1
|
Ge R, Ching CRK, Bassett AS, Kushan L, Antshel KM, van Amelsvoort T, Bakker G, Butcher NJ, Campbell LE, Chow EWC, Craig M, Crossley NA, Cunningham A, Daly E, Doherty JL, Durdle CA, Emanuel BS, Fiksinski A, Forsyth JK, Fremont W, Goodrich‐Hunsaker NJ, Gudbrandsen M, Gur RE, Jalbrzikowski M, Kates WR, Lin A, Linden DEJ, McCabe KL, McDonald‐McGinn D, Moss H, Murphy DG, Murphy KC, Owen MJ, Villalon‐Reina JE, Repetto GM, Roalf DR, Ruparel K, Schmitt JE, Schuite‐Koops S, Angkustsiri K, Sun D, Vajdi A, van den Bree M, Vorstman J, Thompson PM, Vila‐Rodriguez F, Bearden CE. Source-based morphometry reveals structural brain pattern abnormalities in 22q11.2 deletion syndrome. Hum Brain Mapp 2024; 45:e26553. [PMID: 38224541 PMCID: PMC10785196 DOI: 10.1002/hbm.26553] [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: 05/31/2023] [Revised: 11/12/2023] [Accepted: 11/19/2023] [Indexed: 01/17/2024] Open
Abstract
22q11.2 deletion syndrome (22q11DS) is the most frequently occurring microdeletion in humans. It is associated with a significant impact on brain structure, including prominent reductions in gray matter volume (GMV), and neuropsychiatric manifestations, including cognitive impairment and psychosis. It is unclear whether GMV alterations in 22q11DS occur according to distinct structural patterns. Then, 783 participants (470 with 22q11DS: 51% females, mean age [SD] 18.2 [9.2]; and 313 typically developing [TD] controls: 46% females, mean age 18.0 [8.6]) from 13 datasets were included in the present study. We segmented structural T1-weighted brain MRI scans and extracted GMV images, which were then utilized in a novel source-based morphometry (SBM) pipeline (SS-Detect) to generate structural brain patterns (SBPs) that capture co-varying GMV. We investigated the impact of the 22q11.2 deletion, deletion size, intelligence quotient, and psychosis on the SBPs. Seventeen GMV-SBPs were derived, which provided spatial patterns of GMV covariance associated with a quantitative metric (i.e., loading score) for analysis. Patterns of topographically widespread differences in GMV covariance, including the cerebellum, discriminated individuals with 22q11DS from healthy controls. The spatial extents of the SBPs that revealed disparities between individuals with 22q11DS and controls were consistent with the findings of the univariate voxel-based morphometry analysis. Larger deletion size was associated with significantly lower GMV in frontal and occipital SBPs; however, history of psychosis did not show a strong relationship with these covariance patterns. 22q11DS is associated with distinct structural abnormalities captured by topographical GMV covariance patterns that include the cerebellum. Findings indicate that structural anomalies in 22q11DS manifest in a nonrandom manner and in distinct covarying anatomical patterns, rather than a diffuse global process. These SBP abnormalities converge with previously reported cortical surface area abnormalities, suggesting disturbances of early neurodevelopment as the most likely underlying mechanism.
Collapse
Affiliation(s)
- Ruiyang Ge
- Department of PsychiatryUniversity of British ColumbiaVancouverBritish ColumbiaCanada
- Djavad Mowafaghian Centre for Brain HealthUniversity of British ColumbiaVancouverBritish ColumbiaCanada
| | | | - Anne S. Bassett
- Clinical Genetics Research ProgramCentre for Addiction and Mental HealthTorontoOntarioCanada
- The Dalglish Family 22q Clinic, Department of Psychiatry and Division of Cardiology, Department of Medicine, and Toronto General Hospital Research InstituteUniversity Health NetworkTorontoOntarioCanada
- Campbell Family Mental Health Research InstituteCentre for Addiction and Mental HealthTorontoOntarioCanada
- Department of PsychiatryUniversity of TorontoTorontoOntarioCanada
| | - Leila Kushan
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human BehaviorUniversity of California, Los AngelesLos AngelesCaliforniaUSA
| | | | | | - Geor Bakker
- Department of Psychiatry and NeuropsychologyMaastricht UniversityMaastrichtNetherlands
| | - Nancy J. Butcher
- Department of PsychiatryUniversity of TorontoTorontoOntarioCanada
- Child Health Evaluative SciencesThe Hospital for Sick ChildrenTorontoOntarioCanada
| | | | - Eva W. C. Chow
- Clinical Genetics Research ProgramCentre for Addiction and Mental HealthTorontoOntarioCanada
- Department of PsychiatryUniversity of TorontoTorontoOntarioCanada
| | - Michael Craig
- Sackler Institute for Translational Neurodevelopment and Department of Forensic and Neurodevelopmental Sciences, King's College LondonInstitute of Psychiatry, Psychology and NeuroscienceLondonUK
- National Autism UnitBethlem Royal HospitalBeckenhamUK
| | - Nicolas A. Crossley
- Department of PsychiatryPontificia Universidad Catolica de ChileSantiagoChile
| | - Adam Cunningham
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical NeurosciencesCardiff UniversityCardiffUK
| | - Eileen Daly
- Sackler Institute for Translational Neurodevelopment and Department of Forensic and Neurodevelopmental Sciences, King's College LondonInstitute of Psychiatry, Psychology and NeuroscienceLondonUK
| | - Joanne L. Doherty
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical NeurosciencesCardiff UniversityCardiffUK
- Cardiff University Brain Research Imaging Centre, School of PsychologyCardiff UniversityCardiffUK
| | - Courtney A. Durdle
- Department of PediatricsUC Davis MIND InstituteDavisCaliforniaUSA
- Department of Psychological and Brain SciencesUC Santa BarbaraSanta BarbaraCaliforniaUSA
| | - Beverly S. Emanuel
- Division of Human GeneticsThe Children's Hospital of PhiladelphiaPhiladelphiaPennsylvaniaUSA
- Department of Pediatrics, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Ania Fiksinski
- Department of Psychology and Department of Pediatrics, Wilhelmina Children's HospitalUniversity Medical Center UtrechtUtrechtNetherlands
- Department of Psychiatry and Neuropsychology, Division of Mental Health, MHeNSMaastricht UniversityMaastrichtNetherlands
| | - Jennifer K. Forsyth
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human BehaviorUniversity of California, Los AngelesLos AngelesCaliforniaUSA
- Department of PsychologyUniversity of WashingtonSeattleWashingtonUSA
| | - Wanda Fremont
- Department of Psychiatry and Behavioral Sciences State University of New YorkUpstate Medical University SyracuseNew YorkUSA
| | - Naomi J. Goodrich‐Hunsaker
- Department of PediatricsUC Davis MIND InstituteDavisCaliforniaUSA
- Department of NeurologyUniversity of UtahSalt Lake CityUtahUSA
| | - Maria Gudbrandsen
- Sackler Institute for Translational Neurodevelopment and Department of Forensic and Neurodevelopmental Sciences, King's College LondonInstitute of Psychiatry, Psychology and NeuroscienceLondonUK
- Centre for Research in Psychological Wellbeing (CREW), School of PsychologyUniversity of RoehamptonLondonUK
| | - Raquel E. Gur
- Department of Psychiatry, Perelman School of MedicineUniversity of Pennsylvania and Children's Hospital of PhiladelphiaPhiladelphiaPennsylvaniaUSA
| | - Maria Jalbrzikowski
- Department of PsychiatryHarvard Medical SchoolBostonMassachusettsUSA
- Department of Psychiatry and Behavioral SciencesBoston Children's HospitalBostonMassachusettsUSA
| | - Wendy R. Kates
- Department of Psychiatry and Behavioral Sciences State University of New YorkUpstate Medical University SyracuseNew YorkUSA
| | - Amy Lin
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human BehaviorUniversity of California, Los AngelesLos AngelesCaliforniaUSA
- Graduate Interdepartmental Program in NeuroscienceUCLA School of MedicineLos AngelesCaliforniaUSA
| | - David E. J. Linden
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical NeurosciencesCardiff UniversityCardiffUK
| | - Kathryn L. McCabe
- School of PsychologyUniversity of NewcastleCallaghanAustralia
- Department of PediatricsUC Davis MIND InstituteDavisCaliforniaUSA
| | - Donna McDonald‐McGinn
- Department of Pediatrics, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- 22q and You Center, Clinical Genetics Center, and Division of Human GeneticsThe Children's Hospital of PhiladelphiaPhiladelphiaPennsylvaniaUSA
- Department of Human Biology and Medical GeneticsSapienza UniversityRomeItaly
| | - Hayley Moss
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical NeurosciencesCardiff UniversityCardiffUK
| | - Declan G. Murphy
- Sackler Institute for Translational Neurodevelopment and Department of Forensic and Neurodevelopmental Sciences, King's College LondonInstitute of Psychiatry, Psychology and NeuroscienceLondonUK
- Behavioural Genetics Clinic, Adult Autism Service, Behavioural and Developmental Psychiatry Clinical Academic GroupSouth London and Maudsley Foundation NHS TrustLondonUK
| | - Kieran C. Murphy
- Department of PsychiatryRoyal College of Surgeons in IrelandDublinIreland
| | - Michael J. Owen
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical NeurosciencesCardiff UniversityCardiffUK
| | | | - Gabriela M. Repetto
- Centro de Genetica y Genomica, Facultad de MedicinaClinica Alemana Universidad del DesarrolloSantiagoChile
| | - David R. Roalf
- Department of PsychiatryUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Kosha Ruparel
- Department of PsychiatryUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - J. Eric Schmitt
- Department of Radiology and PsychiatryUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Sanne Schuite‐Koops
- Department of PsychiatryUniversity Medical Center Groningen, Rijksuniversiteit GroningenGroningenNetherlands
| | | | - Daqiang Sun
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human BehaviorUniversity of California, Los AngelesLos AngelesCaliforniaUSA
| | - Ariana Vajdi
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human BehaviorUniversity of California, Los AngelesLos AngelesCaliforniaUSA
- Kaiser Permanente Bernard J. Tyson School of Medicine PasadenaCaliforniaUSA
| | - Marianne van den Bree
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical NeurosciencesCardiff UniversityCardiffUK
| | - Jacob Vorstman
- Department of PsychiatryUniversity of TorontoTorontoOntarioCanada
- Program in Genetics and Genome Biology, Research Institute, and Department of PsychiatryThe Hospital for Sick ChildrenTorontoOntarioCanada
| | - Paul M. Thompson
- Departments of Neurology, Psychiatry, Radiology, Engineering, Pediatrics and OphthalmologyUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Fidel Vila‐Rodriguez
- Department of PsychiatryUniversity of British ColumbiaVancouverBritish ColumbiaCanada
- Djavad Mowafaghian Centre for Brain HealthUniversity of British ColumbiaVancouverBritish ColumbiaCanada
- School of Biomedical Engineering University of British Columbia VancouverBritish ColumbiaCanada
| | - Carrie E. Bearden
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human BehaviorUniversity of California, Los AngelesLos AngelesCaliforniaUSA
| |
Collapse
|
2
|
Jalbrzikowski M, Lin A, Vajdi A, Grigoryan V, Kushan L, Ching CRK, Schleifer C, Hayes RA, Chu SA, Sugar CA, Forsyth JK, Bearden CE. Longitudinal trajectories of cortical development in 22q11.2 copy number variants and typically developing controls. Mol Psychiatry 2022; 27:4181-4190. [PMID: 35896619 PMCID: PMC9718681 DOI: 10.1038/s41380-022-01681-w] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Revised: 06/15/2022] [Accepted: 06/27/2022] [Indexed: 02/07/2023]
Abstract
Probing naturally-occurring, reciprocal genomic copy number variations (CNVs) may help us understand mechanisms that underlie deviations from typical brain development. Cross-sectional studies have identified prominent reductions in cortical surface area (SA) and increased cortical thickness (CT) in 22q11.2 deletion carriers (22qDel), with the opposite pattern in duplication carriers (22qDup), but the longitudinal trajectories of these anomalies-and their relationship to clinical symptomatology-are unknown. Here, we examined neuroanatomic changes within a longitudinal cohort of 261 22q11.2 CNV carriers and demographically-matched typically developing (TD) controls (84 22qDel, 34 22qDup, and 143 TD; mean age 18.35, ±10.67 years; 50.47% female). A total of 431 magnetic resonance imaging scans (164 22qDel, 59 22qDup, and 208 TD control scans; mean interscan interval = 20.27 months) were examined. Longitudinal FreeSurfer analysis pipelines were used to parcellate the cortex and calculate average CT and SA for each region. First, general additive mixed models (GAMMs) were used to identify regions with between-group differences in developmental trajectories. Secondly, we investigated whether these trajectories were associated with clinical outcomes. Developmental trajectories of CT were more protracted in 22qDel relative to TD and 22qDup. 22qDup failed to show normative age-related SA decreases. 22qDel individuals with psychosis spectrum symptoms showed two distinct periods of altered CT trajectories relative to 22qDel without psychotic symptoms. In contrast, 22q11.2 CNV carriers with autism spectrum diagnoses showed early alterations in SA trajectories. Collectively, these results provide new insights into altered neurodevelopment in 22q11.2 CNV carriers, which may shed light on neural mechanisms underlying distinct clinical outcomes.
Collapse
Affiliation(s)
- Maria Jalbrzikowski
- Department of Psychiatry and Behavioral Sciences, Boston Children's Hospital, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Amy Lin
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
- Neuroscience Interdepartmental Program, University of California, Los Angeles, CA, USA
| | - Ariana Vajdi
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
| | - Vardui Grigoryan
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
| | - Leila Kushan
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
| | - Christopher R K Ching
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Charles Schleifer
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
- Neuroscience Interdepartmental Program, University of California, Los Angeles, CA, USA
| | - Rebecca A Hayes
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Stephanie A Chu
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
- Neuroscience Interdepartmental Program, University of California, Los Angeles, CA, USA
| | - Catherine A Sugar
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
- Department of Biostatistics, University of California, Los Angeles, CA, USA
| | - Jennifer K Forsyth
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
- Department of Psychology, University of Washington, Seattle, WA, USA
| | - Carrie E Bearden
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA.
- Neuroscience Interdepartmental Program, University of California, Los Angeles, CA, USA.
- Department of Psychology, University of California, Los Angeles, CA, USA.
| |
Collapse
|
3
|
Dwyer D, Koutsouleris N. Annual Research Review: Translational machine learning for child and adolescent psychiatry. J Child Psychol Psychiatry 2022; 63:421-443. [PMID: 35040130 DOI: 10.1111/jcpp.13545] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 09/06/2021] [Indexed: 12/14/2022]
Abstract
Children and adolescents could benefit from the use of predictive tools that facilitate personalized diagnoses, prognoses, and treatment selection. Such tools have not yet been deployed using traditional statistical methods, potentially due to the limitations of the paradigm and the need to leverage large amounts of digital data. This review will suggest that a machine learning approach could address these challenges and is designed to introduce new readers to the background, methods, and results in the field. A rationale is first introduced followed by an outline of fundamental elements of machine learning approaches. To provide an overview of the use of the techniques in child and adolescent literature, a scoping review of broad trends is then presented. Selected studies are also highlighted in order to draw attention to research areas that are closest to translation and studies that exhibit a high degree of experimental innovation. Limitations to the research, and machine learning approaches generally, are outlined in the penultimate section highlighting issues related to sample sizes, validation, clinical utility, and ethical challenges. Finally, future directions are discussed that could enhance the possibility of clinical implementation and address specific questions relevant to the child and adolescent psychiatry. The review gives a broad overview of the machine learning paradigm in order to highlight the benefits of a shift in perspective towards practically oriented statistical solutions that aim to improve clinical care of children and adolescents.
