applications of digital interventions and artificial intelligence within the discipline.
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Affiliation(s)
- Yun-Tian Xie
- Department of Applied Psychology, Changsha Normal University, Changsha 410100, Hunan Province, China
| | - Yu-Jing Yang
- Department of Applied Psychology, Changsha Normal University, Changsha 410100, Hunan Province, China
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Happer JP, Beaton LE, Wagner LC, Hodgkinson CA, Goldman D, Marinkovic K. Neural indices of heritable impulsivity: Impact of the COMT Val158Met polymorphism on frontal beta power during early motor preparation. Biol Psychol 2024; 191:108826. [PMID: 38862067 DOI: 10.1016/j.biopsycho.2024.108826] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2024] [Revised: 05/14/2024] [Accepted: 05/31/2024] [Indexed: 06/13/2024]
Abstract
Studies of COMT Val158Met suggest that the neural circuitry subserving inhibitory control may be modulated by this functional polymorphism altering cortical dopamine availability, thus giving rise to heritable differences in behaviors. Using an anatomically-constrained magnetoencephalography method and stratifying the sample by COMT genotype, from a larger sample of 153 subjects, we examined the spatial and temporal dynamics of beta oscillations during motor execution and inhibition in 21 healthy Met158/Met158 (high dopamine) or 21 Val158/Val158 (low dopamine) genotype individuals during a Go/NoGo paradigm. While task performance was unaffected, Met158 homozygotes demonstrated an overall increase in beta power across regions essential for inhibitory control during early motor preparation (∼100 ms latency), suggestive of a global motor "pause" on behavior. This increase was especially evident on Go trials with slow response speed and was absent during inhibition failures. Such a pause could underlie the tendency of Met158 allele carriers to be more cautious and inhibited. In contrast, Val158 homozygotes exhibited a beta drop during early motor preparation, indicative of high response readiness. This decrease was associated with measures of behavioral disinhibition and consistent with greater extraversion and impulsivity observed in Val homozygotes. These results provide mechanistic insight into genetically-determined interindividual differences of inhibitory control with higher cortical dopamine associated with momentary response hesitation, and lower dopamine leading to motor impulsivity.
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Affiliation(s)
- Joseph P Happer
- San Diego State University/University of California, San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, USA
| | - Lauren E Beaton
- Department of Psychology, San Diego State University, San Diego, CA, USA
| | - Laura C Wagner
- Department of Psychology, San Diego State University, San Diego, CA, USA
| | | | - David Goldman
- Laboratory of Neurogenetics, NIAAA, NIH, Bethesda, MD, USA
| | - Ksenija Marinkovic
- San Diego State University/University of California, San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, USA; Department of Psychology, San Diego State University, San Diego, CA, USA; Department of Radiology, University of California, La Jolla, San Diego, CA, USA.
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Miller AP, Gizer IR. Dual-systems models of the genetic architecture of impulsive personality traits: neurogenetic evidence of distinct but related factors. Psychol Med 2024; 54:1533-1543. [PMID: 38016992 PMCID: PMC11132950 DOI: 10.1017/s0033291723003367] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2023]
Abstract
BACKGROUND Dual-systems models, positing an interaction between two distinct and competing systems (i.e. top-down self-control, and bottom-up reward- or emotion-based drive), provide a parsimonious framework for investigating the interplay between cortical and subcortical brain regions relevant to impulsive personality traits (IPTs) and their associations with psychopathology. Despite recent developments in multivariate analysis of genome-wide association studies (GWAS), molecular genetic investigations of these models have not been conducted. METHODS Using IPT GWAS, we conducted confirmatory genomic structural equation models (GenomicSEM) to empirically evaluate dual-systems models of the genetic architecture of IPTs. Genetic correlations between dual-systems factors and relevant cortical and subcortical neuroimaging phenotypes (regional/structural volume, cortical surface area, cortical thickness) were estimated and compared. RESULTS GenomicSEM dual-systems models underscored important sources of shared and unique genetic variance between top-down and bottom-up constructs. Specifically, a dual-systems genomic model consisting of sensation seeking and lack of self-control factors demonstrated distinct but related sources of genetic influences (rg = 0.60). Genetic correlation analyses provided evidence of differential associations between dual-systems factors and cortical neuroimaging phenotypes (e.g. lack of self-control negatively associated with cortical thickness, sensation seeking positively associated with cortical surface area). No significant associations were observed with subcortical phenotypes. CONCLUSIONS Dual-systems models of the genetic architecture of IPTs tested were consistent with study hypotheses, but associations with relevant neuroimaging phenotypes were mixed (e.g. no associations with subcortical volumes). Findings demonstrate the utility of dual-systems models for studying IPT genetic influences, but also highlight potential limitations as a framework for interpreting IPTs as endophenotypes for psychopathology.
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Affiliation(s)
- Alex P. Miller
- Department of Psychiatry, School of Medicine, Washington University in St. Louis, St. Louis, MO, United States
| | - Ian R. Gizer
- Department of Psychological Sciences, University of Missouri, Columbia, MO, United States
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5
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Thiel K, Lemke H, Winter A, Flinkenflügel K, Waltemate L, Bonnekoh L, Grotegerd D, Dohm K, Hahn T, Förster K, Kanske P, Repple J, Opel N, Redlich R, David F, Forstner AJ, Stein F, Brosch K, Thomas-Odenthal F, Usemann P, Teutenberg L, Straube B, Alexander N, Jamalabadi H, Jansen A, Witt SH, Andlauer TFM, Pfennig A, Bauer M, Nenadić I, Kircher T, Meinert S, Dannlowski U. White and gray matter alterations in bipolar I and bipolar II disorder subtypes compared with healthy controls - exploring associations with disease course and polygenic risk. Neuropsychopharmacology 2024; 49:814-823. [PMID: 38332015 PMCID: PMC10948847 DOI: 10.1038/s41386-024-01812-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Revised: 12/28/2023] [Accepted: 01/21/2024] [Indexed: 02/10/2024]
Abstract
Patients with bipolar disorder (BD) show alterations in both gray matter volume (GMV) and white matter (WM) integrity compared with healthy controls (HC). However, it remains unclear whether the phenotypically distinct BD subtypes (BD-I and BD-II) also exhibit brain structural differences. This study investigated GMV and WM differences between HC, BD-I, and BD-II, along with clinical and genetic associations. N = 73 BD-I, n = 63 BD-II patients and n = 136 matched HC were included. Using voxel-based morphometry and tract-based spatial statistics, main effects of group in GMV and fractional anisotropy (FA) were analyzed. Associations between clinical and genetic features and GMV or FA were calculated using regression models. For FA but not GMV, we found significant differences between groups. BD-I patients showed lower FA compared with BD-II patients (ptfce-FWE = 0.006), primarily in the anterior corpus callosum. Compared with HC, BD-I patients exhibited lower FA in widespread clusters (ptfce-FWE < 0.001), including almost all major projection, association, and commissural fiber tracts. BD-II patients also demonstrated lower FA compared with HC, although less pronounced (ptfce-FWE = 0.049). The results remained unchanged after controlling for clinical and genetic features, for which no independent associations with FA or GMV emerged. Our findings suggest that, at a neurobiological level, BD subtypes may reflect distinct degrees of disease expression, with increasing WM microstructure disruption from BD-II to BD-I. This differential magnitude of microstructural alterations was not clearly linked to clinical and genetic variables. These findings should be considered when discussing the classification of BD subtypes within the spectrum of affective disorders.
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Affiliation(s)
- Katharina Thiel
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Hannah Lemke
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Alexandra Winter
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Kira Flinkenflügel
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Lena Waltemate
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Translational Psychotherapy, Institute of Psychology, University of Göttingen, Göttingen, Germany
| | - Linda Bonnekoh
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Katharina Dohm
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Tim Hahn
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Katharina Förster
- Clinical Psychology and Behavioral Neuroscience, Faculty of Psychology, Technische Universität Dresden, Dresden, Germany
| | - Philipp Kanske
- Clinical Psychology and Behavioral Neuroscience, Faculty of Psychology, Technische Universität Dresden, Dresden, Germany
| | - Jonathan Repple
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Department for Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Goethe University, Frankfurt, Germany
| | - Nils Opel
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Department of Psychiatry, Jena University Hospital/Friedrich-Schiller-University Jena, Jena, Germany
- German Center for Mental Health (DZPG), Halle-Jena-Magdeburg, Germany
| | - Ronny Redlich
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- German Center for Mental Health (DZPG), Halle-Jena-Magdeburg, Germany
- Department of Psychology, University of Halle, Halle, Germany
- Center for Intervention and Research on adaptive and maladaptive brain circuits underlying mental health (C-I-R-C), Jena-Magdeburg-Halle, Halle, Germany
| | - Friederike David
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Andreas J Forstner
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
- Institute of Neuroscience and Medicine (INM-1), Research Center Jülich, Jülich, Germany
| | - Frederike Stein
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), University of Marburg, Marburg, Germany
| | - Katharina Brosch
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), University of Marburg, Marburg, Germany
| | - Florian Thomas-Odenthal
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), University of Marburg, Marburg, Germany
| | - Paula Usemann
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), University of Marburg, Marburg, Germany
| | - Lea Teutenberg
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), University of Marburg, Marburg, Germany
| | - Benjamin Straube
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), University of Marburg, Marburg, Germany
| | - Nina Alexander
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), University of Marburg, Marburg, Germany
| | - Hamidreza Jamalabadi
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), University of Marburg, Marburg, Germany
| | - Andreas Jansen
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), University of Marburg, Marburg, Germany
- Core-Facility Brainimaging, Faculty of Medicine, University of Marburg, Marburg, Germany
| | - Stephanie H Witt
- Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Till F M Andlauer
- Department of Neurology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Andrea Pfennig
- Department of Psychiatry and Psychotherapy, Faculty of Medicine, TU Dresden University of Technology, Dresden, Germany
| | - Michael Bauer
- Department of Psychiatry and Psychotherapy, Faculty of Medicine, TU Dresden University of Technology, Dresden, Germany
| | - Igor Nenadić
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), University of Marburg, Marburg, Germany
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), University of Marburg, Marburg, Germany
| | - Susanne Meinert
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Institute of Translational Neuroscience, University of Münster, Münster, Germany
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany.
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Gong L, Chen K, Zhang H, Zhang S, Xu R, Liu D, Zhang B, Yu S, Xi C. Dopamine multilocus genetic profile influence on reward network in chronic insomnia disorder with depression. Sleep Med 2023; 112:122-128. [PMID: 37839273 DOI: 10.1016/j.sleep.2023.09.026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 08/31/2023] [Accepted: 09/23/2023] [Indexed: 10/17/2023]
Abstract
BACKGROUND Chronic insomnia disorder (CID) is frequently comorbid with depression, and both conditions are believed to involve disruptions in the reward network. However, the potential effects of genetic polymorphisms in modulating this network remain largely unexplored. METHODS In this study, we recruited 50 CID patients with high (CID-HD) and low (CID-LD) depressive symptoms and assessed their reward networks using resting-state functional MRI. Additionally, we calculated the multilocus genetic profile score (MGPS) to examine the influence of depression and dopamine genetic variation on the nucleus accumbens functional connectivity (NAFC) network in CID patients. RESULTS Although the MGPS did not show a significant difference between the two CID groups, its influence on the NAFC network was observed in the salience network (SN) and visual network (VN) in CID patients. When comparing CID-HD patients to CID-LD patients, we found that CID-HD patients exhibited decreased NAFC in the internal reward network, default mode network, SN, and sensorimotor network, while showing increased NAFC in the executive control network (ECN) and VN. Furthermore, the influence of MGPS on the reward network was only significant in CID-HD patients, specifically in the internal reward network and ECN. CONCLUSION These findings suggest that genetic variations related to dopamine may modulate the reward network differently in CID patients with and without depressive symptoms. These results contribute to our understanding of the pathophysiology of polygenic effects underlying brain network abnormalities in CID patients with depression.
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Affiliation(s)
- Liang Gong
- Department of Neurology, Chengdu Second People's Hospital, Chengdu, Sichuan, 610017, China
| | - Kang Chen
- Department of Radiology, Chengdu Second People's Hospital, Chengdu, Sichuan, 610017, China
| | - Hongyu Zhang
- Chengdu Medical College, Chengdu, Sichuan, 610500, China; Chengdu Second People's Hospital, Chengdu, Sichuan, 610017, China
| | - Shang Zhang
- North Sichuan Medical College, Nanchong, Sichuan, 637199, China; Chengdu Second People's Hospital, Chengdu, Sichuan, 610017, China
| | - Ronghua Xu
- Department of Neurology, Chengdu Second People's Hospital, Chengdu, Sichuan, 610017, China
| | - Duan Liu
- Department of Neurology, Chengdu Second People's Hospital, Chengdu, Sichuan, 610017, China
| | - Bei Zhang
- Department of Neurology, Chengdu Second People's Hospital, Chengdu, Sichuan, 610017, China
| | - Siyi Yu
- Department of Acupuncture & Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, 610075, China.
| | - Chunhua Xi
- Department of Neurology, The Third Affiliated Hospital of Anhui Medical University, Heifei, Anhui, 230061, China.
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Stauffer EM, Bethlehem RAI, Dorfschmidt L, Won H, Warrier V, Bullmore ET. The genetic relationships between brain structure and schizophrenia. Nat Commun 2023; 14:7820. [PMID: 38016951 PMCID: PMC10684873 DOI: 10.1038/s41467-023-43567-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Accepted: 11/14/2023] [Indexed: 11/30/2023] Open
Abstract
Genetic risks for schizophrenia are theoretically mediated by genetic effects on brain structure but it has been unclear which genes are associated with both schizophrenia and cortical phenotypes. We accessed genome-wide association studies (GWAS) of schizophrenia (N = 69,369 cases; 236,642 controls), and of three magnetic resonance imaging (MRI) metrics (surface area, cortical thickness, neurite density index) measured at 180 cortical areas (N = 36,843, UK Biobank). Using Hi-C-coupled MAGMA, 61 genes were significantly associated with both schizophrenia and one or more MRI metrics. Whole genome analysis with partial least squares demonstrated significant genetic covariation between schizophrenia and area or thickness of most cortical regions. Genetic similarity between cortical areas was strongly coupled to their phenotypic covariance, and genetic covariation between schizophrenia and brain phenotypes was strongest in the hubs of structural covariance networks. Pleiotropically associated genes were enriched for neurodevelopmental processes and positionally concentrated in chromosomes 3p21, 17q21 and 11p11. Mendelian randomization analysis indicated that genetically determined variation in a posterior cingulate cortical area could be causal for schizophrenia. Parallel analyses of GWAS on bipolar disorder, Alzheimer's disease and height showed that pleiotropic association with MRI metrics was stronger for schizophrenia compared to other disorders.
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Affiliation(s)
| | - Richard A I Bethlehem
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Department of Psychology, University of Cambridge, Cambridge, UK
| | - Lena Dorfschmidt
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Hyejung Won
- Department of Genetics and the Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Varun Warrier
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Department of Psychology, University of Cambridge, Cambridge, UK
| | - Edward T Bullmore
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire & Peterborough NHS Foundation Trust, Cambridge, UK
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Bruzzone SEP, Nasser A, Aripaka SS, Spies M, Ozenne B, Jensen PS, Knudsen GM, Frokjaer VG, Fisher PM. Genetic contributions to brain serotonin transporter levels in healthy adults. Sci Rep 2023; 13:16426. [PMID: 37777558 PMCID: PMC10542378 DOI: 10.1038/s41598-023-43690-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 09/27/2023] [Indexed: 10/02/2023] Open
Abstract
The serotonin transporter (5-HTT) critically shapes serotonin neurotransmission by regulating extracellular brain serotonin levels; it remains unclear to what extent 5-HTT levels in the human brain are genetically determined. Here we applied [11C]DASB positron emission tomography to image brain 5-HTT levels and evaluated associations with five common serotonin-related genetic variants that might indirectly regulate 5-HTT levels (BDNF rs6265, SLC6A4 5-HTTLPR, HTR1A rs6295, HTR2A rs7333412, and MAOA rs1137070) in 140 healthy volunteers. In addition, we explored whether these variants could predict in vivo 5-HTT levels using a five-fold cross-validation random forest framework. MAOA rs1137070 T-carriers showed significantly higher brain 5-HTT levels compared to C-homozygotes (2-11% across caudate, putamen, midbrain, thalamus, hippocampus, amygdala and neocortex). We did not observe significant associations for the HTR1A rs6295 and HTR2A rs7333412 genotypes. Our previously observed lower subcortical 5-HTT availability for rs6265 met-carriers remained in the presence of these additional variants. Despite this significant association, our prediction models showed that genotype moderately improved prediction of 5-HTT in caudate, but effects were not statistically significant after adjustment for multiple comparisons. Our observations provide additional evidence that serotonin-related genetic variants modulate adult human brain serotonin neurotransmission.
