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Zhang K, Jin X, He Y, Wu S, Cui X, Gao X, Huang C, Luo X. Atypical frontotemporal cortical activity in first-episode adolescent-onset schizophrenia during verbal fluency task: A functional near-infrared spectroscopy study. Front Psychiatry 2023; 14:1126131. [PMID: 36970264 PMCID: PMC10030837 DOI: 10.3389/fpsyt.2023.1126131] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Accepted: 02/17/2023] [Indexed: 03/29/2023] Open
Abstract
Background Frontotemporal cortex dysfunction has been found to be associated with cognitive impairment in patients with schizophrenia (SCZ). In patients with adolescent-onset SCZ, a more serious type of SCZ with poorer functional outcome, cognitive impairment appeared to occur at an early stage of the disease. However, the characteristics of frontotemporal cortex involvement in adolescent patients with cognitive impairment are still unclear. In the present study, we aimed to illustrate the frontotemporal hemodynamic response during a cognitive task in adolescents with first-episode SCZ. Methods Adolescents with first-episode SCZ who were aged 12-17 and demographically matched healthy controls (HCs) were recruited. We used a 48-channel functional near-infrared spectroscopy (fNIRS) system to record the concentration of oxygenated hemoglobin (oxy-Hb) in the participants' frontotemporal area during a verbal fluency task (VFT) and analyzed its correlation with clinical characteristics. Results Data from 36 adolescents with SCZ and 38 HCs were included in the analyses. Significant differences were found between patients with SCZ and HCs in 24 channels, mainly covering the dorsolateral prefrontal cortex, superior and middle temporal gyrus and frontopolar area. Adolescents with SCZ showed no increase of oxy-Hb concentration in most channels, while the VFT performance was comparable between the two groups. In SCZ, the intensity of activation was not associated with the severity of symptoms. Finally, receiver operating characteristic analysis indicated that the changes in oxy-Hb concentration could help distinguish the two groups. Conclusion Adolescents with first-episode SCZ showed atypical cortical activity in the frontotemporal area during the VFT, and fNIRS features might be more sensitive indicators in cognitive assessment, indicating that the characteristic hemodynamic response pattern might be potential imaging biomarkers for this population.
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Fan F, Huang J, Tan S, Wang Z, Li Y, Chen S, Li H, Hare S, Du X, Yang F, Tian B, Kochunov P, Tan Y, Hong LE. Association of cortical thickness and cognition with schizophrenia treatment resistance. Psychiatry Clin Neurosci 2023; 77:12-19. [PMID: 36184782 PMCID: PMC9812867 DOI: 10.1111/pcn.13486] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Revised: 06/24/2022] [Accepted: 09/28/2022] [Indexed: 01/07/2023]
Abstract
AIM Approximately a third of patients with schizophrenia fail to adequately respond to antipsychotic medications, a condition known as treatment resistance (TR). We aimed to assess cognitive and cortical thickness deficits and their relationship to TR in schizophrenia. METHOD We recruited patients with schizophrenia (n = 127), including patients at treatment initiation (n = 45), treatment-responsive patients (n = 40) and TR patients (n = 42), and healthy controls (n = 83). Clinical symptoms, neurocognitive function, and structural images were assessed. We performed group comparisons, and explored association of cortical thickness and cognition with TR. RESULTS The TR patients showed significantly more severe clinical symptoms and cognitive impairment relative to the treatment-responsive group. Compared to healthy controls, 56 of 68 brain regions showed significantly reduced cortical thickness in patients with schizophrenia. Reductions in five regions were significantly associated with TR (reduction in TR relative to treatment-responsive patients), i.e. in the right caudal middle frontal gyrus, superior frontal cortex, fusiform gyrus, pars opercularis of the inferior frontal cortex, and supramarginal cortex. Cognition deficits were also significantly correlated with cortical thickness in these five regions in patients with schizophrenia. Cortical thickness of the right caudal middle frontal gyrus, superior frontal cortex and pars opercularis of the inferior frontal cortex also significantly mediated effects of cognitive deficits on TR. CONCLUSION Treatment resistance in schizophrenia was associated with reduced thickness in the right caudal middle frontal gyrus, superior frontal cortex, fusiform gyrus, pars opercularis of the inferior frontal cortex, and supramarginal cortex. Cortical abnormalities further mediate cognitive deficits known to be associated with TR.
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Affiliation(s)
- Fengmei Fan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Junchao Huang
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Shuping Tan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Zhiren Wang
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Yanli Li
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Song Chen
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Hui Li
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Stephanie Hare
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Xiaoming Du
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Fude Yang
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Baopeng Tian
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Yunlong Tan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - L. Elliot Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
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Gribkoff VK, Kaczmarek LK. The Difficult Path to the Discovery of Novel Treatments in Psychiatric Disorders. ADVANCES IN NEUROBIOLOGY 2023; 30:255-285. [PMID: 36928854 PMCID: PMC10599454 DOI: 10.1007/978-3-031-21054-9_11] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/18/2023]
Abstract
CNS diseases, including psychiatric disorders, represent a significant opportunity for the discovery and development of new drugs and therapeutic treatments with the potential to have a significant impact on human health. CNS diseases, however, present particular challenges to therapeutic discovery efforts, and psychiatric diseases/disorders may be among the most difficult. With specific exceptions such as psychostimulants for ADHD, a large number of psychiatric patients are resistant to existing treatments. In addition, clinicians have no way of knowing which psychiatric patients will respond to which drugs. By definition, psychiatric diagnoses are syndromal in nature; determinations of efficacy are often self-reported, and drug discovery is largely model-based. While such models of psychiatric disease are amenable to screening for new drugs, whether cellular or whole-animal based, they have only modest face validity and, more importantly, predictive validity. Multiple academic, pharmaceutical industry, and government agencies are dedicated to the translation of new findings about the neurobiology of major psychiatric disorders into the discovery and advancement of novel therapies. The collaboration of these agencies provide a pathway for developing new therapeutics. These efforts will be greatly helped by recent advances in understanding the genetic bases of psychiatric disorders, the ongoing search for diagnostic and therapy-responsive biomarkers, and the validation of new animal models.
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Affiliation(s)
- Valentin K Gribkoff
- Department of Internal Medicine, Section on Endocrinology, Yale University School of Medicine, New Haven, CT, USA.
| | - Leonard K Kaczmarek
- Department of Pharmacology, Yale University School of Medicine, New Haven, CT, USA.
- Department of Cellular and Molecular Physiology, Yale University School of Medicine, New Haven, CT, USA.
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Zong X, Wang G, Nie Z, Ma S, Kang L, Zhang N, Weng S, Tan Q, Zheng J, Hu M. Longitudinal multi-omics alterations response to 8-week risperidone monotherapy: Evidence linking cortical thickness, transcriptomics and epigenetics. Front Psychiatry 2023; 14:1127353. [PMID: 36937723 PMCID: PMC10018025 DOI: 10.3389/fpsyt.2023.1127353] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Accepted: 02/14/2023] [Indexed: 03/06/2023] Open
Abstract
Background Antipsychotic treatment-related alterations of cortical thickness (CT) and clinical symptoms have been previously corroborated, but less is known about whether the changes are driven by gene expression and epigenetic modifications. Methods Utilizing a prospective design, we recruited 42 treatment-naive first-episode schizophrenia patients (FESP) and 38 healthy controls. Patients were scanned by TI weighted imaging before and after 8-week risperidone monotherapy. CT estimation was automatically performed with the FreeSurfer software package. Participants' peripheral blood genomic DNA methylation (DNAm) status, quantified by using Infinium® Human Methylation 450K BeadChip, was examined in parallel with T1 scanning. In total, CT measures from 118 subjects and genomic DNAm status from 114 subjects were finally collected. Partial least squares (PLS) regression was used to detect the spatial associations between longitudinal CT variations after treatment and cortical transcriptomic data acquired from the Allen Human Brain Atlas. Canonical correlation analysis (CCA) was then performed to identify multivariate associations between DNAm of PLS1 genes and patients' clinical improvement. Results We detected the significant PLS1 component (2,098 genes) related to longitudinal alterations of CT, and the PLS1 genes were significantly enriched in neurobiological processes, and dopaminergic- and cancer-related pathways. Combining Laplacian score and CCA analysis, we further linked DNAm of 33 representative genes from the 2,098 PLS1 genes with patients' reduction rate of clinical symptoms. Conclusions This study firstly revealed that changes of CT and clinical behaviors after treatment may be transcriptionally and epigenetically underlied. We define a "three-step" roadmap which represents a vital step toward the exploration of treatment- and treatment response-related biomarkers on the basis of multiple omics rather than a single omics type as a strategy for advancing precise care.
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Affiliation(s)
- Xiaofen Zong
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, Hubei, China
| | - Gaohua Wang
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, Hubei, China
| | - Zhaowen Nie
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, Hubei, China
| | - Simeng Ma
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, Hubei, China
| | - Lijun Kang
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, Hubei, China
| | - Nan Zhang
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, Hubei, China
| | - Shenhong Weng
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, Hubei, China
- Shenhong Weng
| | - Qing Tan
- School of Mathematics and Statistics, Wuhan University, Wuhan, Hubei, China
- Hubei Key Laboratory of Computational Science, Wuhan University, Wuhan, Hubei, China
- Qing Tan
| | - Junjie Zheng
- The Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, Jiangsu, China
- The Functional Brain Imaging Institute, Nanjing Medical University, Nanjing, Jiangsu, China
- Junjie Zheng
| | - Maolin Hu
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, Hubei, China
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, China
- *Correspondence: Maolin Hu
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Abstract
Schizophrenia is a disabling condition impacting approximately 1% of the worldwide population. Symptoms include positive symptoms (eg, hallucinations, delusions), negative symptoms (eg, avolition, anhedonia), and cognitive impairment. There are likely many different environmental and pathophysiologic etiologies involving distinct neurotransmitters and neurocircuits. Pharmacologic treatment at present consists of dopamine receptor antagonists, which are reasonably effective at treating positive symptoms, but less effective at treating cognitive and negative symptoms. Nondopaminergic medications targeting alternative receptors are under investigation. Supportive psychosocial treatments can work in tandem with antipsychotic medications and optimize patient care.
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Affiliation(s)
- Justin Faden
- Lewis Katz School of Medicine at Temple University, 100 East Lehigh Avenue, Suite 305B, Philadelphia, PA 19125, USA.
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Ma Y, Kvarta MD, Adhikari BM, Chiappelli J, Du X, van der Vaart A, Goldwaser EL, Bruce H, Hatch KS, Gao S, Summerfelt A, Jahanshad N, Thompson PM, Nichols TE, Hong LE, Kochunov P. Association between brain similarity to severe mental illnesses and comorbid cerebral, physical, and cognitive impairments. Neuroimage 2023; 265:119786. [PMID: 36470375 PMCID: PMC9910181 DOI: 10.1016/j.neuroimage.2022.119786] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Revised: 11/10/2022] [Accepted: 12/01/2022] [Indexed: 12/12/2022] Open
Abstract
Severe mental illnesses (SMIs) are often associated with compromised brain health, physical comorbidities, and cognitive deficits, but it is incompletely understood whether these comorbidities are intrinsic to SMI pathophysiology or secondary to having SMIs. We tested the hypothesis that cerebral, cardiometabolic, and cognitive impairments commonly observed in SMIs can be observed in non-psychiatric individuals with SMI-like brain patterns of deviation as seen on magnetic resonance imaging. 22,883 participants free of common neuropsychiatric conditions from the UK Biobank (age = 63.4 ± 7.5 years, range = 45-82 years, 50.9% female) were split into discovery and replication samples. The regional vulnerability index (RVI) was used to quantify each participant's respective brain similarity to meta-analytical patterns of schizophrenia spectrum disorder, bipolar disorder, and major depressive disorder in gray matter thickness, subcortical gray matter volume, and white matter integrity. Cluster analysis revealed five clusters with distinct RVI profiles. Compared with a cluster with no RVI elevation, a cluster with RVI elevation across all SMIs and brain structures showed significantly higher volume of white matter hyperintensities (Cohen's d = 0.59, pFDR < 10-16), poorer cardiovascular (Cohen's d = 0.30, pFDR < 10-16) and metabolic (Cohen's d = 0.12, pFDR = 1.3 × 10-4) health, and slower speed of information processing (|Cohen's d| = 0.11-0.17, pFDR = 1.6 × 10-3-4.6 × 10-8). This cluster also had significantly higher level of C-reactive protein and alcohol use (Cohen's d = 0.11 and 0.28, pFDR = 4.1 × 10-3 and 1.1 × 10-11). Three other clusters with respective RVI elevation in gray matter thickness, subcortical gray matter volume, and white matter integrity showed intermediate level of white matter hyperintensities, cardiometabolic health, and alcohol use. Our results suggest that cerebral, physical, and cognitive impairments in SMIs may be partly intrinsic via shared pathophysiological pathways with SMI-related brain anatomical changes.
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Affiliation(s)
- Yizhou Ma
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA.
| | - Mark D Kvarta
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Bhim M Adhikari
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Joshua Chiappelli
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Xiaoming Du
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Andrew van der Vaart
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Eric L Goldwaser
- Department of Psychiatry, Weill Cornell Medical College/New York-Presbyterian Hospital, New York, NY, USA
| | - Heather Bruce
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Kathryn S Hatch
- School of Medicine, University of California, San Diego, CA, USA
| | - Si Gao
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Ann Summerfelt
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of the University of Southern California, Marina del Rey, CA, USA
| | - Paul M Thompson
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of the University of Southern California, Marina del Rey, CA, USA
| | - Thomas E Nichols
- Big Data Science Institute, Department of Statistics, University of Oxford, Oxford, UK
| | - L Elliot Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
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Chakrabarty M, Bhattacharya K, Chatterjee G, Biswas A, Ghosal M. Pragmatic deficits in patients with schizophrenia and right hemisphere damage: A pilot study. INTERNATIONAL JOURNAL OF LANGUAGE & COMMUNICATION DISORDERS 2023; 58:169-188. [PMID: 36073996 DOI: 10.1111/1460-6984.12778] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Accepted: 07/23/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND While pragmatic deficits are well documented in patients with schizophrenia (SCZ) and right hemisphere damage (RHD), there is a paucity of research comparing the pragmatic deficits of these two groups. Do they experience similar cognitive dysfunction or is there a dissociation between the two patient groups? AIMS To investigate the nature of pragmatic deficits in these two groups and to gain an understanding of the underlying cognitive mechanisms that might be associated with these deficits to further future investigations. METHODS & PROCEDURES A total of 60 participants (15 patients with SCZ; 15 with RHD; 30 (15 + 15) healthy controls (HC) were administered the Bengali Audio-Visual Test-Battery for Assessment of Pragmatic Skills. OUTCOMES & RESULTS Both SCZ and RHD patients were found to have significant pragmatic deficits compared with their matched controls. SCZ patients were found to score significantly better than the RHD group in six out of the 10 pragmatic skills when controlled for age and education. Discriminant function analysis was performed and 86.7% of the cases (HC = 100%, SCZ = 73.3% and RHD = 86.7%) were correctly reclassified into their original categories using the test scores. CONCLUSIONS & IMPLICATIONS The study suggests that there is heterogeneity in the nature of the pragmatic breakdown within and across patient groups. Therefore, individualized restorative measures targeting the disrupted cognitive mechanism(s) might help elevate pragmatic competence and enhance the social functioning of patients with pragmatic deficits. WHAT THIS PAPER ADDS What is already known on the subject Pragmatic deficits are common in adults with cognitive impairments of different etiologies. However, few studies have explored pragmatic deficits across clinical populations. Consequently, very little is known about the nature of pragmatic deficits in patients with schizophrenia and right hemisphere damage. What this paper adds to existing knowledge This work offers preliminary data on pragmatic difficulties in patients with schizophrenia and right hemisphere damage. This study overrides the boundaries of traditional classifications and evaluates pragmatic difficulties in these two clinical populations with reference to the underlying cognitive mechanisms, which might be disrupted. What are the potential or actual clinical implications of this work? The study adds a transdiagnostic perspective suggesting that there might be heterogeneity in pragmatic deficits, both within and across patient groups, and stresses the need for individualized therapy.
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Affiliation(s)
| | | | - Garga Chatterjee
- Psychology Research Unit, Indian Statistical Institute, Kolkata, West Bengal, India
| | - Atanu Biswas
- Bangur Institute of Neurosciences, IPGME&R, Kolkata, West Bengal, India
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Slapø NB, Nerland S, Nordbø Jørgensen K, Mørch-Johnsen L, Pettersen JH, Roelfs D, Parker N, Valstad M, Pentz A, Timpe CMF, Richard G, Beck D, Werner MCF, Lagerberg TV, Melle I, Agartz I, Westlye LT, Steen NE, Andreassen OA, Moberget T, Elvsåshagen T, Jönsson EG. Auditory Cortex Thickness Is Associated With N100 Amplitude in Schizophrenia Spectrum Disorders. SCHIZOPHRENIA BULLETIN OPEN 2023; 4:sgad015. [PMID: 38812720 PMCID: PMC7616042 DOI: 10.1093/schizbullopen/sgad015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 05/31/2024]
Abstract
Background and Hypothesis The auditory cortex (AC) may play a central role in the pathophysiology of schizophrenia and auditory hallucinations (AH). Previous schizophrenia studies report thinner AC and impaired AC function, as indicated by decreased N100 amplitude of the auditory evoked potential. However, whether these structural and functional alterations link to AH in schizophrenia remain poorly understood. Study Design Patients with a schizophrenia spectrum disorder (SCZspect), including patients with a lifetime experience of AH (AH+), without (AH-), and healthy controls underwent magnetic resonance imaging (39 SCZspect, 22 AH+, 17 AH-, and 146 HC) and electroencephalography (33 SCZspect, 17 AH+, 16 AH-, and 144 HC). Cortical thickness of the primary (AC1, Heschl's gyrus) and secondary (AC2, Heschl's sulcus, and the planum temporale) AC was compared between SCZspect and controls and between AH+, AH-, and controls. To examine if the association between AC thickness and N100 amplitude differed between groups, we used regression models with interaction terms. Study Results N100 amplitude was nominally smaller in SCZspect (P = .03, d = 0.42) and in AH- (P = .020, d = 0.61), while AC2 was nominally thinner in AH+ (P = .02, d = 0.53) compared with controls. AC1 thickness was positively associated with N100 amplitude in SCZspect (t = 2.56, P = .016) and AH- (t = 3.18, P = .008), while AC2 thickness was positively associated with N100 amplitude in SCZspect (t = 2.37, P = .024) and in AH+ (t = 2.68, P = .019). Conclusions The novel findings of positive associations between AC thickness and N100 amplitude in SCZspect, suggest that a common neural substrate may underlie AC thickness and N100 amplitude alterations.