Collapse
Affiliation(s)
- Dominic Dwyer
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University, Munich, Germany.,Orygen, The National Centre of Excellence in Youth Mental Health, Melbourne, Australia.,Centre for Youth Mental Health, University of Melbourne, Melbourne, Australia
| | - Nikolaos Koutsouleris
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University, Munich, Germany.,Max-Planck Institute of Psychiatry, Munich, Germany.,Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| |
Collapse
|
4
|
Wang S, Celebi ME, Zhang YD, Yu X, Lu S, Yao X, Zhou Q, Miguel MG, Tian Y, Gorriz JM, Tyukin I. Advances in Data Preprocessing for Biomedical Data Fusion: An Overview of the Methods, Challenges, and Prospects. INFORMATION FUSION 2021; 76:376-421. [DOI: 10.1016/j.inffus.2021.07.001] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/30/2023]
|
5
|
Modenato C, Martin-Brevet S, Moreau CA, Rodriguez-Herreros B, Kumar K, Draganski B, Sønderby IE, Jacquemont S. Lessons Learned From Neuroimaging Studies of Copy Number Variants: A Systematic Review. Biol Psychiatry 2021; 90:596-610. [PMID: 34509290 DOI: 10.1016/j.biopsych.2021.05.028] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Revised: 05/28/2021] [Accepted: 05/30/2021] [Indexed: 01/06/2023]
Abstract
Pathogenic copy number variants (CNVs) and aneuploidies alter gene dosage and are associated with neurodevelopmental psychiatric disorders such as autism spectrum disorder and schizophrenia. Brain mechanisms mediating genetic risk for neurodevelopmental psychiatric disorders remain largely unknown, but there is a rapid increase in morphometry studies of CNVs using T1-weighted structural magnetic resonance imaging. Studies have been conducted one mutation at a time, leaving the field with a complex catalog of brain alterations linked to different genomic loci. Our aim was to provide a systematic review of neuroimaging phenotypes across CNVs associated with developmental psychiatric disorders including autism and schizophrenia. We included 76 structural magnetic resonance imaging studies on 20 CNVs at the 15q11.2, 22q11.2, 1q21.1 distal, 16p11.2 distal and proximal, 7q11.23, 15q11-q13, and 22q13.33 (SHANK3) genomic loci as well as aneuploidies of chromosomes X, Y, and 21. Moderate to large effect sizes on global and regional brain morphometry are observed across all genomic loci, which is in line with levels of symptom severity reported for these variants. This is in stark contrast with the much milder neuroimaging effects observed in idiopathic psychiatric disorders. Data also suggest that CNVs have independent effects on global versus regional measures as well as on cortical surface versus thickness. Findings highlight a broad diversity of regional morphometry patterns across genomic loci. This heterogeneity of brain patterns provides insight into the weak effects reported in magnetic resonance imaging studies of cognitive dimension and psychiatric conditions. Neuroimaging studies across many more variants will be required to understand links between gene function and brain morphometry.
Collapse
Affiliation(s)
- Claudia Modenato
- Laboratory for Research in Neuroimaging, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland
| | - Sandra Martin-Brevet
- Laboratory for Research in Neuroimaging, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland
| | - Clara A Moreau
- Sainte-Justine Hospital Research Center, Montreal, Quebec, Canada; Human Genetics and Cognitive Functions, Centre National de la Recherche Scientifique UMR 3571, Department of Neuroscience, Université de Paris, Institut Pasteur, Paris, France
| | - Borja Rodriguez-Herreros
- Service des Troubles du Spectre de l'Autisme et Apparentés, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland
| | - Kuldeep Kumar
- Sainte-Justine Hospital Research Center, Montreal, Quebec, Canada; Department of Pediatrics, University of Montreal, Montreal, Quebec, Canada
| | - Bogdan Draganski
- Laboratory for Research in Neuroimaging, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland; Neurology Department, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Ida E Sønderby
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway; Norwegian Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, University of Oslo, Oslo, Norway; KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Sébastien Jacquemont
- Sainte-Justine Hospital Research Center, Montreal, Quebec, Canada; Department of Pediatrics, University of Montreal, Montreal, Quebec, Canada.
| |
Collapse
|
6
|
Raballo A, Poletti M, Preti A. Individualized Diagnostic and Prognostic Models for Psychosis Risk Syndromes: Do Not Underestimate Antipsychotic Exposure. Biol Psychiatry 2021; 90:e33-e35. [PMID: 34001370 DOI: 10.1016/j.biopsych.2021.01.020] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Accepted: 03/12/2021] [Indexed: 10/21/2022]
Affiliation(s)
- Andrea Raballo
- Section of Psychiatry, Clinical Psychology and Rehabilitation, Department of Medicine, University of Perugia, Italy; Center for Translational, Phenomenological and Developmental Psychopathology, Perugia University Hospital, Perugia, Italy.
| | - Michele Poletti
- Child and Adolescent Neuropsychiatry Service, Department of Mental Health and Pathological Addiction, Azienda USL-IRCCS di Reggio Emilia, Reggio Emilia, Italy
| | - Antonio Preti
- Department of Neuroscience, University of Turin, Turin, Italy
| |
Collapse
|
7
|
Zöller D, Sandini C, Schaer M, Eliez S, Bassett DS, Van De Ville D. Structural control energy of resting-state functional brain states reveals less cost-effective brain dynamics in psychosis vulnerability. Hum Brain Mapp 2021; 42:2181-2200. [PMID: 33566395 PMCID: PMC8046160 DOI: 10.1002/hbm.25358] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Revised: 12/01/2020] [Accepted: 01/05/2021] [Indexed: 12/19/2022] Open
Abstract
How the brain's white-matter anatomy constrains brain activity is an open question that might give insights into the mechanisms that underlie mental disorders such as schizophrenia. Chromosome 22q11.2 deletion syndrome (22q11DS) is a neurodevelopmental disorder with an extremely high risk for psychosis providing a test case to study developmental aspects of schizophrenia. In this study, we used principles from network control theory to probe the implications of aberrant structural connectivity for the brain's functional dynamics in 22q11DS. We retrieved brain states from resting-state functional magnetic resonance images of 78 patients with 22q11DS and 85 healthy controls. Then, we compared them in terms of persistence control energy; that is, the control energy that would be required to persist in each of these states based on individual structural connectivity and a dynamic model. Persistence control energy was altered in a broad pattern of brain states including both energetically more demanding and less demanding brain states in 22q11DS. Further, we found a negative relationship between persistence control energy and resting-state activation time, which suggests that the brain reduces energy by spending less time in energetically demanding brain states. In patients with 22q11DS, this behavior was less pronounced, suggesting a deficiency in the ability to reduce energy through brain activation. In summary, our results provide initial insights into the functional implications of altered structural connectivity in 22q11DS, which might improve our understanding of the mechanisms underlying the disease.
Collapse
Affiliation(s)
- Daniela Zöller
- Medical Image Processing LaboratoryInstitute of Bioengineering, École Polytechnique Fédérale de Lausanne (EPFL)LausanneSwitzerland
- Department of Radiology and Medical InformaticsUniversity of GenevaGenevaSwitzerland
- Institute of Neuromodulation and NeurotechnologyUniversity of TübingenTübingenGermany
- Developmental Imaging an Psychopathology Laboratory, Department of PsychiatryUniversity of GenevaGenevaSwitzerland
| | - Corrado Sandini
- Institute of Neuromodulation and NeurotechnologyUniversity of TübingenTübingenGermany
| | - Marie Schaer
- Institute of Neuromodulation and NeurotechnologyUniversity of TübingenTübingenGermany
| | - Stephan Eliez
- Institute of Neuromodulation and NeurotechnologyUniversity of TübingenTübingenGermany
| | - Danielle S. Bassett
- Department of BioengineeringUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Department of Electrical & Systems EngineeringUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Department of Physics & AstronomyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Department of PsychiatryUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Dimitri Van De Ville
- Medical Image Processing LaboratoryInstitute of Bioengineering, École Polytechnique Fédérale de Lausanne (EPFL)LausanneSwitzerland
- Department of Radiology and Medical InformaticsUniversity of GenevaGenevaSwitzerland
| |
Collapse
|
8
|
Zhuo C, Cheng L, Li G, Xu Y, Jing R, Li S, Zhang L, Lin X, Zhou C. COMT-Val158Met polymorphism modulates antipsychotic effects on auditory verbal hallucinations and temporal lobe gray matter volumes in healthy individuals-symptom relief accompanied by worrisome volume reductions. Brain Imaging Behav 2021; 14:1373-1381. [PMID: 30712251 PMCID: PMC7572342 DOI: 10.1007/s11682-019-00043-5] [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] [Indexed: 02/07/2023]
Abstract
Investigation of auditory verbal hallucinations (AVHs) in schizophrenics is complicated by psychiatric symptoms. Investigating healthy individuals with AVHs (H-AVHs) can obviate such confounding factors. The objective of this study was to explore the effects of antipsychotic treatment on AVHs and gray matter volumes (GMVs) in H-AVH subjects and whether such are effects are influenced by COMT-Val158Met genotype. Magnetic resonance imaging (MRI) and genotyping studies were completed for 42 H-AVH subjects and 42 well-matched healthy controls (HCs). COMT-Met/Met homozygotes (158th codon) were identified as COMT-Met genotype; COMT-Met/Val heterozygotes and COMT-Val/Val homozygotes were identified as COMT-Val genotype. Data were compared across groups (H-AVH vs. HC, and between genotypes) with two-sample t-tests. The H-AVH COMT-Met group showed a stronger response to antipsychotic treatment than the H-AVH COMT-Val group (p < 0.001). Both H-AVH genotype groups exhibited temporal lobe GMV reductions after treatment, and relative to their respective genotype-matched HC groups. Antipsychotic treatment effects in H-AVH subjects were influenced by COMT-Val158Met genotype and associated with widespread GMV reductions. These findings provide clues for further exploration of treatment targets for AVHs. Treatment associated GMV reductions, however, raise concerns about use of antipsychotics in H-AVH subjects.
Collapse
Affiliation(s)
- Chuanjun Zhuo
- Department of Psychiatric-Neuroimaging-Genetics and Morbidity Laboratory (PNGC-Lab), Tianjin Mental Health Center, Mental Health Teaching Hospital, Nankai University Affiliated Anding Hospital, Tianjin Medical University, Tianjin, 300222, China. .,Department of Psychiatry, Institute of Mental Healthy, Genetic Lab, Jining Medical University, Jining, 272191, China. .,Department of Psychiatry, College of Basic Medical Research, Tianjin Medical University, Tianjin, 300000, China. .,Department of Psychiatry, First Hospital/First Clinical Medical College of Shanxi Medical University, Taiyuan, 030001, China. .,Department of Psychiatry, Wenzhou Seventh People's Hospital, Wenzhou, 325000, China. .,Department of Psychiatry, Shanxi Medical University, Taiyuan, 030000, China.
| | - Langlang Cheng
- Department of Psychiatry, Wenzhou Seventh People's Hospital, Wenzhou, 325000, China
| | - Gongying Li
- Department of Psychiatry, Institute of Mental Healthy, Genetic Lab, Jining Medical University, Jining, 272191, China
| | - Yong Xu
- Department of Psychiatry, First Hospital/First Clinical Medical College of Shanxi Medical University, Taiyuan, 030001, China.,Department of Psychiatry, Shanxi Medical University, Taiyuan, 030000, China
| | - Rixing Jing
- Department of Pattern Recognition, China National Key Laboratory, Institute of Automation, Chinese Academy of Sciences, Beijing, 100191, China.,Department of Pattern Recognition, University of Chinese Academy of Sciences, Beijing, 100191, China
| | - Shen Li
- Department of Psychiatry, College of Basic Medical Research, Tianjin Medical University, Tianjin, 300000, China
| | - Li Zhang
- GHM Institute of CNS Regeneration, Jinan University, Guangzhou, 510632, Guangdong Province, China
| | - Xiaodong Lin
- Department of Psychiatry, Wenzhou Seventh People's Hospital, Wenzhou, 325000, China.
| | - Chunhua Zhou
- Department of Pharmacy, The First Hospital of Hebei Medical University, Shijiazhuang, 050000, China.
| |
Collapse
|
9
|
Bagautdinova J, Zöller D, Schaer M, Padula MC, Mancini V, Schneider M, Eliez S. Altered cortical thickness development in 22q11.2 deletion syndrome and association with psychotic symptoms. Mol Psychiatry 2021; 26:7671-7678. [PMID: 34253864 PMCID: PMC8873018 DOI: 10.1038/s41380-021-01209-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/07/2020] [Revised: 06/15/2021] [Accepted: 06/23/2021] [Indexed: 02/06/2023]
Abstract
Schizophrenia has been extensively associated with reduced cortical thickness (CT), and its neurodevelopmental origin is increasingly acknowledged. However, the exact timing and extent of alterations occurring in preclinical phases remain unclear. With a high prevalence of psychosis, 22q11.2 deletion syndrome (22q11DS) is a neurogenetic disorder that represents a unique opportunity to examine brain maturation in high-risk individuals. In this study, we quantified trajectories of CT maturation in 22q11DS and examined the association of CT development with the emergence of psychotic symptoms. Longitudinal structural MRI data with 1-6 time points were collected from 324 participants aged 5-35 years (N = 148 22q11DS, N = 176 controls), resulting in a total of 636 scans (N = 334 22q11DS, N = 302 controls). Mixed model regression analyses were used to compare CT trajectories between participants with 22q11DS and controls. Further, CT trajectories were compared between participants with 22q11DS who developed (N = 61, 146 scans), or remained exempt of (N = 47; 98 scans) positive psychotic symptoms during development. Compared to controls, participants with 22q11DS showed widespread increased CT, focal reductions in the posterior cingulate gyrus and superior temporal gyrus (STG), and accelerated cortical thinning during adolescence, mainly in frontotemporal regions. Within 22q11DS, individuals who developed psychotic symptoms showed exacerbated cortical thinning in the right STG. Together, these findings suggest that genetic predisposition for psychosis is associated with increased CT starting from childhood and altered maturational trajectories of CT during adolescence, affecting predominantly frontotemporal regions. In addition, accelerated thinning in the STG may represent an early biomarker associated with the emergence of psychotic symptoms.