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Affiliation(s)
- Silvia Elisabetta Portis Bruzzone
- Neurobiology Research Unit, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Arafat Nasser
- Neurobiology Research Unit, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
| | - Sagar Sanjay Aripaka
- Neurobiology Research Unit, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Marie Spies
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Brice Ozenne
- Neurobiology Research Unit, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
- Department of Public Health, Section of Biostatistics, University of Copenhagen, Copenhagen, Denmark
| | - Peter Steen Jensen
- Neurobiology Research Unit, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
| | - Gitte Moos Knudsen
- Neurobiology Research Unit, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Vibe Gedsoe Frokjaer
- Neurobiology Research Unit, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Psychiatric Centre Copenhagen, Copenhagen, Denmark
| | - Patrick MacDonald Fisher
- Neurobiology Research Unit, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark.
- Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark.
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Zheng J, Chen L, Cai G, Wang Y, Huang J, Lin X, Li Y, Yu Q, Chen X, Shi Y, Ye Q. The effect of Parkin gene S/N 167 polymorphism on resting spontaneous brain functional activity in Parkinson's Disease. Parkinsonism Relat Disord 2023; 113:105484. [PMID: 37454429 DOI: 10.1016/j.parkreldis.2023.105484] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 05/09/2023] [Accepted: 06/04/2023] [Indexed: 07/18/2023]
Abstract
BACKGROUND Genetic susceptibility plays a significant role in Parkinson's disease (PD) development. Carriers of the Parkin S/N167 mutation may have an increased risk of PD and altered spontaneous brain activity. OBJECTIVE This study aims to investigate the potential pathogenesis of PD through a comparative analysis of the amplitude of low-frequency fluctuations (ALFF) in resting-state functional magnetic resonance imaging (rs-fMRI) of subjects with Parkin gene S/N 167 polymorphisms, and to examine the association between spontaneous brain activity and clinical scale scores of PD. METHODS A total of 69 PD patients and 84 healthy controls (HC) were included in the study. Each subject was genotyped for the Parkin gene S/N 167 polymorphism and underwent rs-fMRI scans. ALFF analysis was employed to evaluate the relationship among genotypes, interactive brain regions, and clinical symptoms in PD. RESULTS PD patients exhibited decreased ALFF values in the right anterior lobe and vermis of the cerebellum compared to HC. No significant interaction was found between the gene's main effect and the "group × genotype" effect on brain ALFF values. One-factor ANOVA revealed no significant difference in ALFF values between PD subgroups; however, the ALFF values in the right anterior lobe and vermis of the cerebellum were lower in the PD-G and PD-GA groups compared to the HC-G and HC-GA groups. Spearman correlation analysis demonstrated that ALFF values in the PD-GG and PD-GA groups were negatively associated with UPDRS-III scores in the bilateral lingual gyrus (Lingual R/L). CONCLUSION Parkin gene S/N 167 polymorphisms may influence brain functional activity in specific brain regions, and ALFF values are associated with motor symptoms in PD patients.
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Affiliation(s)
- Jingxue Zheng
- Department of Neurology, Fujian Institute of Geriatrics, Fujian Medical University Union Hospital, Fuzhou, Fujian, China; Fudan University Shanghai Cancer Center(Xiamen Branch), Xiamen, Fujian, China
| | - Lina Chen
- Department of Neurology, Fujian Institute of Geriatrics, Fujian Medical University Union Hospital, Fuzhou, Fujian, China
| | - Guoen Cai
- Department of Neurology, Fujian Institute of Geriatrics, Fujian Medical University Union Hospital, Fuzhou, Fujian, China
| | - Yingqing Wang
- Department of Neurology, Fujian Institute of Geriatrics, Fujian Medical University Union Hospital, Fuzhou, Fujian, China
| | - Jieming Huang
- Department of Neurology, Fujian Institute of Geriatrics, Fujian Medical University Union Hospital, Fuzhou, Fujian, China
| | - Xiaoling Lin
- Department of Neurology, Fujian Institute of Geriatrics, Fujian Medical University Union Hospital, Fuzhou, Fujian, China
| | - Yueping Li
- Department of Neurology, Fujian Institute of Geriatrics, Fujian Medical University Union Hospital, Fuzhou, Fujian, China
| | - Qianwen Yu
- Department of Neurology, Fujian Institute of Geriatrics, Fujian Medical University Union Hospital, Fuzhou, Fujian, China
| | - Xiaochun Chen
- Department of Neurology, Fujian Institute of Geriatrics, Fujian Medical University Union Hospital, Fuzhou, Fujian, China; Institute of Neuroscience, Fujian Key Laboratory of Molecular Neurology, Fujian Medical University, Fuzhou, China
| | - Yanchuan Shi
- Department of Neurology, Fujian Institute of Geriatrics, Fujian Medical University Union Hospital, Fuzhou, Fujian, China; Department of Neurology, Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou, Fujian, China.
| | - Qinyong Ye
- Department of Neurology, Fujian Institute of Geriatrics, Fujian Medical University Union Hospital, Fuzhou, Fujian, China; Institute of Neuroscience, Fujian Key Laboratory of Molecular Neurology, Fujian Medical University, Fuzhou, China.
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10
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Pretzsch CM, Ecker C. Structural neuroimaging phenotypes and associated molecular and genomic underpinnings in autism: a review. Front Neurosci 2023; 17:1172779. [PMID: 37457001 PMCID: PMC10347684 DOI: 10.3389/fnins.2023.1172779] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Accepted: 06/09/2023] [Indexed: 07/18/2023] Open
Abstract
Autism has been associated with differences in the developmental trajectories of multiple neuroanatomical features, including cortical thickness, surface area, cortical volume, measures of gyrification, and the gray-white matter tissue contrast. These neuroimaging features have been proposed as intermediate phenotypes on the gradient from genomic variation to behavioral symptoms. Hence, examining what these proxy markers represent, i.e., disentangling their associated molecular and genomic underpinnings, could provide crucial insights into the etiology and pathophysiology of autism. In line with this, an increasing number of studies are exploring the association between neuroanatomical, cellular/molecular, and (epi)genetic variation in autism, both indirectly and directly in vivo and across age. In this review, we aim to summarize the existing literature in autism (and neurotypicals) to chart a putative pathway from (i) imaging-derived neuroanatomical cortical phenotypes to (ii) underlying (neuropathological) biological processes, and (iii) associated genomic variation.
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Affiliation(s)
- Charlotte M. Pretzsch
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, United Kingdom
| | - Christine Ecker
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Frankfurt, Goethe University, Frankfurt, Germany
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11
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Spies M, Murgaš M, Vraka C, Philippe C, Gryglewski G, Nics L, Balber T, Baldinger-Melich P, Hartmann AM, Rujescu D, Hacker M, Winkler-Pjrek E, Winkler D, Lanzenberger R. Impact of genetic variants within serotonin turnover enzymes on human cerebral monoamine oxidase A in vivo. Transl Psychiatry 2023; 13:208. [PMID: 37322010 PMCID: PMC10272199 DOI: 10.1038/s41398-023-02506-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 05/28/2023] [Accepted: 06/01/2023] [Indexed: 06/17/2023] Open
Abstract
Variants within the monoamine oxidase A (MAO-A, MAOA) and tryptophan hydroxylase 2 (TPH2) genes, the main enzymes in cerebral serotonin (5-HT) turnover, affect risk for depression. Depressed cohorts show increased cerebral MAO-A in positron emission tomography (PET) studies. TPH2 polymorphisms might also influence brain MAO-A because availability of substrates (i.e. monoamine concentrations) were shown to affect MAO-A levels. We assessed the effect of MAOA (rs1137070, rs2064070, rs6323) and TPH2 (rs1386494, rs4570625) variants associated with risk for depression and related clinical phenomena on global MAO-A distribution volume (VT) using [11C]harmine PET in 51 participants (21 individuals with seasonal affective disorder (SAD) and 30 healthy individuals (HI)). Statistical analyses comprised general linear models with global MAO-A VT as dependent variable, genotype as independent variable and age, sex, group (individuals with SAD, HI) and season as covariates. rs1386494 genotype significantly affected global MAO-A VT after correction for age, group and sex (p < 0.05, corr.), with CC homozygotes showing 26% higher MAO-A levels. The role of rs1386494 on TPH2 function or expression is poorly understood. Our results suggest rs1386494 might have an effect on either, assuming that TPH2 and MAO-A levels are linked by their common product/substrate, 5-HT. Alternatively, rs1386494 might influence MAO-A levels via another mechanism, such as co-inheritance of other genetic variants. Our results provide insight into how genetic variants within serotonin turnover translate to the cerebral serotonin system. Clinicaltrials.gov Identifier: NCT02582398. EUDAMED Number: CIV-AT-13-01-009583.
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Affiliation(s)
- Marie Spies
- Department of Psychiatry and Psychotherapy, Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Vienna, Austria
| | - Matej Murgaš
- Department of Psychiatry and Psychotherapy, Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Vienna, Austria
| | - Chrysoula Vraka
- Department of Biomedical Imaging and Image-guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Vienna, Austria
| | - Cecile Philippe
- Department of Biomedical Imaging and Image-guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Vienna, Austria
| | - Gregor Gryglewski
- Department of Psychiatry and Psychotherapy, Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Vienna, Austria
- Child Study Center, Yale University, New Haven, CT, USA
| | - Lukas Nics
- Department of Biomedical Imaging and Image-guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Vienna, Austria
| | - Theresa Balber
- Department of Biomedical Imaging and Image-guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Vienna, Austria
- Ludwig Boltzmann Institute Applied Diagnostics, Vienna, Austria
| | - Pia Baldinger-Melich
- Department of Psychiatry and Psychotherapy, Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Vienna, Austria
| | - Annette M Hartmann
- Department of Psychiatry and Psychotherapy, Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Vienna, Austria
| | - Dan Rujescu
- Department of Psychiatry and Psychotherapy, Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Vienna, Austria
| | - Marcus Hacker
- Department of Biomedical Imaging and Image-guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Vienna, Austria
| | - Edda Winkler-Pjrek
- Department of Psychiatry and Psychotherapy, Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Vienna, Austria
| | - Dietmar Winkler
- Department of Psychiatry and Psychotherapy, Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Vienna, Austria
| | - Rupert Lanzenberger
- Department of Psychiatry and Psychotherapy, Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Vienna, Austria.
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12
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Norbury A, Seeley SH, Perez-Rodriguez MM, Feder A. Functional neuroimaging of resilience to trauma: convergent evidence and challenges for future research. Psychol Med 2023; 53:3293-3305. [PMID: 37264949 PMCID: PMC11350638 DOI: 10.1017/s0033291723001162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
Resilience is broadly defined as the ability to adapt successfully following stressful life events. Here, we review functional MRI studies that investigated key psychological factors that have been consistently linked to resilience to severe adversity and trauma exposure. These domains include emotion regulation (including cognitive reappraisal), reward responsivity, and cognitive control. Further, we briefly review functional imaging evidence related to emerging areas of study that may potentially facilitate resilience: namely social cognition, active coping, and successful fear extinction. Finally, we also touch upon ongoing issues in neuroimaging study design that will need to be addressed to enable us to harness insight from such studies to improve treatments for - or, ideally, guard against the development of - debilitating post-traumatic stress syndromes.
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Affiliation(s)
- Agnes Norbury
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Queen Square Institute of Neurology and Mental Health Neuroscience Department, Applied Computational Psychiatry Lab, Max Planck Centre for Computational Psychiatry and Ageing Research, University College London, London, UK
| | - Saren H. Seeley
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - Adriana Feder
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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13
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Alex AM, Buss C, Davis EP, Campos GDL, Donald KA, Fair DA, Gaab N, Gao W, Gilmore JH, Girault JB, Grewen K, Groenewold NA, Hankin BL, Ipser J, Kapoor S, Kim P, Lin W, Luo S, Norton ES, O'Connor TG, Piven J, Qiu A, Rasmussen JM, Skeide MA, Stein DJ, Styner MA, Thompson PM, Wakschlag L, Knickmeyer R. Genetic Influences on the Developing Young Brain and Risk for Neuropsychiatric Disorders. Biol Psychiatry 2023; 93:905-920. [PMID: 36932005 PMCID: PMC10136952 DOI: 10.1016/j.biopsych.2023.01.013] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Revised: 01/09/2023] [Accepted: 01/11/2023] [Indexed: 01/30/2023]
Abstract
Imaging genetics provides an opportunity to discern associations between genetic variants and brain imaging phenotypes. Historically, the field has focused on adults and adolescents; very few imaging genetics studies have focused on brain development in infancy and early childhood (from birth to age 6 years). This is an important knowledge gap because developmental changes in the brain during the prenatal and early postnatal period are regulated by dynamic gene expression patterns that likely play an important role in establishing an individual's risk for later psychiatric illness and neurodevelopmental disabilities. In this review, we summarize findings from imaging genetics studies spanning from early infancy to early childhood, with a focus on studies examining genetic risk for neuropsychiatric disorders. We also introduce the Organization for Imaging Genomics in Infancy (ORIGINs), a working group of the ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) consortium, which was established to facilitate large-scale imaging genetics studies in infancy and early childhood.
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Affiliation(s)
- Ann M Alex
- Institute for Quantitative Health Sciences and Engineering, Michigan State University, East Lansing, Michigan
| | - Claudia Buss
- Charité Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Medical Psychology, Berlin, Germany; Department of Pediatrics, University of California Irvine, Irvine, California; Development, Health and Disease Research Program, University of California Irvine, Irvine, California
| | - Elysia Poggi Davis
- Department of Pediatrics, University of California Irvine, Irvine, California; Department of Psychology, University of Denver, Denver, Colorado
| | - Gustavo de Los Campos
- Institute for Quantitative Health Sciences and Engineering, Michigan State University, East Lansing, Michigan; Departments of Epidemiology & Biostatistics, Michigan State University, East Lansing, Michigan; Department of Statistics & Probability, Michigan State University, East Lansing, Michigan
| | - Kirsten A Donald
- Division of Developmental Paediatrics, Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, University of Cape Town, Cape Town, South Africa; Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Damien A Fair
- Masonic Institute for the Developing Brain, University of Minnesota Medical School, Minneapolis, Minnesota; Institute of Child Development, College of Education and Human Development, University of Minnesota, Minneapolis, Minnesota; Department of Pediatrics, University of Minnesota Medical School, Minneapolis, Minnesota
| | - Nadine Gaab
- Harvard Graduate School of Education, Harvard University, Cambridge, Massachusetts
| | - Wei Gao
- Cedars-Sinai Biomedical Imaging Research Institute, Los Angeles, California; Departments of Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, Los Angeles, California
| | - John H Gilmore
- Department of Psychiatry, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina
| | - Jessica B Girault
- Department of Psychiatry, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina; Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Carrboro, North Carolina
| | - Karen Grewen
- Department of Psychiatry, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina
| | - Nynke A Groenewold
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa; South African Medical Research Council Unit on Child and Adolescent Health, University of Cape Town, Cape Town, South Africa; Department of Paediatrics and Child Health, University of Cape Town, Faculty of Health Sciences, Cape Town, South Africa
| | - Benjamin L Hankin
- Psychology Department, University of Illinois Urbana,-Champaign, Illinois
| | - Jonathan Ipser
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Shreya Kapoor
- Research Group Learning in Early Childhood, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Pilyoung Kim
- Department of Psychology, University of Denver, Denver, Colorado
| | - Weili Lin
- Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Shan Luo
- Department of Medicine, Keck School of Medicine of the University of Southern California, Los Angeles, California; Department of Psychology, University of Southern California, Los Angeles, California; Center for Endocrinology, Diabetes and Metabolism, Children's Hospital Los Angeles, Los Angeles, California
| | - Elizabeth S Norton
- Roxelyn and Richard Pepper Department of Communication Sciences and Disorders, Northwestern University, Evanston, Illinois; Department of Medical Social Sciences and Institute for Innovations in Developmental Sciences, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
| | - Thomas G O'Connor
- Departments of Psychiatry, Psychology, Neuroscience, Obstetrics and Gynecology, University of Rochester, Rochester, New York
| | - Joseph Piven
- Department of Psychiatry, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina; Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Carrboro, North Carolina
| | - Anqi Qiu
- Department of Biomedical Engineering, National University of Singapore, Singapore; NUS (Suzhou) Research Institute, National University of Singapore, China; the Institute for Health, National University of Singapore, Singapore; School of Computer Engineering and Science, Shanghai University, Shanghai, China; Institute of Data Science, National University of Singapore, Singapore; Department of Biomedical Engineering, the Johns Hopkins University, Baltimore, Maryland
| | - Jerod M Rasmussen
- Department of Pediatrics, University of California Irvine, Irvine, California; Development, Health and Disease Research Program, University of California Irvine, Irvine, California
| | - Michael A Skeide
- Department of Psychiatry, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina; Research Group Learning in Early Childhood, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Dan J Stein
- South African Medical Research Council Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry, University of Cape Town, Cape Town, South Africa; Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Martin A Styner
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Paul M Thompson
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of University of the Sunshine Coast, Marina del Rey, California
| | - Laurie Wakschlag
- Department of Medical Social Sciences and Institute for Innovations in Developmental Sciences, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
| | - Rebecca Knickmeyer
- Institute for Quantitative Health Sciences and Engineering, Michigan State University, East Lansing, Michigan; Department of Pediatrics and Human Development, Michigan State University, East Lansing, Michigan.