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Affiliation(s)
- Nora Berz Slapø
- Department of medicine, NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Stener Nerland
- Department of medicine, NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
| | - Kjetil Nordbø Jørgensen
- Department of medicine, NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychiatry, Telemark Hospital, Skien, Norway
| | - Lynn Mørch-Johnsen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- Department of Psychiatry, Østfold Hospital, Grålum, Norway
- Department of Clinical Research, Østfold Hospital, Grålum, Norway
| | | | - Daniel Roelfs
- Department of medicine, NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Nadine Parker
- Department of medicine, NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Mathias Valstad
- Department of medicine, NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
| | - Atle Pentz
- Department of medicine, NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Clara M. F. Timpe
- Department of medicine, NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Geneviève Richard
- Department of medicine, NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Dani Beck
- Department of medicine, NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
| | - Maren C. Frogner Werner
- Department of medicine, NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | | | - Ingrid Melle
- Department of medicine, NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ingrid Agartz
- Department of Psychiatry, Telemark Hospital, Skien, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Sciences, Stockholm Region, Sweden
| | - Lars T. Westlye
- Department of medicine, NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Nils Eiel Steen
- Department of medicine, NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ole A. Andreassen
- Department of medicine, NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Torgeir Moberget
- Department of medicine, NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Behavioral Sciences, Faculty of Health Sciences, Oslo Metropolitan University, OsloMet, Oslo, Norway
| | - Torbjørn Elvsåshagen
- Department of medicine, NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Neurology, Oslo University Hospital, Oslo, Norway
| | - Erik G. Jönsson
- Department of medicine, NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
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Dubey H, Sharma RK, Krishnan S, Knickmeyer R. SARS-CoV-2 (COVID-19) as a possible risk factor for neurodevelopmental disorders. Front Neurosci 2022; 16:1021721. [PMID: 36590303 PMCID: PMC9800937 DOI: 10.3389/fnins.2022.1021721] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Accepted: 11/28/2022] [Indexed: 12/23/2022] Open
Abstract
Pregnant women constitute one of the most vulnerable populations to be affected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, the cause of coronavirus disease 2019. SARS-CoV-2 infection during pregnancy could negatively impact fetal brain development via multiple mechanisms. Accumulating evidence indicates that mother to fetus transmission of SARS-CoV-2 does occur, albeit rarely. When it does occur, there is a potential for neuroinvasion via immune cells, retrograde axonal transport, and olfactory bulb and lymphatic pathways. In the absence of maternal to fetal transmission, there is still the potential for negative neurodevelopmental outcomes as a consequence of disrupted placental development and function leading to preeclampsia, preterm birth, and intrauterine growth restriction. In addition, maternal immune activation may lead to hypomyelination, microglial activation, white matter damage, and reduced neurogenesis in the developing fetus. Moreover, maternal immune activation can disrupt the maternal or fetal hypothalamic-pituitary-adrenal (HPA) axis leading to altered neurodevelopment. Finally, pro-inflammatory cytokines can potentially alter epigenetic processes within the developing brain. In this review, we address each of these potential mechanisms. We propose that SARS-CoV-2 could lead to neurodevelopmental disorders in a subset of pregnant women and that long-term studies are warranted.
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Affiliation(s)
- Harikesh Dubey
- Division of Neuroengineering, Institute for Quantitative Health Sciences and Engineering, Michigan State University, East Lansing, MI, United States
| | - Ravindra K. Sharma
- Department of Physiology and Functional Genomics, University of Florida College of Medicine, Gainesville, FL, United States
| | - Suraj Krishnan
- Jacobi Medical Center, Albert Einstein College of Medicine, The Bronx, NY, United States
| | - Rebecca Knickmeyer
- Division of Neuroengineering, Institute for Quantitative Health Sciences and Engineering, Michigan State University, East Lansing, MI, United States,Department of Pediatrics and Human Development, Michigan State University, East Lansing, MI, United States,*Correspondence: Rebecca Knickmeyer,
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Kia SM, Huijsdens H, Rutherford S, de Boer A, Dinga R, Wolfers T, Berthet P, Mennes M, Andreassen OA, Westlye LT, Beckmann CF, Marquand AF. Closing the life-cycle of normative modeling using federated hierarchical Bayesian regression. PLoS One 2022; 17:e0278776. [PMID: 36480551 PMCID: PMC9731431 DOI: 10.1371/journal.pone.0278776] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Accepted: 11/22/2022] [Indexed: 12/13/2022] Open
Abstract
Clinical neuroimaging data availability has grown substantially in the last decade, providing the potential for studying heterogeneity in clinical cohorts on a previously unprecedented scale. Normative modeling is an emerging statistical tool for dissecting heterogeneity in complex brain disorders. However, its application remains technically challenging due to medical data privacy issues and difficulties in dealing with nuisance variation, such as the variability in the image acquisition process. Here, we approach the problem of estimating a reference normative model across a massive population using a massive multi-center neuroimaging dataset. To this end, we introduce a federated probabilistic framework using hierarchical Bayesian regression (HBR) to complete the life-cycle of normative modeling. The proposed model provides the possibilities to learn, update, and adapt the model parameters on decentralized neuroimaging data. Our experimental results confirm the superiority of HBR in deriving more accurate normative ranges on large multi-site neuroimaging datasets compared to the current standard methods. In addition, our approach provides the possibility to recalibrate and reuse the learned model on local datasets and even on datasets with very small sample sizes. The proposed method will facilitate applications of normative modeling as a medical tool for screening the biological deviations in individuals affected by complex illnesses such as mental disorders.
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Affiliation(s)
- Seyed Mostafa Kia
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Department for Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Hester Huijsdens
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Saige Rutherford
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Department for Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Augustijn de Boer
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Richard Dinga
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Department for Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Thomas Wolfers
- Department of Psychology, University of Oslo, Oslo, Norway
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Pierre Berthet
- Department of Psychology, University of Oslo, Oslo, Norway
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Maarten Mennes
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Ole A. Andreassen
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Lars T. Westlye
- Department of Psychology, University of Oslo, Oslo, Norway
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Christian F. Beckmann
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Department for Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, The Netherlands
- Centre for Functional MRI of the Brain, University of Oxford, Oxford, United Kingdom
| | - Andre F. Marquand
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Department for Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Neuroimaging, Institute of Psychiatry, King’s College London, London, United Kingdom
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261
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Kruse AO, Bustillo JR. Glutamatergic dysfunction in Schizophrenia. Transl Psychiatry 2022; 12:500. [PMID: 36463316 PMCID: PMC9719533 DOI: 10.1038/s41398-022-02253-w] [Citation(s) in RCA: 49] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 11/05/2022] [Accepted: 11/09/2022] [Indexed: 12/04/2022] Open
Abstract
The NMDA-R hypofunction model of schizophrenia started with the clinical observation of the precipitation of psychotic symptoms in patients with schizophrenia exposed to PCP or ketamine. Healthy volunteers exposed to acute low doses of ketamine experienced mild psychosis but also negative and cognitive type symptoms reminiscent of the full clinical picture of schizophrenia. In rodents, acute systemic ketamine resulted in a paradoxical increase in extracellular frontal glutamate as well as of dopamine. Similar increase in prefrontal glutamate was documented with acute ketamine in healthy volunteers with 1H-MRS. Furthermore, sub-chronic low dose PCP lead to reductions in frontal dendritic tree density in rodents. In post-mortem ultrastructural studies in schizophrenia, a broad reduction in dendritic complexity and somal volume of pyramidal cells has been repeatedly described. This most likely accounts for the broad, subtle progressive cortical thinning described with MRI in- vivo. Additionally, prefrontal reductions in the obligatory GluN1 subunit of the NMDA-R has been repeatedly found in post-mortem tissue. The vast 1H-MRS literature in schizophrenia has documented trait-like small increases in glutamate concentrations in striatum very early in the illness, before antipsychotic treatment (the same structure where increased pre-synaptic release of dopamine has been reported with PET). The more recent genetic literature has reliably detected very small risk effects for common variants involving several glutamate-related genes. The pharmacological literature has followed two main tracks, directly informed by the NMDA-R hypo model: agonism at the glycine site (as mostly add-on studies targeting negative and cognitive symptoms); and pre-synaptic modulation of glutamatergic release (as single agents for acute psychosis). Unfortunately, both approaches have failed so far. There is little doubt that brain glutamatergic abnormalities are present in schizophrenia and that some of these are related to the etiology of the illness. The genetic literature directly supports a non- specific etiological role for glutamatergic dysfunction. Whether NMDA-R hypofunction as a specific mechanism accounts for any important component of the illness is still not evident. However, a glutamatergic model still has heuristic value to guide future research in schizophrenia. New tools to jointly examine brain glutamatergic, GABA-ergic and dopaminergic systems in-vivo, early in the illness, may lay the ground for a next generation of clinical trials that go beyond dopamine D2 blockade.
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Affiliation(s)
- Andreas O Kruse
- Department of Psychiatry and Behavioral Sciences, University of New Mexico, Albuquerque, NM, 87131, USA.
| | - Juan R Bustillo
- Department of Psychiatry and Behavioral Sciences, University of New Mexico, Albuquerque, NM, 87131, USA
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262
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Glenn DE, Merenstein JL, Bennett IJ, Michalska KJ. Anxiety symptoms and puberty interactively predict lower cingulum microstructure in preadolescent Latina girls. Sci Rep 2022; 12:20755. [PMID: 36456602 PMCID: PMC9713745 DOI: 10.1038/s41598-022-24803-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Accepted: 11/21/2022] [Indexed: 12/03/2022] Open
Abstract
Preadolescence is a period of increased vulnerability for anxiety, especially among Latina girls. Reduced microstructure (fractional anisotropy; FA) of white matter tracts between limbic and prefrontal regions may underlie regulatory impairments in anxiety. However, developmental research on the association between anxiety and white matter microstructure is mixed, possibly due to interactive influences with puberty. In a sample of 39 Latina girls (8-13 years), we tested whether pubertal stage moderated the association between parent- and child-reported anxiety symptoms and FA in the cingulum and uncinate fasciculus. Parent- but not child-reported anxiety symptoms predicted lower cingulum FA, and this effect was moderated by pubertal stage, such that this association was only significant for prepubertal girls. Neither anxiety nor pubertal stage predicted uncinate fasciculus FA. These findings suggest that anxiety is associated with disruptions in girls' cingulum white matter microstructure and that this relationship undergoes maturational changes during puberty.
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Affiliation(s)
- Dana E Glenn
- Department of Psychology, University of California, Riverside, 900 University Avenue, Riverside, CA, 92521, USA.
| | - Jenna L Merenstein
- Department of Psychology, University of California, Riverside, 900 University Avenue, Riverside, CA, 92521, USA
- Brain Imaging and Analysis Center, Duke University, Durham, NC, USA
| | - Ilana J Bennett
- Department of Psychology, University of California, Riverside, 900 University Avenue, Riverside, CA, 92521, USA
| | - Kalina J Michalska
- Department of Psychology, University of California, Riverside, 900 University Avenue, Riverside, CA, 92521, USA
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263
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Roeckner AR, Sogani S, Michopoulos V, Hinrichs R, van Rooij SJH, Rothbaum BO, Jovanovic T, Ressler KJ, Stevens JS. Sex-dependent risk factors for PTSD: a prospective structural MRI study. Neuropsychopharmacology 2022; 47:2213-2220. [PMID: 36114284 PMCID: PMC9630503 DOI: 10.1038/s41386-022-01452-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Revised: 08/18/2022] [Accepted: 09/01/2022] [Indexed: 11/09/2022]
Abstract
Female individuals are more likely to be diagnosed with PTSD following trauma exposure than males, potentially due, in part, to underlying neurobiological factors. Several brain regions underlying fear learning and expression have previously been associated with PTSD, with the hippocampus, amygdala, dorsal anterior cingulate cortex (dACC), and rostral ACC (rACC) showing altered volume and function in those with PTSD. However, few studies have examined how sex impacts the predictive value of subcortical volumes and cortical thickness in longitudinal PTSD studies. As part of an emergency department study completed at the Grady Trauma Project in Atlanta, GA, N = 93 (40 Female) participants were enrolled within 24 h following a traumatic event. Multi-echo T1-weighted MRI images were collected one-month post-trauma exposure. Bilateral amygdala and hippocampal volumes and rACC and dACC cortical thickness were segmented. To assess the longitudinal course of PTSD, the PTSD Symptom Scale (PSS) was collected 6 months post-trauma. We investigated whether regional volume/thickness interacted with sex to predict later PTSD symptom severity, controlling for PSS score at time of scan, age, race, and trauma type, as well as intracranial volume (ICV) for subcortical volumes. There was a significant interaction between sex and rACC for 6-month PSS, such that right rACC thickness was positively correlated with 6-month PSS scores in females, but not in males. In examining PTSD symptom subtypes and depression symptoms, greater rACC thickness in females predicted greater avoidance symptoms, while smaller rACC thickness in males predicted greater depression symptoms. Amygdala and hippocampus volume and dACC thickness showed no main effect or interaction with sex. The current findings provide evidence for sex-based differences in how brain volume predicts future PTSD severity and symptoms and supports the rACC as being a vital region regarding PTSD. Gender differences should be assessed in future longitudinal PTSD MRI studies for more accurate identification of future PTSD risk following trauma.
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264
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Salvador R, García-León MÁ, Feria-Raposo I, Botillo-Martín C, Martín-Lorenzo C, Corte-Souto C, Aguilar-Valero T, Gil-Sanz D, Porta-Pelayo D, Martín-Carrasco M, Del Olmo-Romero F, Maria Santiago-Bautista J, Herrero-Muñecas P, Castillo-Oramas E, Larrubia-Romero J, Rios-Alvarado Z, Antonio Larraz-Romeo J, Guardiola-Ripoll M, Almodóvar-Payá C, Fatjó-Vilas Mestre M, Sarró S, McKenna PJ, Pomarol-Clotet E, María Castells Bescos E, Felipe Martínez E, Muñoz Hermoso P, Camaño Serna C, Rebolleda Gil C, Feliz Muñoz C, Sevillano De La Fuente P, Sánchez Perez M, Arrece Iriondo I, Vicente Jauregui Berecibar J, Domínguez Panchón A, Felices de la Fuente A, Bosque Gabarre C, Pomarol-Clotet E, HHFingerprints Group. Fingerprints as Predictors of Schizophrenia: A Deep Learning Study. Schizophr Bull 2022; 49:738-745. [PMID: 36444899 PMCID: PMC10154725 DOI: 10.1093/schbul/sbac173] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
BACKGROUND AND HYPOTHESIS The existing developmental bond between fingerprint generation and growth of the central nervous system points to a potential use of fingerprints as risk markers in schizophrenia. However, the high complexity of fingerprints geometrical patterns may require flexible algorithms capable of characterizing such complexity. STUDY DESIGN Based on an initial sample of scanned fingerprints from 612 patients with a diagnosis of non-affective psychosis and 844 healthy subjects, we have built deep learning classification algorithms based on convolutional neural networks. Previously, the general architecture of the network was chosen from exploratory fittings carried out with an independent fingerprint dataset from the National Institute of Standards and Technology. The network architecture was then applied for building classification algorithms (patients vs controls) based on single fingers and multi-input models. Unbiased estimates of classification accuracy were obtained by applying a 5-fold cross-validation scheme. STUDY RESULTS The highest level of accuracy from networks based on single fingers was achieved by the right thumb network (weighted validation accuracy = 68%), while the highest accuracy from the multi-input models was attained by the model that simultaneously used images from the left thumb, index and middle fingers (weighted validation accuracy = 70%). CONCLUSION Although fitted models were based on data from patients with a well established diagnosis, since fingerprints remain lifelong stable after birth, our results imply that fingerprints may be applied as early predictors of psychosis. Specially, if they are used in high prevalence subpopulations such as those of individuals at high risk for psychosis.