Collapse
Affiliation(s)
- Joëlle Bagautdinova
- Developmental Imaging and Psychopathology Laboratory, Department of Psychiatry, Faculty of Medicine, University of Geneva, Geneva, Switzerland.
| | - Daniela Zöller
- grid.8591.50000 0001 2322 4988Developmental Imaging and Psychopathology Laboratory, Department of Psychiatry, Faculty of Medicine, University of Geneva, Geneva, Switzerland ,grid.5333.60000000121839049Medical Image Processing Laboratory, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland ,grid.8591.50000 0001 2322 4988Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland
| | - Marie Schaer
- grid.8591.50000 0001 2322 4988Developmental Imaging and Psychopathology Laboratory, Department of Psychiatry, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Maria Carmela Padula
- grid.8591.50000 0001 2322 4988Developmental Imaging and Psychopathology Laboratory, Department of Psychiatry, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Valentina Mancini
- grid.8591.50000 0001 2322 4988Developmental Imaging and Psychopathology Laboratory, Department of Psychiatry, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Maude Schneider
- grid.8591.50000 0001 2322 4988Developmental Imaging and Psychopathology Laboratory, Department of Psychiatry, Faculty of Medicine, University of Geneva, Geneva, Switzerland ,grid.8591.50000 0001 2322 4988Clinical Psychology Unit for Intellectual and Developmental Disabilities, Faculty of Psychology and Educational Sciences, University of Geneva, Geneva, Switzerland
| | - Stephan Eliez
- grid.8591.50000 0001 2322 4988Developmental Imaging and Psychopathology Laboratory, Department of Psychiatry, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| |
Collapse
|
10
|
Gudbrandsen M, Daly E, Murphy CM, Blackmore CE, Rogdaki M, Mann C, Bletsch A, Kushan L, Bearden CE, Murphy DGM, Craig MC, Ecker C. Brain morphometry in 22q11.2 deletion syndrome: an exploration of differences in cortical thickness, surface area, and their contribution to cortical volume. Sci Rep 2020; 10:18845. [PMID: 33139857 PMCID: PMC7606591 DOI: 10.1038/s41598-020-75811-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2020] [Accepted: 10/16/2020] [Indexed: 01/08/2023] Open
Abstract
22q11.2 Deletion Syndrome (22q11.2DS) is the most common microdeletion in humans, with a heterogenous clinical presentation including medical, behavioural and psychiatric conditions. Previous neuroimaging studies examining the neuroanatomical underpinnings of 22q11.2DS show alterations in cortical volume (CV), cortical thickness (CT) and surface area (SA). The aim of this study was to identify (1) the spatially distributed networks of differences in CT and SA in 22q11.2DS compared to controls, (2) their unique and spatial overlap, as well as (3) their relative contribution to observed differences in CV. Structural MRI scans were obtained from 62 individuals with 22q11.2DS and 57 age-and-gender-matched controls (aged 6-31). Using FreeSurfer, we examined differences in vertex-wise estimates of CV, CT and SA at each vertex, and compared the frequencies of vertices with a unique or overlapping difference for each morphometric feature. Our findings indicate that CT and SA make both common and unique contributions to volumetric differences in 22q11.2DS, and in some areas, their strong opposite effects mask differences in CV. By identifying the neuroanatomic variability in 22q11.2DS, and the separate contributions of CT and SA, we can start exploring the shared and distinct mechanisms that mediate neuropsychiatric symptoms across disorders, e.g. 22q11.2DS-related ASD and/or psychosis/schizophrenia.
Collapse
Affiliation(s)
- M Gudbrandsen
- Department of Forensic and Neurodevelopmental Sciences, and the Sackler Institute for Translational Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College, London, UK
| | - E Daly
- Department of Forensic and Neurodevelopmental Sciences, and the Sackler Institute for Translational Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College, London, UK
| | - C M Murphy
- Department of Forensic and Neurodevelopmental Sciences, and the Sackler Institute for Translational Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College, London, UK
- Behavioural Genetics Clinic, Adult Autism and ADHD Services, Behavioural and Developmental Clinical Academic Group, South London and Maudsley Foundation, NHS, London, UK
| | - C E Blackmore
- Department of Forensic and Neurodevelopmental Sciences, and the Sackler Institute for Translational Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College, London, UK
- Behavioural Genetics Clinic, Adult Autism and ADHD Services, Behavioural and Developmental Clinical Academic Group, South London and Maudsley Foundation, NHS, London, UK
| | - M Rogdaki
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College, London, UK
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College, London, UK
| | - C Mann
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital, Goethe University, Frankfurt, Germany
| | - A Bletsch
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital, Goethe University, Frankfurt, Germany
| | - L Kushan
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California-Los Angeles, Los Angeles, CA, USA
| | - C E Bearden
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California-Los Angeles, Los Angeles, CA, USA
- Department of Psychology, University of California-Los Angeles, Los Angeles, CA, USA
| | - D G M Murphy
- Department of Forensic and Neurodevelopmental Sciences, and the Sackler Institute for Translational Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College, London, UK
| | - M C Craig
- Department of Forensic and Neurodevelopmental Sciences, and the Sackler Institute for Translational Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College, London, UK
- National Autism Unit, Bethlem Royal Hospital, London, UK
| | - Christine Ecker
- Department of Forensic and Neurodevelopmental Sciences, and the Sackler Institute for Translational Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College, London, UK.
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital, Goethe University, Frankfurt, Germany.
| |
Collapse
|
11
|
Jalbrzikowski M. Neuroimaging Phenotypes Associated With Risk and Resilience for Psychosis and Autism Spectrum Disorders in 22q11.2 Microdeletion Syndrome. BIOLOGICAL PSYCHIATRY: COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2020; 6:211-224. [PMID: 33218931 DOI: 10.1016/j.bpsc.2020.08.015] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Revised: 08/26/2020] [Accepted: 08/28/2020] [Indexed: 01/17/2023]
Abstract
Identification of biological risk factors that contribute to the development of complex neuropsychiatric disorders such as psychosis and autism spectrum disorder (ASD) is key for early intervention and detection. Furthermore, parsing the biological heterogeneity associated with these neuropsychiatric syndromes will help us understand the neural mechanisms underlying psychiatric symptom development. The 22q11.2 microdeletion syndrome (22q11DS) is caused by a recurrent genetic mutation that carries significantly increased risk for developing psychosis and/or ASD. In this review, I provide an brief introduction to 22q11DS and discuss common phenotyping strategies that are used to assess psychosis and ASD in this population. I then summarize neuroimaging phenotypes associated with psychosis and ASD in 22q11.DS. Next, I discuss challenges within the field and provide practical suggestions to overcome these obstacles. Finally, I discuss future directions for moving 22q11DS risk and resilience research forward.
Collapse
Affiliation(s)
- Maria Jalbrzikowski
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania.
| |
Collapse
|
12
|
Individualized Diagnostic and Prognostic Models for Patients With Psychosis Risk Syndromes: A Meta-analytic View on the State of the Art. Biol Psychiatry 2020; 88:349-360. [PMID: 32305218 DOI: 10.1016/j.biopsych.2020.02.009] [Citation(s) in RCA: 50] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Revised: 01/25/2020] [Accepted: 02/06/2020] [Indexed: 12/23/2022]
Abstract
BACKGROUND The clinical high risk (CHR) paradigm has facilitated research into the underpinnings of help-seeking individuals at risk for developing psychosis, aiming at predicting and possibly preventing transition to the overt disorder. Statistical methods such as machine learning and Cox regression have provided the methodological basis for this research by enabling the construction of diagnostic models (i.e., distinguishing CHR individuals from healthy individuals) and prognostic models (i.e., predicting a future outcome) based on different data modalities, including clinical, neurocognitive, and neurobiological data. However, their translation to clinical practice is still hindered by the high heterogeneity of both CHR populations and methodologies applied. METHODS We systematically reviewed the literature on diagnostic and prognostic models built on Cox regression and machine learning. Furthermore, we conducted a meta-analysis on prediction performances investigating heterogeneity of methodological approaches and data modality. RESULTS A total of 44 articles were included, covering 3707 individuals for prognostic studies and 1052 individuals for diagnostic studies (572 CHR patients and 480 healthy control subjects). CHR patients could be classified against healthy control subjects with 78% sensitivity and 77% specificity. Across prognostic models, sensitivity reached 67% and specificity reached 78%. Machine learning models outperformed those applying Cox regression by 10% sensitivity. There was a publication bias for prognostic studies yet no other moderator effects. CONCLUSIONS Our results may be driven by substantial clinical and methodological heterogeneity currently affecting several aspects of the CHR field and limiting the clinical implementability of the proposed models. We discuss conceptual and methodological harmonization strategies to facilitate more reliable and generalizable models for future clinical practice.
Collapse
|
13
|
A comparative study of the neuropsychiatric and neurocognitive phenotype in two microdeletion syndromes: Velocardiofacial (22q11.2 deletion) and Williams (7q11.23 deletion) syndromes. Eur Psychiatry 2020; 29:203-10. [DOI: 10.1016/j.eurpsy.2013.07.001] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/11/2013] [Revised: 07/05/2013] [Accepted: 07/09/2013] [Indexed: 02/02/2023] Open
Abstract
AbstractPurpose:22q11.2 deletion syndrome (22q11.2DS) and Williams syndrome (WS) are common neurogenetic microdeletion syndromes. The aim of the present study was to compare the neuropsychiatric and neurocognitive phenotypes of 22q11.2DS and WS.Methods:Forty-five individuals with 22q11.2DS, 24 with WS, 22 with idiopathic developmental disability (DD) and 22 typically developing (TD) controls were compared for the rates of psychiatric disorders as well as cognitive executive and visuospatial functions.Results:We found that while anxiety, mood and disruptive disorders had an equally high prevalence among individuals with 22q11.2DS, WS and DDs, the 22q11.2DS group had the highest rates of psychotic disorders and the WS group had the highest rates of specific phobia. We also found that the WS group demonstrated more severe impairments in both executive and visuospatial functions than the other groups. WS and 22q11.2DS subjects had worse Performance-IQ than Verbal-IQ, a feature typical of non-verbal learning disorders.Conclusion:These findings offer a wide perspective on unique versus common phenotypes in 22q11.2DS and WS.
Collapse
|
14
|
Systematic review and multi-modal meta-analysis of magnetic resonance imaging findings in 22q11.2 deletion syndrome: Is more evidence needed? Neurosci Biobehav Rev 2019; 107:143-153. [DOI: 10.1016/j.neubiorev.2019.09.004] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2018] [Revised: 08/07/2019] [Accepted: 09/02/2019] [Indexed: 11/20/2022]
|
15
|
Pitzianti M, Pontillo M, Vicari S, Armando M, Pasini A. 22q11 microdeletion syndrome and ultra-high risk for psychosis: The role of neurological soft signs as an independent marker of vulnerability for psychosis. Early Interv Psychiatry 2019; 13:1191-1198. [PMID: 30478947 DOI: 10.1111/eip.12754] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2018] [Revised: 10/03/2018] [Accepted: 10/16/2018] [Indexed: 11/28/2022]
Abstract
AIM 22q11 microdeletion syndrome has an increased risk for psychosis, similar to subjects at ultra-high risk for psychosis. Neurological soft signs are considered an endophenotype of psychotic disorders and a marker of vulnerability to Schizophrenia, consisting of overflow movements, dysrhythmia and speed of timed activities. To date, there are no studies that have evaluated the presence of the neurological soft signs in subjects with 22q11 microdeletion syndrome and there are a few studies that have analysed this issue in subjects at ultra-high risk. METHODS We sought to measure neurological soft signs in these two conditions, compared to healthy controls and to analyse the possible correlation between neurological soft signs and positive/negative symptoms both in 22q11 microdeletion syndrome and ultra-high-risk groups. 54 drug-naive patients (29 with 22q11 microdeletion syndrome and 25 at ultra-high risk for psychosis) and 25 healthy controls were evaluated for neurological soft signs. RESULTS Both clinical groups showed a greater number of neurological soft signs compared to healthy control, although the two clinical groups did not differ for the number of neurological soft signs. Positive correlation between speed of timed activities and negative symptoms was found in subjects at ultra-high risk. CONCLUSION Neurological soft signs could represent a marker of atypical neurodevelopment in the two populations examined. Since we did not found a strong correlation between neurological soft signs and positive/negative symptoms, we suggest that neurological soft signs could be indicators of vulnerability to psychosis independent from the psychopathology.
Collapse
Affiliation(s)
- Mariabernarda Pitzianti
- Department of Systems Medicine, Unit of Child Neurology and Psychiatry, "Tor Vergata" University of Rome, Rome, Italy.,Department of neuroscience, USL Umbria 2, Terni, Italy
| | - Maria Pontillo
- Department of Neuroscience, Unit of Child Neuropsychiatry, Children's Hospital Bambino Gesù, IRCCS, Rome, Italy
| | - Stefano Vicari
- Department of Neuroscience, Unit of Child Neuropsychiatry, Children's Hospital Bambino Gesù, IRCCS, Rome, Italy
| | - Marco Armando
- Department of Neuroscience, Unit of Child Neuropsychiatry, Children's Hospital Bambino Gesù, IRCCS, Rome, Italy
| | - Augusto Pasini
- Department of Systems Medicine, Unit of Child Neurology and Psychiatry, "Tor Vergata" University of Rome, Rome, Italy.,Department of neuroscience, USL Umbria 2, Terni, Italy
| |
Collapse
|
16
|
Squarcina L, Dagnew TM, Rivolta MW, Bellani M, Sassi R, Brambilla P. Automated cortical thickness and skewness feature selection in bipolar disorder using a semi-supervised learning method. J Affect Disord 2019; 256:416-423. [PMID: 31229930 DOI: 10.1016/j.jad.2019.06.019] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/30/2019] [Revised: 03/26/2019] [Accepted: 06/07/2019] [Indexed: 01/10/2023]
Abstract
BACKGROUND Bipolar disorder (BD) broadly affects brain structure, in particular areas involved in emotion processing and cognition. In the last years, the psychiatric field's interest in machine learning approaches has been steadily growing, thanks to the potentiality of automatically discriminating patients from healthy controls. METHODS In this work, we employed cortical thickness of 58 regions of interest obtained from magnetic resonance imaging scans of 41 BD patients and 34 healthy controls, to automatically identify the regions which are mostly involved with the disease. We used a semi-supervised method, addressing the criticisms on supervised methods, related to the fact that the diagnosis is not unaffected by uncertainty. RESULTS Our results confirm findings in previous studies, with a classification accuracy of about 75% when mean thickness and skewness of up to five regions are considered. We obtained that the parietal lobe and some areas in the temporal sulcus were the regions which were the most involved with BD. LIMITATIONS The major limitation of our work is the limited size or our dataset, but in line with other recent machine learning works in the field. Moreover, we considered chronic patients, whose brain characteristics may thus be affected. CONCLUSIONS The automatic selection of the brain regions most involved in BD may be of great importance when dealing with the pathogenesis of the disorder. Our method selected regions which are known to be involved with BD, indicating that damage to the identified areas can be considered as a marker of disease.