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14
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Miller AP, Gizer IR. Dual-systems models of the genetic architecture of impulsive personality traits: Neurogenetic evidence of distinct but related factors. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.02.10.23285725. [PMID: 36824800 PMCID: PMC9949186 DOI: 10.1101/2023.02.10.23285725] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/16/2023]
Abstract
Background Dual-systems models provide a parsimonious framework for understanding the interplay between cortical and subcortical brain regions relevant to impulsive personality traits (IPTs) and their associations with psychiatric disorders. Despite recent developments in multivariate analysis of genome-wide association studies (GWAS), molecular genetic investigations of these models have not been conducted. Methods Using extant IPT GWAS, we conducted confirmatory genomic structural equation models (GenomicSEM) to empirically evaluate dual-systems models of the genetic architecture of IPTs. Genetic correlations between results of multivariate GWAS of dual-systems factors and GWAS of relevant cortical and subcortical neuroimaging phenotypes (regional/structural volume, cortical surface area, cortical thickness) were calculated and compared. Results Evaluation of GenomicSEM model fit indices for dual-systems models suggested that these models highlight important sources of shared and unique genetic variance between top-down and bottom-up constructs. Specifically, a dual-systems genomic model consisting of sensation seeking and lack of self-control factors demonstrated distinct but related sources of genetic influences ( r g =.60). Genetic correlation analyses provided evidence of differential associations between dual-systems factors and cortical neuroimaging phenotypes (e.g., lack of self-control negatively associated with cortical thickness, sensation seeking positively associated with cortical surface area). However, no significant associations were observed for subcortical phenotypes inconsistent with hypothesized functional localization of dual-systems constructs. Conclusions Dual-systems models of the genetic architecture of IPTs tested here demonstrate evidence of shared and unique genetic influences and associations with relevant neuroimaging phenotypes. These findings emphasize potential advantages in utilizing dual-systems models to study genetic influences for IPTs and transdiagnostic associations with psychiatric disorders.
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15
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The molecular genetic basis of creativity: a mini review and perspectives. PSYCHOLOGICAL RESEARCH 2023; 87:1-16. [PMID: 35217895 DOI: 10.1007/s00426-022-01649-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Accepted: 01/16/2022] [Indexed: 01/27/2023]
Abstract
Although creativity is one of the defining features of human species, it is just the beginning of an ambitious attempt for psychologists to understand its genetic basis. With ongoing efforts, great progress has been achieved in molecular genetic studies of creativity. In this mini review, we highlighted recent molecular genetic findings for both domain-general and domain-specific creativity, and provided some perspectives for future studies. It is expected that this work will provide an update on the knowledge regarding the molecular genetic basis of creativity, and contribute to the further development of this field.
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16
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Moon SW. Neuroimaging Genetics and Network Analysis in Alzheimer's Disease. Curr Alzheimer Res 2023; 20:526-538. [PMID: 37957920 DOI: 10.2174/0115672050265188231107072215] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Revised: 07/22/2023] [Accepted: 08/13/2023] [Indexed: 11/15/2023]
Abstract
The issue of the genetics in brain imaging phenotypes serves as a crucial link between two distinct scientific fields: neuroimaging genetics (NG). The articles included here provide solid proof that this NG link has considerable synergy. There is a suitable collection of articles that offer a wide range of viewpoints on how genetic variations affect brain structure and function. They serve as illustrations of several study approaches used in contemporary genetics and neuroscience. Genome-wide association studies and candidate-gene association are two examples of genetic techniques. Cortical gray matter structural/volumetric measures from magnetic resonance imaging (MRI) are sources of information on brain phenotypes. Together, they show how various scientific disciplines have benefited from significant technological advances, such as the single-nucleotide polymorphism array in genetics and the development of increasingly higher-resolution MRI imaging. Moreover, we discuss NG's contribution to expanding our knowledge about the heterogeneity within Alzheimer's disease as well as the benefits of different network analyses.
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Affiliation(s)
- Seok Woo Moon
- Department of Psychiatry, Institute of Medical Science, Konkuk University School of Medicine, Chungju, Republic of Korea
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17
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TRIAC Treatment Improves Impaired Brain Network Function and White Matter Loss in Thyroid Hormone Transporter Mct8/Oatp1c1 Deficient Mice. Int J Mol Sci 2022; 23:ijms232415547. [PMID: 36555189 PMCID: PMC9779161 DOI: 10.3390/ijms232415547] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 12/01/2022] [Accepted: 12/05/2022] [Indexed: 12/13/2022] Open
Abstract
Dysfunctions of the thyroid hormone (TH) transporting monocarboxylate transporter MCT8 lead to a complex X-linked syndrome with abnormal serum TH concentrations and prominent neuropsychiatric symptoms (Allan-Herndon-Dudley syndrome, AHDS). The key features of AHDS are replicated in double knockout mice lacking MCT8 and organic anion transporting protein OATP1C1 (Mct8/Oatp1c1 DKO). In this study, we characterize impairments of brain structure and function in Mct8/Oatp1c1 DKO mice using multimodal magnetic resonance imaging (MRI) and assess the potential of the TH analogue 3,3',5-triiodothyroacetic acid (TRIAC) to rescue this phenotype. Structural and functional MRI were performed in 11-weeks-old male Mct8/Oatp1c1 DKO mice (N = 10), wild type controls (N = 7) and Mct8/Oatp1c1 DKO mice (N = 13) that were injected with TRIAC (400 ng/g bw s.c.) daily during the first three postnatal weeks. Grey and white matter volume were broadly reduced in Mct8/Oatp1c1 DKO mice. TRIAC treatment could significantly improve white matter thinning but did not affect grey matter loss. Network-based statistic showed a wide-spread increase of functional connectivity, while graph analysis revealed an impairment of small-worldness and whole-brain segregation in Mct8/Oatp1c1 DKO mice. Both functional deficits could be substantially ameliorated by TRIAC treatment. Our study demonstrates prominent structural and functional brain alterations in Mct8/Oatp1c1 DKO mice that may underlie the psychomotor deficiencies in AHDS. Additionally, we provide preclinical evidence that early-life TRIAC treatment improves white matter loss and brain network dysfunctions associated with TH transporter deficiency.
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18
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Cao H, Hong X, Tost H, Meyer-Lindenberg A, Schwarz E. Advancing translational research in neuroscience through multi-task learning. Front Psychiatry 2022; 13:993289. [PMID: 36465289 PMCID: PMC9714033 DOI: 10.3389/fpsyt.2022.993289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Accepted: 10/24/2022] [Indexed: 11/18/2022] Open
Abstract
Translational research in neuroscience is increasingly focusing on the analysis of multi-modal data, in order to account for the biological complexity of suspected disease mechanisms. Recent advances in machine learning have the potential to substantially advance such translational research through the simultaneous analysis of different data modalities. This review focuses on one of such approaches, the so-called "multi-task learning" (MTL), and describes its potential utility for multi-modal data analyses in neuroscience. We summarize the methodological development of MTL starting from conventional machine learning, and present several scenarios that appear particularly suitable for its application. For these scenarios, we highlight different types of MTL algorithms, discuss emerging technological adaptations, and provide a step-by-step guide for readers to apply the MTL approach in their own studies. With its ability to simultaneously analyze multiple data modalities, MTL may become an important element of the analytics repertoire used in future neuroscience research and beyond.
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Affiliation(s)
- Han Cao
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Xudong Hong
- Department of Computer Vision and Machine Learning, Max Planck Institute for Informatics, Saarbrücken, Germany
- Department of Language Science and Technology, Saarland University, Saarbrücken, Germany
| | - Heike Tost
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Andreas Meyer-Lindenberg
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Emanuel Schwarz
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
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Vouga Ribeiro N, Tavares V, Bramon E, Toulopoulou T, Valli I, Shergill S, Murray R, Prata D. Effects of psychosis-associated genetic markers on brain volumetry: a systematic review of replicated findings and an independent validation. Psychol Med 2022; 52:1-16. [PMID: 36168994 PMCID: PMC9811278 DOI: 10.1017/s0033291722002896] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Revised: 08/13/2022] [Accepted: 08/24/2022] [Indexed: 01/12/2023]
Abstract
BACKGROUND Given psychotic illnesses' high heritability and associations with brain structure, numerous neuroimaging-genetics findings have been reported in the last two decades. However, few findings have been replicated. In the present independent sample we aimed to replicate any psychosis-implicated SNPs (single nucleotide polymorphisms), which had previously shown at least two main effects on brain volume. METHODS A systematic review for SNPs showing a replicated effect on brain volume yielded 25 studies implicating seven SNPs in five genes. Their effect was then tested in 113 subjects with either schizophrenia, bipolar disorder, 'at risk mental state' or healthy state, for whole-brain and region-of-interest (ROI) associations with grey and white matter volume changes, using voxel-based morphometry. RESULTS We found FWER-corrected (Family-wise error rate) (i.e. statistically significant) associations of: (1) CACNA1C-rs769087-A with larger bilateral hippocampus and thalamus white matter, across the whole brain; and (2) CACNA1C-rs769087-A with larger superior frontal gyrus, as ROI. Higher replication concordance with existing literature was found, in decreasing order, for: (1) CACNA1C-rs769087-A, with larger dorsolateral-prefrontal/superior frontal gyrus and hippocampi (both with anatomical and directional concordance); (2) ZNF804A-rs11681373-A, with smaller angular gyrus grey matter and rectus gyri white matter (both with anatomical and directional concordance); and (3) BDNF-rs6265-T with superior frontal and middle cingulate gyri volume change (with anatomical and allelic concordance). CONCLUSIONS Most literature findings were not herein replicated. Nevertheless, high degree/likelihood of replication was found for two genome-wide association studies- and one candidate-implicated SNPs, supporting their involvement in psychosis and brain structure.
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Affiliation(s)
- Nuno Vouga Ribeiro
- Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal
- Instituto de Biofísica e Engenharia Biomédica, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal
| | - Vânia Tavares
- Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal
- Instituto de Biofísica e Engenharia Biomédica, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal
| | - Elvira Bramon
- Division of Psychiatry, University College London, London, UK
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’ College London, London, UK
- Institute of Cognitive Neuroscience, University College London, London, UK
| | - Timothea Toulopoulou
- Department of Psychology & National Magnetic Resonance Research Center (UMRAM), Aysel Sabuncu Brain Research Centre (ASBAM), Bilkent University, Ankara, Turkey
| | - Isabel Valli
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’ College London, London, UK
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain
| | - Sukhi Shergill
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’ College London, London, UK
| | - Robin Murray
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’ College London, London, UK
| | - Diana Prata
- Instituto de Biofísica e Engenharia Biomédica, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal
- Department of Old Age Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
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Qi S, Sui J, Pearlson G, Bustillo J, Perrone-Bizzozero NI, Kochunov P, Turner JA, Fu Z, Shao W, Jiang R, Yang X, Liu J, Du Y, Chen J, Zhang D, Calhoun VD. Derivation and utility of schizophrenia polygenic risk associated multimodal MRI frontotemporal network. Nat Commun 2022; 13:4929. [PMID: 35995794 PMCID: PMC9395379 DOI: 10.1038/s41467-022-32513-8] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Accepted: 08/03/2022] [Indexed: 12/23/2022] Open
Abstract
Schizophrenia is a highly heritable psychiatric disorder characterized by widespread functional and structural brain abnormalities. However, previous association studies between MRI and polygenic risk were mostly ROI-based single modality analyses, rather than identifying brain-based multimodal predictive biomarkers. Based on schizophrenia polygenic risk scores (PRS) from healthy white people within the UK Biobank dataset (N = 22,459), we discovered a robust PRS-associated brain pattern with smaller gray matter volume and decreased functional activation in frontotemporal cortex, which distinguished schizophrenia from controls with >83% accuracy, and predicted cognition and symptoms across 4 independent schizophrenia cohorts. Further multi-disease comparisons demonstrated that these identified frontotemporal alterations were most severe in schizophrenia and schizo-affective patients, milder in bipolar disorder, and indistinguishable from controls in autism, depression and attention-deficit hyperactivity disorder. These findings indicate the potential of the identified PRS-associated multimodal frontotemporal network to serve as a trans-diagnostic gene intermediated brain biomarker specific to schizophrenia.
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Affiliation(s)
- Shile Qi
- College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
| | - Jing Sui
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.
| | - Godfrey Pearlson
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - Juan Bustillo
- Departments of Psychiatry and Behavioral Sciences, University of New Mexico, Albuquerque, NM, USA
| | - Nora I Perrone-Bizzozero
- Departments of Psychiatry and Behavioral Sciences, University of New Mexico, Albuquerque, NM, USA
| | - Peter Kochunov
- Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Jessica A Turner
- Department of Psychology, Georgia State University, Atlanta, GA, USA
| | - Zening Fu
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), [Georgia State University, Georgia Institute of Technology, Emory University], Atlanta, GA, USA
| | - Wei Shao
- College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China
| | - Rongtao Jiang
- Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA
| | - Xiao Yang
- Huaxi Brain Research Center, West China Hospital of Sichuan University, Chengdu, China
| | - Jingyu Liu
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), [Georgia State University, Georgia Institute of Technology, Emory University], Atlanta, GA, USA
| | - Yuhui Du
- School of Computer & Information Technology, Shanxi University, Taiyuan, China
| | - Jiayu Chen
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), [Georgia State University, Georgia Institute of Technology, Emory University], Atlanta, GA, USA.
| | - Daoqiang Zhang
- College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
| | - Vince D Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), [Georgia State University, Georgia Institute of Technology, Emory University], Atlanta, GA, USA
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21
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Cattarinussi G, Delvecchio G, Sambataro F, Brambilla P. The effect of polygenic risk scores for major depressive disorder, bipolar disorder and schizophrenia on morphological brain measures: A systematic review of the evidence. J Affect Disord 2022; 310:213-222. [PMID: 35533776 DOI: 10.1016/j.jad.2022.05.007] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Revised: 04/27/2022] [Accepted: 05/04/2022] [Indexed: 01/26/2023]
Abstract
BACKGROUND Major depressive disorder (MDD), bipolar disorder (BD) and schizophrenia (SCZ) share clinical features and genetic bases. Magnetic Resonance Imaging (MRI) studies assessing the effect of polygenic risk score (PRS) for psychiatric disorders on brain structure show heterogeneous results. Therefore, we provided an overview of the existing evidence on the association between PRS for MDD, BD and SCZ and MRI abnormalities in clinical and healthy populations. METHODS A search on PubMed, Web of Science and Scopus was performed to identify the studies exploring the effect of PRS for MDD, BD and SCZ on MRI measures. A total of 25 studies were included (N = 13 on healthy individuals and N = 12 on clinical populations). RESULTS Both in affected and unaffected individuals, PRS for BD and SCZ showed either positive or negative correlations with cortical thickness (CT), mostly involving fronto-temporal areas, whereas PRS for MDD was associated with cortical alterations in prefrontal regions in healthy subjects. LIMITATIONS The heterogeneity in the methods limits the conclusions of this review. CONCLUSIONS Overall the evidence on the effect of PRS for MDD, BD and SCZ on brain is considerably heterogeneous and far to be conclusive. However, from the results emerged that PRS for MDD, BD and SCZ were associated with widespread cortical abnormalities in all the populations explored, suggesting that genetic risk for MDD, BD and SCZ might affect neurodevelopmental processes, resulting in cortical alterations that transcend diagnostic boundaries and seem to be independent from the clinical status.
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Affiliation(s)
- Giulia Cattarinussi
- Department of Neuroscience (DNS), University of Padova, Padua, Italy; Padua Neuroscience Center, University of Padova, Padua, Italy
| | - Giuseppe Delvecchio
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy.
| | - Fabio Sambataro
- Department of Neuroscience (DNS), University of Padova, Padua, Italy; Padua Neuroscience Center, University of Padova, Padua, Italy
| | - Paolo Brambilla
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy; Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
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22
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Bi XA, Xing Z, Zhou W, Li L, Xu L. Pathogeny Detection for Mild Cognitive Impairment via Weighted Evolutionary Random Forest with Brain Imaging and Genetic Data. IEEE J Biomed Health Inform 2022; 26:3068-3079. [PMID: 35157601 DOI: 10.1109/jbhi.2022.3151084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
Medical imaging technology and gene sequencing technology have long been widely used to analyze the pathogenesis and make precise diagnoses of mild cognitive impairment (MCI). However, few studies involve the fusion of radiomics data with genomics data to make full use of the complementarity between different omics to detect pathogenic factors of MCI. This paper performs multimodal fusion analysis based on functional magnetic resonance imaging (fMRI) data and single nucleotide polymorphism (SNP) data of MCI patients. In specific, first, using correlation analysis methods on sequence information of regions of interests (ROIs) and digitalized gene sequences, the fusion features of samples are constructed. Then, introducing weighted evolution strategy into ensemble learning, a novel weighted evolutionary random forest (WERF) model is built to eliminate the inefficient features. Consequently, with the help of WERF, an overall multimodal data analysis framework is established to effectively identify MCI patients and extract pathogenic factors. Based on the data of MCI patients from the ADNI database and compared with some existing popular methods, the superiority in performance of the framework is verified. Our study has great potential to be an effective tool for pathogenic factors detection of MCI.