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Affiliation(s)
- Raymond Salvador
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | - María Ángeles García-León
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | - Isabel Feria-Raposo
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain.,Benito Menni Complex Assistencial en Salut Mental, Barcelona, Spain.,Unidad de Investigación en Cuidados y Servicios de Salud, Instituto de Salud Carlos III (Investén-ISCIII), Madrid, Spain
| | | | | | | | | | - David Gil-Sanz
- Centro Hospitalario Padre Menni, Santander, Spain.,Universidad Europea del Atlántico, Santander, Spain
| | | | | | - Francisco Del Olmo-Romero
- Complejo Asistencial Benito Menni, Ciempozuelos, Madrid, Spain.,Clínica San Miguel Hermanas Hospitalarias, Madrid, Spain
| | | | | | | | | | | | | | - Maria Guardiola-Ripoll
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | - Carmen Almodóvar-Payá
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | - Mar Fatjó-Vilas Mestre
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain.,Departament de Biologia Evolutiva, Ecologia i Ciències Ambientals, Facultat de Biologia, Universitat de Barcelona, Barcelona, Spain
| | - Salvador Sarró
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | - Peter J McKenna
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | | | - Edith Pomarol-Clotet
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | | | | | | | | | | | | | | | | | | | | | | | | | | | - Edith Pomarol-Clotet
- FIDMAG Germanes Hospitalàries Research Foundation , Barcelona , Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III , Madrid , Spain
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265
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Hallucinations and Brain Morphology Across Early Adolescence: A Longitudinal Neuroimaging Study. Biol Psychiatry 2022; 92:781-790. [PMID: 35871096 DOI: 10.1016/j.biopsych.2022.05.013] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Revised: 04/27/2022] [Accepted: 05/09/2022] [Indexed: 01/11/2023]
Abstract
BACKGROUND Psychotic disorders have been widely associated with structural brain abnormalities. However, it is unclear whether brain structure predicts psychotic experiences in youth from the general population, owing to an overall paucity of studies and predominantly cross-sectional designs. Here, the authors investigated longitudinal associations between brain morphology and hallucinations from childhood to early adolescence. METHODS This study was embedded in the population-based Generation R Study. Children underwent structural neuroimaging at age 10 years (N = 2042); a subsample received a second scan at age 14 years (n = 964). Hallucinations were assessed at ages 10 and 14 years and studied as a binary variable. Cross-lagged panel models and generalized linear mixed-effects models were fitted to examine longitudinal associations between brain morphology and hallucinations. RESULTS Smaller total gray and white matter volumes and total cortical surface area at baseline were associated with a higher occurrence of hallucinations between ages 10 and 14 years. The regions associated with hallucinations were widespread, including the frontal, parietal, temporal, and occipital lobes, as well as the insula and cingulate cortex. Analyses of subcortical structures revealed that smaller baseline hippocampal volumes were longitudinally associated with hallucinations, although this association was no longer significant following adjustment for intracranial volume. No evidence for reverse temporality was observed (i.e., hallucinations predicting brain differences). CONCLUSIONS The findings from this longitudinal study suggest that global structural brain differences are associated with the development of hallucinations. These results extend findings from clinical populations and provide evidence for a neurodevelopmental vulnerability across the psychosis continuum.
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266
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Chang X, Zhao W, Kang J, Xiang S, Xie C, Corona-Hernández H, Palaniyappan L, Feng J. Language abnormalities in schizophrenia: binding core symptoms through contemporary empirical evidence. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2022; 8:95. [PMID: 36371445 PMCID: PMC9653408 DOI: 10.1038/s41537-022-00308-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Accepted: 10/26/2022] [Indexed: 06/16/2023]
Abstract
Both the ability to speak and to infer complex linguistic messages from sounds have been claimed as uniquely human phenomena. In schizophrenia, formal thought disorder (FTD) and auditory verbal hallucinations (AVHs) are manifestations respectively relating to concrete disruptions of those abilities. From an evolutionary perspective, Crow (1997) proposed that "schizophrenia is the price that Homo sapiens pays for the faculty of language". Epidemiological and experimental evidence points to an overlap between FTD and AVHs, yet a thorough investigation examining their shared neural mechanism in schizophrenia is lacking. In this review, we synthesize observations from three key domains. First, neuroanatomical evidence indicates substantial shared abnormalities in language-processing regions between FTD and AVHs, even in the early phases of schizophrenia. Second, neurochemical studies point to a glutamate-related dysfunction in these language-processing brain regions, contributing to verbal production deficits. Third, genetic findings further show how genes that overlap between schizophrenia and language disorders influence neurodevelopment and neurotransmission. We argue that these observations converge into the possibility that a glutamatergic dysfunction in language-processing brain regions might be a shared neural basis of both FTD and AVHs. Investigations of language pathology in schizophrenia could facilitate the development of diagnostic tools and treatments, so we call for multilevel confirmatory analyses focused on modulations of the language network as a therapeutic goal in schizophrenia.
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Affiliation(s)
- Xiao Chang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
- Zhangjiang Fudan International Innovation Center, Shanghai, China
| | - Wei Zhao
- MOE-LCSM, School of Mathematics and Statistics, Hunan Normal University, Changsha, PR China
| | - Jujiao Kang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
- Shanghai Center for Mathematical Sciences, Shanghai, China
| | - Shitong Xiang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
| | - Chao Xie
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
| | - Hugo Corona-Hernández
- Department of Biomedical Sciences of Cells & Systems, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Lena Palaniyappan
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, Quebec, Canada.
- Robarts Research Institute, University of Western Ontario, London, Ontario, Canada.
- Lawson Health Research Institute, London, Ontario, Canada.
| | - Jianfeng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China.
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.
- Zhangjiang Fudan International Innovation Center, Shanghai, China.
- Shanghai Center for Mathematical Sciences, Shanghai, China.
- Department of Computer Science, University of Warwick, Coventry, UK.
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267
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Hettwer MD, Larivière S, Park BY, van den Heuvel OA, Schmaal L, Andreassen OA, Ching CRK, Hoogman M, Buitelaar J, van Rooij D, Veltman DJ, Stein DJ, Franke B, van Erp TGM, Jahanshad N, Thompson PM, Thomopoulos SI, Bethlehem RAI, Bernhardt BC, Eickhoff SB, Valk SL. Coordinated cortical thickness alterations across six neurodevelopmental and psychiatric disorders. Nat Commun 2022; 13:6851. [PMID: 36369423 PMCID: PMC9652311 DOI: 10.1038/s41467-022-34367-6] [Citation(s) in RCA: 50] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Accepted: 10/24/2022] [Indexed: 11/13/2022] Open
Abstract
Neuropsychiatric disorders are increasingly conceptualized as overlapping spectra sharing multi-level neurobiological alterations. However, whether transdiagnostic cortical alterations covary in a biologically meaningful way is currently unknown. Here, we studied co-alteration networks across six neurodevelopmental and psychiatric disorders, reflecting pathological structural covariance. In 12,024 patients and 18,969 controls from the ENIGMA consortium, we observed that co-alteration patterns followed normative connectome organization and were anchored to prefrontal and temporal disease epicenters. Manifold learning revealed frontal-to-temporal and sensory/limbic-to-occipitoparietal transdiagnostic gradients, differentiating shared illness effects on cortical thickness along these axes. The principal gradient aligned with a normative cortical thickness covariance gradient and established a transcriptomic link to cortico-cerebello-thalamic circuits. Moreover, transdiagnostic gradients segregated functional networks involved in basic sensory, attentional/perceptual, and domain-general cognitive processes, and distinguished between regional cytoarchitectonic profiles. Together, our findings indicate that shared illness effects occur in a synchronized fashion and along multiple levels of hierarchical cortical organization.
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Affiliation(s)
- M D Hettwer
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.
- Max Planck School of Cognition, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
- Institute of Neuroscience and Medicine, Brain & Behavior (INM-7), Research Centre Jülich, Jülich, Germany.
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
| | - S Larivière
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - B Y Park
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
- Department of Data Science, Inha University, Incheon, Republic of Korea
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea
| | - O A van den Heuvel
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Anatomy and Neuroscience and Psychiatry, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - L Schmaal
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, VIC, Australia
- Orygen, Parkville, VIC, Australia
| | - O A Andreassen
- NORMENT Centre, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - C R K Ching
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - M Hoogman
- Departments of Psychiatry and Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - J Buitelaar
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - D van Rooij
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - D J Veltman
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Anatomy and Neuroscience and Psychiatry, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - D J Stein
- South African Medical Research Council Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry & Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - B Franke
- Departments of Psychiatry and Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - T G M van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine Hall, Irvine, CA, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, Irvine, CA, USA
| | - N Jahanshad
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - P M Thompson
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - S I Thomopoulos
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - R A I Bethlehem
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - B C Bernhardt
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - S B Eickhoff
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Institute of Neuroscience and Medicine, Brain & Behavior (INM-7), Research Centre Jülich, Jülich, Germany
| | - S L Valk
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.
- Institute of Neuroscience and Medicine, Brain & Behavior (INM-7), Research Centre Jülich, Jülich, Germany.
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
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Rootes-Murdy K, Edmond JT, Jiang W, Rahaman MA, Chen J, Perrone-Bizzozero NI, Calhoun VD, van Erp TGM, Ehrlich S, Agartz I, Jönsson EG, Andreassen OA, Westlye LT, Wang L, Pearlson GD, Glahn DC, Hong E, Buchanan RW, Kochunov P, Voineskos A, Malhotra A, Tamminga CA, Liu J, Turner JA. Clinical and cortical similarities identified between bipolar disorder I and schizophrenia: A multivariate approach. Front Hum Neurosci 2022; 16:1001692. [PMID: 36438633 PMCID: PMC9684186 DOI: 10.3389/fnhum.2022.1001692] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2022] [Accepted: 10/17/2022] [Indexed: 01/06/2024] Open
Abstract
BACKGROUND Structural neuroimaging studies have identified similarities in the brains of individuals diagnosed with schizophrenia (SZ) and bipolar I disorder (BP), with overlap in regions of gray matter (GM) deficits between the two disorders. Recent studies have also shown that the symptom phenotypes associated with SZ and BP may allow for a more precise categorization than the current diagnostic criteria. In this study, we sought to identify GM alterations that were unique to each disorder and whether those alterations were also related to unique symptom profiles. MATERIALS AND METHODS We analyzed the GM patterns and clinical symptom presentations using independent component analysis (ICA), hierarchical clustering, and n-way biclustering in a large (N ∼ 3,000), merged dataset of neuroimaging data from healthy volunteers (HV), and individuals with either SZ or BP. RESULTS Component A showed a SZ and BP < HV GM pattern in the bilateral insula and cingulate gyrus. Component B showed a SZ and BP < HV GM pattern in the cerebellum and vermis. There were no significant differences between diagnostic groups in these components. Component C showed a SZ < HV and BP GM pattern bilaterally in the temporal poles. Hierarchical clustering of the PANSS scores and the ICA components did not yield new subgroups. N-way biclustering identified three unique subgroups of individuals within the sample that mapped onto different combinations of ICA components and symptom profiles categorized by the PANSS but no distinct diagnostic group differences. CONCLUSION These multivariate results show that diagnostic boundaries are not clearly related to structural differences or distinct symptom profiles. Our findings add support that (1) BP tend to have less severe symptom profiles when compared to SZ on the PANSS without a clear distinction, and (2) all the gray matter alterations follow the pattern of SZ < BP < HV without a clear distinction between SZ and BP.
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Affiliation(s)
- Kelly Rootes-Murdy
- Department of Psychology, Georgia State University, Atlanta, GA, United States
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, Georgia State University, Emory University, Atlanta, GA, United States
| | - Jesse T. Edmond
- Department of Psychology, Georgia State University, Atlanta, GA, United States
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, Georgia State University, Emory University, Atlanta, GA, United States
| | - Wenhao Jiang
- Department of Psychosomatics and Psychiatry, Medical School, Zhongda Hospital, Institute of Psychosomatics, Southeast University, Nanjing, China
| | - Md A. Rahaman
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, Georgia State University, Emory University, Atlanta, GA, United States
| | - Jiayu Chen
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, Georgia State University, Emory University, Atlanta, GA, United States
| | | | - Vince D. Calhoun
- Department of Psychology, Georgia State University, Atlanta, GA, United States
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, Georgia State University, Emory University, Atlanta, GA, United States
| | - Theo G. M. van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California, Irvine, Irvine, CA, United States
- Center for the Neurobiology of Learning and Memory, University of California, Irvine, Irvine, CA, United States
| | - Stefan Ehrlich
- Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Dresden, Germany
| | - Ingrid Agartz
- Division of Mental Health and Addiction, Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, Oslo University Hospital, University of Oslo, Oslo, Norway
- Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institute and Stockholm Health Care Services, Stockholm, Sweden
- K. G. Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
| | - Erik G. Jönsson
- Division of Mental Health and Addiction, Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, Oslo University Hospital, University of Oslo, Oslo, Norway
- Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institute and Stockholm Health Care Services, Stockholm, Sweden
| | - Ole A. Andreassen
- Division of Mental Health and Addiction, Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, Oslo University Hospital, University of Oslo, Oslo, Norway
- K. G. Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Lars T. Westlye
- Division of Mental Health and Addiction, Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, Oslo University Hospital, University of Oslo, Oslo, Norway
- K. G. Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Lei Wang
- Psychiatry and Behavioral Health, Ohio State Wexner Medical Center, Columbus, OH, United States
| | - Godfrey D. Pearlson
- Department of Psychiatry, Yale University, New Haven, CT, United States
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford Hospital, Hartford, CT, United States
| | - David C. Glahn
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford Hospital, Hartford, CT, United States
- Boston Children’s Hospital and Harvard Medical School, Boston, MA, United States
| | - Elliot Hong
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Robert W. Buchanan
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Peter Kochunov
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Aristotle Voineskos
- Department of Psychiatry, Centre for Addiction and Mental Health, University of Toronto, Toronto, ON, Canada
| | - Anil Malhotra
- Division of Psychiatry Research, Zucker Hillside Hospital, Queens, NY, United States
| | - Carol A. Tamminga
- Department of Psychiatry, University of Texas Southwestern Medical School, Dallas, TX, United States
| | - Jingyu Liu
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, Georgia State University, Emory University, Atlanta, GA, United States
| | - Jessica A. Turner
- Psychiatry and Behavioral Health, Ohio State Wexner Medical Center, Columbus, OH, United States
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269
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Grey matter volume and its association with cognitive impairment and peripheral cytokines in excited individuals with schizophrenia. Brain Imaging Behav 2022; 16:2618-2626. [DOI: 10.1007/s11682-022-00717-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/14/2022] [Indexed: 11/09/2022]
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270
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Lloyd EC. Large-Scale Analysis of Brain Morphometry in Anorexia Nervosa. Biol Psychiatry 2022; 92:e41-e42. [PMID: 36202545 PMCID: PMC11060508 DOI: 10.1016/j.biopsych.2022.07.026] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/16/2022] [Accepted: 07/22/2022] [Indexed: 11/30/2022]
Affiliation(s)
- E Caitlin Lloyd
- Department of Psychiatry, Columbia University Irving Medical Center, New York, and the New York State Psychiatric Institute, New York, New York.
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271
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Hansen JY, Shafiei G, Markello RD, Smart K, Cox SML, Nørgaard M, Beliveau V, Wu Y, Gallezot JD, Aumont É, Servaes S, Scala SG, DuBois JM, Wainstein G, Bezgin G, Funck T, Schmitz TW, Spreng RN, Galovic M, Koepp MJ, Duncan JS, Coles JP, Fryer TD, Aigbirhio FI, McGinnity CJ, Hammers A, Soucy JP, Baillet S, Guimond S, Hietala J, Bedard MA, Leyton M, Kobayashi E, Rosa-Neto P, Ganz M, Knudsen GM, Palomero-Gallagher N, Shine JM, Carson RE, Tuominen L, Dagher A, Misic B. Mapping neurotransmitter systems to the structural and functional organization of the human neocortex. Nat Neurosci 2022; 25:1569-1581. [PMID: 36303070 PMCID: PMC9630096 DOI: 10.1038/s41593-022-01186-3] [Citation(s) in RCA: 265] [Impact Index Per Article: 88.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Accepted: 09/20/2022] [Indexed: 01/13/2023]
Abstract
Neurotransmitter receptors support the propagation of signals in the human brain. How receptor systems are situated within macro-scale neuroanatomy and how they shape emergent function remain poorly understood, and there exists no comprehensive atlas of receptors. Here we collate positron emission tomography data from more than 1,200 healthy individuals to construct a whole-brain three-dimensional normative atlas of 19 receptors and transporters across nine different neurotransmitter systems. We found that receptor profiles align with structural connectivity and mediate function, including neurophysiological oscillatory dynamics and resting-state hemodynamic functional connectivity. Using the Neurosynth cognitive atlas, we uncovered a topographic gradient of overlapping receptor distributions that separates extrinsic and intrinsic psychological processes. Finally, we found both expected and novel associations between receptor distributions and cortical abnormality patterns across 13 disorders. We replicated all findings in an independently collected autoradiography dataset. This work demonstrates how chemoarchitecture shapes brain structure and function, providing a new direction for studying multi-scale brain organization.