Collapse
Affiliation(s)
- L Squarcina
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, University of Milan, Milan, Italy.
| | - T M Dagnew
- Department of Computer Science, University of Milan, Milan, Italy.
| | - M W Rivolta
- Department of Computer Science, University of Milan, Milan, Italy
| | - M Bellani
- Department of Neurosciences, Biomedicine and Movement Sciences, Section of Psychiatry, University of Verona, Italy
| | - R Sassi
- Department of Computer Science, University of Milan, Milan, Italy
| | - P Brambilla
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, University of Milan, Milan, Italy; Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| |
Collapse
|
17
|
Zhuo C, Xu Y, Zhang L, Jing R, Zhou C. The Effect of Dopamine Antagonist Treatment on Auditory Verbal Hallucinations in Healthy Individuals Is Clearly Influenced by COMT Genotype and Accompanied by Corresponding Brain Structural and Functional Alterations: An Artificially Controlled Pilot Study. Front Genet 2019; 10:92. [PMID: 30894870 PMCID: PMC6414462 DOI: 10.3389/fgene.2019.00092] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2018] [Accepted: 01/29/2019] [Indexed: 11/29/2022] Open
Abstract
Few studies have been conducted to explore the influence of the catechol-o-methyltransferase (COMT) genotype on the severity of and treatment efficacy on auditory verbal hallucination (AVH) symptoms in healthy individuals with AVHs (Hi-AVHs). We hypothesized that the efficacy of dopamine antagonist treatment on AVHs in Hi-AVHs may be influenced by their COMT genotype and may be accompanied by corresponding brain alterations. To preliminarily investigate and test our hypothesis in an artificially controlled pilot study, we enrolled 42 Hi-AVHs as subjects and used magnetic resonance imaging and genetic methods to explore the basis brain features to investigate whether the efficacy of dopamine antagonist treatment on AVHs in Hi-AVH subjects was influenced by their COMT genotype or not. We found that COMT-met genotype subjects’ treatment response was better than that of COMT-val subjects. Although COMT-met genotype subjects demonstrated an increase in global functional connectivity density (gFCD) but no difference on gray matter volume (GMV) compared to COMT-val genotype subjects at baseline, notably, we found that both groups demonstrated gFCD and GMV reduction after treatment, but the reduction was more widespread in COMT-met genotype subjects than in COMT-val genotype subjects. This is the first study to report that Hi-AVH subjects’ baseline brain functional features are influenced by their COMT genotypes and that the COMT-met genotype subjects exhibit better responses to dopamine antagonists but have more widespread GMV and gFCD reduction than subjects with the COMT-val genotype. Despite several limitations, these findings may provide auxiliary information to further explain the mechanisms of AVHs and provide a clue for scholars to further explore specific treatment targets for AVHs in Hi-AVH subjects or in schizophrenia patients.
Collapse
Affiliation(s)
- Chuanjun Zhuo
- Department of Psychiatric-Neuroimaging-Genetics and Comorbidity Laboratory (PNGC-Lab), Tianjin Mental Health Centre, Mental Health Teaching Hospital of Tianjin Medical University, Tianjin Anding Hospital, Tianjin, China.,Department of Psychiatry, College of Basic Medical Science, Tianjin Medical University, Tianjin, China.,Department of Psychiatry, First Hospital/First Clinical Medical College of Shanxi Medical University, Taiyuan, China.,MDT Center for Cognitive Impairment and Sleep Disorders, First Hospital of Shanxi Medical University, Taiyuan, China.,Department of Psychiatry, Institute of Mental Health, Jining Medical University, Jining, China
| | - Yong Xu
- Department of Psychiatry, First Hospital/First Clinical Medical College of Shanxi Medical University, Taiyuan, China.,MDT Center for Cognitive Impairment and Sleep Disorders, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Li Zhang
- GHM Institute of CNS Regeneration, Jinan University, Guangzhou, China
| | - Rixing Jing
- Department of Pattern Recognition, China National Key Laboratory, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,Department of Pattern Recognition, University of Chinese Academy of Sciences, Beijing, China
| | - Chunhua Zhou
- Department of Pharmacy, The First Hospital of Hebei Medical University, Shijiazhuang, China
| |
Collapse
|
18
|
Padula MC, Schaer M, Armando M, Sandini C, Zöller D, Scariati E, Schneider M, Eliez S. Cortical morphology development in patients with 22q11.2 deletion syndrome at ultra-high risk of psychosis. Psychol Med 2018; 48:2375-2383. [PMID: 29338796 DOI: 10.1017/s0033291717003920] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
BACKGROUND Patients with 22q11.2 deletion syndrome (22q11DS) present a high risk of developing psychosis. While clinical and cognitive predictors for the conversion towards a full-blown psychotic disorder are well defined and largely used in practice, neural biomarkers do not yet exist. However, a number of investigations indicated an association between abnormalities in cortical morphology and higher symptoms severities in patients with 22q11DS. Nevertheless, few studies included homogeneous groups of patients differing in their psychotic symptoms profile. METHODS In this study, we included 22 patients meeting the criteria for an ultra-high-risk (UHR) psychotic state and 22 age-, gender- and IQ-matched non-UHR patients. Measures of cortical morphology, including cortical thickness, volume, surface area and gyrification, were compared between the two groups using mass-univariate and multivariate comparisons. Furthermore, the development of these measures was tested in the two groups using a mixed-model approach. RESULTS Our results showed differences in cortical volume and surface area in UHR patients compared with non-UHR. In particular, we found a positive association between surface area and the rate of change of global functioning, suggesting that higher surface area is predictive of improved functioning with age. We also observed accelerated cortical thinning during adolescence in UHR patients with 22q11DS. CONCLUSIONS These results, although preliminary, suggest that alterations in cortical volume and surface area as well as altered development of cortical thickness may be associated to a greater probability to develop psychosis in 22q11DS.
Collapse
Affiliation(s)
- Maria Carmela Padula
- Developmental Imaging and Psychopathology Laboratory,Department of Psychiatry,University of Geneva School of Medicine,Geneva,Switzerland
| | - Marie Schaer
- Developmental Imaging and Psychopathology Laboratory,Department of Psychiatry,University of Geneva School of Medicine,Geneva,Switzerland
| | - Marco Armando
- Developmental Imaging and Psychopathology Laboratory,Department of Psychiatry,University of Geneva School of Medicine,Geneva,Switzerland
| | - Corrado Sandini
- Developmental Imaging and Psychopathology Laboratory,Department of Psychiatry,University of Geneva School of Medicine,Geneva,Switzerland
| | - Daniela Zöller
- Developmental Imaging and Psychopathology Laboratory,Department of Psychiatry,University of Geneva School of Medicine,Geneva,Switzerland
| | - Elisa Scariati
- Developmental Imaging and Psychopathology Laboratory,Department of Psychiatry,University of Geneva School of Medicine,Geneva,Switzerland
| | - Maude Schneider
- Developmental Imaging and Psychopathology Laboratory,Department of Psychiatry,University of Geneva School of Medicine,Geneva,Switzerland
| | - Stephan Eliez
- Developmental Imaging and Psychopathology Laboratory,Department of Psychiatry,University of Geneva School of Medicine,Geneva,Switzerland
| |
Collapse
|
19
|
Sandini C, Scariati E, Padula MC, Schneider M, Schaer M, Van De Ville D, Eliez S. Cortical Dysconnectivity Measured by Structural Covariance Is Associated With the Presence of Psychotic Symptoms in 22q11.2 Deletion Syndrome. BIOLOGICAL PSYCHIATRY: COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2018; 3:433-442. [PMID: 29735153 DOI: 10.1016/j.bpsc.2017.04.008] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/07/2017] [Accepted: 04/24/2017] [Indexed: 01/08/2023]
Abstract
BACKGROUND 22q11.2 deletion syndrome (22q11DS) is the third-largest known genetic risk factor for the development of psychosis. Dysconnectivity has consistently been implicated in the physiopathology of psychosis. Structural covariance of cortical morphology is a method of exploring connectivity among brain regions that to date has not been employed in 22q11DS. METHODS In the present study we employed structural covariance of cortical thickness to explore connectivity alterations in a group of 108 patients with 22q11DS compared with 96 control subjects. We subsequently divided patients into two subgroups of 31 subjects each according to the presence of attenuated psychotic symptoms. FreeSurfer software was used to obtain the mean cortical thickness in 148 brain regions from T1-weighted 3T images. For each population we reconstructed a brain graph using Pearson correlation between the average thickness of each couple of brain regions, which we characterized in terms of mean correlation strength and in terms of network architecture using graph theory. RESULTS Patients with 22q11DS presented increased mean correlation strength, but there was no difference in global architecture compared with control subjects. However, symptomatic patients presented increased mean correlation strength coupled with increased segregation and decreased integration compared with both control subjects and nonsymptomatic patients. They also presented increased centrality for a cluster of anterior cingulate and dorsomedial prefrontal regions. CONCLUSIONS These results confirm the importance of cortical dysconnectivity in the physiopathology of psychosis. Moreover they support the significance of aberrant anterior cingulate connectivity.
Collapse
Affiliation(s)
- Corrado Sandini
- Developmental Imaging and Psychopathology Laboratory, University of Geneva School of Medicine, Switzerland.
| | - Elisa Scariati
- Developmental Imaging and Psychopathology Laboratory, University of Geneva School of Medicine, Switzerland
| | - Maria Carmela Padula
- Developmental Imaging and Psychopathology Laboratory, University of Geneva School of Medicine, Switzerland
| | - Maude Schneider
- Developmental Imaging and Psychopathology Laboratory, University of Geneva School of Medicine, Switzerland; Center for Contextual Psychiatry, Research Group Psychiatry, Department of Neuroscience, KU Leuven, Leuven, Belgium
| | - Marie Schaer
- Developmental Imaging and Psychopathology Laboratory, University of Geneva School of Medicine, Switzerland; Stanford Cognitive and Systems Neuroscience Laboratory, Stanford University School of Medicine, Stanford, California
| | - Dimitri Van De Ville
- Department of Radiology and Medical Informatics, University of Geneva, Switzerland; Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Stephan Eliez
- Developmental Imaging and Psychopathology Laboratory, University of Geneva School of Medicine, Switzerland; Department of Genetic Medicine and Development, University of Geneva School of Medicine, Switzerland
| |
Collapse
|
20
|
Abstract
Recent large-scale genomic studies have confirmed that schizophrenia is a polygenic syndrome and have implicated a number of biological pathways in its aetiology. Both common variants individually of small effect and rarer but more penetrant genetic variants have been shown to play a role in the pathogenesis of the disorder. No simple Mendelian forms of the condition have been identified, but progress has been made in stratifying risk on the basis of the polygenic burden of common variants individually of small effect, and the contribution of rarer variants of larger effect such as Copy Number Variants (CNVs). Pathway analysis of risk-associated variants has begun to identify specific biological processes implicated in risk for the disorder, including elements of the glutamatergic NMDA receptor complex and post synaptic density, voltage-gated calcium channels, targets of the Fragile X Mental Retardation Protein (FMRP targets) and immune pathways. Genetic studies have also been used to drive genomic imaging approaches to the investigation of brain markers associated with risk for the disorder. Genomic imaging approaches have been applied both to investigate the effect of polygenic risk and to study the impact of individual higher-penetrance variants such as CNVs. Both genomic and genomic imaging approaches offer potential for the stratification of patients and at-risk groups and the development of better biomarkers of risk and treatment response; however, further research is needed to integrate this work and realise the full potential of these approaches.
Collapse
|
21
|
Padula MC, Schaer M, Scariati E, Mutlu AK, Zöller D, Schneider M, Eliez S. Quantifying indices of short- and long-range white matter connectivity at each cortical vertex. PLoS One 2017; 12:e0187493. [PMID: 29141024 PMCID: PMC5687731 DOI: 10.1371/journal.pone.0187493] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2017] [Accepted: 10/20/2017] [Indexed: 01/27/2023] Open
Abstract
Several neurodevelopmental diseases are characterized by impairments in cortical morphology along with altered white matter connectivity. However, the relationship between these two measures is not yet clear. In this study, we propose a novel methodology to compute and display metrics of white matter connectivity at each cortical point. After co-registering the extremities of the tractography streamlines with the cortical surface, we computed two measures of connectivity at each cortical vertex: the mean tracts’ length, and the proportion of short- and long-range connections. The proposed measures were tested in a clinical sample of 62 patients with 22q11.2 deletion syndrome (22q11DS) and 57 typically developing individuals. Using these novel measures, we achieved a fine-grained visualization of the white matter connectivity patterns at each vertex of the cortical surface. We observed an intriguing pattern of both increased and decreased short- and long-range connectivity in 22q11DS, that provides novel information about the nature and topology of white matter alterations in the syndrome. We argue that the method presented in this study opens avenues for additional analyses of the relationship between cortical properties and patterns of underlying structural connectivity, which will help clarifying the intrinsic mechanisms that lead to altered brain structure in neurodevelopmental disorders.
Collapse
Affiliation(s)
- Maria Carmela Padula
- Developmental Imaging and Psychopathology Laboratory, University of Geneva School of medicine, Geneva, Switzerland
- * E-mail:
| | - Marie Schaer
- Developmental Imaging and Psychopathology Laboratory, University of Geneva School of medicine, Geneva, Switzerland
| | - Elisa Scariati
- Developmental Imaging and Psychopathology Laboratory, University of Geneva School of medicine, Geneva, Switzerland
| | - A. Kadir Mutlu
- Neuro-Electronics Research Flanders, Leuven, The Netherlands
| | - Daniela Zöller
- Developmental Imaging and Psychopathology Laboratory, University of Geneva School of medicine, Geneva, Switzerland
- Medical Image Processing Laboratory, Institute of Bioengineering, Ecole Polytechnique Fédérale Lausanne (EPFL), Lausanne, Switzerland
| | - Maude Schneider
- Developmental Imaging and Psychopathology Laboratory, University of Geneva School of medicine, Geneva, Switzerland
| | - Stephan Eliez
- Developmental Imaging and Psychopathology Laboratory, University of Geneva School of medicine, Geneva, Switzerland
- Department of Genetic Medicine and Development, University of Geneva School of medicine, Geneva, Switzerland
| |
Collapse
|
22
|
Kesler SR, Rao A, Blayney DW, Oakley-Girvan IA, Karuturi M, Palesh O. Predicting Long-Term Cognitive Outcome Following Breast Cancer with Pre-Treatment Resting State fMRI and Random Forest Machine Learning. Front Hum Neurosci 2017; 11:555. [PMID: 29187817 PMCID: PMC5694825 DOI: 10.3389/fnhum.2017.00555] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2017] [Accepted: 11/01/2017] [Indexed: 01/09/2023] Open
Abstract
We aimed to determine if resting state functional magnetic resonance imaging (fMRI) acquired at pre-treatment baseline could accurately predict breast cancer-related cognitive impairment at long-term follow-up. We evaluated 31 patients with breast cancer (age 34–65) prior to any treatment, post-chemotherapy and 1 year later. Cognitive testing scores were normalized based on data obtained from 43 healthy female controls and then used to categorize patients as impaired or not based on longitudinal changes. We measured clustering coefficient, a measure of local connectivity, by applying graph theory to baseline resting state fMRI and entered these metrics along with relevant patient-related and medical variables into random forest classification. Incidence of cognitive impairment at 1 year follow-up was 55% and was predicted by classification algorithms with up to 100% accuracy (p < 0.0001). The neuroimaging-based model was significantly more accurate than a model involving patient-related and medical variables (p = 0.005). Hub regions belonging to several distinct functional networks were the most important predictors of cognitive outcome. Characteristics of these hubs indicated potential spread of brain injury from default mode to other networks over time. These findings suggest that resting state fMRI is a promising tool for predicting future cognitive impairment associated with breast cancer. This information could inform treatment decision making by identifying patients at highest risk for long-term cognitive impairment.