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23
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Bao J, Wen Z, Kim M, Saykin AJ, Thompson PM, Zhao Y, Shen L. Identifying imaging genetic associations via regional morphometricity estimation. PACIFIC SYMPOSIUM ON BIOCOMPUTING. PACIFIC SYMPOSIUM ON BIOCOMPUTING 2022; 27:97-108. [PMID: 34890140 PMCID: PMC8730533] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Brain imaging genetics is an emerging research field aiming to reveal the genetic basis of brain traits captured by imaging data. Inspired by heritability analysis, the concept of morphometricity was recently introduced to assess trait association with whole brain morphology. In this study, we extend the concept of morphometricity from its original definition at the whole brain level to a more focal level based on a region of interest (ROI). We propose a novel framework to identify the SNP-ROI association via regional morphometricity estimation of each studied single nucleotide polymorphism (SNP). We perform an empirical study on the structural MRI and genotyping data from a landmark Alzheimer's disease (AD) biobank; and yield promising results. Our findings indicate that the AD-related SNPs have higher overall regional morphometricity estimates than the SNPs not yet related to AD. This observation suggests that the variance of AD SNPs can be explained more by regional morphometric features than non-AD SNPs, supporting the value of imaging traits as targets in studying AD genetics. Also, we identified 11 ROIs, where the AD/non-AD SNPs and significant/insignificant morphometricity estimation of the corresponding SNPs in these ROIs show strong dependency. Supplementary motor area (SMA) and dorsolateral prefrontal cortex (DPC) are enriched by these ROIs. Our results also demonstrate that using all the detailed voxel-level measures within the ROI to incorporate morphometric information outperforms using only a single average ROI measure, and thus provides improved power to detect imaging genetic associations.
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Affiliation(s)
- Jingxuan Bao
- Department of Biostatistics, Epidemiology and Informatics University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Zixuan Wen
- Department of Biostatistics, Epidemiology and Informatics University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Mansu Kim
- Department of Biostatistics, Epidemiology and Informatics University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Andrew J. Saykin
- Indiana Alzheimer Disease Center, Department of Radiology and Imaging Sciences Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Paul M. Thompson
- Imaging Genetics Center, Stevens Institute for Neuroimaging and Informatics University of Southern California School of Medicine, Marina del Rey, CA 90292, USA
| | - Yize Zhao
- Department of Biostatistics Yale University School of Public Health, New Haven, CT 06511, USA
| | - Li Shen
- Department of Biostatistics, Epidemiology and Informatics University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
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24
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Mo C, Ye Z, Ke H, Lu T, Canida T, Liu S, Wu Q, Zhao Z, Ma Y, Elliot Hong L, Kochunov P, Ma T, Chen S. A new Mendelian Randomization method to estimate causal effects of multivariable brain imaging exposures. PACIFIC SYMPOSIUM ON BIOCOMPUTING. PACIFIC SYMPOSIUM ON BIOCOMPUTING 2022; 27:73-84. [PMID: 34890138 PMCID: PMC8669774] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
The advent of simultaneously collected imaging-genetics data in large study cohorts provides an unprecedented opportunity to assess the causal effect of brain imaging traits on externally measured experimental results (e.g., cognitive tests) by treating genetic variants as instrumental variables. However, classic Mendelian Randomization methods are limited when handling high-throughput imaging traits as exposures to identify causal effects. We propose a new Mendelian Randomization framework to jointly select instrumental variables and imaging exposures, and then estimate the causal effect of multivariable imaging data on the outcome. We validate the proposed method with extensive data analyses and compare it with existing methods. We further apply our method to evaluate the causal effect of white matter microstructure integrity (WM) on cognitive function. The findings suggest that our method achieved better performance regarding sensitivity, bias, and false discovery rate compared to individually assessing the causal effect of a single exposure and jointly assessing the causal effect of multiple exposures without dimension reduction. Our application results indicated that WM measures across different tracts have a joint causal effect that significantly impacts the cognitive function among the participants from the UK Biobank.
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Affiliation(s)
- Chen Mo
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland 21201, United States of America
| | - Zhenyao Ye
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland 21201, United States of America
| | - Hongjie Ke
- Department of Mathematics, University of Maryland, College Park, Maryland 20740, United States of America
| | - Tong Lu
- Department of Mathematics, University of Maryland, College Park, Maryland 20740, United States of America
| | - Travis Canida
- Department of Mathematics, University of Maryland, College Park, Maryland 20740, United States of America
| | - Song Liu
- School of Computer Science and Technology, Qilu University of Technology (Shandong Academy of Sciences), Jinan, Shandong 250353, China
| | - Qiong Wu
- Department of Mathematics, University of Maryland, College Park, Maryland 20740, United States of America
| | - Zhiwei Zhao
- Department of Mathematics, University of Maryland, College Park, Maryland 20740, United States of America
| | - Yizhou Ma
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland 21201, United States of America
| | - L. Elliot Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland 21201, United States of America
| | - Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland 21201, United States of America
| | - Tianzhou Ma
- Department of Epidemiology and Biostatistics, School of Public Health, University of Maryland, College Park, Maryland 20740, United States of America
| | - Shuo Chen
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland 21201, United States of America
- Division of Biostatistics and Bioinformatics, Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland 21201, United States of America
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25
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Duan J, Zhang J, Liu L, Wen Y. A guidance of model selection for genomic prediction based on linear mixed models for complex traits. Front Genet 2022; 13:1017380. [PMID: 36276959 PMCID: PMC9581223 DOI: 10.3389/fgene.2022.1017380] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Accepted: 09/20/2022] [Indexed: 11/27/2022] Open
Abstract
Brain imaging outcomes are important for Alzheimer's disease (AD) detection, and their prediction based on both genetic and demographic risk factors can facilitate the ongoing prevention and treatment of AD. Existing studies have identified numerous significantly AD-associated SNPs. However, how to make the best use of them for prediction analyses remains unknown. In this research, we first explored the relationship between genetic architecture and prediction accuracy of linear mixed models via visualizing the Manhattan plots generated based on the data obtained from the Wellcome Trust Case Control Consortium, and then constructed prediction models for eleven AD-related brain imaging outcomes using data from United Kingdom Biobank and Alzheimer's Disease Neuroimaging Initiative studies. We found that the simple Manhattan plots can be informative for the selection of prediction models. For traits that do not exhibit any significant signals from the Manhattan plots, the simple genomic best linear unbiased prediction (gBLUP) model is recommended due to its robust and accurate prediction performance as well as its computational efficiency. For diseases and traits that show spiked signals on the Manhattan plots, the latent Dirichlet process regression is preferred, as it can flexibly accommodate both the oligogenic and omnigenic models. For the prediction of AD-related traits, the Manhattan plots suggest their polygenic nature, and gBLUP has achieved robust performance for all these traits. We found that for these AD-related traits, genetic factors themselves only explain a very small proportion of the heritability, and the well-known AD risk factors can substantially improve the prediction model.
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Affiliation(s)
- Jiefang Duan
- Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, China
| | - Jiayu Zhang
- Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, China
| | - Long Liu
- Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, China
| | - Yalu Wen
- Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, China.,Department of Statistics, University of Auckland, Auckland, New Zealand
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26
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Bondy E, Bogdan R. Understanding Anhedonia from a Genomic Perspective. Curr Top Behav Neurosci 2022; 58:61-79. [PMID: 35152374 PMCID: PMC9375777 DOI: 10.1007/7854_2021_293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Anhedonia, or the decreased ability to experience pleasure, is a cardinal symptom of major depression that commonly occurs within other forms of psychopathology. Supportive of long-held theory that anhedonia represents a genetically influenced vulnerability marker for depression, evidence from twin studies suggests that it is moderately-largely heritable. However, the genomic sources of this heritability are just beginning to be understood. In this review, we survey what is known about the genomic architecture underlying anhedonia and related constructs. We briefly review twin and initial candidate gene studies before focusing on genome-wide association study (GWAS) and polygenic efforts. As large samples are needed to reliably detect the small effects that typically characterize common genetic variants, the study of anhedonia and related phenotypes conflicts with current genomic research requirements and frameworks that prioritize sample size over precise phenotyping. This has resulted in few and underpowered studies of anhedonia-related constructs that have largely failed to reliably identify individual variants. Nonetheless, the polygenic architecture of anhedonia-related constructs identified in these studies has genetic overlap with depression and schizophrenia as well as related brain structure (e.g., striatal volume), providing important clues to etiology that may usefully guide refinement in nosology. As we await the accumulation of larger samples for more well-powered GWAS of reward-related constructs, novel analytic techniques that leverage GWAS summary statistics (e.g., genomic structural equation modeling) may currently be used to help characterize how the genomic architecture of anhedonia is shared and distinct from that underlying other constructs (e.g., depression, neuroticism, anxiety).
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Affiliation(s)
- Erin Bondy
- Department of Psychological and Brain Sciences, Washington University in Saint Louis, St. Louis, MO, USA
| | - Ryan Bogdan
- Department of Psychological and Brain Sciences, Washington University in Saint Louis, St. Louis, MO, USA.
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27
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Stauffer EM, Bethlehem RAI, Warrier V, Murray GK, Romero-Garcia R, Seidlitz J, Bullmore ET. Grey and white matter microstructure is associated with polygenic risk for schizophrenia. Mol Psychiatry 2021; 26:7709-7718. [PMID: 34462574 PMCID: PMC8872982 DOI: 10.1038/s41380-021-01260-5] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Revised: 07/26/2021] [Accepted: 07/30/2021] [Indexed: 02/07/2023]
Abstract
Recent discovery of approximately 270 common genetic variants associated with schizophrenia has enabled polygenic risk scores (PRS) to be measured in the population. We hypothesized that normal variation in PRS would be associated with magnetic resonance imaging (MRI) phenotypes of brain morphometry and tissue composition. We used the largest extant genome-wide association dataset (N = 69,369 cases and N = 236,642 healthy controls) to measure PRS for schizophrenia in a large sample of adults from the UK Biobank (Nmax = 29,878) who had multiple micro- and macrostructural MRI metrics measured at each of 180 cortical areas, seven subcortical structures, and 15 major white matter tracts. Linear mixed-effect models were used to investigate associations between PRS and brain structure at global and regional scales, controlled for multiple comparisons. Polygenic risk was significantly associated with reduced neurite density index (NDI) at global brain scale, at 149 cortical regions, five subcortical structures, and 14 white matter tracts. Other microstructural parameters, e.g., fractional anisotropy, that were correlated with NDI were also significantly associated with PRS. Genetic effects on multiple MRI phenotypes were co-located in temporal, cingulate, and prefrontal cortical areas, insula, and hippocampus. Post-hoc bidirectional Mendelian randomization analyses provided preliminary evidence in support of a causal relationship between (reduced) thalamic NDI and (increased) risk of schizophrenia. Risk-related reduction in NDI is plausibly indicative of reduced density of myelinated axons and dendritic arborization in large-scale cortico-subcortical networks. Cortical, subcortical, and white matter microstructure may be linked to the genetic mechanisms of schizophrenia.
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Affiliation(s)
- Eva-Maria Stauffer
- Department of Psychiatry, Cambridge Biomedical Campus, University of Cambridge, Cambridge, UK.
| | - Richard A I Bethlehem
- Department of Psychiatry, Cambridge Biomedical Campus, University of Cambridge, Cambridge, UK
| | - Varun Warrier
- Department of Psychiatry, Cambridge Biomedical Campus, University of Cambridge, Cambridge, UK
| | - Graham K Murray
- Department of Psychiatry, Cambridge Biomedical Campus, University of Cambridge, Cambridge, UK
- Cambridgeshire and Peterborough NHS Trust, Elizabeth House, Fulbourn Hospital, Cambridge, UK
- Institute for Molecular Bioscience, University of Queensland, St Lucia, QLD, Australia
| | - Rafael Romero-Garcia
- Department of Psychiatry, Cambridge Biomedical Campus, University of Cambridge, Cambridge, UK
| | - Jakob Seidlitz
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | - Edward T Bullmore
- Department of Psychiatry, Cambridge Biomedical Campus, University of Cambridge, Cambridge, UK
- Cambridgeshire and Peterborough NHS Trust, Elizabeth House, Fulbourn Hospital, Cambridge, UK
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28
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Troiani V, Crist RC, Doyle GA, Ferraro TN, Beiler D, Ranck S, McBryan K, Jarvis MA, Barbour JS, Han JJ, Ness RJ, Berrettini WH, Robishaw JD. Genetics and prescription opioid use (GaPO): study design for consenting a cohort from an existing biobank to identify clinical and genetic factors influencing prescription opioid use and abuse. BMC Med Genomics 2021; 14:253. [PMID: 34702274 PMCID: PMC8547564 DOI: 10.1186/s12920-021-01100-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Accepted: 10/15/2021] [Indexed: 01/10/2023] Open
Abstract
BACKGROUND Prescription opioids (POs) are commonly used to treat moderate to severe chronic pain in the health system setting. Although they improve quality of life for many patients, more work is needed to identify both the clinical and genetic factors that put certain individuals at high risk for developing opioid use disorder (OUD) following use of POs for pain relief. With a greater understanding of important risk factors, physicians will be better able to identify patients at highest risk for developing OUD for whom non-opioid alternative therapies and treatments should be considered. METHODS We are conducting a prospective observational study that aims to identify the clinical and genetic factors most stongly associated with OUD. The study design leverages an existing biobank that includes whole exome sequencing and array genotyping. The biobank is maintained within an integrated health system, allowing for the large-scale capture and integration of genetic and non-genetic data. Participants are enrolled into the health system biobank via informed consent and then into a second study that focuses on opioid medication use. Data capture includes validated self-report surveys measuring addiction severity, depression, anxiety, and nicotine use, as well as additional clinical, prescription, and brain imaging data extracted from electronic health records. DISCUSSION We will harness this multimodal data capture to establish meaningful patient phenotypes in order to understand the genetic and non-genetic contributions to OUD.
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Affiliation(s)
- Vanessa Troiani
- Geisinger Clinic, Geisinger, Danville, PA, USA.
- Department of Translational Data Science and Informatics, Geisinger, Danville, PA, USA.
- Neuroscience Institute, Geisinger, Danville, PA, USA.
- Department of Basic Sciences, Geisinger Commonwealth School of Medicine, Scranton, PA, USA.
| | - Richard C Crist
- Center for Neurobiology and Behavior, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Glenn A Doyle
- Center for Neurobiology and Behavior, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Thomas N Ferraro
- Center for Neurobiology and Behavior, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Biomedical Sciences, Cooper Medical School of Rowan University, Camden, NJ, USA
| | | | | | | | | | | | - John J Han
- Department of Pain Medicine, Geisinger Medical Center, Danville, PA, USA
| | - Ryan J Ness
- Department of Pain Medicine, Geisinger Medical Center, Danville, PA, USA
| | - Wade H Berrettini
- Geisinger Clinic, Geisinger, Danville, PA, USA
- Department of Biomedical Sciences, Cooper Medical School of Rowan University, Camden, NJ, USA
| | - Janet D Robishaw
- Department of Biomedical Science, Schmidt College of Medicine of Florida Atlantic University, Boca Raton, FL, USA
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29
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Ye Z, Mo C, Liu S, Hatch KS, Gao S, Ma Y, Hong LE, Thompson PM, Jahanshad N, Acheson A, Garavan H, Shen L, Nichols TE, Kochunov P, Chen S, Ma T. White Matter Integrity and Nicotine Dependence: Evaluating Vertical and Horizontal Pleiotropy. Front Neurosci 2021; 15:738037. [PMID: 34720862 PMCID: PMC8551454 DOI: 10.3389/fnins.2021.738037] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Accepted: 09/01/2021] [Indexed: 01/26/2023] Open
Abstract
Tobacco smoking is an addictive behavior that supports nicotine dependence and is an independent risk factor for cancer and other illnesses. Its neurogenetic mechanisms are not fully understood but may act through alterations in the cerebral white matter (WM). We hypothesized that the vertical pleiotropic pathways, where genetic variants influence a trait that in turn influences another trait, link genetic factors, integrity of cerebral WM, and nicotine addiction. We tested this hypothesis using individual genetic factors, WM integrity measured by fractional anisotropy (FA), and nicotine dependence-related smoking phenotypes, including smoking status (SS) and cigarettes per day (CPDs), in a large epidemiological sample collected by the UK Biobank. We performed a genome-wide association study (GWAS) to identify previously reported loci associated with smoking behavior. Smoking was found to be associated with reduced WM integrity in multiple brain regions. We then evaluated two competing vertical pathways: Genes → WM integrity → Smoking versus Genes → Smoking → WM integrity and a horizontal pleiotropy pathway where genetic factors independently affect both smoking and WM integrity. The causal pathway analysis identified 272 pleiotropic single-nucleotide polymorphisms (SNPs) whose effects on SS were mediated by FA, as well as 22 pleiotropic SNPs whose effects on FA were mediated by CPD. These SNPs were mainly located in important susceptibility genes for smoking-induced diseases NCAM1 and IREB2. Our findings revealed the role of cerebral WM in the maintenance of the complex addiction and provided potential genetic targets for future research in examining how changes in WM integrity contribute to the nicotine effects on the brain.