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Affiliation(s)
- Justine Y Hansen
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Golia Shafiei
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Ross D Markello
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Kelly Smart
- Yale PET Center, Yale School of Medicine, New Haven, CT, USA
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - Sylvia M L Cox
- Department of Psychiatry, McGill University, Montréal, QC, Canada
| | - Martin Nørgaard
- Department of Psychology, Center for Reproducible Neuroscience, Stanford University, Stanford, CA, USA
- Neurobiology Research Unit, Cimbi & OpenNeuroPET, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
| | - Vincent Beliveau
- Neurobiology Research Unit, Cimbi & OpenNeuroPET, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | - Yanjun Wu
- Yale PET Center, Yale School of Medicine, New Haven, CT, USA
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - Jean-Dominique Gallezot
- Yale PET Center, Yale School of Medicine, New Haven, CT, USA
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - Étienne Aumont
- Cognitive Pharmacology Research Unit, UQAM, Montréal, QC, Canada
| | - Stijn Servaes
- McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montréal, QC, Canada
| | | | | | | | - Gleb Bezgin
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
- McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montréal, QC, Canada
| | - Thomas Funck
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
| | - Taylor W Schmitz
- Department of Physiology and Pharmacology, University of Western Ontario, London, ON, Canada
| | - R Nathan Spreng
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Marian Galovic
- Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich, Zurich, Switzerland
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Chalfont Centre for Epilepsy, Chalfont Saint Peter, UK
| | - Matthias J Koepp
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Chalfont Centre for Epilepsy, Chalfont Saint Peter, UK
| | - John S Duncan
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Chalfont Centre for Epilepsy, Chalfont Saint Peter, UK
| | - Jonathan P Coles
- Department of Medicine, Division of Anaesthesia, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
| | - Tim D Fryer
- Department of Clinical Neurosciences, Wolfson Brain Imaging Centre, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
| | - Franklin I Aigbirhio
- Department of Clinical Neurosciences, Wolfson Brain Imaging Centre, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
| | - Colm J McGinnity
- King's College London and Guy's and St. Thomas' PET Centre, Division of Imaging Sciences and Biomedical Engineering, King's College London, London, UK
| | - Alexander Hammers
- King's College London and Guy's and St. Thomas' PET Centre, Division of Imaging Sciences and Biomedical Engineering, King's College London, London, UK
| | - Jean-Paul Soucy
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Sylvain Baillet
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Synthia Guimond
- Department of Psychiatry, Royal's Institute of Mental Health Research, University of Ottawa, Ottawa, ON, Canada
- Department of Psychoeducation and Psychology, University of Quebec in Outaouais, Gatineau, QC, Canada
| | - Jarmo Hietala
- Department of Psychiatry, University of Turku and Turku University Hospital, Turku, Finland
| | - Marc-André Bedard
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
- Cognitive Pharmacology Research Unit, UQAM, Montréal, QC, Canada
| | - Marco Leyton
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
- Department of Psychiatry, McGill University, Montréal, QC, Canada
| | - Eliane Kobayashi
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Pedro Rosa-Neto
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
- McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montréal, QC, Canada
| | - Melanie Ganz
- Neurobiology Research Unit, Cimbi & OpenNeuroPET, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
| | - Gitte M Knudsen
- Neurobiology Research Unit, Cimbi & OpenNeuroPET, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Nicola Palomero-Gallagher
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
- C. and O. Vogt Institute for Brain Research, Medical Faculty, University Hospital Düsseldorf, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
| | - James M Shine
- Brain and Mind Centre, University of Sydney, Sydney, NSW, Australia
| | - Richard E Carson
- Yale PET Center, Yale School of Medicine, New Haven, CT, USA
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - Lauri Tuominen
- Department of Psychiatry, Royal's Institute of Mental Health Research, University of Ottawa, Ottawa, ON, Canada
| | - Alain Dagher
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Bratislav Misic
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada.
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272
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Chesters RA, Pepper F, Morgan C, Cooper JD, Howes OD, Vernon AC, Stone JM. Brain volume in chronic ketamine users - relationship to sub-threshold psychotic symptoms and relevance to schizophrenia. Psychopharmacology (Berl) 2022; 239:3421-3429. [PMID: 34228135 PMCID: PMC9584979 DOI: 10.1007/s00213-021-05873-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Accepted: 05/05/2021] [Indexed: 11/23/2022]
Abstract
RATIONALE Ketamine may model aspects of schizophrenia arising through NMDA receptor activity deficits. Although acute ketamine can induce effects resembling both positive and negative psychotic symptoms, chronic use may be a closer model of idiopathic psychosis. OBJECTIVES We tested the hypotheses that ketamine users had lower brain volumes, as measured using MRI, and greater sub-threshold psychotic symptoms relative to a poly-drug user control group. METHODS Ketamine users (n = 17) and poly-drug using controls (n = 19) were included in the study. All underwent volumetric MRI imaging and measurement of sub-threshold psychotic symptoms using the Comprehensive Assessment of At-Risk Mental State (CAARMS). Freesurfer was used to analyse differences in regional brain volume, cortical surface area and thickness between ketamine users and controls. The relationship between CAARMS ratings and brain volume was also investigated in ketamine users. RESULTS Ketamine users were found to have significantly lower grey matter volumes of the nucleus accumbens, caudate nucleus, cerebellum and total cortex (FDR p < 0.05; Cohen's d = 0.36-0.75). Within the cortex, ketamine users had significantly lower grey matter volumes within the frontal, temporal and parietal cortices (Cohen's d 0.7-1.31; FDR p < 0.05). They also had significantly higher sub-threshold psychotic symptoms (p < 0.05). Frequency of ketamine use showed an inverse correlation with cerebellar volume (p < 0.001), but there was no relationship between regional brain volumes and sub-threshold psychotic symptoms. CONCLUSIONS Chronic ketamine use may cause lower grey matter volumes as well as inducing sub-threshold psychotic symptoms, although these likely arise through distinct mechanisms.
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Affiliation(s)
- Robert A Chesters
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, London, SE5 8AF, UK
| | - Fiona Pepper
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, London, SE5 8AF, UK
| | | | - Jonathan D Cooper
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, London, SE5 8AF, UK
- Departments of Pediatrics, Genetics and Neurology, Medical School, Washington University in St Louis, 660S Euclid Ave, St Louis, MO, 63110, USA
| | - Oliver D Howes
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, London, SE5 8AF, UK
- South London and Maudsley NHS Trust, London, SE5 8AZ, UK
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, SE1 1UL, UK
| | - Anthony C Vernon
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, London, SE5 8AF, UK
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, SE1 1UL, UK
| | - James M Stone
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, London, SE5 8AF, UK.
- South London and Maudsley NHS Trust, London, SE5 8AZ, UK.
- Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, Falmer, BN1 9RY, UK.
- Sussex Partnership NHS Foundation Trust, Eastbourne, BN21 2UD, UK.
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273
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Ghosh A, Kaur S, Shah R, Oomer F, Avasthi A, Ahuja CK, Basu D, Nehra R, Khandelwal N. Surface-based brain morphometry in schizophrenia vs. cannabis-induced psychosis: A controlled comparison. J Psychiatr Res 2022; 155:286-294. [PMID: 36170756 DOI: 10.1016/j.jpsychires.2022.09.034] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 08/19/2022] [Accepted: 09/16/2022] [Indexed: 10/31/2022]
Abstract
BACKGROUND & AIM We examined group differences in cortical thickness and surface-parameters among age and handedness--matched persons with cannabis-induced psychosis (CIP), schizophrenia with heavy cannabis use (SZC), and healthy controls (HC). METHODS We recruited 31 men with SZC, 28 with CIP, and 30 with HC. We used the Psychiatric Research Interview for Substance and Mental Disorders to differentiate between CIP and SZC. We processed and analyzed T1 MR images using the Surface-based Brain Morphometry (SBM) pipeline of the CAT-12 toolbox within the statistical parametric mapping. After pre-processing, volumes were segmented using surface and thickness estimation for the analysis of the region of interest. We used the projection-based thickness method to assess the cortical thickness and Desikan-Killiany atlas for cortical parcellation. RESULTS We observed the lowest cortical thickness, depth, and gyrification in the SZC, followed by CIP and the control groups. The differences were predominantly seen in frontal cortices, with limited parietal and temporal regions involvement. After False Discovery Rate (FDR) corrections and post-hoc analysis, SZC had reduced cortical thickness than HC in the middle and inferior frontal, right entorhinal, and left postcentral regions. Cortical thickness of SZC was also significantly lower than CIP in bilateral postcentral and right middle frontal regions. We found negative correlations (after FDR corrections) between the duration of cannabis use and cortical thickness in loci of parietal and occipital cortices. CONCLUSION Our study suggested cortical structural abnormalities in schizophrenia, in reference to healthy controls and cannabis-induced psychosis, indicating different pathophysiology of SZC and CIP.
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Affiliation(s)
- Abhishek Ghosh
- Drug De-addiction and Treatment Centre, Department of Psychiatry, Postgraduate Institute of Medical Education and Research, Chandigarh, India.
| | - Simranjit Kaur
- Thapar Institute of Engineering and Technology, Punjab, India
| | - Raghav Shah
- Drug De-addiction and Treatment Centre, Department of Psychiatry, Postgraduate Institute of Medical Education and Research, Chandigarh, India
| | - Fareed Oomer
- Chasefarm Hospital, Barnet, Enfield & Haringey Mental Health Trust, Enfield, UK
| | - Ajit Avasthi
- Department of Psychiatry, Postgraduate Institute of Medical Education & Research, Chandigarh, India
| | - Chirag K Ahuja
- Department of Radio-diagnosis and Imaging, Postgraduate Institute of Medical Education & Research, Chandigarh, India
| | - Debasish Basu
- Chasefarm Hospital, Barnet, Enfield & Haringey Mental Health Trust, Enfield, UK
| | - Ritu Nehra
- Department of Psychiatry, Postgraduate Institute of Medical Education & Research, Chandigarh, India
| | - Niranjan Khandelwal
- Department of Radio-diagnosis and Imaging, Postgraduate Institute of Medical Education & Research, Chandigarh, India
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274
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Kochunov P, Ma Y, Hatch KS, Gao S, Jahanshad N, Thompson PM, Adhikari BM, Bruce H, Van der vaart A, Goldwaser EL, Sotiras A, Kvarta MD, Ma T, Chen S, Nichols TE, Hong LE. Brain-wide versus genome-wide vulnerability biomarkers for severe mental illnesses. Hum Brain Mapp 2022; 43:4970-4983. [PMID: 36040723 PMCID: PMC9582367 DOI: 10.1002/hbm.26056] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 07/21/2022] [Accepted: 08/02/2022] [Indexed: 01/06/2023] Open
Abstract
Severe mental illnesses (SMI), including major depressive (MDD), bipolar (BD), and schizophrenia spectrum (SSD) disorders have multifactorial risk factors and capturing their complex etiopathophysiology in an individual remains challenging. Regional vulnerability index (RVI) was used to measure individual's brain-wide similarity to the expected SMI patterns derived from meta-analytical studies. It is analogous to polygenic risk scores (PRS) that measure individual's similarity to genome-wide patterns in SMI. We hypothesized that RVI is an intermediary phenotype between genome and symptoms and is sensitive to both genetic and environmental risks for SMI. UK Biobank sample of N = 17,053/19,265 M/F (age = 64.8 ± 7.4 years) and an independent sample of SSD patients and controls (N = 115/111 M/F, age = 35.2 ± 13.4) were used to test this hypothesis. UKBB participants with MDD had significantly higher RVI-MDD (Cohen's d = 0.20, p = 1 × 10-23 ) and PRS-MDD (d = 0.17, p = 1 × 10-15 ) than nonpsychiatric controls. UKBB participants with BD and SSD showed significant elevation in the respective RVIs (d = 0.65 and 0.60; p = 3 × 10-5 and .009, respectively) and PRS (d = 0.57 and 1.34; p = .002 and .002, respectively). Elevated RVI-SSD were replicated in an independent sample (d = 0.53, p = 5 × 10-5 ). RVI-MDD and RVI-SSD but not RVI-BD were associated with childhood adversity (p < .01). In nonpsychiatric controls, elevation in RVI and PRS were associated with lower cognitive performance (p < 10-5 ) in six out of seven domains and showed specificity with disorder-associated deficits. In summary, the RVI is a novel brain index for SMI and shows similar or better specificity for SMI than PRS, and together they may complement each other in the efforts to characterize the genomic to brain level risks for SMI.
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Affiliation(s)
- Peter Kochunov
- Maryland Psychiatric Research Center, Department of PsychiatryUniversity of Maryland School of MedicineBaltimoreMarylandUSA
| | - Yizhou Ma
- Maryland Psychiatric Research Center, Department of PsychiatryUniversity of Maryland School of MedicineBaltimoreMarylandUSA
| | - Kathryn S. Hatch
- Maryland Psychiatric Research Center, Department of PsychiatryUniversity of Maryland School of MedicineBaltimoreMarylandUSA
| | - Si Gao
- Maryland Psychiatric Research Center, Department of PsychiatryUniversity of Maryland School of MedicineBaltimoreMarylandUSA
| | - Neda Jahanshad
- Imaging Genetics Center, Stevens Neuroimaging & Informatics InstituteKeck School of Medicine of USCLos AngelesCaliforniaUSA
| | - Paul M. Thompson
- Imaging Genetics Center, Stevens Neuroimaging & Informatics InstituteKeck School of Medicine of USCLos AngelesCaliforniaUSA
| | - Bhim M. Adhikari
- Maryland Psychiatric Research Center, Department of PsychiatryUniversity of Maryland School of MedicineBaltimoreMarylandUSA
| | - Heather Bruce
- Maryland Psychiatric Research Center, Department of PsychiatryUniversity of Maryland School of MedicineBaltimoreMarylandUSA
| | - Andrew Van der vaart
- Maryland Psychiatric Research Center, Department of PsychiatryUniversity of Maryland School of MedicineBaltimoreMarylandUSA
| | - Eric L. Goldwaser
- Maryland Psychiatric Research Center, Department of PsychiatryUniversity of Maryland School of MedicineBaltimoreMarylandUSA
| | - Aris Sotiras
- Institute of Informatics, University of WashingtonSchool of MedicineSt. LouisMissouriUSA
| | - Mark D. Kvarta
- Maryland Psychiatric Research Center, Department of PsychiatryUniversity of Maryland School of MedicineBaltimoreMarylandUSA
| | - Tianzhou Ma
- Department of Epidemiology and BiostatisticsUniversity of MarylandCollege ParkMarylandUSA
| | - Shuo Chen
- Maryland Psychiatric Research Center, Department of PsychiatryUniversity of Maryland School of MedicineBaltimoreMarylandUSA
| | - Thomas E. Nichols
- Nuffield Department of Population HealthUniversity of OxfordOxfordUK
| | - L. Elliot Hong
- Maryland Psychiatric Research Center, Department of PsychiatryUniversity of Maryland School of MedicineBaltimoreMarylandUSA
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Walton E, Bernardoni F, Batury VL, Bahnsen K, Larivière S, Abbate-Daga G, Andres-Perpiña S, Bang L, Bischoff-Grethe A, Brooks SJ, Campbell IC, Cascino G, Castro-Fornieles J, Collantoni E, D'Agata F, Dahmen B, Danner UN, Favaro A, Feusner JD, Frank GKW, Friederich HC, Graner JL, Herpertz-Dahlmann B, Hess A, Horndasch S, Kaplan AS, Kaufmann LK, Kaye WH, Khalsa SS, LaBar KS, Lavagnino L, Lazaro L, Manara R, Miles AE, Milos GF, Monteleone AM, Monteleone P, Mwangi B, O'Daly O, Pariente J, Roesch J, Schmidt UH, Seitz J, Shott ME, Simon JJ, Smeets PAM, Tamnes CK, Tenconi E, Thomopoulos SI, van Elburg AA, Voineskos AN, von Polier GG, Wierenga CE, Zucker NL, Jahanshad N, King JA, Thompson PM, Berner LA, Ehrlich S. Brain Structure in Acutely Underweight and Partially Weight-Restored Individuals With Anorexia Nervosa: A Coordinated Analysis by the ENIGMA Eating Disorders Working Group. Biol Psychiatry 2022; 92:730-738. [PMID: 36031441 PMCID: PMC12145862 DOI: 10.1016/j.biopsych.2022.04.022] [Citation(s) in RCA: 62] [Impact Index Per Article: 20.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Revised: 04/01/2022] [Accepted: 04/28/2022] [Indexed: 11/15/2022]
Abstract
BACKGROUND The pattern of structural brain abnormalities in anorexia nervosa (AN) is still not well understood. While several studies report substantial deficits in gray matter volume and cortical thickness in acutely underweight patients, others find no differences, or even increases in patients compared with healthy control subjects. Recent weight regain before scanning may explain some of this heterogeneity. To clarify the extent, magnitude, and dependencies of gray matter changes in AN, we conducted a prospective, coordinated meta-analysis of multicenter neuroimaging data. METHODS We analyzed T1-weighted structural magnetic resonance imaging scans assessed with standardized methods from 685 female patients with AN and 963 female healthy control subjects across 22 sites worldwide. In addition to a case-control comparison, we conducted a 3-group analysis comparing healthy control subjects with acutely underweight AN patients (n = 466) and partially weight-restored patients in treatment (n = 251). RESULTS In AN, reductions in cortical thickness, subcortical volumes, and, to a lesser extent, cortical surface area were sizable (Cohen's d up to 0.95), widespread, and colocalized with hub regions. Highlighting the effects of undernutrition, these deficits were associated with lower body mass index in the AN sample and were less pronounced in partially weight-restored patients. CONCLUSIONS The effect sizes observed for cortical thickness deficits in acute AN are the largest of any psychiatric disorder investigated in the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) Consortium to date. These results confirm the importance of considering weight loss and renutrition in biomedical research on AN and underscore the importance of treatment engagement to prevent potentially long-lasting structural brain changes in this population.