Collapse
Affiliation(s)
- Shelli R Kesler
- Department of Neuro-Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Arvind Rao
- Department of Bioinformatics and Computational Biology, University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Douglas W Blayney
- Division of Medical Oncology, School of Medicine, Stanford University, Palo Alto, CA, United States
| | | | - Meghan Karuturi
- Department of Breast Medical Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Oxana Palesh
- Department of Psychiatry and Behavioral Sciences, School of Medicine, Stanford University, Palo Alto, CA, United States
| |
Collapse
|
23
|
Sanders AFP, Hobbs DA, Stephenson DD, Laird RD, Beaton EA. Working Memory Impairments in Chromosome 22q11.2 Deletion Syndrome: The Roles of Anxiety and Stress Physiology. J Autism Dev Disord 2017; 47:992-1005. [PMID: 28083777 DOI: 10.1007/s10803-016-3011-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
Stress and anxiety have a negative impact on working memory systems by competing for executive resources and attention. Broad memory deficits, anxiety, and elevated stress have been reported in individuals with chromosome 22q11.2 deletion syndrome (22q11.2DS). We investigated anxiety and physiological stress reactivity in relation to visuospatial working memory impairments in 20 children with 22q11.2DS and 32 typically developing (TD) children ages 7 to 16. Children with 22q11.2DS demonstrated poorer working memory, reduced post-stress respiratory sinus arrhythmia recovery, and overall increased levels of cortisol in comparison to TD children. Anxiety, but not physiological stress responsivity, mediated the relationship between 22q11.2DS diagnosis and visuospatial working memory impairment. Findings indicate that anxiety exacerbates impaired working memory in children with 22q11.2DS.
Collapse
Affiliation(s)
- Ashley F P Sanders
- Department of Psychology, University of New Orleans, 2000 Lakeshore Drive, New Orleans, LA, 70148, USA
| | - Diana A Hobbs
- Department of Psychology, University of New Orleans, 2000 Lakeshore Drive, New Orleans, LA, 70148, USA
| | - David D Stephenson
- Department of Psychology, University of New Orleans, 2000 Lakeshore Drive, New Orleans, LA, 70148, USA
| | - Robert D Laird
- Department of Psychology, University of New Orleans, 2000 Lakeshore Drive, New Orleans, LA, 70148, USA
| | - Elliott A Beaton
- Department of Psychology, University of New Orleans, 2000 Lakeshore Drive, New Orleans, LA, 70148, USA.
| |
Collapse
|
24
|
Padula MC, Scariati E, Schaer M, Sandini C, Ottet MC, Schneider M, Van De Ville D, Eliez S. Altered structural network architecture is predictive of the presence of psychotic symptoms in patients with 22q11.2 deletion syndrome. NEUROIMAGE-CLINICAL 2017; 16:142-150. [PMID: 28794975 PMCID: PMC5540832 DOI: 10.1016/j.nicl.2017.07.023] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/27/2017] [Revised: 07/13/2017] [Accepted: 07/24/2017] [Indexed: 11/10/2022]
Abstract
22q11.2 deletion syndrome (22q11DS) represents a homogeneous model of schizophrenia particularly suitable for the search of neural biomarkers of psychosis. Impairments in structural connectivity related to the presence of psychotic symptoms have been reported in patients with 22q11DS. However, the relationships between connectivity changes in patients with different symptomatic profiles are still largely unknown and warrant further investigations. In this study, we used structural connectivity to discriminate patients with 22q11DS with (N = 31) and without (N = 31) attenuated positive psychotic symptoms. Different structural connectivity measures were used, including the number of streamlines connecting pairs of brain regions, graph theoretical measures, and diffusion measures. We used univariate group comparisons as well as predictive multivariate approaches. The univariate comparison of connectivity measures between patients with or without attenuated positive psychotic symptoms did not give significant results. However, the multivariate prediction revealed that altered structural network architecture discriminates patient subtypes (accuracy = 67.7%). Among the regions contributing to the classification we found the anterior cingulate cortex, which is known to be associated to the presence of psychotic symptoms in patients with 22q11DS. Furthermore, a significant discrimination (accuracy = 64%) was obtained with fractional anisotropy and radial diffusivity in the left inferior longitudinal fasciculus and the right cingulate gyrus. Our results point to alterations in structural network architecture and white matter microstructure in patients with 22q11DS with attenuated positive symptoms, mainly involving connections of the limbic system. These alterations may therefore represent a potential biomarker for an increased risk of psychosis that should be further tested in longitudinal studies. Altered network architecture discriminates psychotic patients with 22q11DS; Altered diffusivity measures are evident in psychotic patients with 22q11DS; White matter alterations associated to psychosis are located in limbic regions.
Collapse
Affiliation(s)
- Maria C Padula
- Developmental Imaging and Psychopathology Laboratory, Department of Psychiatry, University of Geneva School of medicine, Geneva, Switzerland
| | - Elisa Scariati
- Developmental Imaging and Psychopathology Laboratory, Department of Psychiatry, University of Geneva School of medicine, Geneva, Switzerland
| | - Marie Schaer
- Developmental Imaging and Psychopathology Laboratory, Department of Psychiatry, University of Geneva School of medicine, Geneva, Switzerland
| | - Corrado Sandini
- Developmental Imaging and Psychopathology Laboratory, Department of Psychiatry, University of Geneva School of medicine, Geneva, Switzerland
| | - Marie Christine Ottet
- Developmental Imaging and Psychopathology Laboratory, Department of Psychiatry, University of Geneva School of medicine, Geneva, Switzerland
| | - Maude Schneider
- Developmental Imaging and Psychopathology Laboratory, Department of Psychiatry, University of Geneva School of medicine, Geneva, Switzerland
| | - Dimitri Van De Ville
- Medical Image Processing Lab, Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.,Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland
| | - Stephan Eliez
- Developmental Imaging and Psychopathology Laboratory, Department of Psychiatry, University of Geneva School of medicine, Geneva, Switzerland.,Department of Genetic Medicine and Development, University of Geneva School of medicine, Geneva, Switzerland
| |
Collapse
|
25
|
Tylee DS, Kikinis Z, Quinn TP, Antshel KM, Fremont W, Tahir MA, Zhu A, Gong X, Glatt SJ, Coman IL, Shenton ME, Kates WR, Makris N. Machine-learning classification of 22q11.2 deletion syndrome: A diffusion tensor imaging study. NEUROIMAGE-CLINICAL 2017; 15:832-842. [PMID: 28761808 PMCID: PMC5522376 DOI: 10.1016/j.nicl.2017.04.029] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/26/2017] [Revised: 03/27/2017] [Accepted: 04/04/2017] [Indexed: 11/27/2022]
Abstract
Chromosome 22q11.2 deletion syndrome (22q11.2DS) is a genetic neurodevelopmental syndrome that has been studied intensively in order to understand relationships between the genetic microdeletion, brain development, cognitive function, and the emergence of psychiatric symptoms. White matter microstructural abnormalities identified using diffusion tensor imaging methods have been reported to affect a variety of neuroanatomical tracts in 22q11.2DS. In the present study, we sought to combine two discovery-based approaches: (1) white matter query language was used to parcellate the brain's white matter into tracts connecting pairs of 34, bilateral cortical regions and (2) the diffusion imaging characteristics of the resulting tracts were analyzed using a machine-learning method called support vector machine in order to optimize the selection of a set of imaging features that maximally discriminated 22q11.2DS and comparison subjects. With this unique approach, we both confirmed previously-recognized 22q11.2DS-related abnormalities in the inferior longitudinal fasciculus (ILF), and identified, for the first time, 22q11.2DS-related anomalies in the middle longitudinal fascicle and the extreme capsule, which may have been overlooked in previous, hypothesis-guided studies. We further observed that, in participants with 22q11.2DS, ILF metrics were significantly associated with positive prodromal symptoms of psychosis.
Collapse
Key Words
- (-fp), fronto-parietal aspect
- (-to), temporo-occipital aspect
- (-tp), temporo-parietal aspect
- (22q11.2DS), 22q11.2 deletion syndrome
- (AD), axial diffusivity
- (DTI), diffusion tensor imaging
- (DWI), diffusion weighted image
- (EmC), extreme capsule
- (FA), fractional anisotropy
- (FOV), field of view
- (GDS), Gordon Diagnostic Systems
- (ILF), inferior longitudinal fasciculus
- (MdLF), middle longitudinal fascicle
- (RD), radial diffusivity
- (ROI), region of interest
- (SIPS), Structured Interview for Prodromal Syndromes
- (SRS), Social Responsiveness Scale
- (STG), superior temporal gyrus
- (SVM), support vector machine
- (UKF), Unscented Kalman Filter
- (WAIS-III), Wechsler Adult Intelligence Scale – 3rd edition
- (WMQL), white matter query language
- (dTP), dorsal temporal pole
- 22q11.2 deletion syndrome
- Callosal asymmetry
- Diffusion tensor imaging
- Extreme capsule
- Inferior longitudinal fasciculus
- Machine-learning
- Middle longitudinal fascicle
- Support vector machine
- Velocardiofacial syndrome
- White matter query language
Collapse
Affiliation(s)
- Daniel S Tylee
- Department of Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, NY, USA; Department of Psychiatry and Behavioral Sciences; SUNY Upstate Medical University, Syracuse, NY, USA
| | - Zora Kikinis
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
| | - Thomas P Quinn
- Bioinformatics Core Research Group, Deakin University, Geelong, Victoria, Australia
| | | | - Wanda Fremont
- Department of Psychiatry and Behavioral Sciences; SUNY Upstate Medical University, Syracuse, NY, USA.
| | - Muhammad A Tahir
- Department of Psychiatry and Behavioral Sciences; SUNY Upstate Medical University, Syracuse, NY, USA
| | - Anni Zhu
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Xue Gong
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Stephen J Glatt
- Department of Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, NY, USA; Department of Psychiatry and Behavioral Sciences; SUNY Upstate Medical University, Syracuse, NY, USA.
| | - Ioana L Coman
- Department of Psychiatry and Behavioral Sciences; SUNY Upstate Medical University, Syracuse, NY, USA.
| | - Martha E Shenton
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; VA Boston Healthcare System, Harvard Medical School, Brockton, MA, USA.
| | - Wendy R Kates
- Department of Psychiatry and Behavioral Sciences; SUNY Upstate Medical University, Syracuse, NY, USA.
| | - Nikos Makris
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
| |
Collapse
|
26
|
Adolescence is the starting point of sex-dichotomous COMT genetic effects. Transl Psychiatry 2017; 7:e1141. [PMID: 28556830 PMCID: PMC5584523 DOI: 10.1038/tp.2017.109] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2017] [Revised: 02/28/2017] [Accepted: 04/11/2017] [Indexed: 01/09/2023] Open
Abstract
The catechol-o-methyltransferase (COMT) genetic variations produce pleiotropic behavioral/neuroanatomical effects. Some of these effects may vary among sexes. However, the developmental trajectories of COMT-by-sex interactions are unclear. Here we found that extreme COMT reduction, in both humans (22q11.2 deletion syndrome COMT Met) and mice (COMT-/-), was associated to cortical thinning only after puberty and only in females. Molecular biomarkers, such as tyrosine hydroxylase, Akt and neuronal/cellular counting, confirmed that COMT-by-sex divergent effects started to appear at the cortical level during puberty. These biochemical differences were absent in infancy. Finally, developmental cognitive assessment in 22q11DS and COMT knockout mice established that COMT-by-sex-dichotomous effects in executive functions were already apparent in adolescence. These findings uncover that genetic variations severely reducing COMT result in detrimental cortical and cognitive development selectively in females after their sexual maturity. This highlights the importance of taking into account the combined effect of genetics, sex and developmental stage.
Collapse
|
27
|
Thompson CA, Karelis J, Middleton FA, Gentile K, Coman IL, Radoeva PD, Mehta R, Fremont WP, Antshel KM, Faraone SV, Kates WR. Associations between neurodevelopmental genes, neuroanatomy, and ultra high risk symptoms of psychosis in 22q11.2 deletion syndrome. Am J Med Genet B Neuropsychiatr Genet 2017; 174:295-314. [PMID: 28139055 DOI: 10.1002/ajmg.b.32515] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/14/2016] [Accepted: 11/07/2016] [Indexed: 11/06/2022]
Abstract
22q11.2 deletion syndrome is a neurogenetic disorder resulting in the deletion of over 40 genes. Up to 40% of individuals with 22q11.2DS develop schizophrenia, though little is known about the underlying mechanisms. We hypothesized that allelic variation in functional polymorphisms in seven genes unique to the deleted region would affect lobar brain volumes, which would predict risk for psychosis in youth with 22q11.2DS. Participants included 56 individuals (30 males) with 22q11.2DS. Anatomic MR images were collected and processed using Freesurfer. Participants were genotyped for 10 SNPs in the COMT, DGCR8, GNB1L, PIK4CA, PRODH, RTN4R, and ZDHHC8 genes. All subjects were assessed for ultra high risk symptoms of psychosis. Allelic variation of the rs701428 SNP of RTN4R was significantly associated with volumetric differences in gray matter of the lingual gyrus and cuneus of the occipital lobe. Moreover, occipital gray matter volumes were robustly associated with ultra high risk symptoms of psychosis in the presence of the G allele of rs701428. Our results suggest that RTN4R, a relatively under-studied gene at the 22q11 locus, constitutes a susceptibility gene for psychosis in individuals with this syndrome through its alteration of the architecture of the brain. © 2017 Wiley Periodicals, Inc.
Collapse
Affiliation(s)
- Carlie A Thompson
- Department of Psychiatry and Behavioral Sciences, SUNY Upstate Medical University, Syracuse, New York
| | - Jason Karelis
- Department of Psychiatry and Behavioral Sciences, SUNY Upstate Medical University, Syracuse, New York
| | - Frank A Middleton
- Department of Psychiatry and Behavioral Sciences, SUNY Upstate Medical University, Syracuse, New York.,Department of Neuroscience, SUNY Upstate Medical University, Syracuse, New York
| | - Karen Gentile
- Department of Neuroscience, SUNY Upstate Medical University, Syracuse, New York
| | - Ioana L Coman
- Department of Computer Science, SUNY Oswego, Oswego, New York
| | - Petya D Radoeva
- Department of Psychiatry, University of Washington, Seattle, Washington
| | - Rashi Mehta
- Department of Radiology, SUNY Upstate Medical University, Syracuse, New York
| | - Wanda P Fremont
- Department of Psychiatry and Behavioral Sciences, SUNY Upstate Medical University, Syracuse, New York
| | - Kevin M Antshel
- Department of Psychiatry and Behavioral Sciences, SUNY Upstate Medical University, Syracuse, New York.,Department of Psychology, Syracuse University, Syracuse, New York
| | - Stephen V Faraone
- Department of Psychiatry and Behavioral Sciences, SUNY Upstate Medical University, Syracuse, New York
| | - Wendy R Kates
- Department of Psychiatry and Behavioral Sciences, SUNY Upstate Medical University, Syracuse, New York
| |
Collapse
|
28
|
Radoeva PD, Bansal R, Antshel KM, Fremont W, Peterson BS, Kates WR. Longitudinal study of cerebral surface morphology in youth with 22q11.2 deletion syndrome, and association with positive symptoms of psychosis. J Child Psychol Psychiatry 2017; 58:305-314. [PMID: 27786353 PMCID: PMC5340081 DOI: 10.1111/jcpp.12657] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 09/16/2016] [Indexed: 12/13/2022]
Abstract
BACKGROUND 22q11.2 deletion syndrome (22q11DS) is a genetic disorder that greatly increases risk of developing schizophrenia. We previously characterized cerebral surface morphology trajectories from late childhood to mid adolescence in a cohort of youth with 22q11DS. Herein, we extend the study period into early adulthood, and describe further the trajectories associated with severe psychiatric symptoms in this cohort. METHODS Participants included 76 youth with 22q11DS and 30 unaffected siblings, assessed at three timepoints, during which high resolution, anatomic magnetic resonance images were acquired. High-dimensional, nonlinear warping algorithms were applied to images in order to derive characteristics of cerebral surface morphology for each participant at each timepoint. Repeated-measures, linear regressions using a mixed model were conducted, while covarying for age and sex. RESULTS Alterations in cerebral surface morphology during late adolescence/early adulthood in individuals with 22q11DS were observed in the lateral frontal, orbitofrontal, temporal, parietal, occipital, and cerebellar regions. An Age x Diagnosis interaction revealed that relative to unaffected siblings, individuals with 22q11DS showed age-related surface protrusions in the prefrontal cortex (which remained stable or increased during early adulthood), and surface indentations in posterior regions (which seemed to level off during late adolescence). Symptoms of psychosis were associated with a trajectory of surface indentations in the orbitofrontal and parietal regions. CONCLUSIONS These results advance our understanding of cerebral maturation in individuals with 22q11DS, and provide clinically relevant information about the psychiatric phenotype associated with the longitudinal trajectory of cortical surface morphology in youth with this genetic syndrome.