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Affiliation(s)
- Zhenyao Ye
- Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine, University of Maryland, Baltimore, Baltimore, MD, United States
- Division of Biostatistics and Bioinformatics, Department of Epidemiology and Public Health, School of Medicine, University of Maryland, Baltimore, Baltimore, MD, United States
| | - Chen Mo
- Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine, University of Maryland, Baltimore, Baltimore, MD, United States
- Division of Biostatistics and Bioinformatics, Department of Epidemiology and Public Health, School of Medicine, University of Maryland, Baltimore, Baltimore, MD, United States
| | - Song Liu
- School of Computer Science and Technology, Qilu University of Technology, Shandong Academy of Sciences, Jinan, China
| | - Kathryn S Hatch
- Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine, University of Maryland, Baltimore, Baltimore, MD, United States
| | - Si Gao
- Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine, University of Maryland, Baltimore, Baltimore, MD, United States
| | - Yizhou Ma
- Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine, University of Maryland, Baltimore, Baltimore, MD, United States
| | - L Elliot Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine, University of Maryland, Baltimore, Baltimore, MD, United States
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States
| | - Ashley Acheson
- Department of Psychiatry and Behavioral Sciences, University of Arkansas for Medical Sciences, Little Rock, AR, United States
| | - Hugh Garavan
- Department of Psychiatry, The University of Vermont, Burlington, VT, United States
| | - Li Shen
- Department of Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Thomas E Nichols
- Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine, University of Maryland, Baltimore, Baltimore, MD, United States
| | - Shuo Chen
- Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine, University of Maryland, Baltimore, Baltimore, MD, United States
- Division of Biostatistics and Bioinformatics, Department of Epidemiology and Public Health, School of Medicine, University of Maryland, Baltimore, Baltimore, MD, United States
| | - Tianzhou Ma
- Department of Epidemiology and Biostatistics, School of Public Health, University of Maryland, College Park, College Park, MD, United States
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Vilor-Tejedor N, Garrido-Martín D, Rodriguez-Fernandez B, Lamballais S, Guigó R, Gispert JD. Multivariate Analysis and Modelling of multiple Brain endOphenotypes: Let's MAMBO! Comput Struct Biotechnol J 2021; 19:5800-5810. [PMID: 34765095 PMCID: PMC8567328 DOI: 10.1016/j.csbj.2021.10.019] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Revised: 10/08/2021] [Accepted: 10/12/2021] [Indexed: 12/01/2022] Open
Abstract
Imaging genetic studies aim to test how genetic information influences brain structure and function by combining neuroimaging-based brain features and genetic data from the same individual. Most studies focus on individual correlation and association tests between genetic variants and a single measurement of the brain. Despite the great success of univariate approaches, given the capacity of neuroimaging methods to provide a multiplicity of cerebral phenotypes, the development and application of multivariate methods become crucial. In this article, we review novel methods and strategies focused on the analysis of multiple phenotypes and genetic data. We also discuss relevant aspects of multi-trait modelling in the context of neuroimaging data.
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Affiliation(s)
- Natalia Vilor-Tejedor
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Barcelona, Spain
- Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, Netherlands
- Universitat Pompeu Fabra, Barcelona, Spain
| | - Diego Garrido-Martín
- Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Barcelona, Spain
| | | | - Sander Lamballais
- Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, Netherlands
| | - Roderic Guigó
- Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales y Nanomedicina, Madrid, Spain
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31
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Penninck L, Ibrahim EC, Artiges E, Gorgievski V, Desrivières S, Farley S, Filippi I, de Macedo CEA, Belzeaux R, Banaschewski T, Bokde ALW, Quinlan EB, Flor H, Grigis A, Garavan H, Gowland P, Heinz A, Brühl R, Nees F, Papadopoulos Orfanos D, Paus T, Poustka L, Fröhner JH, Smolka MN, Walter H, Whelan R, Grenier J, Schumann G, Paillère Martinot ML, Tzavara ET, Martinot JL. Immune-Related Genetic Overlap Between Regional Gray Matter Reductions and Psychiatric Symptoms in Adolescents, and Gene-Set Validation in a Translational Model. Front Syst Neurosci 2021; 15:725413. [PMID: 34658802 PMCID: PMC8514661 DOI: 10.3389/fnsys.2021.725413] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Accepted: 08/31/2021] [Indexed: 11/23/2022] Open
Abstract
Adolescence is a period of vulnerability for the maturation of gray matter (GM) and also for the onset of psychiatric disorders such as major depressive disorder (MDD), bipolar disorder and schizophrenia. Chronic neuroinflammation is considered to play a role in the etiology of these illnesses. However, the involvement of neuroinflammation in the observed link between regional GM volume reductions and psychiatric symptoms is not established yet. Here, we investigated a possible common immune-related genetic link between these two phenomena in european adolescents recruited from the community. Hippocampal and medial prefrontal cortex (mPFC) were defined a priori as regions of interest (ROIs). Their GM volumes were extracted in 1,563 14-year-olds from the IMAGEN database. We found a set of 26 SNPs that correlated with the hippocampal volumes and 29 with the mPFC volumes at age 14. We formed two ROI-Related Immune-gene scores (RRI) with the inflammation SNPs that correlated to hippocampal GM volume and to mPFC GM volume. The predictive ability of both RRIs with regards to the presence of psychiatric symptoms at age 18 was investigated by correlating the RRIs with psychometric questionnaires obtained at age 18. The RRIs (but not control scores constructed with random SNPs) correlated with the presence of depressive symptoms, positive psychotic symptoms, and externalizing symptoms in later adolescence. In addition, the effect of childhood maltreatment, one of the major environmental risk factors for depression and other mental disorders, interacted with the RRI effect. We next sought to validate this finding by investigating our set of inflammatory genes in a translational animal model of early life adversity. Mice were subjected to a protocol of maternal separation at an early post-natal age. We evaluated depressive behaviors in separated and non-separated mice at adolescence and their correlations with the concomitant expression of our genes in whole blood samples. We show that in mice, early life adversity affected the expression of our set of genes in peripheral blood, and that levels of expression correlated with symptoms of negative affect in adolescence. Overall, our translational findings in adolescent mice and humans provide a novel validated gene-set of immune-related genes for further research in the early stages of mood disorders.
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Affiliation(s)
- Lukas Penninck
- Institut National de la Santé et de la Recherche Médicale, INSERM U1299 “Trajectoires Développementales en Psychiatrie”, Université Paris-Saclay, Ecole Normale Supérieure Paris-Saclay, CNRS, Centre Borelli, Gif-sur-Yvette, France
| | - El Chérif Ibrahim
- Aix Marseille Univ, CNRS, INT, Inst Neurosci Timone, Marseille, France
| | - Eric Artiges
- Institut National de la Santé et de la Recherche Médicale, INSERM U1299 “Trajectoires Développementales en Psychiatrie”, Université Paris-Saclay, Ecole Normale Supérieure Paris-Saclay, CNRS, Centre Borelli, Gif-sur-Yvette, France
- EPS Barthelemy Durand, Etampes, France
| | | | - Sylvane Desrivières
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology & Neuroscience, SGDP Centre, King’s College London, London, United Kingdom
| | | | - Irina Filippi
- Institut National de la Santé et de la Recherche Médicale, INSERM U1299 “Trajectoires Développementales en Psychiatrie”, Université Paris-Saclay, Ecole Normale Supérieure Paris-Saclay, CNRS, Centre Borelli, Gif-sur-Yvette, France
| | | | - Raoul Belzeaux
- Aix Marseille Univ, CNRS, INT, Inst Neurosci Timone, Marseille, France
- AP-HM, Hôpital Sainte Marguerite, Pôle de Psychiatrie Universitaire Solaris, Marseille, France
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Arun L. W. Bokde
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Erin Burke Quinlan
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology & Neuroscience, SGDP Centre, King’s College London, London, United Kingdom
| | - Herta Flor
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Department of Psychology, School of Social Sciences, University of Mannheim, Mannheim, Germany
| | - Antoine Grigis
- NeuroSpin, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Hugh Garavan
- Department of Psychiatry and Psychology, University of Vermont, Burlington, VT, United States
| | - Penny Gowland
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, United Kingdom
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy, CCM, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Rüdiger Brühl
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig, Germany
| | - Frauke Nees
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Institute of Medical Psychology and Medical Sociology, University Medical Center Schleswig Holstein, Kiel University, Kiel, Germany
| | | | - Tomáš Paus
- Department of Psychiatry, Faculty of Medicine and Centre Hospitalier Universitaire Sainte-Justine, University of Montreal, Montreal, QC, Canada
- Department of Psychology and Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, Göttingen, Germany
| | - Juliane H. Fröhner
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Michael N. Smolka
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy, CCM, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Robert Whelan
- School of Psychology and Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
| | | | - Gunter Schumann
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology & Neuroscience, SGDP Centre, King’s College London, London, United Kingdom
- PONS Research Group, Department of Psychiatry and Psychotherapy, Humboldt University, Berlin and Leibniz Institute for Neurobiology, Magdeburg, Germany
- Institute for Science and Technology of Brain-inspired Intelligence (ISTBI), Fudan University, Shanghai, China
| | - Marie-Laure Paillère Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM U1299 “Trajectoires Développementales en Psychiatrie”, Université Paris-Saclay, Ecole Normale Supérieure Paris-Saclay, CNRS, Centre Borelli, Gif-sur-Yvette, France
- AP-HP.Sorbonne Université, Department of Child and Adolescent Psychiatry, Pitié-Salpêtrière Hospital, Paris, France
| | - Eleni T. Tzavara
- University of Paris, CNRS, INCC, Paris, France
- AP-HM, Hôpital Sainte Marguerite, Pôle de Psychiatrie Universitaire Solaris, Marseille, France
- Fondation Fondamental, Créteil, France
| | - Jean-Luc Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM U1299 “Trajectoires Développementales en Psychiatrie”, Université Paris-Saclay, Ecole Normale Supérieure Paris-Saclay, CNRS, Centre Borelli, Gif-sur-Yvette, France
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Ke F, Kong W, Wang S. Identifying Imaging Genetics Biomarkers of Alzheimer's Disease by Multi-Task Sparse Canonical Correlation Analysis and Regression. Front Genet 2021; 12:706986. [PMID: 34422007 PMCID: PMC8375409 DOI: 10.3389/fgene.2021.706986] [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: 05/08/2021] [Accepted: 07/19/2021] [Indexed: 11/29/2022] Open
Abstract
Imaging genetics combines neuroimaging and genetics to assess the relationships between genetic variants and changes in brain structure and metabolism. Sparse canonical correlation analysis (SCCA) models are well-known tools for identifying meaningful biomarkers in imaging genetics. However, most SCCA models incorporate only diagnostic status information, which poses challenges for finding disease-specific biomarkers. In this study, we proposed a multi-task sparse canonical correlation analysis and regression (MT-SCCAR) model to reveal disease-specific associations between single nucleotide polymorphisms and quantitative traits derived from multi-modal neuroimaging data in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort. MT-SCCAR uses complementary information carried by multiple-perspective cognitive scores and encourages group sparsity on genetic variants. In contrast with two other multi-modal SCCA models, MT-SCCAR embedded more accurate neuropsychological assessment information through linear regression and enhanced the correlation coefficients, leading to increased identification of high-risk brain regions. Furthermore, MT-SCCAR identified primary genetic risk factors for Alzheimer’s disease (AD), including rs429358, and found some association patterns between genetic variants and brain regions. Thus, MT-SCCAR contributes to deciphering genetic risk factors of brain structural and metabolic changes by identifying potential risk biomarkers.
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Affiliation(s)
- Fengchun Ke
- College of Information Engineering, Shanghai Maritime University, Shanghai, China
| | - Wei Kong
- College of Information Engineering, Shanghai Maritime University, Shanghai, China
| | - Shuaiqun Wang
- College of Information Engineering, Shanghai Maritime University, Shanghai, China
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33
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Kibitov AO, Mazo GE. [Anhedonia in depression: neurobiological and genetic aspects]. Zh Nevrol Psikhiatr Im S S Korsakova 2021; 121:146-154. [PMID: 33834733 DOI: 10.17116/jnevro2021121031146] [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: 11/17/2022]
Abstract
Anhedonia is indeed a pathogenetically important clinical phenotype and a promising endophenotype for depressive symptoms with a very high contribution of biological and genetic factors. Neurobiological mechanisms of anhedonia are impaired functioning of the reward system of the brain, which is confirmed by many neuroimaging, genetic and experimental studies. Anhedonia has a trans-diagnoctic character and should be understood as a complex phenomenon, and it is important to correctly evaluate it within the framework of a particular research paradigm. It seems optimal to form several complementary research strategies that evaluate the most important «facets» of anhedonia, regardless of the nosological form of the disease, within the framework of one study using various methods to search for adequate biomarkers of anhedonia severity (genetic, neuroimaging, biochemical). Given the high-quality organization of such comprehensive studies based on the correct methodology of evidence-based medicine, it is likely that significant biomarker systems will be available in the near future, which, if replicated in independent samples, can be used to personalize the diagnosis and treatment of depression.
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Affiliation(s)
- A O Kibitov
- Bekhterev National Medical Research Center for Psychiatry and Neurology, St. Petersburg, Russia.,Serbsky National Medical Research Center on Psychiatry and Addictions, Moscow, Russia
| | - G E Mazo
- Bekhterev National Medical Research Center for Psychiatry and Neurology, St. Petersburg, Russia
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Hoffmann A, Spengler D. Single-Cell Transcriptomics Supports a Role of CHD8 in Autism. Int J Mol Sci 2021; 22:3261. [PMID: 33806835 PMCID: PMC8004931 DOI: 10.3390/ijms22063261] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Revised: 03/16/2021] [Accepted: 03/20/2021] [Indexed: 12/16/2022] Open
Abstract
Chromodomain helicase domain 8 (CHD8) is one of the most frequently mutated and most penetrant genes in the autism spectrum disorder (ASD). Individuals with CHD8 mutations show leading symptoms of autism, macrocephaly, and facial dysmorphisms. The molecular and cellular mechanisms underpinning the early onset and development of these symptoms are still poorly understood and prevent timely and more efficient therapies of patients. Progress in this area will require an understanding of "when, why and how cells deviate from their normal trajectories". High-throughput single-cell RNA sequencing (sc-RNAseq) directly quantifies information-bearing RNA molecules that enact each cell's biological identity. Here, we discuss recent insights from sc-RNAseq of CRISPR/Cas9-editing of Chd8/CHD8 during mouse neocorticogenesis and human cerebral organoids. Given that the deregulation of the balance between excitation and inhibition (E/I balance) in cortical and subcortical circuits is thought to represent a major etiopathogenetic mechanism in ASD, we focus on the question of whether, and to what degree, results from current sc-RNAseq studies support this hypothesis. Beyond that, we discuss the pros and cons of these approaches and further steps to be taken to harvest the full potential of these transformative techniques.
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Affiliation(s)
| | - Dietmar Spengler
- Translational Research in Psychiatry, Max Planck Institute of Psychiatry, 80804 Munich, Germany;
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Corsico P. "It's all about delivery": researchers and health professionals' views on the moral challenges of accessing neurobiological information in the context of psychosis. BMC Med Ethics 2021; 22:11. [PMID: 33557813 PMCID: PMC7869514 DOI: 10.1186/s12910-020-00551-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Accepted: 10/21/2020] [Indexed: 12/05/2022] Open
Abstract
Background The convergence of neuroscience, genomics, and data science holds promise to unveil the neurobiology of psychosis and to produce new ways of preventing, diagnosing, and treating psychotic illness. Yet, moral challenges arise in neurobiological research and in the clinical translation of research findings. This article investigates the views of relevant actors in mental health on the moral challenges of accessing neurobiological information in the context of psychosis. Methods Semi-structured individual interviews with two groups: researchers employed in the National Health Service (NHS) or a university in England (n = 14), and mental health professionals employed in NHS mental health services (n = 14). This article compares results in the two groups (total n = 28). Results This article presents findings around three conceptual areas: (1) research ethics as mostly unproblematic, (2) psychosis, neurobiological information, and mental health care, and (3) identity, relationships, and the future. These areas are drawn from the themes and topics that emerged in the interviews across the two groups of participants. Researchers and health professionals provided similar accounts of the moral challenges of accessing—which includes acquisition, communication, and use of—neurobiological information in the context of psychosis. Acquiring neurobiological information was perceived as mostly unproblematic, provided ethical safeguards are put in place. Conversely, participants argued that substantive moral challenges arise from how neurobiological information is delivered—that is, communicated and used—in research and in clinical care. Neurobiological information was seen as a powerful tool in the process through which individuals define their identity and establish personal and clinical goals. The pervasiveness of this narrative tool may influence researchers and health professionals’ perception of ethical principles and moral obligations. Conclusions This study suggests that the moral challenges that arise from accessing neurobiological information in the context of psychosis go beyond traditional research and clinical ethics concerns. Reflecting on how accessing neurobiological information can influence individual self-narratives will be vital to ensure the ethical translation of neuroscience and genomics into mental health. Trial registration The study did not involve a health care intervention on human participants. It was retrospectively registered on 11 July 2018, registration number: researchregistry4255.
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Affiliation(s)
- Paolo Corsico
- Centre for Social Ethics and Policy, Department of Law, School of Social Sciences, The University of Manchester, Williamson Building, Oxford Road, Manchester, M13 9PL, UK.