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Affiliation(s)
- Esther Walton
- Department of Psychology, University of Bath, Bath, United Kingdom
| | - Fabio Bernardoni
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
| | - Victoria-Luise Batury
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
| | - Klaas Bahnsen
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
| | - Sara Larivière
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec
| | - Giovanni Abbate-Daga
- Eating Disorders Center for Treatment and Research, University of Turin, Turin, Italy
| | - Susana Andres-Perpiña
- Department of Child and Adolescent Psychiatry and Psychology, Institut Clinic de Neurociències, Hospital Clínic Universitari, Centro de Investigación Biomédica en Red de Salud Mental, Institut d'Investigacions Biomèdiques August Pi i Sunyer, University of Barcelona, Barcelona, Spain
| | - Lasse Bang
- Norwegian Institute of Public Health, Oslo; Regional Department for Eating Disorders, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Amanda Bischoff-Grethe
- Department of Psychiatry, University of California San Diego, La Jolla, California; Eating Disorders Center for Treatment and Research, University of California San Diego, La Jolla, California
| | - Samantha J Brooks
- School of Psychology, Faculty of Health Sciences, Liverpool John Moores University, Liverpool, United Kingdom; Department of Neuroscience, Uppsala University, Sweden
| | - Iain C Campbell
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom; Eating Disorders Unit, Department of Psychological Medicine, King's College London, London, United Kingdom
| | - Giammarco Cascino
- Section of Neurosciences, Department of Medicine, Surgery and Dentistry, Scuola Medica Salernitana, University of Salerno, Salerno, Italy
| | - Josefina Castro-Fornieles
- Department of Child and Adolescent Psychiatry and Psychology, Institut Clinic de Neurociències, Hospital Clínic Universitari, Centro de Investigación Biomédica en Red de Salud Mental, Institut d'Investigacions Biomèdiques August Pi i Sunyer, University of Barcelona, Barcelona, Spain
| | | | | | - Brigitte Dahmen
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Rheinisch-Westfälische Technische Hochschule Aachen, Aachen, Germany
| | - Unna N Danner
- Altrecht Eating Disorders Rintveld, Altrecht Mental Health Institute, Zeist, the Netherlands; Faculty of Social Sciences, Utrecht University, Utrecht, the Netherlands
| | - Angela Favaro
- Department of Neuroscience, University of Padova, Padova, Italy; Padova Neuroscience Center, University of Padova, Padova, Italy
| | - Jamie D Feusner
- Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario, Canada; Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, California
| | - Guido K W Frank
- Department of Psychiatry, University of California San Diego, La Jolla, California; Eating Disorders Center for Treatment and Research, University of California San Diego, La Jolla, California
| | - Hans-Christoph Friederich
- Centre for Psychosocial Medicine, Department of General Internal Medicine and Psychosomatics, University Hospital Heidelberg, Heidelberg, Germany
| | - John L Graner
- Center for Cognitive Neuroscience, Duke University, Durham, North Carolina
| | - Beate Herpertz-Dahlmann
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Rheinisch-Westfälische Technische Hochschule Aachen, Aachen, Germany
| | - Andreas Hess
- Institute for Pharmacology and Toxicology, University Erlangen-Nuremberg, Erlangen, Germany
| | - Stefanie Horndasch
- Department of Child and Adolescent Psychiatry, University Clinic Erlangen, Erlangen, Germany
| | - Allan S Kaplan
- Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario, Canada
| | - Lisa-Katrin Kaufmann
- Department of Consultation-Liaison Psychiatry and Psychosomatics, University Hospital Zurich, University of Zurich; Division of Neuropsychology, Department of Psychology, University of Zurich, Zurich, Switzerland
| | - Walter H Kaye
- Department of Psychiatry, University of California San Diego, La Jolla, California; Eating Disorders Center for Treatment and Research, University of California San Diego, La Jolla, California
| | - Sahib S Khalsa
- Laureate Institute for Brain Research, University of Tulsa, Tulsa, Oklahoma; Oxley College of Health Sciences, University of Tulsa, Tulsa, Oklahoma
| | - Kevin S LaBar
- Center for Cognitive Neuroscience, Duke University, Durham, North Carolina
| | - Luca Lavagnino
- Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, McGovern Medical School, University of Texas Health Science Center at Houston, Houston Texas
| | - Luisa Lazaro
- Department of Child and Adolescent Psychiatry and Psychology, Institut Clinic de Neurociències, Hospital Clínic Universitari, Centro de Investigación Biomédica en Red de Salud Mental, Institut d'Investigacions Biomèdiques August Pi i Sunyer, University of Barcelona, Barcelona, Spain
| | - Renzo Manara
- Department of Neuroscience, University of Padova, Padova, Italy
| | - Amy E Miles
- Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario, Canada
| | - Gabriella F Milos
- Department of Consultation-Liaison Psychiatry and Psychosomatics, University Hospital Zurich, University of Zurich
| | | | - Palmiero Monteleone
- Section of Neurosciences, Department of Medicine, Surgery and Dentistry, Scuola Medica Salernitana, University of Salerno, Salerno, Italy
| | - Benson Mwangi
- Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, McGovern Medical School, University of Texas Health Science Center at Houston, Houston Texas
| | - Owen O'Daly
- Centre for Neuroimaging Studies, King's College London, London, United Kingdom; Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Jose Pariente
- Magnetic Resonance Image Core Facility, Institut d'Investigacions Biomèdiques August Pi i Sunyer, Barcelona, Spain
| | - Julie Roesch
- Department of Neuroradiology, University Clinic Erlangen, Erlangen, Germany
| | - Ulrike H Schmidt
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom; Eating Disorders Unit, Department of Psychological Medicine, King's College London, London, United Kingdom
| | - Jochen Seitz
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Rheinisch-Westfälische Technische Hochschule Aachen, Aachen, Germany
| | - Megan E Shott
- Department of Psychiatry, University of California San Diego, La Jolla, California; Eating Disorders Center for Treatment and Research, University of California San Diego, La Jolla, California
| | - Joe J Simon
- Centre for Psychosocial Medicine, Department of General Internal Medicine and Psychosomatics, University Hospital Heidelberg, Heidelberg, Germany
| | - Paul A M Smeets
- UMC Utrecht Brain Center, Utrecht University, Utrecht, the Netherlands; Division of Human Nutrition and Health, Wageningen University, Wageningen, the Netherlands
| | - Christian K Tamnes
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; PROMENTA Research Center, Department of Psychology, University of Oslo, Oslo, Norway; Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
| | - Elena Tenconi
- Department of Neuroscience, University of Padova, Padova, Italy; Padova Neuroscience Center, University of Padova, Padova, Italy
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, California
| | - Annemarie A van Elburg
- Altrecht Eating Disorders Rintveld, Altrecht Mental Health Institute, Zeist, the Netherlands; Faculty of Social Sciences, Utrecht University, Utrecht, the Netherlands
| | - Aristotle N Voineskos
- Campbell Family Mental Health Research Institute, University of Toronto, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Georg G von Polier
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Rheinisch-Westfälische Technische Hochschule Aachen, Aachen, Germany; Institute for Neuroscience and Medicine: Brain and Behaviour, Forschungszentrum Jülich, Jülich, Germany; Department of Child and Adolescent Psychiatry, University Hospital Frankfurt, Goethe University, Frankfurt, Germany
| | - Christina E Wierenga
- Department of Psychiatry, University of California San Diego, La Jolla, California; Eating Disorders Center for Treatment and Research, University of California San Diego, La Jolla, California
| | - Nancy L Zucker
- Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, North Carolina
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, California
| | - Joseph A King
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, California
| | - Laura A Berner
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Stefan Ehrlich
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany; Eating Disorders Research and Treatment Center, Department of Child and Adolescent Psychiatry, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany.
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276
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Xie M, Zhao Z, Dai M, Wu Y, Huang Y, Liu Y, Tang Y, Xiao L, Wei W, Zhang G, Du X, Li C, Guo W, Ma X, Deng W, Wang Q, Li T. Associations between urban birth or childhood trauma and first-episode schizophrenia mediated by low IQ. SCHIZOPHRENIA 2022; 8:89. [PMID: 36309513 PMCID: PMC9617944 DOI: 10.1038/s41537-022-00289-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Accepted: 09/17/2022] [Indexed: 11/09/2022]
Abstract
Exposure to urban birth, childhood trauma, and lower Intelligence Quotient (IQ) were the most well-established risk factors for schizophrenia in developed countries. In developing countries, whether urban birth is a risk factor for schizophrenia and how these factors are related to one another remain unclear. This study aimed to investigate whether IQ mediates the relationship between urban birth or childhood trauma and first-episode schizophrenia (FES) in China. Birthplace, childhood trauma questionnaire (CTQ), and IQ were collected from 144 patients with FES and 256 healthy controls (HCs). Hierarchical logistic regression analysis was conducted to investigate the associations between birthplace, childhood trauma, IQ, and FES. Furthermore, mediation analysis was used to explore the mediation of IQ in the relationship between birthplace or childhood trauma and FES. After adjusting for age, sex and educational attainment, the final model identified urban birth (odds ratio (OR) = 3.15, 95% CI = 1.54, 6.44) and childhood trauma (OR = 2.79, 95% CI = 1.92, 4.06) were associated an elevated risk for FES. The 52.94% total effect of birthplace on the risk of FES could be offset by IQ (indirect effect/direct effect). The association between childhood trauma and FES could be partly explained by IQ (22.5%). In total, the mediation model explained 70.5% of the total variance in FES. Our study provides evidence that urban birth and childhood trauma are associated with an increased risk of FES. Furthermore, IQ mediates the relationship between urban birth or childhood trauma and FES.
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Affiliation(s)
- Min Xie
- grid.412901.f0000 0004 1770 1022Mental Health Center, West China Hospital, Sichuan University, 610041 Chengdu, Sichuan China
| | - Zhengyang Zhao
- grid.412901.f0000 0004 1770 1022Mental Health Center, West China Hospital, Sichuan University, 610041 Chengdu, Sichuan China
| | - Minhan Dai
- grid.412901.f0000 0004 1770 1022Mental Health Center, West China Hospital, Sichuan University, 610041 Chengdu, Sichuan China
| | - Yulu Wu
- grid.412901.f0000 0004 1770 1022Mental Health Center, West China Hospital, Sichuan University, 610041 Chengdu, Sichuan China
| | - Yunqi Huang
- grid.412901.f0000 0004 1770 1022Mental Health Center, West China Hospital, Sichuan University, 610041 Chengdu, Sichuan China
| | - Yunjia Liu
- grid.412901.f0000 0004 1770 1022Mental Health Center, West China Hospital, Sichuan University, 610041 Chengdu, Sichuan China
| | - Yiguo Tang
- grid.412901.f0000 0004 1770 1022Mental Health Center, West China Hospital, Sichuan University, 610041 Chengdu, Sichuan China
| | - Liling Xiao
- grid.412901.f0000 0004 1770 1022Mental Health Center, West China Hospital, Sichuan University, 610041 Chengdu, Sichuan China
| | - Wei Wei
- grid.412901.f0000 0004 1770 1022Mental Health Center, West China Hospital, Sichuan University, 610041 Chengdu, Sichuan China
| | - Guangya Zhang
- grid.263761.70000 0001 0198 0694Department of Psychiatry, Suzhou Psychiatric Hospital, The Affiliated Guangji Hospital of Soochow University, Suzhou, China
| | - Xiangdong Du
- grid.263761.70000 0001 0198 0694Department of Psychiatry, Suzhou Psychiatric Hospital, The Affiliated Guangji Hospital of Soochow University, Suzhou, China
| | - Chuanwei Li
- grid.263761.70000 0001 0198 0694Department of Psychiatry, Suzhou Psychiatric Hospital, The Affiliated Guangji Hospital of Soochow University, Suzhou, China
| | - Wanjun Guo
- grid.13402.340000 0004 1759 700XAffiliated Mental Health Centre & Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, 310013 Hangzhou, Zhejiang China
| | - Xiaohong Ma
- grid.412901.f0000 0004 1770 1022Mental Health Center, West China Hospital, Sichuan University, 610041 Chengdu, Sichuan China
| | - Wei Deng
- grid.13402.340000 0004 1759 700XAffiliated Mental Health Centre & Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, 310013 Hangzhou, Zhejiang China
| | - Qiang Wang
- grid.412901.f0000 0004 1770 1022Mental Health Center, West China Hospital, Sichuan University, 610041 Chengdu, Sichuan China
| | - Tao Li
- grid.13402.340000 0004 1759 700XAffiliated Mental Health Centre & Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, 310013 Hangzhou, Zhejiang China
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277
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Mapping the genetic architecture of cortical morphology through neuroimaging: progress and perspectives. Transl Psychiatry 2022; 12:447. [PMID: 36241627 PMCID: PMC9568576 DOI: 10.1038/s41398-022-02193-5] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Revised: 09/06/2022] [Accepted: 09/20/2022] [Indexed: 11/26/2022] Open
Abstract
Cortical morphology is a key determinant of cognitive ability and mental health. Its development is a highly intricate process spanning decades, involving the coordinated, localized expression of thousands of genes. We are now beginning to unravel the genetic architecture of cortical morphology, thanks to the recent availability of large-scale neuroimaging and genomic data and the development of powerful biostatistical tools. Here, we review the progress made in this field, providing an overview of the lessons learned from genetic studies of cortical volume, thickness, surface area, and folding as captured by neuroimaging. It is now clear that morphology is shaped by thousands of genetic variants, with effects that are region- and time-dependent, thereby challenging conventional study approaches. The most recent genome-wide association studies have started discovering common genetic variants influencing cortical thickness and surface area, yet together these explain only a fraction of the high heritability of these measures. Further, the impact of rare variants and non-additive effects remains elusive. There are indications that the quickly increasing availability of data from whole-genome sequencing and large, deeply phenotyped population cohorts across the lifespan will enable us to uncover much of the missing heritability in the upcoming years. Novel approaches leveraging shared information across measures will accelerate this process by providing substantial increases in statistical power, together with more accurate mapping of genetic relationships. Important challenges remain, including better representation of understudied demographic groups, integration of other 'omics data, and mapping of effects from gene to brain to behavior across the lifespan.
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278
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Korda AI, Andreou C, Avram M, Handels H, Martinetz T, Borgwardt S. Chaos analysis of the brain topology in first-episode psychosis and clinical high risk patients. Front Psychiatry 2022; 13:965128. [PMID: 36311536 PMCID: PMC9606602 DOI: 10.3389/fpsyt.2022.965128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Accepted: 09/16/2022] [Indexed: 11/17/2022] Open
Abstract
Structural MRI studies in first-episode psychosis (FEP) and in clinical high risk (CHR) patients have consistently shown volumetric abnormalities in frontal, temporal, and cingulate cortex areas. The aim of the present study was to employ chaos analysis for the identification of brain topology differences in people with psychosis. Structural MRI were acquired from 77 FEP, 73 CHR and 44 healthy controls (HC). Chaos analysis of the gray matter distribution was performed: First, the distances of each voxel from the center of mass in the gray matter image was calculated. Next, the distances multiplied by the voxel intensity were represented as a spatial-series, which then was analyzed by extracting the Largest-Lyapunov-Exponent (lambda). The lambda brain map depicts thus how the gray matter topology changes. Between-group differences were identified by (a) comparing the lambda brain maps, which resulted in statistically significant differences in FEP and CHR compared to HC; and (b) matching the lambda series with the Morlet wavelet, which resulted in statistically significant differences in the scalograms of FEP against CHR and HC. The proposed framework using spatial-series extraction enhances the between-group differences of FEP, CHR and HC subjects, verifies diagnosis-relevant features and may potentially contribute to the identification of structural biomarkers for psychosis.
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Affiliation(s)
- Alexandra I. Korda
- Translational Psychiatry, Department of Psychiatry and Psycotherapy, University of Lübeck, Lübeck, Germany
| | - Christina Andreou
- Translational Psychiatry, Department of Psychiatry and Psycotherapy, University of Lübeck, Lübeck, Germany
| | - Mihai Avram
- Translational Psychiatry, Department of Psychiatry and Psycotherapy, University of Lübeck, Lübeck, Germany
| | - Heinz Handels
- Institute of Medical Informatics, University of Lübeck, Lübeck, Germany
| | - Thomas Martinetz
- Institute for Neuro- and Bioinformatics, University of Lübeck, Lübeck, Germany
| | - Stefan Borgwardt
- Translational Psychiatry, Department of Psychiatry and Psycotherapy, University of Lübeck, Lübeck, Germany
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279
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Du X, Wei X, Ding H, Yu Y, Xie Y, Ji Y, Zhang Y, Chai C, Liang M, Li J, Zhuo C, Yu C, Qin W. Unraveling schizophrenia replicable functional connectivity disruption patterns across sites. Hum Brain Mapp 2022; 44:156-169. [PMID: 36222054 PMCID: PMC9783440 DOI: 10.1002/hbm.26108] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Revised: 09/19/2022] [Accepted: 09/20/2022] [Indexed: 02/05/2023] Open
Abstract
Functional connectivity (FC) disruption is a remarkable characteristic of schizophrenia. However, heterogeneous patterns reported across sites severely hindered its clinical generalization. Based on qualified nodal-based FC of 340 schizophrenia patients (SZ) and 348 normal controls (NC) acquired from seven different scanners, this study compared four commonly used site-effect correction methods in removing the site-related heterogeneities, and then tried to cluster the abnormal FCs into several replicable and independent disrupted subnets across sites, related them to clinical symptoms, and evaluated their potentials in schizophrenia classification. Among the four site-related heterogeneity correction methods, ComBat harmonization (F1 score: 0.806 ± 0.145) achieved the overall best balance between sensitivity and false discovery rate in unraveling the aberrant FCs of schizophrenia in the local and public data sets. Hierarchical clustering analysis identified three replicable FC disruption subnets across the local and public data sets: hypo-connectivity within sensory areas (Net1), hypo-connectivity within thalamus, striatum, and ventral attention network (Net2), and hyper-connectivity between thalamus and sensory processing system (Net3). Notably, the derived composite FC within Net1 was negatively correlated with hostility and disorientation in the public validation set (p < .05). Finally, the three subnet-specific composite FCs (Best area under the receiver operating characteristic curve [AUC] = 0.728) can robustly and meaningfully discriminate the SZ from NC with comparable performance with the full identified FCs features (best AUC = 0.765) in the out-of-sample public data set (Z = -1.583, p = .114). In conclusion, ComBat harmonization was most robust in detecting aberrant connectivity for schizophrenia. Besides, the three subnet-specific composite FC measures might be replicable neuroimaging markers for schizophrenia.