Collapse
Affiliation(s)
- Petya D. Radoeva
- Department of Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, New York, USA
| | - Ravi Bansal
- Children’s Hospital Los Angeles and the Keck School of Medicine at the University of Southern California, Los Angeles, California, USA
| | - Kevin M. Antshel
- Department of Psychology, Syracuse University, Syracuse, New York, USA
| | - Wanda Fremont
- Department of Psychiatry and Behavioral Sciences, SUNY Upstate Medical University, Syracuse, New York, USA
| | - Bradley S. Peterson
- Children’s Hospital Los Angeles and the Keck School of Medicine at the University of Southern California, Los Angeles, California, USA
| | - Wendy R. Kates
- Department of Psychiatry and Behavioral Sciences, SUNY Upstate Medical University, Syracuse, New York, USA
| |
Collapse
|
29
|
Berhanu D, Mattiaccio LM, Antshel KM, Fremont W, Middleton FA, Kates WR. Cortical-amygdala volumetric ratios predict onset of symptoms of psychosis in 22q11.2 deletion syndrome. Psychiatry Res 2017; 259:10-15. [PMID: 27918911 PMCID: PMC5456453 DOI: 10.1016/j.pscychresns.2016.11.006] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/03/2016] [Revised: 10/10/2016] [Accepted: 11/23/2016] [Indexed: 01/09/2023]
Abstract
Dysfunction of cortical circuitry involving prefrontal cortex, cingulate gyrus and mesial temporal lobe has been implicated in the pathophysiology of psychotic symptoms. 22q11.2 deletion syndrome (22q11DS) is a neurogenetic disorder that comports a 25-fold increased risk of developing psychosis. Morphological changes in the neuroanatomy of this syndrome may represent a biological risk factor for the development of psychosis. The present study explored ratios between cortical volumes and the amygdala. We also explored relationships between these ratios and the eventual development of psychosis in youth with 22q11DS. A group of 73 individuals with 22q11DS, 32 community controls, and 27 unaffected siblings were followed every three years, at four timepoints. We analyzed baseline ratios between 34 bilateral FreeSurfer-generated cortical volumes and amygdala, and examined whether baseline cortical ratios predicted positive symptoms of psychosis 12 years later, at the 4th timepoint. Youth with 22q11DS demonstrated significantly smaller cortical volume-to-amygdala ratios in left anterior cingulate, occipital and parietal cortices. An increased risk of developing psychotic episodes in individuals with 22q11DS was associated with a lower cortical volume- to-amygdala ratio, suggesting that cortico-limbic circuitry may play an important role in emotional modulation and may underlie the pathophysiology of positive symptoms of psychosis.
Collapse
Affiliation(s)
- David Berhanu
- Lisbon University, Faculty of Medicine, Lisbon, Portugal; SUNY Upstate Medical University, Syracuse, NY, USA
| | | | | | | | | | | |
Collapse
|
30
|
Santos AO, Rossi NF, Tandel MDCFF, Richieri-Costa A, Giacheti CM. Aspectos da fluência em tarefa de narrativa oral na síndrome del22q11.2. Codas 2016; 28:373-8. [DOI: 10.1590/2317-1782/20162015179] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2015] [Accepted: 10/06/2015] [Indexed: 11/21/2022] Open
Abstract
RESUMO Objetivo Investigar os aspectos da fluência em tarefa de narrativa oral na síndrome del22q11.2 e comparar com indivíduos com desenvolvimento típico de linguagem. Método Participaram deste estudo 15 indivíduos com diagnóstico da síndrome del22q11.2, de ambos os gêneros, com idade cronológica de sete a 17 anos, que foram comparados a 15 indivíduos com desenvolvimento típico de linguagem, semelhantes quanto ao gênero e à idade cronológica. A narrativa oral foi eliciada com o livro Frog Where Are You?, e os aspectos da fluência foram analisados quanto ao tipo e frequência de disfluência (comum e gaga) e velocidade de fala. Foram analisados também o número e a duração das pausas. Os achados foram analisados estatisticamente. Resultados O grupo com a síndrome del22q11.2 apresentou média superior em relação ao grupo sem a síndrome, para a porcentagem de disfluências comuns, principalmente hesitação e revisão. O grupo com a síndrome também apresentou média superior para disfluências gagas, sendo a pausa a disfluência mais frequente. Quanto à velocidade de fala, o grupo com a síndrome apresentou média inferior para o número de palavras e sílabas por minuto. Assim sendo, conclui-se que os indivíduos com a síndrome del22q11.2 apresentaram mais dificuldades para narrar do que os seus pares. Conclusão Os aspectos da fluência investigados foram semelhantes entre os grupo com a síndrome del22q11.2 e com desenvolvimento típico de linguagem quanto à presença de hesitação, revisão e pausa na narrativa oral, porém distinto quanto à frequência dessas disfluências, que foi superior para os indivíduos com a síndrome.
Collapse
|
31
|
Biswas AB, Furniss F. Cognitive phenotype and psychiatric disorder in 22q11.2 deletion syndrome: A review. RESEARCH IN DEVELOPMENTAL DISABILITIES 2016; 53-54:242-257. [PMID: 26942704 DOI: 10.1016/j.ridd.2016.02.010] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/17/2015] [Revised: 02/20/2016] [Accepted: 02/22/2016] [Indexed: 06/05/2023]
Abstract
The behavioural phenotype of 22q11.2 deletion syndrome syndrome (22q11DS), one of the most common human multiple anomaly syndromes, frequently includes intellectual disability (ID) together with high risk of diagnosis of psychotic disorders including schizophrenia. Candidate cognitive endophenotypes include problems with retrieval of contextual information from memory and in executive control and focussing of attention. 22q11DS may offer a model of the relationship between ID and risk of psychiatric disorder. This paper reviews research on the relationship between the cognitive phenotype and the development of psychiatric disorders in 22q11DS. Aspects of cognitive function including verbal I.Q., visual memory, and executive function, are associated with mental health outcome in people with 22q11DS. This relationship may result from a common neurobiological basis for the cognitive difficulties and psychiatric disorders. Some of the cognitive difficulties experienced by people with 22q11DS, especially in attention, memory retrieval, and face processing, may, however, in themselves constitute risk factors for development of hallucinations and paranoid delusions. Future research into factors leading to psychiatric disorder in people with 22q11DS should include assessment of social and psychological factors including life events, symptoms associated with trauma, attachment, and self-esteem, which together with cognitive risk factors may mediate mental health outcome.
Collapse
Affiliation(s)
- Asit B Biswas
- Leicestershire Partnership NHS Trust & University of Leicester* Leicester Frith Hospital, Groby Road, Leicester LE3 9QF, UK.
| | - Frederick Furniss
- The Hesley Group* Doncaster* U.K. & University of Leicester, 104 Regent Road, Leicester LE1 7LT, UK.
| |
Collapse
|
32
|
Scott JA, Goodrich-Hunsaker N, Kalish K, Lee A, Hunsaker MR, Schumann CM, Carmichael OT, Simon TJ. The hippocampi of children with chromosome 22q11.2 deletion syndrome have localized anterior alterations that predict severity of anxiety. J Psychiatry Neurosci 2016; 41:203-13. [PMID: 26599134 PMCID: PMC4853211 DOI: 10.1503/jpn.140299] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Individuals with 22q11.2 deletion syndrome (22q11.2DS) have an elevated risk for schizophrenia, which increases with history of childhood anxiety. Altered hippocampal morphology is a common neuroanatomical feature of 22q11.2DS and idiopathic schizophrenia. Relating hippocampal structure in children with 22q11.2DS to anxiety and impaired cognitive ability could lead to hippocampus-based characterization of psychosis-proneness in this at-risk population. METHODS We measured hippocampal volume using a semiautomated approach on MRIs collected from typically developing children and children with 22q11.2DS. We then analyzed hippocampal morphology with Localized Components Analysis. We tested the modulating roles of diagnostic group, hippocampal volume, sex and age on local hippocampal shape components. Lastly, volume and shape components were tested as covariates of IQ and anxiety. RESULTS We included 48 typically developing children and 69 children with 22q11.2DS in our study. Hippocampal volume was reduced bilaterally in children with 22q11.2DS, and these children showed greater variation in the shape of the anterior hippocampus than typically developing children. Children with 22q11.2DS had greater inward deformation of the anterior hippocampus than typically developing children. Greater inward deformation of the anterior hippocampus was associated with greater severity of anxiety, specifically fear of physical injury, within the 22q11.2DS group. LIMITATIONS Shape alterations are not specific to hippocampal subfields. CONCLUSION Alterations in the structure of the anterior hippocampus likely affect function and may impact limbic circuitry. We suggest these alterations potentially contribute to anxiety symptoms in individuals with 22q11.2DS through modulatory pathways. Altered hippocampal morphology may be uniquely linked to anxiety risk factors for schizophrenia, which could be a powerful neuroanatomical marker of schizophrenia risk and hence protection.
Collapse
Affiliation(s)
- Julia A. Scott
- Correspondence to: J.A. Scott, Center for Neuroscience, 1544 Newton Court, University of California, Davis CA, United States;
| | | | | | | | | | | | | | | |
Collapse
|
33
|
Scariati E, Padula MC, Schaer M, Eliez S. Long-range dysconnectivity in frontal and midline structures is associated to psychosis in 22q11.2 deletion syndrome. J Neural Transm (Vienna) 2016; 123:823-39. [PMID: 27094177 DOI: 10.1007/s00702-016-1548-z] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2015] [Accepted: 04/04/2016] [Indexed: 12/23/2022]
Abstract
Patients affected by 22q11.2 deletion syndrome (22q11DS) present a characteristic cognitive and psychiatric profile and have a genetic predisposition to develop schizophrenia. Although brain morphological alterations have been shown in the syndrome, they do not entirely account for the complex clinical picture of the patients with 22q11DS and for their high risk of psychotic symptoms. Since Friston proposed the "disconnection hypothesis" in 1998, schizophrenia is commonly considered as a disorder of brain connectivity. In this study, we review existing evidence pointing to altered brain structural and functional connectivity in 22q11DS, with a specific focus on the role of dysconnectivity in the emergence of psychotic symptoms. We show that widespread alterations of structural and functional connectivity have been described in association with 22q11DS. Moreover, alterations involving long-range association tracts as well as midline structures, such as the corpus callosum and the cingulate gyrus, have been associated with psychotic symptoms in this population. These results suggest common mechanisms for schizophrenia in syndromic and non-syndromic populations. Future directions for investigations are also discussed.
Collapse
Affiliation(s)
- E Scariati
- Office Médico-Pédagogique, Department of Psychiatry, University of Geneva, Rue David-Dufour 1, Case Postale 50, 1211, Genève 8, Switzerland.
| | - M C Padula
- Office Médico-Pédagogique, Department of Psychiatry, University of Geneva, Rue David-Dufour 1, Case Postale 50, 1211, Genève 8, Switzerland.
| | - M Schaer
- Office Médico-Pédagogique, Department of Psychiatry, University of Geneva, Rue David-Dufour 1, Case Postale 50, 1211, Genève 8, Switzerland.,Stanford Cognitive and Systems Neuroscience Laboratory, Stanford University, Stanford, CA, USA
| | - S Eliez
- Office Médico-Pédagogique, Department of Psychiatry, University of Geneva, Rue David-Dufour 1, Case Postale 50, 1211, Genève 8, Switzerland.,Department of Genetic Medicine and Development, University of Geneva, Geneva, Switzerland
| |
Collapse
|
34
|
Longitudinal study of premorbid adjustment in 22q11.2 deletion (velocardiofacial) syndrome and association with psychosis. Dev Psychopathol 2016; 29:93-106. [PMID: 26864886 DOI: 10.1017/s0954579416000018] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Velocardiofacial syndrome, also known as 22q11.2 deletion syndrome (22q11DS), is associated with an increased risk of major psychiatric disorders, including schizophrenia. The emergence of psychotic symptoms in individuals with schizophrenia in the general population is often preceded by a premorbid period of poor or worsening social and/or academic functioning. Our current study evaluated premorbid adjustment (via the Cannon-Spoor Premorbid Adjustment Scale [PAS]) and psychotic symptoms (via the Structured Interview for Prodromal Symptoms and the Kiddie Schedule for Affective Disorders and Schizophrenia for School-Age Children-Present and Lifetime Version) in youth with 22q11DS (N = 96), unaffected siblings (N = 40), and community controls (N = 50). The PAS scores indicated greater maladjustment during all developmental periods in individuals with 22q11DS compared to the controls. Many participants with 22q11DS had chronically poor (n = 33) or deteriorating (n = 6) PAS scores. In 22q11DS, chronically poor PAS trajectories and poor childhood and early adolescence academic domain and total PAS scores significantly increased the risk of prodromal symptoms or overt psychosis. Taking into account the catechol-O-methyltransferase (COMT) genotype, the best predictor of (prodromal) psychosis was the early adolescence academic domain score, which yielded higher sensitivity and specificity in the subgroup of youth with 22q11DS and the high-activity (valine) allele. PAS scores may help identify individuals at higher risk for psychosis.