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36
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Coronado C, Wade NE, Aguinaldo LD, Mejia MH, Jacobus J. Neurocognitive Correlates of Adolescent Cannabis Use: An Overview of Neural Activation Patterns in Task-Based Functional MRI Studies. JOURNAL OF PEDIATRIC NEUROPSYCHOLOGY 2021; 6:1-13. [PMID: 33425663 DOI: 10.1007/s40817-020-00076-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Adolescence is dynamic and comprises physiological, psychological, and neurocognitive changes. Notably, many developmentally associated neurobiological changes (e.g., synaptic pruning, myelination) coincide with peak substances use prevalence rates, particularly for cannabis use. Cannabis remains the most commonly used illicit drug among adolescents with 23.9% reporting cannabis use in the last year (Johnston et al., 2019). Adolescents who engage in cannabis use often show poorer neurocognitive performance and alterations in structural and functional brain development as compared to their non-using peers (Jacobus & Tapert, 2014). Over the past several decades, the cognitive domains most consistently associated with cannabis use among adolescents are learning and memory and several facets of executive functioning (e.g., inhibitory control, decision-making). Functional magnetic resonance imaging (fMRI) is a non-invasive method for probing the neural substrates underlying possible cannabis-related changes in cognition. This brief review aims to synthesize recent findings on the relationship between adolescent (≤25 years old) cannabis use and neural response during task-based functional magnetic resonance imaging (fMRI). Findings thus far suggest aberrant, often hyperactive, response to task-based stimuli in youth cannabis users. When considering the future directions of fMRI research with cannabis-using youth, review of existing studies also highlights the need for more prospective research with diverse samples.
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Affiliation(s)
- Clarisa Coronado
- Department of Psychiatry, University of California, San Diego, California, USA
| | - Natasha E Wade
- Department of Psychiatry, University of California, San Diego, California, USA
| | - Laika D Aguinaldo
- Department of Psychiatry, University of California, San Diego, California, USA
| | | | - Joanna Jacobus
- Department of Psychiatry, University of California, San Diego, California, USA
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Maltreatment timing, HPA axis functioning, multigenic risk, and depressive symptoms in African American youth: Differential associations without moderated mediation. Dev Psychopathol 2021; 32:1838-1853. [PMID: 33427169 DOI: 10.1017/s0954579420000589] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
Utilizing a large (N = 739), ancestrally homogenous sample, the current study aimed to better understand biological risk processes involved in the development of depressive symptoms in maltreated, African American children age 8-12 years. Maltreatment was independently coded from Child Protective Services records and maternal report. Self-reported depressive symptoms were attained in the context of a week-long, summer research camp. DNA was acquired from buccal cell or saliva samples and genotyped for nine polymorphisms in four hypothalamic-pituitary-adrenal (HPA)-axis-related genes: FKBP5, NR3C1, NR3C2, and CRHR1. Salivary cortisol samples were collected each morning (9 a.m.) and late afternoon (4 p.m.) throughout the week to assess HPA functioning. Results revealed that experiences of maltreatment beginning prior to age 5 were most predictive of depressive symptoms, whereas maltreatment onset after age 5 was most predictive of HPA axis dysregulation (blunted daytime cortisol patterns). Multigenic risk did not relate to HPA functioning, nor did it moderate the relationship between maltreatment and HPA activity. There was no mediation of the relationship between maltreatment and depressive symptoms by HPA dysfunction. Results are interpreted through a developmental psychopathology lens, emphasizing the principle of equifinality while carefully appraising racial differences. Implications for future research, particularly the need for longitudinal studies, and important methodological considerations are discussed.
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Todeva-Radneva A, Paunova R, Kandilarova S, St Stoyanov D. The Value of Neuroimaging Techniques in the Translation and Transdiagnostic Validation of Psychiatric Diagnoses - Selective Review. Curr Top Med Chem 2021; 20:540-553. [PMID: 32003690 DOI: 10.2174/1568026620666200131095328] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Revised: 12/09/2019] [Accepted: 12/12/2019] [Indexed: 01/05/2023]
Abstract
Psychiatric diagnosis has long been perceived as more of an art than a science since its foundations lie within the observation, and the self-report of the patients themselves and objective diagnostic biomarkers are lacking. Furthermore, the diagnostic tools in use not only stray away from the conventional medical framework but also remain invalidated with evidence-based concepts. However, neuroscience, as a source of valid objective knowledge has initiated the process of a paradigm shift underlined by the main concept of psychiatric disorders being "brain disorders". It is also a bridge closing the explanatory gap among the different fields of medicine via the translation of the knowledge within a multidisciplinary framework. The contemporary neuroimaging methods, such as fMRI provide researchers with an entirely new set of tools to reform the current status quo by creating an opportunity to define and validate objective biomarkers that can be translated into clinical practice. Combining multiple neuroimaging techniques with the knowledge of the role of genetic factors, neurochemical imbalance and neuroinflammatory processes in the etiopathophysiology of psychiatric disorders is a step towards a comprehensive biological explanation of psychiatric disorders and a final differentiation of psychiatry as a well-founded medical science. In addition, the neuroscientific knowledge gained thus far suggests a necessity for directional change to exploring multidisciplinary concepts, such as multiple causality and dimensionality of psychiatric symptoms and disorders. A concomitant viewpoint transition of the notion of validity in psychiatry with a focus on an integrative validatory approach may facilitate the building of a collaborative bridge above the wall existing between the scientific fields analyzing the mind and those studying the brain.
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Affiliation(s)
- Anna Todeva-Radneva
- Department of Psychiatry and Medical Psychology and Scientific Research Institute, The Medical University of Plovdiv, Plovdiv, Bulgaria
| | - Rositsa Paunova
- Department of Psychiatry and Medical Psychology and Scientific Research Institute, The Medical University of Plovdiv, Plovdiv, Bulgaria
| | - Sevdalina Kandilarova
- Department of Psychiatry and Medical Psychology and Scientific Research Institute, The Medical University of Plovdiv, Plovdiv, Bulgaria
| | - Drozdstoy St Stoyanov
- Department of Psychiatry and Medical Psychology and Scientific Research Institute, The Medical University of Plovdiv, Plovdiv, Bulgaria
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Mascarell Maričić L, Walter H, Rosenthal A, Ripke S, Quinlan EB, Banaschewski T, Barker GJ, Bokde ALW, Bromberg U, Büchel C, Desrivières S, Flor H, Frouin V, Garavan H, Itterman B, Martinot JL, Martinot MLP, Nees F, Orfanos DP, Paus T, Poustka L, Hohmann S, Smolka MN, Fröhner JH, Whelan R, Kaminski J, Schumann G, Heinz A. The IMAGEN study: a decade of imaging genetics in adolescents. Mol Psychiatry 2020; 25:2648-2671. [PMID: 32601453 PMCID: PMC7577859 DOI: 10.1038/s41380-020-0822-5] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/05/2019] [Revised: 04/10/2020] [Accepted: 06/12/2020] [Indexed: 11/17/2022]
Abstract
Imaging genetics offers the possibility of detecting associations between genotype and brain structure as well as function, with effect sizes potentially exceeding correlations between genotype and behavior. However, study results are often limited due to small sample sizes and methodological differences, thus reducing the reliability of findings. The IMAGEN cohort with 2000 young adolescents assessed from the age of 14 onwards tries to eliminate some of these limitations by offering a longitudinal approach and sufficient sample size for analyzing gene-environment interactions on brain structure and function. Here, we give a systematic review of IMAGEN publications since the start of the consortium. We then focus on the specific phenotype 'drug use' to illustrate the potential of the IMAGEN approach. We describe findings with respect to frontocortical, limbic and striatal brain volume, functional activation elicited by reward anticipation, behavioral inhibition, and affective faces, and their respective associations with drug intake. In addition to describing its strengths, we also discuss limitations of the IMAGEN study. Because of the longitudinal design and related attrition, analyses are underpowered for (epi-) genome-wide approaches due to the limited sample size. Estimating the generalizability of results requires replications in independent samples. However, such densely phenotyped longitudinal studies are still rare and alternative internal cross-validation methods (e.g., leave-one out, split-half) are also warranted. In conclusion, the IMAGEN cohort is a unique, very well characterized longitudinal sample, which helped to elucidate neurobiological mechanisms involved in complex behavior and offers the possibility to further disentangle genotype × phenotype interactions.
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Affiliation(s)
- Lea Mascarell Maričić
- Department of Psychiatry and Psychotherapy, Charité-Universitätsmedizin Berlin, Campus Charité Mitte, Berlin, Germany
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy, Charité-Universitätsmedizin Berlin, Campus Charité Mitte, Berlin, Germany
| | - Annika Rosenthal
- Department of Psychiatry and Psychotherapy, Charité-Universitätsmedizin Berlin, Campus Charité Mitte, Berlin, Germany
| | - Stephan Ripke
- Department of Psychiatry and Psychotherapy, Charité-Universitätsmedizin Berlin, Campus Charité Mitte, Berlin, Germany
| | - Erin Burke Quinlan
- Department of Social Genetic & Developmental Psychiatry, Institute of Psychiatry, King's College London, London, UK
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159, Mannheim, Germany
| | - Gareth J Barker
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Arun L W Bokde
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Uli Bromberg
- University Medical Centre Hamburg-Eppendorf, House W34, 3.OG, Martinistr. 52, 20246, Hamburg, Germany
| | - Christian Büchel
- Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
| | - Sylvane Desrivières
- Department of Social Genetic & Developmental Psychiatry, Institute of Psychiatry, King's College London, London, UK
| | - Herta Flor
- Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
- Department of Psychology, School of Social Sciences, University of Mannheim, 68131, Mannheim, Germany
| | - Vincent Frouin
- NeuroSpin, CEA, Université Paris-Saclay, F-91191, Gif-sur-Yvette, France
| | - Hugh Garavan
- Departments of Psychiatry and Psychology, University of Vermont, Burlington, VT, 05405, USA
| | - Bernd Itterman
- Physikalisch-Technische Bundesanstalt (PTB), Abbestr. 2-12, Berlin, Germany
| | - Jean-Luc Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM Unit 1000 "Neuroimaging& Psychiatry", University Paris Sud, University Paris Descartes-Sorbonne Paris Cité, and Maison de Solenn, Paris, France
| | - Marie-Laure Paillère Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM Unit 1000 "Neuroimaging & Psychiatry", University Paris Sud, University Paris Descartes, Sorbonne Université, and AP-HP, Department of Child and Adolescent Psychiatry, Pitié-Salpêtrière Hospital, Paris, France
| | - Frauke Nees
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159, Mannheim, Germany
- Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
| | | | - Tomáš Paus
- Rotman Research Institute, Baycrest and Departments of Psychology and Psychiatry, University of Toronto, Toronto, ON, M6A 2E1, Canada
| | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, von-Siebold-Str. 5, 37075, Göttingen, Germany
| | - Sarah Hohmann
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159, Mannheim, Germany
| | - Michael N Smolka
- Department of Psychiatry and Neuroimaging Center, TechnischeUniversität Dresden, Dresden, Germany
| | - Juliane H Fröhner
- Department of Psychiatry and Neuroimaging Center, TechnischeUniversität Dresden, Dresden, Germany
| | - Robert Whelan
- School of Psychology and Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
| | - Jakob Kaminski
- Department of Psychiatry and Psychotherapy, Charité-Universitätsmedizin Berlin, Campus Charité Mitte, Berlin, Germany
- Berlin Institute of Health, Berlin, Germany
| | - Gunter Schumann
- Department of Social Genetic & Developmental Psychiatry, Institute of Psychiatry, King's College London, London, UK
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy, Charité-Universitätsmedizin Berlin, Campus Charité Mitte, Berlin, Germany.
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Siminski N, Böhme S, Zeller JBM, Becker MPI, Bruchmann M, Hofmann D, Breuer F, Mühlberger A, Schiele MA, Weber H, Schartner C, Deckert J, Pauli P, Reif A, Domschke K, Straube T, Herrmann MJ. BNST and amygdala activation to threat: Effects of temporal predictability and threat mode. Behav Brain Res 2020; 396:112883. [PMID: 32860830 DOI: 10.1016/j.bbr.2020.112883] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Revised: 08/14/2020] [Accepted: 08/21/2020] [Indexed: 12/28/2022]
Abstract
Recent animal and human studies highlight the uncertainty about the onset of an aversive event as a crucial factor for the involvement of the centromedial amygdala (CM) and bed nucleus of the stria terminalis (BNST) activity. However, studies investigating temporally predictable or unpredictable threat anticipation and confrontation processes are rare. Furthermore, the few existing fMRI studies analyzing temporally predictable and unpredictable threat processes used small sample sizes or limited fMRI paradigms. Therefore, we measured functional brain activity in 109 predominantly female healthy participants during a temporally predictable-unpredictable threat paradigm, which aimed to solve limited aspects of recent studies. Results showed higher BNST activity compared to the CM during the cue indicating that the upcoming confrontation is aversive relative to the cue indicating an upcoming neutral confrontation. Both the CM and BNST showed higher activity during the confrontation with unpredictable and aversive stimuli, but the reaction to aversive confrontation relative to neutral confrontation was stronger in the CM compared to the BNST. Additional modulation analyses by NPSR1 rs324981 genotype revealed higher BNST activity relative to the CM in unpredictable anticipation relative to predictable anticipation in T-carriers compared to AA carriers. Our results indicate that during the confrontation with aversive or neutral stimuli, temporal unpredictability modulates CM and BNST activity. Further, there is a differential activity concerning threat processing, as BNST is more involved when focussing on fear-related anticipation processes and CM is more involved when focussing on threat confrontation.
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Affiliation(s)
- N Siminski
- Center of Mental Health, Dept. of Psychiatry, Psychosomatics, and Psychotherapy, University Hospital of Wuerzburg, Wuerzburg, Germany
| | - S Böhme
- Department of Clinical Psychology and Psychotherapy, Institute of Psychology, University of Regensburg, Regensburg, Germany; Department of Clinical Psychology and Psychotherapy, University of Erlangen, Erlangen, Germany
| | - J B M Zeller
- Center of Mental Health, Dept. of Psychiatry, Psychosomatics, and Psychotherapy, University Hospital of Wuerzburg, Wuerzburg, Germany
| | - M P I Becker
- Institute of Medical Psychology and Systems Neuroscience, University of Muenster, Muenster, Germany
| | - M Bruchmann
- Institute of Medical Psychology and Systems Neuroscience, University of Muenster, Muenster, Germany
| | - D Hofmann
- Institute of Medical Psychology and Systems Neuroscience, University of Muenster, Muenster, Germany
| | - F Breuer
- Fraunhofer Institute for Integrated Circuits (IIS), Development Center for X-ray Technology (EZRT), Wuerzburg, Germany
| | - A Mühlberger
- Department of Clinical Psychology and Psychotherapy, Institute of Psychology, University of Regensburg, Regensburg, Germany
| | - M A Schiele
- Department of Psychiatry and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - H Weber
- Center of Mental Health, Dept. of Psychiatry, Psychosomatics, and Psychotherapy, University Hospital of Wuerzburg, Wuerzburg, Germany
| | - C Schartner
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Frankfurt am Main, Germany
| | - J Deckert
- Center of Mental Health, Dept. of Psychiatry, Psychosomatics, and Psychotherapy, University Hospital of Wuerzburg, Wuerzburg, Germany
| | - P Pauli
- Department of Psychology (Biological Psychology, Clinical Psychology, and Psychotherapy), University of Wuerzburg, Wuerzburg, Germany
| | - A Reif
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Frankfurt am Main, Germany
| | - K Domschke
- Department of Psychiatry and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany; Center for Basics in Neuro Modulation, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - T Straube
- Institute of Medical Psychology and Systems Neuroscience, University of Muenster, Muenster, Germany
| | - M J Herrmann
- Center of Mental Health, Dept. of Psychiatry, Psychosomatics, and Psychotherapy, University Hospital of Wuerzburg, Wuerzburg, Germany.
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41
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Zhang Y, Vaidya N, Iyengar U, Sharma E, Holla B, Ahuja CK, Barker GJ, Basu D, Bharath RD, Chakrabarti A, Desrivieres S, Elliott P, Fernandes G, Gourisankar A, Heron J, Hickman M, Jacob P, Jain S, Jayarajan D, Kalyanram K, Kartik K, Krishna M, Krishnaveni G, Kumar K, Kumaran K, Kuriyan R, Murthy P, Orfanos DP, Purushottam M, Rangaswamy M, Kupard SS, Singh L, Singh R, Subodh BN, Thennarasu K, Toledano M, Varghese M, Benegal V, Schumann G. The Consortium on Vulnerability to Externalizing Disorders and Addictions (c-VEDA): an accelerated longitudinal cohort of children and adolescents in India. Mol Psychiatry 2020; 25:1618-1630. [PMID: 32203154 DOI: 10.1038/s41380-020-0656-1] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/01/2019] [Revised: 01/06/2020] [Accepted: 01/17/2020] [Indexed: 01/29/2023]
Abstract
The global burden of disease attributable to externalizing disorders such as alcohol misuse calls urgently for effective prevention and intervention. As our current knowledge is mainly derived from high-income countries such in Europe and North-America, it is difficult to address the wider socio-cultural, psychosocial context, and genetic factors in which risk and resilience are embedded in low- and medium-income countries. c-VEDA was established as the first and largest India-based multi-site cohort investigating the vulnerabilities for the development of externalizing disorders, addictions, and other mental health problems. Using a harmonised data collection plan coordinated with multiple cohorts in China, USA, and Europe, baseline data were collected from seven study sites between November 2016 and May 2019. Nine thousand and ten participants between the ages of 6 and 23 were assessed during this time, amongst which 1278 participants underwent more intensive assessments including MRI scans. Both waves of follow-ups have started according to the accelerated cohort structure with planned missingness design. Here, we present descriptive statistics on several key domains of assessments, and the full baseline dataset will be made accessible for researchers outside the consortium in September 2019. More details can be found on our website [cveda.org].