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Affiliation(s)
- Xiaotong Du
- Department of RadiologyTianjin Medical University General HospitalTianjinChina,Tianjin Key Lab of Functional ImagingTianjin Medical University General HospitalTianjinChina
| | - Xiaotong Wei
- Department of RadiologyTianjin Medical University General HospitalTianjinChina,Tianjin Key Lab of Functional ImagingTianjin Medical University General HospitalTianjinChina
| | - Hao Ding
- Department of RadiologyTianjin Medical University General HospitalTianjinChina,Tianjin Key Lab of Functional ImagingTianjin Medical University General HospitalTianjinChina,School of Medical ImagingTianjin Medical UniversityTianjinChina
| | - Ying Yu
- Department of RadiologyTianjin Medical University General HospitalTianjinChina,Tianjin Key Lab of Functional ImagingTianjin Medical University General HospitalTianjinChina
| | - Yingying Xie
- Department of RadiologyTianjin Medical University General HospitalTianjinChina,Tianjin Key Lab of Functional ImagingTianjin Medical University General HospitalTianjinChina
| | - Yi Ji
- Department of RadiologyTianjin Medical University General HospitalTianjinChina,Tianjin Key Lab of Functional ImagingTianjin Medical University General HospitalTianjinChina
| | - Yu Zhang
- Department of RadiologyTianjin Medical University General HospitalTianjinChina,Tianjin Key Lab of Functional ImagingTianjin Medical University General HospitalTianjinChina
| | - Chao Chai
- Department of RadiologyTianjin Medical University General HospitalTianjinChina,Tianjin Key Lab of Functional ImagingTianjin Medical University General HospitalTianjinChina
| | - Meng Liang
- Department of RadiologyTianjin Medical University General HospitalTianjinChina,Tianjin Key Lab of Functional ImagingTianjin Medical University General HospitalTianjinChina,School of Medical ImagingTianjin Medical UniversityTianjinChina
| | - Jie Li
- Department of Psychiatry Functional Neuroimaging LaboratoryTianjin Mental Health Center, Tianjin Anding HospitalTianjinChina
| | - Chuanjun Zhuo
- Department of Psychiatry Functional Neuroimaging LaboratoryTianjin Mental Health Center, Tianjin Anding HospitalTianjinChina
| | - Chunshui Yu
- Department of RadiologyTianjin Medical University General HospitalTianjinChina,Tianjin Key Lab of Functional ImagingTianjin Medical University General HospitalTianjinChina,School of Medical ImagingTianjin Medical UniversityTianjinChina
| | - Wen Qin
- Department of RadiologyTianjin Medical University General HospitalTianjinChina,Tianjin Key Lab of Functional ImagingTianjin Medical University General HospitalTianjinChina
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280
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Zhou H, Wang D, Cao B, Zhang X. Association of reduced cortical thickness and psychopathological symptoms in patients with first-episode drug-naïve schizophrenia. Int J Psychiatry Clin Pract 2022; 27:42-50. [PMID: 36193901 DOI: 10.1080/13651501.2022.2129067] [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] [Indexed: 10/10/2022]
Abstract
OBJECTIVE There is growing evidence that reduced cortical thickness has been considered to be a central abnormality in schizophrenia. Brain imaging studies have demonstrated that the cerebral cortex becomes thinner in patients with first-episode schizophrenia. This study aimed to examine whether cortical thickness is altered in drug-naïve schizophrenia in a Chinese Han population and the relationship between cortical thickness and clinical symptoms. METHODS We compared cortical thickness in 41 schizophrenia patients and 30 healthy controls. Psychopathology of patients with schizophrenia was assessed using the Positive and Negative Syndrome Scale (PANSS). RESULTS The cortical thickness of left banks of superior temporal sulcus, left lateral occipital gyrus, left rostral middle frontal gyrus, right inferior parietal lobule and right lateral occipital gyrus in schizophrenia patients was generally thinner compared with healthy controls. Correlation analysis revealed a negative correlation between cortical thickness of the left banks of superior temporal sulcus and general psychopathology of PANSS. CONCLUSIONS Our results suggest that cortical thickness abnormalities are already present early in the onset of schizophrenia and are associated with psychopathological symptoms, suggesting that it plays an important role in the pathogenesis and symptomatology of schizophrenia.Key points(1) The first-episode drug-naïve schizophrenia had reduced cortical thickness than the controls.(2) Cortical thickness was associated with psychopathological symptoms in patients with schizophrenia.
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Affiliation(s)
- Huixia Zhou
- CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, PR China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, PR China
| | - Dongmei Wang
- CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, PR China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, PR China
| | - Bo Cao
- Department of Psychiatry, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Canada.,Department of Psychiatry and Behavioral Sciences, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Xiangyang Zhang
- CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, PR China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, PR China
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281
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Eratne D, Janelidze S, Malpas CB, Loi S, Walterfang M, Merritt A, Diouf I, Blennow K, Zetterberg H, Cilia B, Wannan C, Bousman C, Everall I, Zalesky A, Jayaram M, Thomas N, Berkovic SF, Hansson O, Velakoulis D, Pantelis C, Santillo A, Stehmann C, Cadwallader C, Fowler C, Ravanfar P, Farrand S, Keem M, Kang M, Watson R, Yassi N, Kaylor-Hughes C, Kanaan R, Perucca P, Vivash L, Ali R, O’Brien TJ, Masters CL, Collins S, Kelso W, Evans A, King A, Kwan P, Gunn J, Goranitis I, Pan T, Lewis C, Kalincik T. Plasma neurofilament light chain protein is not increased in treatment-resistant schizophrenia and first-degree relatives. Aust N Z J Psychiatry 2022; 56:1295-1305. [PMID: 35179048 DOI: 10.1177/00048674211058684] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
OBJECTIVE Schizophrenia, a complex psychiatric disorder, is often associated with cognitive, neurological and neuroimaging abnormalities. The processes underlying these abnormalities, and whether a subset of people with schizophrenia have a neuroprogressive or neurodegenerative component to schizophrenia, remain largely unknown. Examining fluid biomarkers of diverse types of neuronal damage could increase our understanding of these processes, as well as potentially provide clinically useful biomarkers, for example with assisting with differentiation from progressive neurodegenerative disorders such as Alzheimer and frontotemporal dementias. METHODS This study measured plasma neurofilament light chain protein (NfL) using ultrasensitive Simoa technology, to investigate the degree of neuronal injury in a well-characterised cohort of people with treatment-resistant schizophrenia on clozapine (n = 82), compared to first-degree relatives (an at-risk group, n = 37), people with schizophrenia not treated with clozapine (n = 13), and age- and sex-matched controls (n = 59). RESULTS We found no differences in NfL levels between treatment-resistant schizophrenia (mean NfL, M = 6.3 pg/mL, 95% confidence interval: [5.5, 7.2]), first-degree relatives (siblings, M = 6.7 pg/mL, 95% confidence interval: [5.2, 8.2]; parents, M after adjusting for age = 6.7 pg/mL, 95% confidence interval: [4.7, 8.8]), controls (M = 5.8 pg/mL, 95% confidence interval: [5.3, 6.3]) and not treated with clozapine (M = 4.9 pg/mL, 95% confidence interval: [4.0, 5.8]). Exploratory, hypothesis-generating analyses found weak correlations in treatment-resistant schizophrenia, between NfL and clozapine levels (Spearman's r = 0.258, 95% confidence interval: [0.034, 0.457]), dyslipidaemia (r = 0.280, 95% confidence interval: [0.064, 0.470]) and a negative correlation with weight (r = -0.305, 95% confidence interval: [-0.504, -0.076]). CONCLUSION Treatment-resistant schizophrenia does not appear to be associated with neuronal, particularly axonal degeneration. Further studies are warranted to investigate the utility of NfL to differentiate treatment-resistant schizophrenia from neurodegenerative disorders such as behavioural variant frontotemporal dementia, and to explore NfL in other stages of schizophrenia such as the prodome and first episode.
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Affiliation(s)
- Dhamidhu Eratne
- Neuropsychiatry, The Royal Melbourne Hospital, Parkville, VIC, Australia.,Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, VIC, Australia
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences, Faculty of Medicine, Lund University, Lund, Sweden
| | - Charles B Malpas
- Clinical Outcomes Research Unit (CORe), Department of Medicine, The Royal Melbourne Hospital, The University of Melbourne, Melbourne, VIC, Australia.,Department of Neurology, The Royal Melbourne Hospital, Melbourne, VIC, Australia.,Melbourne School of Psychological Sciences, The University of Melbourne, Melbourne, VIC, Australia
| | - Samantha Loi
- Neuropsychiatry, The Royal Melbourne Hospital, Parkville, VIC, Australia.,Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, VIC, Australia
| | - Mark Walterfang
- Neuropsychiatry, The Royal Melbourne Hospital, Parkville, VIC, Australia.,Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, VIC, Australia
| | - Antonia Merritt
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, VIC, Australia
| | - Ibrahima Diouf
- Clinical Outcomes Research Unit (CORe), Department of Medicine, The Royal Melbourne Hospital, The University of Melbourne, Melbourne, VIC, Australia.,Department of Neurology, The Royal Melbourne Hospital, Melbourne, VIC, Australia
| | - Kaj Blennow
- Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology, Sahlgrenska University Hospital, University of Gothenburg, Mölndal, Sweden
| | - Henrik Zetterberg
- Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology, Sahlgrenska University Hospital, University of Gothenburg, Mölndal, Sweden.,Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden.,Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK.,UK Dementia Research Institute, University College London (UCL), London, UK.,Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
| | - Brandon Cilia
- The University of Melbourne, Parkville, VIC, Australia
| | - Cassandra Wannan
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, VIC, Australia
| | - Chad Bousman
- Departments of Medical Genetics, Psychiatry, and Physiology & Pharmacology, University of Calgary, Calgary, AB, Canada
| | - Ian Everall
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Andrew Zalesky
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, VIC, Australia
| | - Mahesh Jayaram
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, VIC, Australia.,Mid West Area Mental Health Service, Melbourne Health, Sunshine, VIC, Australia
| | - Naveen Thomas
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, VIC, Australia.,Mid West Area Mental Health Service, Melbourne Health, Sunshine, VIC, Australia
| | - Samuel F Berkovic
- Epilepsy Research Centre, Department of Medicine, Austin Health, The University of Melbourne, Heidelberg, VIC, Australia
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences, Faculty of Medicine, Lund University, Lund, Sweden
| | - Dennis Velakoulis
- Neuropsychiatry, The Royal Melbourne Hospital, Parkville, VIC, Australia.,Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, VIC, Australia
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, VIC, Australia.,Mid West Area Mental Health Service, Melbourne Health, Sunshine, VIC, Australia
| | - Alexander Santillo
- Clinical Memory Research Unit, Department of Clinical Sciences, Faculty of Medicine, Lund University, Lund, Sweden
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Lalousis PA, Schmaal L, Wood SJ, Reniers RLEP, Barnes NM, Chisholm K, Griffiths SL, Stainton A, Wen J, Hwang G, Davatzikos C, Wenzel J, Kambeitz-Ilankovic L, Andreou C, Bonivento C, Dannlowski U, Ferro A, Lichtenstein T, Riecher-Rössler A, Romer G, Rosen M, Bertolino A, Borgwardt S, Brambilla P, Kambeitz J, Lencer R, Pantelis C, Ruhrmann S, Salokangas RKR, Schultze-Lutter F, Schmidt A, Meisenzahl E, Koutsouleris N, Dwyer D, Upthegrove R. Neurobiologically Based Stratification of Recent-Onset Depression and Psychosis: Identification of Two Distinct Transdiagnostic Phenotypes. Biol Psychiatry 2022; 92:552-562. [PMID: 35717212 PMCID: PMC10128104 DOI: 10.1016/j.biopsych.2022.03.021] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 02/04/2022] [Accepted: 03/01/2022] [Indexed: 12/17/2022]
Abstract
BACKGROUND Identifying neurobiologically based transdiagnostic categories of depression and psychosis may elucidate heterogeneity and provide better candidates for predictive modeling. We aimed to identify clusters across patients with recent-onset depression (ROD) and recent-onset psychosis (ROP) based on structural neuroimaging data. We hypothesized that these transdiagnostic clusters would identify patients with poor outcome and allow more accurate prediction of symptomatic remission than traditional diagnostic structures. METHODS HYDRA (Heterogeneity through Discriminant Analysis) was trained on whole-brain volumetric measures from 577 participants from the discovery sample of the multisite PRONIA study to identify neurobiologically driven clusters, which were then externally validated in the PRONIA replication sample (n = 404) and three datasets of chronic samples (Centre for Biomedical Research Excellence, n = 146; Mind Clinical Imaging Consortium, n = 202; Munich, n = 470). RESULTS The optimal clustering solution was two transdiagnostic clusters (cluster 1: n = 153, 67 ROP, 86 ROD; cluster 2: n = 149, 88 ROP, 61 ROD; adjusted Rand index = 0.618). The two clusters contained both patients with ROP and patients with ROD. One cluster had widespread gray matter volume deficits and more positive, negative, and functional deficits (impaired cluster), and one cluster revealed a more preserved neuroanatomical signature and more core depressive symptomatology (preserved cluster). The clustering solution was internally and externally validated and assessed for clinical utility in predicting 9-month symptomatic remission, outperforming traditional diagnostic structures. CONCLUSIONS We identified two transdiagnostic neuroanatomically informed clusters that are clinically and biologically distinct, challenging current diagnostic boundaries in recent-onset mental health disorders. These results may aid understanding of the etiology of poor outcome patients transdiagnostically and improve development of stratified treatments.
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Affiliation(s)
- Paris Alexandros Lalousis
- Institute for Mental Health, University of Birmingham, Birmingham, United Kingdom; Centre for Human Brain Health, University of Birmingham, Birmingham, United Kingdom.
| | - Lianne Schmaal
- Orygen, Parkville, Victoria, Australia; Centre for Youth Mental Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Stephen J Wood
- Institute for Mental Health, University of Birmingham, Birmingham, United Kingdom; Orygen, Parkville, Victoria, Australia; Centre for Youth Mental Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Renate L E P Reniers
- Institute for Mental Health, University of Birmingham, Birmingham, United Kingdom; Centre for Human Brain Health, University of Birmingham, Birmingham, United Kingdom; Institute of Clinical Sciences, University of Birmingham, Birmingham, United Kingdom
| | - Nicholas M Barnes
- Institute of Clinical Sciences, University of Birmingham, Birmingham, United Kingdom
| | - Katharine Chisholm
- Institute for Mental Health, University of Birmingham, Birmingham, United Kingdom; Department of Psychology, Aston University, Birmingham, United Kingdom
| | - Sian Lowri Griffiths
- Institute for Mental Health, University of Birmingham, Birmingham, United Kingdom; Centre for Human Brain Health, University of Birmingham, Birmingham, United Kingdom
| | - Alexandra Stainton
- Orygen, Parkville, Victoria, Australia; Centre for Youth Mental Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Junhao Wen
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Gyujoon Hwang
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Christos Davatzikos
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Julian Wenzel
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital, University of Cologne, Cologne, Germany
| | - Lana Kambeitz-Ilankovic
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital, University of Cologne, Cologne, Germany
| | | | - Carolina Bonivento
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy; Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, University of Milan, Milan, Italy
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Adele Ferro
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy; Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, University of Milan, Milan, Italy
| | - Theresa Lichtenstein
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital, University of Cologne, Cologne, Germany
| | | | - Georg Romer
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Marlene Rosen
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital, University of Cologne, Cologne, Germany
| | - Alessandro Bertolino
- Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Stefan Borgwardt
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital, University of Cologne, Cologne, Germany; Department of Psychiatry and Psychotherapy, University of Lübeck, Lübeck, Germany
| | - Paolo Brambilla
- Department of Psychiatry, University of Basel, Basel, Switzerland; Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Joseph Kambeitz
- Department of Psychiatry and Psychotherapy, Ludwig Maxmilians University, Munich, Germany
| | - Rebekka Lencer
- Institute for Translational Psychiatry, University of Münster, Münster, Germany; Department of Psychiatry, University of Basel, Basel, Switzerland
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, University of Melbourne, Melbourne, Victoria, Australia
| | - Stephan Ruhrmann
- Department of Psychiatry, University of Basel, Basel, Switzerland
| | | | - Frauke Schultze-Lutter
- Department of Psychiatry and Psychotherapy, University of Düsseldorf, Düsseldorf, Germany; University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland; Department of Psychology and Mental Health, Faculty of Psychology, Airlangga University, Surabaya, Indonesia
| | - André Schmidt
- Department of Psychiatry, University of Basel, Basel, Switzerland
| | - Eva Meisenzahl
- Department of Psychiatry and Psychotherapy, University of Düsseldorf, Düsseldorf, Germany
| | - Nikolaos Koutsouleris
- Department of Psychiatry and Psychotherapy, Ludwig Maxmilians University, Munich, Germany
| | - Dominic Dwyer
- Department of Psychiatry and Psychotherapy, Ludwig Maxmilians University, Munich, Germany
| | - Rachel Upthegrove
- Institute for Mental Health, University of Birmingham, Birmingham, United Kingdom; Centre for Human Brain Health, University of Birmingham, Birmingham, United Kingdom; Birmingham Early Interventions Service, Birmingham Women's and Children's NHS Foundation Trust, Birmingham, United Kingdom
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283
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Kosaraju S, Galatzer-Levy I, Schultebraucks K, Winters S, Hinrichs R, Reddi PJ, Maples-Keller JL, Hudak L, Michopoulos V, Jovanovic T, Ressler KJ, Allen JW, Stevens JS. Associations among civilian mild traumatic brain injury with loss of consciousness, posttraumatic stress disorder symptom trajectories, and structural brain volumetric data. J Trauma Stress 2022; 35:1521-1534. [PMID: 35776892 DOI: 10.1002/jts.22858] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 05/14/2022] [Accepted: 05/16/2022] [Indexed: 11/08/2022]
Abstract
Posttraumatic stress disorder (PTSD) is prevalent and associated with significant morbidity. Mild traumatic brain injury (mTBI) concurrent with psychiatric trauma may be associated with PTSD. Prior studies of PTSD-related structural brain alterations have focused on military populations. The current study examined correlations between PTSD, acute mTBI, and structural brain alterations longitudinally in civilian patients (N = 504) who experienced a recent Criterion A traumatic event. Participants who reported loss of consciousness (LOC) were characterized as having mTBI; all others were included in the control group. PTSD symptoms were assessed at enrollment and over the following year; a subset of participants (n = 89) underwent volumetric brain MRI (M = 53 days posttrauma). Classes of PTSD symptom trajectories were modeled using latent growth mixture modeling. Associations between PTSD symptom trajectories and cortical thicknesses or subcortical volumes were assessed using a moderator-based regression. mTBI with LOC during trauma was positively correlated with the likelihood of developing a chronic PTSD symptom trajectory. mTBI showed significant interactions with cortical thickness in the rostral anterior cingulate cortex (rACC) in predicting PTSD symptoms, r = .461-.463. Bilateral rACC thickness positively predicted PTSD symptoms but only among participants who endorsed LOC, p < .001. The results demonstrate positive correlations between mTBI with LOC and PTSD symptom trajectories, and findings related to mTBI with LOC and rACC thickness interactions in predicting subsequent chronic PTSD symptoms suggest the importance of further understanding the role of mTBI in the context of PTSD to inform intervention and risk stratification.