Collapse
|
35
|
Padula MC, Schaer M, Scariati E, Schneider M, Van De Ville D, Debbané M, Eliez S. Structural and functional connectivity in the default mode network in 22q11.2 deletion syndrome. J Neurodev Disord 2015; 7:23. [PMID: 26236404 PMCID: PMC4522079 DOI: 10.1186/s11689-015-9120-y] [Citation(s) in RCA: 42] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/21/2015] [Accepted: 06/25/2015] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The neural endophenotype associated with 22q11.2 deletion syndrome (22q11DS) includes deviant cortical development and alterations in brain connectivity. Resting-state functional magnetic resonance imaging (fMRI) findings also reported disconnectivity within the default mode network (DMN). In this study, we explored the relationship between functional and structural DMN connectivity and their changes with age in patients with 22q11DS in comparison to control participants. Given previous evidence of an association between DMN disconnectivity and the manifestation of psychotic symptoms, we further investigated this relationship in our group of patients with 22q11DS. METHODS T1-weighted, diffusion, and resting-state fMRI scans were acquired from 41 patients with 22q11DS and 43 control participants aged 6 to 28 years. A data-driven approach based on independent component analysis (ICA) was used to identify the DMN and to define regions of interest for the structural and functional connectivity analysis. Prodromal psychotic symptoms were assessed in adolescents and adults using the positive symptom scores of the Structured Interview of Prodromal Syndromes (SIPS). Connectivity measures were compared between groups and correlated with age. Repeating the between-group analysis in three different age bins further assessed the presence of age-related alterations in DMN connectivity. Structural and functional connectivity measures were then correlated with the SIPS scores. RESULTS A simultaneous reduction of functional and structural connectivity between core medial nodes of the DMN was observed. Furthermore, structural connectivity measures significantly increased with age in the control group but not in patients with 22q11DS, suggesting the presence of an age-related alteration of the DMN structural connections. No correlations were found between the DMN disconnectivity and expression of prodromal symptoms in 22q11DS. CONCLUSIONS These findings indicate the presence of functional and structural DMN disconnectivity in 22q11DS and that patients with 22q11DS fail to develop normal structural connections between medial DMN nodes. This suggests the presence of altered neurodevelopmental trajectories in 22q11DS.
Collapse
Affiliation(s)
- Maria Carmela Padula
- Office Médico-Pédagogique, Department of Psychiatry, University of Geneva, Rue David-Dufour 1, Case Postale 50, 1211 Genève 8, Switzerland
| | - Marie Schaer
- Office Médico-Pédagogique, Department of Psychiatry, University of Geneva, Rue David-Dufour 1, Case Postale 50, 1211 Genève 8, Switzerland ; Stanford Cognitive and Systems Neuroscience Laboratory, Stanford University, Stanford, CA USA
| | - Elisa Scariati
- Office Médico-Pédagogique, Department of Psychiatry, University of Geneva, Rue David-Dufour 1, Case Postale 50, 1211 Genève 8, Switzerland
| | - Maude Schneider
- Office Médico-Pédagogique, Department of Psychiatry, University of Geneva, Rue David-Dufour 1, Case Postale 50, 1211 Genève 8, Switzerland
| | - Dimitri Van De Ville
- Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland ; Medical Image Processing Lab, Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Martin Debbané
- Office Médico-Pédagogique, Department of Psychiatry, University of Geneva, Rue David-Dufour 1, Case Postale 50, 1211 Genève 8, Switzerland ; Adolescence Clinical Psychology Research Unit, Faculty of Psychology and Educational Sciences, Geneva, Switzerland ; Research Department of Clinical, Educational and Health Psychology, University College London, London, U K
| | - Stephan Eliez
- Office Médico-Pédagogique, Department of Psychiatry, University of Geneva, Rue David-Dufour 1, Case Postale 50, 1211 Genève 8, Switzerland ; Department of Genetic Medicine and Development, University of Geneva, Geneva, Switzerland
| |
Collapse
|
36
|
Meechan DW, Maynard TM, Tucker ES, Fernandez A, Karpinski BA, Rothblat LA, LaMantia AS. Modeling a model: Mouse genetics, 22q11.2 Deletion Syndrome, and disorders of cortical circuit development. Prog Neurobiol 2015; 130:1-28. [PMID: 25866365 DOI: 10.1016/j.pneurobio.2015.03.004] [Citation(s) in RCA: 68] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2014] [Revised: 03/24/2015] [Accepted: 03/29/2015] [Indexed: 12/21/2022]
Abstract
Understanding the developmental etiology of autistic spectrum disorders, attention deficit/hyperactivity disorder and schizophrenia remains a major challenge for establishing new diagnostic and therapeutic approaches to these common, difficult-to-treat diseases that compromise neural circuits in the cerebral cortex. One aspect of this challenge is the breadth and overlap of ASD, ADHD, and SCZ deficits; another is the complexity of mutations associated with each, and a third is the difficulty of analyzing disrupted development in at-risk or affected human fetuses. The identification of distinct genetic syndromes that include behavioral deficits similar to those in ASD, ADHC and SCZ provides a critical starting point for meeting this challenge. We summarize clinical and behavioral impairments in children and adults with one such genetic syndrome, the 22q11.2 Deletion Syndrome, routinely called 22q11DS, caused by micro-deletions of between 1.5 and 3.0 MB on human chromosome 22. Among many syndromic features, including cardiovascular and craniofacial anomalies, 22q11DS patients have a high incidence of brain structural, functional, and behavioral deficits that reflect cerebral cortical dysfunction and fall within the spectrum that defines ASD, ADHD, and SCZ. We show that developmental pathogenesis underlying this apparent genetic "model" syndrome in patients can be defined and analyzed mechanistically using genomically accurate mouse models of the deletion that causes 22q11DS. We conclude that "modeling a model", in this case 22q11DS as a model for idiopathic ASD, ADHD and SCZ, as well as other behavioral disorders like anxiety frequently seen in 22q11DS patients, in genetically engineered mice provides a foundation for understanding the causes and improving diagnosis and therapy for these disorders of cortical circuit development.
Collapse
Affiliation(s)
- Daniel W Meechan
- Institute for Neuroscience, Department of Pharmacology & Physiology, The George Washington University, Washington, DC, United States
| | - Thomas M Maynard
- Institute for Neuroscience, Department of Pharmacology & Physiology, The George Washington University, Washington, DC, United States
| | - Eric S Tucker
- Department of Neurobiology and Anatomy, Neuroscience Graduate Program, and Center for Neuroscience, West Virginia University School of Medicine, Morgantown, West Virginia
| | - Alejandra Fernandez
- Institute for Neuroscience, Department of Pharmacology & Physiology, The George Washington University, Washington, DC, United States
| | - Beverly A Karpinski
- Institute for Neuroscience, Department of Pharmacology & Physiology, The George Washington University, Washington, DC, United States
| | - Lawrence A Rothblat
- Institute for Neuroscience, Department of Pharmacology & Physiology, The George Washington University, Washington, DC, United States; Department of Psychology, The George Washington University, Washington, DC, United States
| | - Anthony-S LaMantia
- Institute for Neuroscience, Department of Pharmacology & Physiology, The George Washington University, Washington, DC, United States.
| |
Collapse
|
37
|
Kates WR, Olszewski AK, Gnirke MH, Kikinis Z, Nelson J, Antshel KM, Fremont W, Radoeva PD, Middleton FA, Shenton ME, Coman IL. White matter microstructural abnormalities of the cingulum bundle in youths with 22q11.2 deletion syndrome: associations with medication, neuropsychological function, and prodromal symptoms of psychosis. Schizophr Res 2015; 161:76-84. [PMID: 25066496 PMCID: PMC4277733 DOI: 10.1016/j.schres.2014.07.010] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2014] [Revised: 07/02/2014] [Accepted: 07/03/2014] [Indexed: 11/17/2022]
Abstract
BACKGROUND The 22q11.2 deletion syndrome (22q11.2DS) is regarded as an etiologically homogenous model for understanding neuroanatomic disruptions associated with a high risk for schizophrenia. This study utilized diffusion tensor imaging (DTI) to analyze white matter microstructure in individuals with 22q11.2DS. We focused on the cingulum bundle (CB), previously shown to be disrupted in patients with schizophrenia and associated with symptoms of psychosis. METHODS White matter microstructure was assessed in the anterior, superior, and posterior CB using the tractography algorithm in DTIStudio. Neuropsychological function, presence of prodromal symptoms of psychosis, and medication history were assessed in all participants. RESULTS Relative to controls, young adults with 22q11.2DS showed alterations in most DTI metrics of the CB. Alterations were associated with positive prodromal symptoms of psychosis. However, when individuals with 22q11.2DS were divided by usage of antipsychotics/mood stabilizers, the medicated and non-medicated groups differed significantly in axial diffusivity of the anterior CB and in fractional anisotropy of the superior CB. DTI metrics did not differ between the medicated group and the control group. CONCLUSIONS Results suggest that the microstructure of the CB is altered in individuals with 22q11.2DS, and that those alterations may underlie positive prodromal symptoms of psychosis. Our findings further provide preliminary evidence that antipsychotic/mood stabilizer usage may have a reparative effect on white matter microstructure in prodromal 22q11.2DS, independent of the potential effects of psychosis. Future studies of white matter pathology in individuals with 22q11.2DS should test for potential effects of medication on white matter microstructure.
Collapse
Affiliation(s)
- Wendy R Kates
- Department of Psychiatry and Behavioral Sciences, State University of New York at Upstate Medical University, Syracuse, NY, United States.
| | - Amy K Olszewski
- Department of Psychiatry and Behavioral Sciences, State University of New York at Upstate Medical University, Syracuse, NY, United States
| | - Matthew H Gnirke
- Department of Psychiatry and Behavioral Sciences, State University of New York at Upstate Medical University, Syracuse, NY, United States
| | - Zora Kikinis
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States
| | - Joshua Nelson
- Department of Psychiatry and Behavioral Sciences, State University of New York at Upstate Medical University, Syracuse, NY, United States
| | - Kevin M Antshel
- Department of Psychiatry and Behavioral Sciences, State University of New York at Upstate Medical University, Syracuse, NY, United States; Department of Psychology, Syracuse University, Syracuse, NY, United States
| | - Wanda Fremont
- Department of Psychiatry and Behavioral Sciences, State University of New York at Upstate Medical University, Syracuse, NY, United States
| | - Petya D Radoeva
- Department of Psychiatry and Behavioral Sciences, State University of New York at Upstate Medical University, Syracuse, NY, United States
| | - Frank A Middleton
- Department of Psychiatry and Behavioral Sciences, State University of New York at Upstate Medical University, Syracuse, NY, United States; Department of Neuroscience and Physiology, State University of New York at Upstate Medical University, Syracuse, NY, United States
| | - Martha E Shenton
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States; Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States; VA Boston Healthcare System, Brockton Division, Brockton, MA, United States
| | - Ioana L Coman
- Department of Psychiatry and Behavioral Sciences, State University of New York at Upstate Medical University, Syracuse, NY, United States
| |
Collapse
|
38
|
Abstract
Machine learning techniques are increasingly being used in making relevant predictions and inferences on individual subjects neuroimaging scan data. Previous studies have mostly focused on categorical discrimination of patients and matched healthy controls and more recently, on prediction of individual continuous variables such as clinical scores or age. However, these studies are greatly hampered by the large number of predictor variables (voxels) and low observations (subjects) also known as the curse-of-dimensionality or small-n-large-p problem. As a result, feature reduction techniques such as feature subset selection and dimensionality reduction are used to remove redundant predictor variables and experimental noise, a process which mitigates the curse-of-dimensionality and small-n-large-p effects. Feature reduction is an essential step before training a machine learning model to avoid overfitting and therefore improving model prediction accuracy and generalization ability. In this review, we discuss feature reduction techniques used with machine learning in neuroimaging studies.
Collapse
Affiliation(s)
- Benson Mwangi
- UT Center of Excellence on Mood Disorders, Department of Psychiatry and Behavioral Sciences, UT Houston Medical School, Houston, TX, 77054, USA,
| | | | | |
Collapse
|
39
|
Mapping genetically controlled neural circuits of social behavior and visuo-motor integration by a preliminary examination of atypical deletions with Williams syndrome. PLoS One 2014; 9:e104088. [PMID: 25105779 PMCID: PMC4126723 DOI: 10.1371/journal.pone.0104088] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2013] [Accepted: 07/10/2014] [Indexed: 01/09/2023] Open
Abstract
In this study of eight rare atypical deletion cases with Williams-Beuren syndrome (WS; also known as 7q11.23 deletion syndrome) consisting of three different patterns of deletions, compared to typical WS and typically developing (TD) individuals, we show preliminary evidence of dissociable genetic contributions to brain structure and human cognition. Univariate and multivariate pattern classification results of morphometric brain patterns complemented by behavior implicate a possible role for the chromosomal region that includes: 1) GTF2I/GTF2IRD1 in visuo-spatial/motor integration, intraparietal as well as overall gray matter structures, 2) the region spanning ABHD11 through RFC2 including LIMK1, in social cognition, in particular approachability, as well as orbitofrontal, amygdala and fusiform anatomy, and 3) the regions including STX1A, and/or CYLN2 in overall white matter structure. This knowledge contributes to our understanding of the role of genetics on human brain structure, cognition and pathophysiology of altered cognition in WS. The current study builds on ongoing research designed to characterize the impact of multiple genes, gene-gene interactions and changes in gene expression on the human brain.
Collapse
|
40
|
Dennis EL, Thompson PM. Typical and atypical brain development: a review of neuroimaging studies. DIALOGUES IN CLINICAL NEUROSCIENCE 2014. [PMID: 24174907 PMCID: PMC3811107 DOI: 10.31887/dcns.2013.15.3/edennis] [Citation(s) in RCA: 78] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
In the course of development, the brain undergoes a remarkable process of restructuring as it adapts to the environment and becomes more efficient in processing information. A variety of brain imaging methods can be used to probe how anatomy, connectivity, and function change in the developing brain. Here we review recent discoveries regarding these brain changes in both typically developing individuals and individuals with neurodevelopmental disorders. We begin with typical development, summarizing research on changes in regional brain volume and tissue density, cortical thickness, white matter integrity, and functional connectivity. Space limits preclude the coverage of all neurodevelopmental disorders; instead, we cover a representative selection of studies examining neural correlates of autism, attention deficit/hyperactivity disorder, Fragile X, 22q11.2 deletion syndrome, Williams syndrome, Down syndrome, and Turner syndrome. Where possible, we focus on studies that identify an age by diagnosis interaction, suggesting an altered developmental trajectory. The studies we review generally cover the developmental period from infancy to early adulthood. Great progress has been made over the last 20 years in mapping how the brain matures with MR technology. With ever-improving technology, we expect this progress to accelerate, offering a deeper understanding of brain development, and more effective interventions for neurodevelopmental disorders.
Collapse
Affiliation(s)
- Emily L Dennis
- Imaging Genetics Center, Laboratory of Neuro Imaging, Dept of Neurology & Psychiatry, UCLA School of Medicine, Los Angeles, California, USA
| | | |
Collapse
|
41
|
Haller S, Lovblad KO, Giannakopoulos P, Van De Ville D. Multivariate Pattern Recognition for Diagnosis and Prognosis in Clinical Neuroimaging: State of the Art, Current Challenges and Future Trends. Brain Topogr 2014; 27:329-37. [DOI: 10.1007/s10548-014-0360-z] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2013] [Accepted: 03/10/2014] [Indexed: 01/04/2023]
|
42
|
Scariati E, Schaer M, Richiardi J, Schneider M, Debbané M, Van De Ville D, Eliez S. Identifying 22q11.2 Deletion Syndrome and Psychosis Using Resting-State Connectivity Patterns. Brain Topogr 2014; 27:808-21. [DOI: 10.1007/s10548-014-0356-8] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2013] [Accepted: 02/12/2014] [Indexed: 11/30/2022]
|
43
|
Shah JL, Tandon N, Keshavan MS. Psychosis prediction and clinical utility in familial high-risk studies: selective review, synthesis, and implications for early detection and intervention. Early Interv Psychiatry 2013; 7:345-60. [PMID: 23693118 PMCID: PMC5218827 DOI: 10.1111/eip.12054] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/17/2012] [Accepted: 03/23/2013] [Indexed: 02/02/2023]
Abstract
AIM Accurate prediction of which high-risk individuals will go on to develop psychosis would assist early intervention and prevention paradigms. We sought to review investigations of prospective psychosis prediction based on markers and variables examined in longitudinal familial high-risk (FHR) studies. METHODS We performed literature searches in MedLine, PubMed and PsycINFO for articles assessing performance characteristics of predictive clinical tests in FHR studies of psychosis. Studies were included if they reported on one or more predictive variables in subjects at FHR for psychosis. We complemented this search strategy with references drawn from articles, reviews, book chapters and monographs. RESULTS Across generations of FHR projects, predictive studies have investigated behavioural, cognitive, psychometric, clinical, neuroimaging and other markers. Recent analyses have incorporated multivariate and multi-domain approaches to risk ascertainment, with generally modest results. CONCLUSIONS Although a broad range of risk factors has been identified, no individual marker or combination of markers can at this time enable accurate prospective prediction of emerging psychosis for individuals at FHR. We outline the complex and multi-level nature of psychotic illness, the myriad of factors influencing its development, and methodological hurdles to accurate and reliable prediction. Prospects and challenges for future generations of FHR studies are discussed in the context of early detection and intervention strategies.