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Affiliation(s)
- Yuning Zhang
- Centre for Population Neuroscience and Precision Medicine (PONS), MRC Social, Genetic and Developmental Psychiatry (SGDP) Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.,Centre for Innovation in Mental Health, School of Psychology, University of Southampton, Southampton, UK
| | - Nilakshi Vaidya
- Centre for Population Neuroscience and Precision Medicine (PONS), MRC Social, Genetic and Developmental Psychiatry (SGDP) Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.,Centre for Addiction Medicine, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | - Udita Iyengar
- Centre for Population Neuroscience and Precision Medicine (PONS), MRC Social, Genetic and Developmental Psychiatry (SGDP) Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Eesha Sharma
- Department of Child & Adolescent Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | - Bharath Holla
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | - Chirag K Ahuja
- Department of Radiodiagnosis and Imaging, Postgraduate Institute of Medical Education & Research, Chandigarh, India
| | - Gareth J Barker
- Department of Neuroimaging, Institute of Psychology, Psychiatry & Neuroscience, London, King's College, London, UK
| | - Debasish Basu
- Department of Psychiatry, Postgraduate Institute of Medical Education & Research, Chandigarh, India
| | - Rose Dawn Bharath
- Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | | | - Sylvane Desrivieres
- Centre for Population Neuroscience and Precision Medicine (PONS), MRC Social, Genetic and Developmental Psychiatry (SGDP) Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Paul Elliott
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
| | - Gwen Fernandes
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | | | - Jon Heron
- Centre for Public Health, Bristol Medical School, University of Bristol, Bristol, UK
| | | | - Preeti Jacob
- Department of Child & Adolescent Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | - Sanjeev Jain
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | - Deepak Jayarajan
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | | | | | - Murali Krishna
- Foundation for Research and Advocacy in Mental Health, Mysuru, India
| | - Ghattu Krishnaveni
- Epidemiology Research Unit, CSI Holdsworth Memorial Hospital, Mysuru, India
| | - Keshav Kumar
- Department of Mental Health and Clinical Psychology, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | - Kalyanaraman Kumaran
- Epidemiology Research Unit, CSI Holdsworth Memorial Hospital, Mysuru, India.,MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK
| | - Rebecca Kuriyan
- Division of Nutrition, St John's Research Institute, Bengaluru, India
| | - Pratima Murthy
- Centre for Addiction Medicine, National Institute of Mental Health and Neurosciences, Bengaluru, India.,Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | | | - Meera Purushottam
- Molecular Genetics Laboratory, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | - Madhavi Rangaswamy
- Department of Psychology, CHRIST (deemed to be university), Bengaluru, India
| | - Sunita Simon Kupard
- Department of Psychiatry & Department of Medical Ethics, St. John's Medical College & Hospital, Bengaluru, India
| | - Lenin Singh
- Department of Psychiatry, Regional Institute of Medical Sciences, Imphal, Manipur, India
| | - Roshan Singh
- Department of Psychiatry, Regional Institute of Medical Sciences, Imphal, Manipur, India
| | - B N Subodh
- Department of Psychiatry, Postgraduate Institute of Medical Education & Research, Chandigarh, India
| | - Kandavel Thennarasu
- Department of Biostatistics, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | - Mireille Toledano
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
| | - Mathew Varghese
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | - Vivek Benegal
- Centre for Addiction Medicine, National Institute of Mental Health and Neurosciences, Bengaluru, India.
| | - Gunter Schumann
- Centre for Population Neuroscience and Precision Medicine (PONS), MRC Social, Genetic and Developmental Psychiatry (SGDP) Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK. .,Population Neuroscience and Precision Medicine (PONS), LIN-Charite Research Group Department of Psychiatry and Psychotherapy, Charite, CCM, Humboldt University, Berlin, Germany. .,Institute for Science and Technology of Brain-inspired Intelligence (ISTBI), Fudan University, Shanghai, PR China.
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42
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Palk A, Illes J, Thompson PM, Stein DJ. Ethical issues in global neuroimaging genetics collaborations. Neuroimage 2020; 221:117208. [PMID: 32736000 DOI: 10.1016/j.neuroimage.2020.117208] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2019] [Revised: 06/09/2020] [Accepted: 07/24/2020] [Indexed: 10/23/2022] Open
Abstract
Neuroimaging genetics is a rapidly developing field that combines neuropsychiatric genetics studies with imaging modalities to investigate how genetic variation influences brain structure and function. As both genetic and imaging technologies improve further, their combined power may hold translational potential in terms of improving psychiatric nosology, diagnosis, and treatment. While neuroimaging genetics studies offer a number of scientific advantages, they also face challenges. In response to some of these challenges, global neuroimaging genetics collaborations have been created to pool and compare brain data and replicate study findings. Attention has been paid to ethical issues in genetics, neuroimaging, and multi-site collaborative research, respectively, but there have been few substantive discussions of the ethical issues generated by the confluence of these areas in global neuroimaging genetics collaborations. Our discussion focuses on two areas: benefits and risks of global neuroimaging genetics collaborations and the potential impact of neuroimaging genetics research findings in low- and middle-income countries. Global neuroimaging genetics collaborations have the potential to enhance relations between countries and address global mental health challenges, however there are risks regarding inequity, exploitation and data sharing. Moreover, neuroimaging genetics research in low- and middle-income countries must address the issue of feedback of findings and the risk of essentializing and stigmatizing interpretations of mental disorders. We conclude by examining how the notion of solidarity, informed by an African Ethics framework, may justify some of the suggestions made in our discussion.
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Affiliation(s)
- Andrea Palk
- Department of Philosophy, Stellenbosch University, Bag X1, Matieland, Stellenbosch, 7602, South Africa.
| | - Judy Illes
- Neuroethics Canada, Division of Neurology, Department of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Paul M Thompson
- Imaging Genetics Center, Mark & Mary Stevens Institute for Neuroimaging & Informatics, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Dan J Stein
- SA MRC Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry & Neuroscience Institute, University of Cape Town, Groote Schuur Hospital, Cape Town 7925, South Africa
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43
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Spies M, Nasser A, Ozenne B, Jensen PS, Knudsen GM, Fisher PM. Common HTR2A variants and 5-HTTLPR are not associated with human in vivo serotonin 2A receptor levels. Hum Brain Mapp 2020; 41:4518-4528. [PMID: 32697408 PMCID: PMC7555071 DOI: 10.1002/hbm.25138] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2020] [Revised: 05/08/2020] [Accepted: 06/16/2020] [Indexed: 12/22/2022] Open
Abstract
The serotonin 2A receptor (5‐HT2AR) is implicated in the pathophysiology and treatment of various psychiatric disorders. [18F]altanserin and [11C]Cimbi‐36 positron emission tomography (PET) allow for high‐resolution imaging of 5‐HT2AR in the living human brain. Cerebral 5‐HT2AR binding is strongly genetically determined, though the impact of specific variants is poorly understood. Candidate gene studies suggest that HTR2A single nucleotide polymorphisms including rs6311/rs6313, rs6314, and rs7997012 may influence risk for psychiatric disorders and mediate treatment response. Although known to impact in vitro expression of 5‐HT2AR or other serotonin (5‐HT) proteins, their effect on human in vivo brain 5‐HT2AR binding has as of yet been insufficiently studied. We thus assessed the extent to which these variants and the commonly studied 5‐HTTLPR predict neocortex in vivo 5‐HT2AR binding in healthy adult humans. We used linear regression analyses and likelihood ratio tests in 197 subjects scanned with [18F]altanserin or [11C]Cimbi‐36 PET. Although we observed genotype group differences in 5‐HT2AR binding of up to ~10%, no genetic variants were statistically significantly predictive of 5‐HT2AR binding in what is the largest human in vivo 5‐HT2AR imaging genetics study to date. Thus, in vitro and post mortem results suggesting effects on 5‐HT2AR expression did not carry over to the in vivo setting. To any extent these variants might affect clinical risk, our findings do not support that 5‐HT2AR binding mediates such effects. Our observations indicate that these individual variants do not significantly contribute to genetic load on human in vivo 5‐HT2AR binding.
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Affiliation(s)
- Marie Spies
- Neurobiology Research Unit, Rigshospitalet, Copenhagen, Denmark.,Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Arafat Nasser
- Neurobiology Research Unit, Rigshospitalet, Copenhagen, Denmark
| | - Brice Ozenne
- Neurobiology Research Unit, Rigshospitalet, Copenhagen, Denmark.,Department of Public Health, Section of Biostatistics, University of Copenhagen, Copenhagen, Denmark
| | - Peter S Jensen
- Neurobiology Research Unit, Rigshospitalet, Copenhagen, Denmark
| | - Gitte M Knudsen
- Neurobiology Research Unit, Rigshospitalet, Copenhagen, Denmark
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Hashem S, Nisar S, Bhat AA, Yadav SK, Azeem MW, Bagga P, Fakhro K, Reddy R, Frenneaux MP, Haris M. Genetics of structural and functional brain changes in autism spectrum disorder. Transl Psychiatry 2020; 10:229. [PMID: 32661244 PMCID: PMC7359361 DOI: 10.1038/s41398-020-00921-3] [Citation(s) in RCA: 60] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/20/2020] [Revised: 06/05/2020] [Accepted: 06/09/2020] [Indexed: 12/21/2022] Open
Abstract
Autism spectrum disorder (ASD) is a neurological and developmental disorder characterized by social impairment and restricted interactive and communicative behaviors. It may occur as an isolated disorder or in the context of other neurological, psychiatric, developmental, and genetic disorders. Due to rapid developments in genomics and imaging technologies, imaging genetics studies of ASD have evolved in the last few years. Increased risk for ASD diagnosis is found to be related to many specific single-nucleotide polymorphisms, and the study of genetic mechanisms and noninvasive imaging has opened various approaches that can help diagnose ASD at the nascent level. Identifying risk genes related to structural and functional changes in the brain of ASD patients provide a better understanding of the disease's neuropsychiatry and can help identify targets for therapeutic intervention that could be useful for the clinical management of ASD patients.
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Affiliation(s)
- Sheema Hashem
- Functional and Molecular Imaging Laboratory, Sidra Medicine, Doha, Qatar
| | - Sabah Nisar
- Functional and Molecular Imaging Laboratory, Sidra Medicine, Doha, Qatar
| | - Ajaz A Bhat
- Functional and Molecular Imaging Laboratory, Sidra Medicine, Doha, Qatar
| | | | | | - Puneet Bagga
- Center for Magnetic Resonance and Optical Imaging, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Khalid Fakhro
- Department of Human Genetics, Sidra Medicine, Doha, Qatar
- Department of Genetic Medicine, Weill Cornell Medical College, Doha, Qatar
| | - Ravinder Reddy
- Center for Magnetic Resonance and Optical Imaging, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | | | - Mohammad Haris
- Functional and Molecular Imaging Laboratory, Sidra Medicine, Doha, Qatar.
- Laboratory Animal Research Center, Qatar University, Doha, Qatar.
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45
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Boehm I, Walton E, Alexander N, Batury VL, Seidel M, Geisler D, King JA, Weidner K, Roessner V, Ehrlich S. Peripheral serotonin transporter DNA methylation is linked to increased salience network connectivity in females with anorexia nervosa. J Psychiatry Neurosci 2020; 45:206-213. [PMID: 31823595 PMCID: PMC7828979 DOI: 10.1503/jpn.190016] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND Epigenetic variation in the serotonin transporter gene (SLC6A4) has been shown to modulate the functioning of brain circuitry associated with the salience network and may heighten the risk for mental illness. This study is, to our knowledge, the first to test this epigenome–brain–behaviour pathway in patients with anorexia nervosa. METHODS We obtained resting-state functional connectivity (rsFC) data and blood samples from 55 acutely underweight female patients with anorexia nervosa and 55 age-matched female healthy controls. We decomposed imaging data using independent component analysis. We used bisulfite pyrosequencing to analyze blood DNA methylation within the promoter region of SLC6A4. We then explored salience network rsFC patterns in the group × methylation interaction. RESULTS We identified a positive relationship between SLC6A4 methylation levels and rsFC between the dorsolateral prefrontal cortex and the salience network in patients with anorexia nervosa compared to healthy controls. Increased rsFC in the salience network mediated the link between SLC6A4 methylation and eating disorder symptoms in patients with anorexia nervosa. We confirmed findings of rsFC alterations for CpG-specific methylation at a locus with evidence of methylation correspondence between brain and blood tissue. LIMITATIONS This study was cross-sectional in nature, the sample size was modest for the method and methylation levels were measured peripherally, so findings cannot be fully generalized to brain tissue. CONCLUSION This study sheds light on the neurobiological process of how epigenetic variation in the SLC6A4 gene may relate to rsFC in the salience network that is linked to psychopathology in anorexia nervosa.