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Affiliation(s)
- Siddhartha Kosaraju
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Isaac Galatzer-Levy
- Department of Psychiatry, New York University School of Medicine, New York, New York, USA
| | - Katharina Schultebraucks
- Department of Emergency Medicine, Vagelos School of Physicians and Surgeons, Columbia University Medical Center, New York, New York, USA
| | - Sterling Winters
- Department of Psychiatry, Wayne State University School of Medicine, Detroit, Michigan, USA
| | - Rebecca Hinrichs
- Department of Psychiatry, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Preethi J Reddi
- Department of Biology, Emory University School of Medicine, Atlanta, Georgia, USA
| | | | - Lauren Hudak
- Department of Emergency Medicine, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Vasiliki Michopoulos
- Department of Psychiatry, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Tanja Jovanovic
- Department of Psychiatry, Wayne State University School of Medicine, Detroit, Michigan, USA
| | - Kerry J Ressler
- Department of Psychiatry, McLean Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Jason W Allen
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Jennifer S Stevens
- Department of Psychiatry, New York University School of Medicine, New York, New York, USA
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284
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Barbu MC, Harris M, Shen X, Aleks S, Green C, Amador C, Walker R, Morris S, Adams M, Sandu A, McNeil C, Waiter G, Evans K, Campbell A, Wardlaw J, Steele D, Murray A, Porteous D, McIntosh A, Whalley H. Epigenome-wide association study of global cortical volumes in generation Scotland: Scottish family health study. Epigenetics 2022; 17:1143-1158. [PMID: 34738878 PMCID: PMC9542280 DOI: 10.1080/15592294.2021.1997404] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Revised: 10/18/2021] [Accepted: 10/21/2021] [Indexed: 01/22/2023] Open
Abstract
A complex interplay of genetic and environmental risk factors influence global brain structural alterations associated with brain health and disease. Epigenome-wide association studies (EWAS) of global brain imaging phenotypes have the potential to reveal the mechanisms of brain health and disease and can lead to better predictive analytics through the development of risk scores.We perform an EWAS of global brain volumes in Generation Scotland using peripherally measured whole blood DNA methylation (DNAm) from two assessments, (i) at baseline recruitment, ~6 years prior to MRI assessment (N = 672) and (ii) concurrent with MRI assessment (N=565). Four CpGs at baseline were associated with global cerebral white matter, total grey matter, and whole-brain volume (Bonferroni p≤7.41×10-8, βrange = -1.46x10-6 to 9.59 × 10-7). These CpGs were annotated to genes implicated in brain-related traits, including psychiatric disorders, development, and ageing. We did not find significant associations in the meta-analysis of the EWAS of the two sets concurrent with imaging at the corrected level.These findings reveal global brain structural changes associated with DNAm measured ~6 years previously, indicating a potential role of early DNAm modifications in brain structure. Although concurrent DNAm was not associated with global brain structure, the nominally significant findings identified here present a rationale for future investigation of associations between DNA methylation and structural brain phenotypes in larger population-based samples.
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Affiliation(s)
- Miruna Carmen Barbu
- Division of Psychiatry, The University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Mat Harris
- Division of Psychiatry, The University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Xueyi Shen
- Division of Psychiatry, The University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Stolicyn Aleks
- Division of Psychiatry, The University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Claire Green
- Division of Psychiatry, The University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Carmen Amador
- Mrc Human Genetics Unit, Institute of Genetics and Cancer, the University of Edinburgh, UK
| | - Rosie Walker
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, the University of Edinburgh, UK
- Centre for Clinical Brain Sciences, The University of Edinburgh, UK
| | - Stewart Morris
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, the University of Edinburgh, UK
- Centre for Clinical Brain Sciences, The University of Edinburgh, UK
| | - Mark Adams
- Division of Psychiatry, The University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Anca Sandu
- Aberdeen Biomedical Imaging Centre, The Institute of Medical Sciences, University of Aberdeen, UK
| | - Christopher McNeil
- Aberdeen Biomedical Imaging Centre, The Institute of Medical Sciences, University of Aberdeen, UK
| | - Gordon Waiter
- Aberdeen Biomedical Imaging Centre, The Institute of Medical Sciences, University of Aberdeen, UK
| | - Kathryn Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, the University of Edinburgh, UK
- Centre for Clinical Brain Sciences, The University of Edinburgh, UK
| | - Archie Campbell
- Mrc Human Genetics Unit, Institute of Genetics and Cancer, the University of Edinburgh, UK
| | - Joanna Wardlaw
- Centre for Clinical Brain Sciences, The University of Edinburgh, UK
| | - Douglas Steele
- Imaging Science and Technology, School of Medicine, University of Dundee, DundeeUK
| | - Alison Murray
- Aberdeen Biomedical Imaging Centre, The Institute of Medical Sciences, University of Aberdeen, UK
| | - David Porteous
- Mrc Human Genetics Unit, Institute of Genetics and Cancer, the University of Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, School of Philosophy, Psychology and Language Sciences, The University of Edinburgh, UK
| | - Andrew McIntosh
- Division of Psychiatry, The University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, School of Philosophy, Psychology and Language Sciences, The University of Edinburgh, UK
| | - Heather Whalley
- Division of Psychiatry, The University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
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285
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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: 12] [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.
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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.
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286
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Ringin E, Cropley V, Zalesky A, Bruggemann J, Sundram S, Weickert CS, Weickert TW, Bousman CA, Pantelis C, Van Rheenen TE. The impact of smoking status on cognition and brain morphology in schizophrenia spectrum disorders. Psychol Med 2022; 52:3097-3115. [PMID: 33443010 DOI: 10.1017/s0033291720005152] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
BACKGROUND Cigarette smoking is associated with worse cognition and decreased cortical volume and thickness in healthy cohorts. Chronic cigarette smoking is prevalent in schizophrenia spectrum disorders (SSD), but the effects of smoking status on the brain and cognition in SSD are not clear. This study aimed to understand whether cognitive performance and brain morphology differed between smoking and non-smoking individuals with SSD compared to healthy controls. METHODS Data were obtained from the Australian Schizophrenia Research Bank. Cognitive functioning was measured in 299 controls and 455 SSD patients. Cortical volume, thickness and surface area data were analysed from T1-weighted structural scans obtained in a subset of the sample (n = 82 controls, n = 201 SSD). Associations between smoking status (cigarette smoker/non-smoker), cognition and brain morphology were tested using analyses of covariance, including diagnosis as a moderator. RESULTS No smoking by diagnosis interactions were evident, and no significant differences were revealed between smokers and non-smokers across any of the variables measured, with the exception of a significantly thinner left posterior cingulate in smokers compared to non-smokers. Several main effects of smoking in the cognitive, volume and thickness analyses were initially significant but did not survive false discovery rate (FDR) correction. CONCLUSIONS Despite the general absence of significant FDR-corrected findings, trend-level effects suggest the possibility that subtle smoking-related effects exist but were not uncovered due to low statistical power. An investigation of this topic is encouraged to confirm and expand on our findings.
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Affiliation(s)
- Elysha Ringin
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia
| | - Vanessa Cropley
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia
- Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Andrew Zalesky
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia
- Department of Electrical and Electronic Engineering, University of Melbourne, Melbourne, VIC, Australia
| | - Jason Bruggemann
- School of Psychiatry, University of New South Wales, New South Wales, Australia
- Neuroscience Research Australia, New South Wales, Australia
| | - Suresh Sundram
- Florey Institute of Neuroscience and Mental Health, Melbourne, Australia
- Department of Psychiatry, School of Clinical Sciences, Monash University, Clayton, Australia
- Mental Health Program, Monash Health, Clayton, Victoria, Australia
| | - Cynthia Shannon Weickert
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia
- School of Psychiatry, University of New South Wales, New South Wales, Australia
- Neuroscience Research Australia, New South Wales, Australia
- Department of Neuroscience & Physiology, Upstate Medical University, Syracuse, New York 13210, USA
| | - Thomas W Weickert
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia
- School of Psychiatry, University of New South Wales, New South Wales, Australia
- Neuroscience Research Australia, New South Wales, Australia
- Department of Neuroscience & Physiology, Upstate Medical University, Syracuse, New York 13210, USA
| | - Chad A Bousman
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia
- Departments of Medical Genetics, Psychiatry, and Physiology & Pharmacology, University of Calgary, Calgary, AB, Canada
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia
- Florey Institute of Neuroscience and Mental Health, Melbourne, Australia
| | - Tamsyn E Van Rheenen
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia
- Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia
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287
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Multiscale neural gradients reflect transdiagnostic effects of major psychiatric conditions on cortical morphology. Commun Biol 2022; 5:1024. [PMID: 36168040 PMCID: PMC9515219 DOI: 10.1038/s42003-022-03963-z] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Accepted: 09/07/2022] [Indexed: 02/06/2023] Open
Abstract
It is increasingly recognized that multiple psychiatric conditions are underpinned by shared neural pathways, affecting similar brain systems. Here, we carried out a multiscale neural contextualization of shared alterations of cortical morphology across six major psychiatric conditions (autism spectrum disorder, attention deficit/hyperactivity disorder, major depression disorder, obsessive-compulsive disorder, bipolar disorder, and schizophrenia). Our framework cross-referenced shared morphological anomalies with respect to cortical myeloarchitecture and cytoarchitecture, as well as connectome and neurotransmitter organization. Pooling disease-related effects on MRI-based cortical thickness measures across six ENIGMA working groups, including a total of 28,546 participants (12,876 patients and 15,670 controls), we identified a cortex-wide dimension of morphological changes that described a sensory-fugal pattern, with paralimbic regions showing the most consistent alterations across conditions. The shared disease dimension was closely related to cortical gradients of microstructure as well as neurotransmitter axes, specifically cortex-wide variations in serotonin and dopamine. Multiple sensitivity analyses confirmed robustness with respect to slight variations in analytical choices. Our findings embed shared effects of common psychiatric conditions on brain structure in multiple scales of brain organization, and may provide insights into neural mechanisms of transdiagnostic vulnerability.
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288
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Mowry BJ, Periyasamy S. Genome‐Wide Association Studies in Schizophrenia. ELS 2022:1-14. [DOI: 10.1002/9780470015902.a0025337] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
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289
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Huang Z, Ruan D, Huang B, Zhou T, Shi C, Yu X, Chan RCK, Wang Y, Pu C. Negative symptoms correlate with altered brain structural asymmetry in amygdala and superior temporal region in schizophrenia patients. Front Psychiatry 2022; 13:1000560. [PMID: 36226098 PMCID: PMC9548644 DOI: 10.3389/fpsyt.2022.1000560] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Accepted: 09/05/2022] [Indexed: 11/18/2022] Open
Abstract
Negative symptoms play an important role in development and treatment of schizophrenia. However, brain changes relevant to negative symptoms are still unclear. This study examined brain structural abnormalities and their asymmetry in schizophrenia patients and the association with negative symptoms. Fifty-nine schizophrenia patients and 66 healthy controls undertook structural brain scans. Schizophrenia patients were further divided into predominant negative symptoms (PNS, n = 18) and non-PNS (n = 34) subgroups. Negative symptoms were assessed by the Negative Symptom Assessment (NSA). T1-weighted images were preprocessed with FreeSurfer to estimate subcortical volumes, cortical thickness and surface areas, asymmetry Index (AI) was then calculated. MANOVA was performed for group differences while partial correlations in patients were analyzed between altered brain structures and negative symptoms. Compared to healthy controls, schizophrenia patients exhibited thinner cortices in frontal and temporal regions, and decreased leftward asymmetry of superior temporal gyrus (STG) in cortical thickness. Patients with PNS exhibited increased rightward asymmetry of amygdala volumes than non-PNS subgroup. In patients, AI of cortical thickness in the STG was negatively correlated with NSA-Emotion scores (r = -0.30, p = 0.035), while AI of amygdala volume was negatively correlated with NSA-Communication (r = -0.30, p = 0.039) and NSA-Total scores (r = -0.30, p = 0.038). Our findings suggested schizophrenia patients exhibited cortical thinning and altered lateralization of brain structures. Emotion and communication dimensions of negative symptoms also correlated with the structural asymmetry of amygdala and superior temporal regions in schizophrenia patients.
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Affiliation(s)
- Zetao Huang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Dun Ruan
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Bingjie Huang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Tianhang Zhou
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Chuan Shi
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Xin Yu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Raymond C. K. Chan
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Yi Wang
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Chengcheng Pu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
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290
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Kiltschewskij DJ, Reay WR, Cairns MJ. Evidence of genetic overlap and causal relationships between blood-based biochemical traits and human cortical anatomy. Transl Psychiatry 2022; 12:373. [PMID: 36075890 PMCID: PMC9458732 DOI: 10.1038/s41398-022-02141-3] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/13/2022] [Revised: 08/18/2022] [Accepted: 08/25/2022] [Indexed: 01/08/2023] Open
Abstract
Psychiatric disorders such as schizophrenia are commonly associated with structural brain alterations affecting the cortex. Recent genetic evidence suggests circulating metabolites and other biochemical traits play a causal role in many psychiatric disorders which could be mediated by changes in the cerebral cortex. Here, we leveraged publicly available genome-wide association study data to explore shared genetic architecture and evidence for causal relationships between a panel of 50 biochemical traits and measures of cortical thickness and surface area. Linkage disequilibrium score regression identified 191 genetically correlated biochemical-cortical trait pairings, with consistent representation of blood cell counts and other biomarkers such as C-reactive protein (CRP), haemoglobin and calcium. Spatially organised patterns of genetic correlation were additionally uncovered upon clustering of region-specific correlation profiles. Interestingly, by employing latent causal variable models, we found strong evidence suggesting CRP and vitamin D exert causal effects on region-specific cortical thickness, with univariable and multivariable Mendelian randomization further supporting a negative causal relationship between serum CRP levels and thickness of the lingual region. Our findings suggest a subset of biochemical traits exhibit shared genetic architecture and potentially causal relationships with cortical structure in functionally distinct regions, which may contribute to alteration of cortical structure in psychiatric disorders.
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Affiliation(s)
- Dylan J Kiltschewskij
- School of Biomedical Sciences and Pharmacy, The University of Newcastle, Callaghan, NSW, Australia
- Precision Medicine Research Program, Hunter Medical Research Institute, New Lambton, NSW, Australia
| | - William R Reay
- School of Biomedical Sciences and Pharmacy, The University of Newcastle, Callaghan, NSW, Australia
- Precision Medicine Research Program, Hunter Medical Research Institute, New Lambton, NSW, Australia
| | - Murray J Cairns
- School of Biomedical Sciences and Pharmacy, The University of Newcastle, Callaghan, NSW, Australia.
- Precision Medicine Research Program, Hunter Medical Research Institute, New Lambton, NSW, Australia.