Collapse
Affiliation(s)
- Jai L Shah
- Massachusetts Mental Health Center, Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA; Department of Psychiatry, Harvard Medical School, Boston, Massachusetts, USA; Connecticut Mental Health Center, New Haven, Connecticut, USA; Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut, USA
| | | | | |
Collapse
|
44
|
Cortisol levels and risk for psychosis: initial findings from the North American prodrome longitudinal study. Biol Psychiatry 2013; 74:410-7. [PMID: 23562006 PMCID: PMC3707958 DOI: 10.1016/j.biopsych.2013.02.016] [Citation(s) in RCA: 166] [Impact Index Per Article: 15.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/29/2012] [Revised: 01/31/2013] [Accepted: 02/03/2013] [Indexed: 12/18/2022]
Abstract
BACKGROUND Studies of biomarkers of hypothalamic-pituitary-adrenal activity indicate that psychotic disorders are associated with elevated cortisol. This study examined cortisol levels in healthy control subjects and individuals who met clinical high-risk (CHR) criteria for psychosis. It was hypothesized that cortisol levels would be 1) elevated in the CHR group relative to control subjects, 2) positively correlated with symptom severity, and 3) most elevated in CHR patients who transition to psychotic level severity. METHODS Baseline assessments were conducted at eight centers in the North American Prodrome Longitudinal Study. The present CHR sample included 256 individuals meeting the Scale for Prodromal Symptoms criteria and 141 control subjects, all of whom underwent baseline assessment and measurement of salivary cortisol. RESULTS Consistent with previous reports, there was an effect of age on cortisol, with increases through the adolescent/early adult years. Analysis of covariance showed a main effect of diagnostic group, with the CHR group showing higher cortisol. There were modest, positive correlations of cortisol with baseline symptom severity, and analysis of covariance revealed higher baseline cortisol in those who transitioned to psychotic level symptoms when compared with healthy control subjects and CHR subjects who remitted. CONCLUSIONS The present findings add to accumulating evidence of heightened cortisol secretion in CHR individuals. The findings also indicate nonspecific associations between cortisol levels and symptom severity, as well as symptom progression. The role of hypothalamic-pituitary-adrenal activity in prediction of conversion to psychosis and its relation with other biomarkers of risk should receive attention in future research.
Collapse
|
45
|
Ottet MC, Schaer M, Debbané M, Cammoun L, Thiran JP, Eliez S. Graph theory reveals dysconnected hubs in 22q11DS and altered nodal efficiency in patients with hallucinations. Front Hum Neurosci 2013; 7:402. [PMID: 24046733 PMCID: PMC3763187 DOI: 10.3389/fnhum.2013.00402] [Citation(s) in RCA: 55] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2013] [Accepted: 07/09/2013] [Indexed: 11/13/2022] Open
Abstract
Schizophrenia is postulated to be the prototypical dysconnection disorder, in which hallucinations are the core symptom. Due to high heterogeneity in methodology across studies and the clinical phenotype, it remains unclear whether the structural brain dysconnection is global or focal and if clinical symptoms result from this dysconnection. In the present work, we attempt to clarify this issue by studying a population considered as a homogeneous genetic sub-type of schizophrenia, namely the 22q11.2 deletion syndrome (22q11.2DS). Cerebral MRIs were acquired for 46 patients and 48 age and gender matched controls (aged 6-26, respectively mean age = 15.20 ± 4.53 and 15.28 ± 4.35 years old). Using the Connectome mapper pipeline (connectomics.org) that combines structural and diffusion MRI, we created a whole brain network for each individual. Graph theory was used to quantify the global and local properties of the brain network organization for each participant. A global degree loss of 6% was found in patients' networks along with an increased Characteristic Path Length. After identifying and comparing hubs, a significant loss of degree in patients' hubs was found in 58% of the hubs. Based on Allen's brain network model for hallucinations, we explored the association between local efficiency and symptom severity. Negative correlations were found in the Broca's area (p < 0.004), the Wernicke area (p < 0.023) and a positive correlation was found in the dorsolateral prefrontal cortex (DLPFC) (p < 0.014). In line with the dysconnection findings in schizophrenia, our results provide preliminary evidence for a targeted alteration in the brain network hubs' organization in individuals with a genetic risk for schizophrenia. The study of specific disorganization in language, speech and thought regulation networks sharing similar network properties may help to understand their role in the hallucination mechanism.
Collapse
Affiliation(s)
- Marie-Christine Ottet
- Departement of Psychiatry, Office Médico-Pédagogique (OMP), University of Geneva School of Medicine Geneva, Switzerland ; Signal Processing Laboratory (LTS5), Swiss Federal Institute of Technology (EPFL) Lausanne, Switzerland
| | | | | | | | | | | |
Collapse
|
46
|
Schreiner MJ, Lazaro MT, Jalbrzikowski M, Bearden CE. Converging levels of analysis on a genomic hotspot for psychosis: insights from 22q11.2 deletion syndrome. Neuropharmacology 2013; 68:157-73. [PMID: 23098994 PMCID: PMC3677073 DOI: 10.1016/j.neuropharm.2012.09.012] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2012] [Revised: 09/04/2012] [Accepted: 09/17/2012] [Indexed: 10/27/2022]
Abstract
Schizophrenia is a devastating neurodevelopmental disorder that, despite extensive research, still poses a considerable challenge to attempts to unravel its heterogeneity, and the complex biochemical mechanisms by which it arises. While the majority of cases are of unknown etiology, accumulating evidence suggests that rare genetic mutations, such as 22q11.2 Deletion Syndrome (22qDS), can play a significant role in predisposition to the illness. Up to 25% of individuals with 22qDS eventually develop schizophrenia; conversely, this deletion is estimated to account for 1-2% of schizophrenia cases overall. This locus of Chromosome 22q11.2 contains genes that encode for proteins and enzymes involved in regulating neurotransmission, neuronal development, myelination, microRNA processing, and post-translational protein modifications. As a consequence of the deletion, affected individuals exhibit cognitive dysfunction, structural and functional brain abnormalities, and neurodevelopmental anomalies that parallel many of the phenotypic characteristics of schizophrenia. As an illustration of the value of rare, highly penetrant genetic subtypes for elucidating pathological mechanisms of complex neuropsychiatric disorders, we provide here an overview of the cellular, network, and systems-level anomalies found in 22qDS, and review the intriguing evidence for this disorder's association with schizophrenia. This article is part of the Special Issue entitled 'Neurodevelopmental Disorders'.
Collapse
Affiliation(s)
- Matthew J. Schreiner
- Interdepartmental Neuroscience Program, University of California, Los Angeles, USA
| | - Maria T. Lazaro
- Interdepartmental Neuroscience Program, University of California, Los Angeles, USA
| | | | - Carrie E. Bearden
- Department of Psychology, University of California, Los Angeles, USA
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, USA
| |
Collapse
|
47
|
Smith DV, Clithero JA, Rorden C, Karnath HO. Decoding the anatomical network of spatial attention. Proc Natl Acad Sci U S A 2013; 110:1518-23. [PMID: 23300283 PMCID: PMC3557038 DOI: 10.1073/pnas.1210126110] [Citation(s) in RCA: 99] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
The study of stroke patients with modern lesion-symptom analysis techniques has yielded valuable insights into the representation of spatial attention in the human brain. Here we introduce an approach--multivariate pattern analysis--that no longer assumes independent contributions of brain regions but rather quantifies the joint contribution of multiple brain regions in determining behavior. In a large sample of stroke patients, we found patterns of damage more predictive of spatial neglect than the best-performing single voxel. In addition, modeling multiple brain regions--those that are frequently damaged and, importantly, spared--provided more predictive information than modeling single regions. Interestingly, we also found that the superior temporal gyrus demonstrated a consistent ability to improve classifier performance when added to other regions, implying uniquely predictive information. In sharp contrast, classifier performance for both the angular gyrus and insular cortex was reliably enhanced by the addition of other brain regions, suggesting these regions lack independent predictive information for spatial neglect. Our findings highlight the utility of multivariate pattern analysis in lesion mapping, furnishing neuroscience with a modern approach for using lesion data to study human brain function.
Collapse
Affiliation(s)
- David V. Smith
- Department of Psychology and Neuroscience and
- Center for Cognitive Neuroscience, Duke University, Durham, NC 27708
| | - John A. Clithero
- Center for Cognitive Neuroscience, Duke University, Durham, NC 27708
| | - Christopher Rorden
- Department of Psychology, University of South Carolina, Columbia, SC, 29208; and
| | - Hans-Otto Karnath
- Department of Psychology, University of South Carolina, Columbia, SC, 29208; and
- Center of Neurology, Division of Neuropsychology, Hertie-Institute for Clinical Brain Research, University of Tuebingen, 72076 Tuebingen, Germany
| |
Collapse
|
48
|
Squarcione C, Torti MC, Di Fabio F, Biondi M. 22q11 deletion syndrome: a review of the neuropsychiatric features and their neurobiological basis. Neuropsychiatr Dis Treat 2013; 9:1873-84. [PMID: 24353423 PMCID: PMC3862513 DOI: 10.2147/ndt.s52188] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
The 22q11.2 deletion syndrome (22q11DS) is caused by an autosomal dominant microdeletion of chromosome 22 at the long arm (q) 11.2 band. The 22q11DS is among the most clinically variable syndromes, with more than 180 features related with the deletion, and is associated with an increased risk of psychiatric disorders, accounting for up to 1%-2% of schizophrenia cases. In recent years, several genes located on chromosome 22q11 have been linked to schizophrenia, including those encoding catechol-O-methyltransferase and proline dehydrogenase, and the interaction between these and other candidate genes in the deleted region is an important area of research. It has been suggested that haploinsufficiency of some genes within the 22q11.2 region may contribute to the characteristic psychiatric phenotype and cognitive functioning of schizophrenia. Moreover, an extensive literature on neuroimaging shows reductions of the volumes of both gray and white matter, and these findings suggest that this reduction may be predictive of increased risk of prodromal psychotic symptoms in 22q11DS patients. Experimental and standardized cognitive assessments alongside neuroimaging may be important to identify one or more endophenotypes of schizophrenia, as well as a predictive prodrome that can be preventively treated during childhood and adolescence. In this review, we summarize recent data about the 22q11DS, in particular those addressing the neuropsychiatric and cognitive phenotypes associated with the deletion, underlining the recent advances in the studies about the genetic architecture of the syndrome.
Collapse
Affiliation(s)
- Chiara Squarcione
- Department of Neurology and Psychiatry, Sapienza University of Rome, Rome, Italy
| | - Maria Chiara Torti
- Department of Neurology and Psychiatry, Sapienza University of Rome, Rome, Italy
| | - Fabio Di Fabio
- Department of Neurology and Psychiatry, Sapienza University of Rome, Rome, Italy
| | - Massimo Biondi
- Department of Neurology and Psychiatry, Sapienza University of Rome, Rome, Italy
| |
Collapse
|
49
|
Sinderberry B, Brown S, Hammond P, Stevens AF, Schall U, Murphy DGM, Murphy KC, Campbell LE. Subtypes in 22q11.2 deletion syndrome associated with behaviour and neurofacial morphology. RESEARCH IN DEVELOPMENTAL DISABILITIES 2013; 34:116-125. [PMID: 22940165 DOI: 10.1016/j.ridd.2012.07.025] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/11/2012] [Revised: 07/24/2012] [Accepted: 07/24/2012] [Indexed: 06/01/2023]
Abstract
22q11.2 deletion syndrome (22q11DS) has a complex phenotype with more than 180 characteristics, including cardiac anomalies, cleft palate, intellectual disabilities, a typical facial morphology, and mental health problems. However, the variable phenotype makes it difficult to predict clinical outcome, such as the high prevalence of psychosis among adults with 22q11DS (~25-30% vs. ~1% in the general population). The purpose of this study was to investigate whether subtypes exist among people with 22q11DS, with a similar phenotype and an increased risk of developing mental health problems. Physical, cognitive and behavioural data from 50 children and adolescents with 22q11DS were included in a k-means cluster analysis. Two distinct phenotypes were identified: Type-1 presented with a more severe phenotype including significantly impaired verbal memory, lower intellectual and academic ability, as well as statistically significant reduced total brain volume. In addition, we identified a trend effect for reduced temporal grey matter. Type-1 also presented with autism-spectrum traits, whereas Type-2 could be described as having more 22q11DS-typical face morphology, being predominately affected by executive function deficits, but otherwise being relatively high functioning with regard to cognition and behaviour. The confirmation of well-defined subtypes in 22q11DS can lead to better prognostic information enabling early identification of people with 22q11DS at high risk of psychiatric disorders. The identification of subtypes in a group of people with a relatively homogenous genetic deletion such as 22q11DS is also valuable to understand clinical outcomes.
Collapse
Affiliation(s)
- Brooke Sinderberry
- School of Medicine and Public Health, University of Newcastle, New South Wales, Australia.
| | | | | | | | | | | | | | | |
Collapse
|
50
|
Abstract
PURPOSE OF REVIEW Chromosome 22, the first human chromosome to be completely sequenced, is prone to genomic alterations. Copy-number variants (CNVs) are common because of an enrichment of low-copy repeat sequences that precipitate a high frequency of nonallelic homologous misalignments and unequal recombination during meiosis. Among these is one of the most common multiple anomaly syndromes in humans and the most common microdeletion syndrome, velocardiofacial syndrome (VCFS), also known as 22q11.2 deletion syndrome and DiGeorge syndrome. This review will focus on the recent literature dealing with both the molecular and clinical aspects of chromosome 22 genomic variations. Although the literature covering this area is expansive, the majority is descriptive or analytical of the problems presented by these genomic disorders, and there is little evidence of translational research including treatment outcomes. RECENT FINDINGS With the increased use of microarray analysis in both research and clinical practice, variations in CNVs are becoming elucidated. Genomic analysis continues to characterize genes and gene effect. Research on the COMT gene continues to yield interesting findings, including a possible sex-mediated effect because of its regulatory role with estrogen. There is a small amount of treatment outcome data relevant to neuropsychiatric disorders in VCFS, but based on small samples and short-term follow-up. SUMMARY Although hundreds of studies in the past year have focused on genomic disorders of chromosome 22, little progress has been made in the implementation of translational research, even for more common disorders including VCFS.
Collapse
|