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Affiliation(s)
- Ilka Boehm
- From the Division of Psychological and Social Medicine and Developmental Neurosciences, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany (Boehm, Walton, Batury, Seidel, Geisler, King, Ehrlich); the Department of Psychology, University of Bath, Bath, UK (Walton); the Department of Psychology, Faculty of Human Sciences, Medical School Hamburg, Hamburg, Germany (Alexander); the Department of Psychotherapy and Psychosomatic Medicine, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany (Weidner); the Department of Child and Adolescent Psychiatry, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany (Roessner); and the Eating Disorders Research and Treatment Center at the Department of Child and Adolescent Psychiatry, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany (Ehrlich)
| | - Esther Walton
- From the Division of Psychological and Social Medicine and Developmental Neurosciences, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany (Boehm, Walton, Batury, Seidel, Geisler, King, Ehrlich); the Department of Psychology, University of Bath, Bath, UK (Walton); the Department of Psychology, Faculty of Human Sciences, Medical School Hamburg, Hamburg, Germany (Alexander); the Department of Psychotherapy and Psychosomatic Medicine, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany (Weidner); the Department of Child and Adolescent Psychiatry, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany (Roessner); and the Eating Disorders Research and Treatment Center at the Department of Child and Adolescent Psychiatry, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany (Ehrlich)
| | - Nina Alexander
- From the Division of Psychological and Social Medicine and Developmental Neurosciences, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany (Boehm, Walton, Batury, Seidel, Geisler, King, Ehrlich); the Department of Psychology, University of Bath, Bath, UK (Walton); the Department of Psychology, Faculty of Human Sciences, Medical School Hamburg, Hamburg, Germany (Alexander); the Department of Psychotherapy and Psychosomatic Medicine, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany (Weidner); the Department of Child and Adolescent Psychiatry, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany (Roessner); and the Eating Disorders Research and Treatment Center at the Department of Child and Adolescent Psychiatry, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany (Ehrlich)
| | - Victoria-Luise Batury
- From the Division of Psychological and Social Medicine and Developmental Neurosciences, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany (Boehm, Walton, Batury, Seidel, Geisler, King, Ehrlich); the Department of Psychology, University of Bath, Bath, UK (Walton); the Department of Psychology, Faculty of Human Sciences, Medical School Hamburg, Hamburg, Germany (Alexander); the Department of Psychotherapy and Psychosomatic Medicine, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany (Weidner); the Department of Child and Adolescent Psychiatry, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany (Roessner); and the Eating Disorders Research and Treatment Center at the Department of Child and Adolescent Psychiatry, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany (Ehrlich)
| | - Maria Seidel
- From the Division of Psychological and Social Medicine and Developmental Neurosciences, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany (Boehm, Walton, Batury, Seidel, Geisler, King, Ehrlich); the Department of Psychology, University of Bath, Bath, UK (Walton); the Department of Psychology, Faculty of Human Sciences, Medical School Hamburg, Hamburg, Germany (Alexander); the Department of Psychotherapy and Psychosomatic Medicine, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany (Weidner); the Department of Child and Adolescent Psychiatry, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany (Roessner); and the Eating Disorders Research and Treatment Center at the Department of Child and Adolescent Psychiatry, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany (Ehrlich)
| | - Daniel Geisler
- From the Division of Psychological and Social Medicine and Developmental Neurosciences, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany (Boehm, Walton, Batury, Seidel, Geisler, King, Ehrlich); the Department of Psychology, University of Bath, Bath, UK (Walton); the Department of Psychology, Faculty of Human Sciences, Medical School Hamburg, Hamburg, Germany (Alexander); the Department of Psychotherapy and Psychosomatic Medicine, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany (Weidner); the Department of Child and Adolescent Psychiatry, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany (Roessner); and the Eating Disorders Research and Treatment Center at the Department of Child and Adolescent Psychiatry, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany (Ehrlich)
| | - Joseph A. King
- From the Division of Psychological and Social Medicine and Developmental Neurosciences, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany (Boehm, Walton, Batury, Seidel, Geisler, King, Ehrlich); the Department of Psychology, University of Bath, Bath, UK (Walton); the Department of Psychology, Faculty of Human Sciences, Medical School Hamburg, Hamburg, Germany (Alexander); the Department of Psychotherapy and Psychosomatic Medicine, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany (Weidner); the Department of Child and Adolescent Psychiatry, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany (Roessner); and the Eating Disorders Research and Treatment Center at the Department of Child and Adolescent Psychiatry, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany (Ehrlich)
| | - Kerstin Weidner
- From the Division of Psychological and Social Medicine and Developmental Neurosciences, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany (Boehm, Walton, Batury, Seidel, Geisler, King, Ehrlich); the Department of Psychology, University of Bath, Bath, UK (Walton); the Department of Psychology, Faculty of Human Sciences, Medical School Hamburg, Hamburg, Germany (Alexander); the Department of Psychotherapy and Psychosomatic Medicine, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany (Weidner); the Department of Child and Adolescent Psychiatry, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany (Roessner); and the Eating Disorders Research and Treatment Center at the Department of Child and Adolescent Psychiatry, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany (Ehrlich)
| | - Veit Roessner
- From the Division of Psychological and Social Medicine and Developmental Neurosciences, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany (Boehm, Walton, Batury, Seidel, Geisler, King, Ehrlich); the Department of Psychology, University of Bath, Bath, UK (Walton); the Department of Psychology, Faculty of Human Sciences, Medical School Hamburg, Hamburg, Germany (Alexander); the Department of Psychotherapy and Psychosomatic Medicine, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany (Weidner); the Department of Child and Adolescent Psychiatry, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany (Roessner); and the Eating Disorders Research and Treatment Center at the Department of Child and Adolescent Psychiatry, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany (Ehrlich)
| | - Stefan Ehrlich
- From the Division of Psychological and Social Medicine and Developmental Neurosciences, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany (Boehm, Walton, Batury, Seidel, Geisler, King, Ehrlich); the Department of Psychology, University of Bath, Bath, UK (Walton); the Department of Psychology, Faculty of Human Sciences, Medical School Hamburg, Hamburg, Germany (Alexander); the Department of Psychotherapy and Psychosomatic Medicine, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany (Weidner); the Department of Child and Adolescent Psychiatry, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany (Roessner); and the Eating Disorders Research and Treatment Center at the Department of Child and Adolescent Psychiatry, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany (Ehrlich)
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Chen J, Ye W, Li L, Su J, Huang Y, Liu L, Wu L, Yan C. Paeoniflorin regulates the hypothalamic-pituitary-adrenal axis negative feedback in a rat model of post-traumatic stress disorder. IRANIAN JOURNAL OF BASIC MEDICAL SCIENCES 2020; 23:439-448. [PMID: 32489558 PMCID: PMC7239430 DOI: 10.22038/ijbms.2020.41214.9738] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/18/2019] [Accepted: 09/25/2019] [Indexed: 11/25/2022]
Abstract
OBJECTIVES To investigate the effects of paeoniflorin (PEF) on the hypothalamic-pituitary-adrenal (HPA) axis feedback function of post-traumatic stress disorder (PTSD). MATERIALS AND METHODS Single-prolonged stress (SPS) was used to establish a PTSD-like rat model. The contents of plasma corticosterone (CORT), adrenocorticotropin hormone (ACTH) and corticotropin-releasing hormone (CRH) were measured by ELISA. Glucocorticoid receptor (GR), mineralocorticoid receptor (MR), adrenocorticotropic hormone-releasing factor I receptor (CRF1R), and adrenocorticotropic hormone-releasing factor II receptor (CRF2R) in the hippocampus and amygdala were measured by RT-PCR and immunohistochemistry. RESULTS The results showed that on day 8 after SPS, model rats showed enhanced HPA axis negative feedback lasting to day 29. On day 29, plasma CORT levels increased in model rats, while plasma CRH levels had no significant difference on days 8, 22, and 29. The expression of GR and MR of model rats significantly increased in the hippocampus, while the expression of GR, MR, and CRF1R significantly decreased in the amygdala. After 14 days of continuous administration of PEF, the enhanced negative feedback was inhibited, and the plasma CORT level significantly reduced after 21 days of administration. Moreover, PEF could significantly decrease the expression of GR and MR in the hippocampus, and increase the expression of GR, MR, and CRF1R significantly in the amygdala. CONCLUSION PEF could regulate HPA axis dysfunction in a rat model of PTSD, which may be related to regulating expression of GR and MR in the hippocampus and amygdala and regulating expression of CRF1R in the amygdala.
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Affiliation(s)
- Jie Chen
- The Research Centre of Basic Integrative Medicine, Guangzhou University of Chinese Medicine, Guangzhou 510006, China
| | - Weiqiong Ye
- The Research Centre of Basic Integrative Medicine, Guangzhou University of Chinese Medicine, Guangzhou 510006, China
| | - Ling Li
- Department of Pathology and Pathophysiology, School of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Junfang Su
- The Research Centre of Basic Integrative Medicine, Guangzhou University of Chinese Medicine, Guangzhou 510006, China
| | - Yunling Huang
- The Research Centre of Basic Integrative Medicine, Guangzhou University of Chinese Medicine, Guangzhou 510006, China
| | - Lingyun Liu
- The Research Centre of Basic Integrative Medicine, Guangzhou University of Chinese Medicine, Guangzhou 510006, China
| | - Lili Wu
- The Research Centre of Basic Integrative Medicine, Guangzhou University of Chinese Medicine, Guangzhou 510006, China
| | - Can Yan
- The Research Centre of Basic Integrative Medicine, Guangzhou University of Chinese Medicine, Guangzhou 510006, China
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Xu Q, Guo L, Cheng J, Wang M, Geng Z, Zhu W, Zhang B, Liao W, Qiu S, Zhang H, Xu X, Yu Y, Gao B, Han T, Yao Z, Cui G, Liu F, Qin W, Zhang Q, Li MJ, Liang M, Chen F, Xian J, Li J, Zhang J, Zuo XN, Wang D, Shen W, Miao Y, Yuan F, Lui S, Zhang X, Xu K, Zhang LJ, Ye Z, Yu C. CHIMGEN: a Chinese imaging genetics cohort to enhance cross-ethnic and cross-geographic brain research. Mol Psychiatry 2020; 25:517-529. [PMID: 31827248 PMCID: PMC7042768 DOI: 10.1038/s41380-019-0627-6] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/26/2018] [Revised: 11/21/2019] [Accepted: 11/27/2019] [Indexed: 02/05/2023]
Abstract
The Chinese Imaging Genetics (CHIMGEN) study establishes the largest Chinese neuroimaging genetics cohort and aims to identify genetic and environmental factors and their interactions that are associated with neuroimaging and behavioral phenotypes. This study prospectively collected genomic, neuroimaging, environmental, and behavioral data from more than 7000 healthy Chinese Han participants aged 18-30 years. As a pioneer of large-sample neuroimaging genetics cohorts of non-Caucasian populations, this cohort can provide new insights into ethnic differences in genetic-neuroimaging associations by being compared with Caucasian cohorts. In addition to micro-environmental measurements, this study also collects hundreds of quantitative macro-environmental measurements from remote sensing and national survey databases based on the locations of each participant from birth to present, which will facilitate discoveries of new environmental factors associated with neuroimaging phenotypes. With lifespan environmental measurements, this study can also provide insights on the macro-environmental exposures that affect the human brain as well as their timing and mechanisms of action.
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Affiliation(s)
- Qiang Xu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, 300052, Tianjin, China
| | - Lining Guo
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, 300052, Tianjin, China
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, 450052, Zhengzhou, China
| | - Meiyun Wang
- Department of Radiology, Zhengzhou University People's Hospital and Henan Provincial People's Hospital, 450003, Zhengzhou, China
- Henan Key Laboratory for Medical Imaging of Neurological Diseases, 450003, Zhengzhou, China
| | - Zuojun Geng
- Department of Medical Imaging, The Second Hospital of Hebei Medical University, 050000, Shijiazhuang, China
| | - Wenzhen Zhu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 430030, Wuhan, China
| | - Bing Zhang
- Department of Radiology, Drum Tower Hospital, Medical School of Nanjing University, 210008, Nanjing, China
| | - Weihua Liao
- Department of Radiology, Xiangya Hospital, Central South University, 410008, Changsha, China
- National Clinical Research Center for Geriatric Disorder, 410008, Changsha, China
| | - Shijun Qiu
- Department of Medical Imaging, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, 510405, Guangzhou, China
| | - Hui Zhang
- Department of Radiology, The First Hospital of Shanxi Medical University, 030001, Taiyuan, China
| | - Xiaojun Xu
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University, School of Medicine, 310009, Hangzhou, China
| | - Yongqiang Yu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, 230022, Hefei, China
| | - Bo Gao
- Department of Radiology, Yantai Yuhuangding Hospital, 264000, Yantai, China
| | - Tong Han
- Department of Radiology, Tianjin Huanhu Hospital, 300350, Tianjin, China
- Tianjin Key Laboratory of Cerebral Vascular and Neurodegenerative Diseases, 300350, Tianjin, China
| | - Zhenwei Yao
- Department of Radiology, Huashan Hosptial, Fudan University, 200040, Shanghai, China
| | - Guangbin Cui
- Functional and Molecular Imaging Key Lab of Shaanxi Province & Department of Radiology, Tangdu Hospital, The Military Medical University of PLA Airforce (Fourth Military Medical University), 710038, Xi'an, China
| | - Feng Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, 300052, Tianjin, China
| | - Wen Qin
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, 300052, Tianjin, China
| | - Quan Zhang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, 300052, Tianjin, China
| | - Mulin Jun Li
- Collaborative Innovation Center of Tianjin for Medical Epigenetics, Tianjin Key Laboratory of Medical Epigenetics, School of Basic Medical Sciences, Tianjin Medical University, 300070, Tianjin, China
| | - Meng Liang
- School of Medical Imaging, Tianjin Medical University, 300203, Tianjin, China
| | - Feng Chen
- Department of Radiology, Hainan General Hospital, 570311, Haikou, China
| | - Junfang Xian
- Department of Radiology, Beijing Tongren Hospital, Capital Medical University, 100730, Beijing, China
| | - Jiance Li
- Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, 325000, Wenzhou, China
| | - Jing Zhang
- Department of Magnetic Resonance, Lanzhou University Second Hospital, 730050, Lanzhou, China
| | - Xi-Nian Zuo
- Department of Psychology, University of Chinese Academy of Sciences (CAS), 100049, Beijing, China
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, 100101, Beijing, China
| | - Dawei Wang
- Department of Radiology, Qilu Hospital of Shandong University, 250012, Jinan, China
| | - Wen Shen
- Department of Radiology, Tianjin First Center Hospital, 300192, Tianjin, China
| | - Yanwei Miao
- Department of Radiology, The First Affiliated Hospital of Dalian Medical University, 116011, Dalian, China
| | - Fei Yuan
- Department of Radiology, Pingjin Hospital, Logistics University of Chinese People's Armed Police Forces, 300162, Tianjin, China
| | - Su Lui
- Department of Radiology, The Center for Medical Imaging, West China Hospital of Sichuan University, 610041, Chengdu, China
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, 325000, Wenzhou, China
| | - Xiaochu Zhang
- CAS Key Laboratory of Brain Function and Disease, University of Science and Technology of China, 230026, Hefei, China
- School of Life Sciences, University of Science & Technology of China, 230026, Hefei, China
| | - Kai Xu
- Department of Radiology, The Affiliated Hospital of Xuzhou Medical University, 221006, Xuzhou, China
- School of Medical Imaging, Xuzhou Medical University, 221004, Xuzhou, China
| | - Long Jiang Zhang
- Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, 210002, Nanjing, China
| | - Zhaoxiang Ye
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, 300060, Tianjin, China
| | - Chunshui Yu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, 300052, Tianjin, China.
- CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China.
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A study combining whole-exome sequencing and structural neuroimaging analysis for major depressive disorder. J Affect Disord 2020; 262:31-39. [PMID: 31706157 DOI: 10.1016/j.jad.2019.10.039] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/03/2019] [Revised: 10/01/2019] [Accepted: 10/27/2019] [Indexed: 12/30/2022]
Abstract
BACKGROUND Genetic variations associated with major depressive disorder (MDD) may affect the structural aspects of neural networks mediated by the molecular pathways involved in neuronal survival and synaptic plasticity. However, few studies have applied a novel approach such as whole-exome sequencing (WES) analysis to investigate the genetic contribution to the neurostructural changes in MDD. METHODS In the first part of the study, we investigated rare variants of selected genes from previous WES studies using a WES analysis in 184 patients with MDD and 82 healthy controls. In the second part of the study, we explored the association between the common genetic variants from the WES analysis and cortical thickness in 91 patients with MDD and 75 healthy controls. The gray-matter thickness of each cortical region was measured using FreeSurfer. RESULTS We identified recurrent non-silent variants in 24 MDD-related genes including FASN, MYH13, UNC13D, LILRA1, CACNA1B, TRIO, HOMER3, and BCAR3, and observed eleven recurrently altered copy number alternations where a gain on 15q11.2 and losses on 7q34 and 15q11.1-q11.2 in MDD genomes. We also found that rs11592462 in CDH23, a calcium-dependent cell-adhesion molecule encoding gene, was significantly associated with thinning in the right anterior cingulate cortex. LIMITATION The small sample size may lead our findings to be underpowered regarding rare variants. CONCLUSION The present study identified that non-synonymous rare variants were significantly associated with risk of MDD and found that genetic contributions to the development of MDD may be mediated by alterations in cortical thickness of emotion-processing neural circuits.
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de Marvao A, Dawes TJW, O'Regan DP. Artificial Intelligence for Cardiac Imaging-Genetics Research. Front Cardiovasc Med 2020; 6:195. [PMID: 32039240 PMCID: PMC6985036 DOI: 10.3389/fcvm.2019.00195] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Accepted: 12/27/2019] [Indexed: 12/18/2022] Open
Abstract
Cardiovascular conditions remain the leading cause of mortality and morbidity worldwide, with genotype being a significant influence on disease risk. Cardiac imaging-genetics aims to identify and characterize the genetic variants that influence functional, physiological, and anatomical phenotypes derived from cardiovascular imaging. High-throughput DNA sequencing and genotyping have greatly accelerated genetic discovery, making variant interpretation one of the key challenges in contemporary clinical genetics. Heterogeneous, low-fidelity phenotyping and difficulties integrating and then analyzing large-scale genetic, imaging and clinical datasets using traditional statistical approaches have impeded process. Artificial intelligence (AI) methods, such as deep learning, are particularly suited to tackle the challenges of scalability and high dimensionality of data and show promise in the field of cardiac imaging-genetics. Here we review the current state of AI as applied to imaging-genetics research and discuss outstanding methodological challenges, as the field moves from pilot studies to mainstream applications, from one dimensional global descriptors to high-resolution models of whole-organ shape and function, from univariate to multivariate analysis and from candidate gene to genome-wide approaches. Finally, we consider the future directions and prospects of AI imaging-genetics for ultimately helping understand the genetic and environmental underpinnings of cardiovascular health and disease.
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Affiliation(s)
| | | | - Declan P. O'Regan
- MRC London Institute of Medical Sciences, Imperial College London, London, United Kingdom
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Monoamine and neuroendocrine gene-sets associate with frustration-based aggression in a gender-specific manner. Eur Neuropsychopharmacol 2020; 30:75-86. [PMID: 29191428 DOI: 10.1016/j.euroneuro.2017.11.016] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2017] [Revised: 11/05/2017] [Accepted: 11/09/2017] [Indexed: 12/23/2022]
Abstract
Investigating phenotypic heterogeneity in aggression and understanding the molecular biological basis of aggression subtypes may lead to new prevention and treatment options. In the current study, we evaluated the taxonomy of aggression and examined specific genetic mechanisms underlying aggression subtypes in healthy males and females. Confirmatory Factor Analysis (CFA) was used to replicate a recently reported three-factor model of the Reactive Proactive Questionnaire (RPQ) in healthy adults (n = 661; median age 24.0 years; 41% male). Gene-set association analysis, aggregating common genetic variants within (a combination of) three molecular pathways previously implicated in aggression, i.e. serotonergic, dopaminergic, and neuroendocrine signaling, was conducted with MAGMA software in males and females separately (total n = 395) for aggression subtypes. We replicate the three-factor CFA model of the RPQ, and found males to score significantly higher on one of these factors compared to females: proactive aggression. The genetic association analysis showed a female-specific association of genetic variation in the combined gene-set with a different factor of the RPQ; reactive aggression due to internal frustration. Both the neuroendocrine and serotonergic gene-sets contributed significantly to this association. Our genetic findings are subtype- and sex-specific, stressing the value of efforts to reduce heterogeneity in research of aggression etiology. Importantly, subtype- and sex-differences in the underlying pathophysiology of aggression suggest that optimal treatment options will have to be tailored to the individual patient. Male and female needs of intervention might differ, stressing the need for sex-specific further research of aggression. Our work highlights opportunities for sample size maximization offered by population-based studies of aggression.
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