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291
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Associations between brain imaging and polygenic scores of mental health and educational attainment in children aged 9-11. Neuroimage 2022; 263:119611. [PMID: 36070838 DOI: 10.1016/j.neuroimage.2022.119611] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Revised: 08/03/2022] [Accepted: 09/03/2022] [Indexed: 12/25/2022] Open
Abstract
Psychiatric disorders are highly heritable and polygenic, and many have their peak onset in late childhood and adolescence, a period of tremendous changes. Although the neurodevelopmental antecedents of mental illness are widely acknowledged, research in youth population cohorts is still scarce, preventing our progress towards the early characterization of these disorders. We included 7,124 children (9-11 years old) from the Adolescent Brain and Cognitive Development Study to map the associations of structural and diffusion brain imaging with common genetic variants and polygenic scores for psychiatric disorders and educational attainment. We used principal component analysis to derive imaging components, and calculated their heritability. We then assessed the relationship of imaging components with genetic and clinical psychiatric risk with univariate models and Canonical correlation analysis (CCA). Most imaging components had moderate heritability. Univariate models showed limited evidence and small associations of polygenic scores with brain structure at this age. CCA revealed two significant modes of covariation. The first mode linked higher polygenic scores for educational attainment with less externalizing problems and larger surface area. The second mode related higher polygenic scores for schizophrenia, bipolar disorder, and autism spectrum disorder to higher global cortical thickness, smaller white matter volumes of the fornix and cingulum, larger medial occipital surface area and smaller surface area of lateral and medial temporal regions. While cross-validation suggested limited generalizability, our results highlight the potential of multivariate models to better understand the transdiagnostic and distributed relationships between mental health and brain structure in late childhood.
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292
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Bahnsen K, Bernardoni F, King JA, Geisler D, Weidner K, Roessner V, Patel Y, Paus T, Ehrlich S. Dynamic Structural Brain Changes in Anorexia Nervosa: A Replication Study, Mega-analysis, and Virtual Histology Approach. J Am Acad Child Adolesc Psychiatry 2022; 61:1168-1181. [PMID: 35390458 DOI: 10.1016/j.jaac.2022.03.026] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Revised: 02/07/2022] [Accepted: 03/28/2022] [Indexed: 11/28/2022]
Abstract
OBJECTIVE Several, but not all, previous studies of brain structure in anorexia nervosa (AN) have reported reductions in gray matter volume and cortical thickness (CT) in acutely underweight patients, which seem to reverse upon weight gain. The biological mechanisms underlying these dynamic alterations remain unclear. METHOD In this structural magnetic resonance imaging study, we first replicated and extended previous results in (1) a larger independent sample of 75 acutely underweight adolescent and young adult female patients with AN (acAN; n = 54 rescanned longitudinally after partial weight restoration), 34 weight-recovered individuals with a history of AN (recAN), and 139 healthy controls (HC); and 2) a greater combined sample compiled of both our previous samples and the present replication sample (120 acAN [90 rescanned longitudinally], 68 recAN, and 207 HC). Next, we applied a "virtual histology" approach to the combined data, investigating relations between interregional profiles of differences in CT and profiles of cell-specific gene expression. Finally, we used the ENIGMA toolbox to relate aforementioned CT profiles to normative structural and functional connectomics. RESULTS We confirmed sizeable and widespread reductions of CT as well as volumes (and, to a lesser extent, surface area) in acAN and rapid increases related to partial weight restoration. No differences were detected between either short- or long-term weight-recovered patients and HC. The virtual histology analysis identified associations between gene expression profiles of S1 pyramidal cells and oligodendrocytes and brain regions with more marked differences in CT, whereas the remaining regions were those with a greater expression of genes specific to CA1 pyramidal, astrocytes, microglia, and ependymal cells. Furthermore, the most affected regions were also more functionally and structurally connected. CONCLUSION The overall data pattern deviates from findings in other psychiatric disorders. Both virtual histology and connectomics analyses indicated that brain regions most affected in AN are also the most energetically demanding.
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Affiliation(s)
| | | | | | | | | | | | | | - Tomáš Paus
- University of Toronto, Canada; University of Montreal, Canada
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293
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McWhinney SR, Brosch K, Calhoun VD, Crespo-Facorro B, Crossley NA, Dannlowski U, Dickie E, Dietze LMF, Donohoe G, Du Plessis S, Ehrlich S, Emsley R, Furstova P, Glahn DC, Gonzalez- Valderrama A, Grotegerd D, Holleran L, Kircher TTJ, Knytl P, Kolenic M, Lencer R, Nenadić I, Opel N, Pfarr JK, Rodrigue AL, Rootes-Murdy K, Ross AJ, Sim K, Škoch A, Spaniel F, Stein F, Švancer P, Tordesillas-Gutiérrez D, Undurraga J, Váquez-Bourgon J, Voineskos A, Walton E, Weickert TW, Weickert CS, Thompson PM, van Erp TGM, Turner JA, Hajek T. Obesity and brain structure in schizophrenia - ENIGMA study in 3021 individuals. Mol Psychiatry 2022; 27:3731-3737. [PMID: 35739320 PMCID: PMC9902274 DOI: 10.1038/s41380-022-01616-5] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Revised: 04/27/2022] [Accepted: 05/06/2022] [Indexed: 02/08/2023]
Abstract
Schizophrenia is frequently associated with obesity, which is linked with neurostructural alterations. Yet, we do not understand how the brain correlates of obesity map onto the brain changes in schizophrenia. We obtained MRI-derived brain cortical and subcortical measures and body mass index (BMI) from 1260 individuals with schizophrenia and 1761 controls from 12 independent research sites within the ENIGMA-Schizophrenia Working Group. We jointly modeled the statistical effects of schizophrenia and BMI using mixed effects. BMI was additively associated with structure of many of the same brain regions as schizophrenia, but the cortical and subcortical alterations in schizophrenia were more widespread and pronounced. Both BMI and schizophrenia were primarily associated with changes in cortical thickness, with fewer correlates in surface area. While, BMI was negatively associated with cortical thickness, the significant associations between BMI and surface area or subcortical volumes were positive. Lastly, the brain correlates of obesity were replicated among large studies and closely resembled neurostructural changes in major depressive disorders. We confirmed widespread associations between BMI and brain structure in individuals with schizophrenia. People with both obesity and schizophrenia showed more pronounced brain alterations than people with only one of these conditions. Obesity appears to be a relevant factor which could account for heterogeneity of brain imaging findings and for differences in brain imaging outcomes among people with schizophrenia.
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Affiliation(s)
- Sean R. McWhinney
- grid.55602.340000 0004 1936 8200Department of Psychiatry, Dalhousie University, Halifax, NS Canada
| | - Katharina Brosch
- grid.10253.350000 0004 1936 9756Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Vince D. Calhoun
- grid.189967.80000 0001 0941 6502Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, Emory University, Atlanta, GA USA
| | - Benedicto Crespo-Facorro
- grid.469673.90000 0004 5901 7501Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain ,grid.411109.c0000 0000 9542 1158IBiS, University Hospital Virgen del Rocio, Sevilla, Spain ,grid.9224.d0000 0001 2168 1229Department of Psychiatry, School of Medicine, University of Sevilla, Sevilla, Spain
| | - Nicolas A. Crossley
- grid.7870.80000 0001 2157 0406Department of Psychiatry, School of Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile ,grid.13097.3c0000 0001 2322 6764Department of Psychosis Studies, King’s College London, London, UK
| | - Udo Dannlowski
- grid.5949.10000 0001 2172 9288Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Erin Dickie
- grid.17063.330000 0001 2157 2938Centre for Addiction & Mental Health, Department of Psychiatry, University of Toronto, Toronto, ON Canada
| | - Lorielle M. F. Dietze
- grid.55602.340000 0004 1936 8200Department of Psychiatry, Dalhousie University, Halifax, NS Canada
| | - Gary Donohoe
- grid.6142.10000 0004 0488 0789Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland Galway, Galway, Ireland
| | - Stefan Du Plessis
- grid.11956.3a0000 0001 2214 904XDepartment of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa ,grid.415021.30000 0000 9155 0024SAMRC Genomics of Brain Disorders Unit, Cape Town, South Africa
| | - Stefan Ehrlich
- grid.4488.00000 0001 2111 7257Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Dresden, Germany
| | - Robin Emsley
- grid.11956.3a0000 0001 2214 904XDepartment of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Petra Furstova
- grid.447902.cNational Institute of Mental Health, Klecany, Czech Republic
| | - David C. Glahn
- grid.2515.30000 0004 0378 8438Department of Psychiatry & Behavioral Sciences, Boston Children’s Hospital, Boston, MA USA ,grid.38142.3c000000041936754XDepartment of Psychiatry, Harvard Medical School, Boston, MA USA ,grid.277313.30000 0001 0626 2712Olin Neuropsychiatry Research Center, Institute of Living, Hartford, CT USA
| | - Alfonso Gonzalez- Valderrama
- grid.440629.d0000 0004 5934 6911School of Medicine, Universidad Finis Terrae, Santiago, Chile ,Early Intervention in Psychosis Program, Instituto Psiquiátrico ‘Dr. José Horwitz B.’, Santiago, Chile
| | - Dominik Grotegerd
- grid.5949.10000 0001 2172 9288Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Laurena Holleran
- grid.6142.10000 0004 0488 0789Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland Galway, Galway, Ireland
| | - Tilo T. J. Kircher
- grid.10253.350000 0004 1936 9756Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Pavel Knytl
- grid.447902.cNational Institute of Mental Health, Klecany, Czech Republic ,grid.4491.80000 0004 1937 116XCharles University, Third Faculty of Medicine, Prague, Czech Republic
| | - Marian Kolenic
- grid.447902.cNational Institute of Mental Health, Klecany, Czech Republic ,grid.4491.80000 0004 1937 116XCharles University, Third Faculty of Medicine, Prague, Czech Republic
| | - Rebekka Lencer
- grid.5949.10000 0001 2172 9288Institute for Translational Psychiatry, University of Münster, Münster, Germany ,grid.4562.50000 0001 0057 2672Department of Pscyhiatry and Psychotherapy, University of Lübeck, Lübeck, Germany
| | - Igor Nenadić
- grid.10253.350000 0004 1936 9756Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Nils Opel
- grid.5949.10000 0001 2172 9288Institute for Translational Psychiatry, University of Münster, Münster, Germany ,grid.9613.d0000 0001 1939 2794Department of Psychiatry, Jena University Hospital/Friedrich-Schiller-University Jena, Jena, Germany
| | - Julia-Katharina Pfarr
- grid.10253.350000 0004 1936 9756Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Amanda L. Rodrigue
- grid.2515.30000 0004 0378 8438Department of Psychiatry & Behavioral Sciences, Boston Children’s Hospital, Boston, MA USA ,grid.38142.3c000000041936754XDepartment of Psychiatry, Harvard Medical School, Boston, MA USA
| | - Kelly Rootes-Murdy
- grid.256304.60000 0004 1936 7400Department of Psychology, Georgia State University, Atlanta, GA USA
| | - Alex J. Ross
- grid.55602.340000 0004 1936 8200Department of Psychiatry, Dalhousie University, Halifax, NS Canada
| | - Kang Sim
- grid.414752.10000 0004 0469 9592West Region, Institute of Mental Health, Singapore, Singapore ,grid.4280.e0000 0001 2180 6431Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore ,grid.59025.3b0000 0001 2224 0361Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Antonín Škoch
- grid.447902.cNational Institute of Mental Health, Klecany, Czech Republic ,grid.418930.70000 0001 2299 1368Department of Diagnostic and Interventional Radiology, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - Filip Spaniel
- grid.447902.cNational Institute of Mental Health, Klecany, Czech Republic ,grid.4491.80000 0004 1937 116XCharles University, Third Faculty of Medicine, Prague, Czech Republic
| | - Frederike Stein
- grid.10253.350000 0004 1936 9756Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Patrik Švancer
- grid.447902.cNational Institute of Mental Health, Klecany, Czech Republic ,grid.4491.80000 0004 1937 116XCharles University, Third Faculty of Medicine, Prague, Czech Republic
| | - Diana Tordesillas-Gutiérrez
- grid.484299.a0000 0004 9288 8771Department of Radiology, Marqués de Valdecilla University Hospital, Valdecilla Biomedical Research Institute IDIVAL, Santander, Spain ,grid.469953.40000 0004 1757 2371Computación Avanzada y Ciencia, Instituto de Física de Cantabria, CSIC, Santander, Spain
| | - Juan Undurraga
- Early Intervention in Psychosis Program, Instituto Psiquiátrico ‘Dr. José Horwitz B.’, Santiago, Chile ,grid.412187.90000 0000 9631 4901Department of Neurology and Psychiatry. Faculty of Medicine, Clínica Alemana Universidad del Desarrollo, Santiago, Chile
| | - Javier Váquez-Bourgon
- grid.469673.90000 0004 5901 7501Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain ,grid.7821.c0000 0004 1770 272XDepartment of Medicine and Psychiatry, School of Medicine, University of Cantabria, Santander, Spain ,grid.411325.00000 0001 0627 4262Department of Psychiatry, Marqués de Valdecilla University Hospital, Valdecilla Biomedical Research Institute IDIVAL, Santander, Spain
| | - Aristotle Voineskos
- grid.17063.330000 0001 2157 2938Centre for Addiction & Mental Health, Department of Psychiatry, University of Toronto, Toronto, ON Canada
| | - Esther Walton
- grid.7340.00000 0001 2162 1699Department of Psychology, University of Bath, Bath, UK
| | - Thomas W. Weickert
- grid.411023.50000 0000 9159 4457Department of Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, NY USA ,grid.250407.40000 0000 8900 8842Neuroscience Research Australia, Randwick, NSW Australia
| | - Cynthia Shannon Weickert
- grid.411023.50000 0000 9159 4457Department of Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, NY USA ,grid.250407.40000 0000 8900 8842Neuroscience Research Australia, Randwick, NSW Australia ,grid.1005.40000 0004 4902 0432School of Psychiatry, University of New South Wales, Sydney, NSW Australia
| | - Paul M. Thompson
- grid.42505.360000 0001 2156 6853Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA USA
| | - Theo G. M. van Erp
- grid.266093.80000 0001 0668 7243Psychiatry and Human Behavior, University of California Irvine, Irvine, CA USA ,grid.266093.80000 0001 0668 7243Center for the Neurobiology of Learning and Memory, University of California Irvine, Irvine, CA USA
| | - Jessica A. Turner
- grid.256304.60000 0004 1936 7400Department of Psychology, Georgia State University, Atlanta, GA USA
| | - Tomas Hajek
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada. .,National Institute of Mental Health, Klecany, Czech Republic.
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Ku BS, Aberizk K, Addington J, Bearden CE, Cadenhead KS, Cannon TD, Carrión RE, Compton MT, Cornblatt BA, Druss BG, Mathalon DH, Perkins DO, Tsuang MT, Woods SW, Walker EF. The Association Between Neighborhood Poverty and Hippocampal Volume Among Individuals at Clinical High-Risk for Psychosis: The Moderating Role of Social Engagement. Schizophr Bull 2022; 48:1032-1042. [PMID: 35689540 PMCID: PMC9434451 DOI: 10.1093/schbul/sbac055] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Reductions in hippocampal volume (HV) have been associated with both prolonged exposure to stress and psychotic illness. This study sought to determine whether higher levels of neighborhood poverty would be associated with reduced HV among individuals at clinical high-risk for psychosis (CHR-P), and whether social engagement would moderate this association. This cross-sectional study included a sample of participants (N = 174, age-range = 12-33 years, 35.1% female) recruited for the second phase of the North American Prodrome Longitudinal Study. Generalized linear mixed models tested the association between neighborhood poverty and bilateral HV, as well as the moderating role of social engagement on this association. Higher levels of neighborhood poverty were associated with reduced left (β = -0.180, P = .016) and right HV (β = -0.185, P = .016). Social engagement significantly moderated the relation between neighborhood poverty and bilateral HV. In participants with lower levels of social engagement (n = 77), neighborhood poverty was associated with reduced left (β = -0.266, P = .006) and right HV (β = -0.316, P = .002). Among participants with higher levels of social engagement (n = 97), neighborhood poverty was not significantly associated with left (β = -0.010, P = .932) or right HV (β = 0.087, P = .473). In this study, social engagement moderated the inverse relation between neighborhood poverty and HV. These findings demonstrate the importance of including broader environmental influences and indices of social engagement when conceptualizing adversity and potential interventions for individuals at CHR-P.
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Affiliation(s)
- Benson S Ku
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GAUSA
| | | | - Jean Addington
- Department of Psychiatry, University of Calgary, Calgary, Alberta, Canada
| | - Carrie E Bearden
- Departments of Psychiatry and Biobehavioral Sciences and Psychology, Semel Institute for Neuroscience and Human Behavior, UCLA, Los Angeles, USA
| | | | - Tyrone D Cannon
- Department of Psychiatry, Yale University, New Haven, CTUSA
- Department of Psychology, Yale University, New Haven, CTUSA
| | - Ricardo E Carrión
- Division of Psychiatry Research, The Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY, USA
- Department of Psychiatry, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
| | - Michael T Compton
- Department of Psychiatry, Columbia University Vagelos College of Physicians and Surgeons, and New York State Psychiatric Institute, New York, NY, USA
| | - Barbara A Cornblatt
- Division of Psychiatry Research, The Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY, USA
- Department of Psychiatry, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
| | - Benjamin G Druss
- Department of Health Policy and Management, Rollins School of Public Health, Emory University, Atlanta, GAUSA
| | - Daniel H Mathalon
- Department of Psychiatry, University of California, and San Francisco Veterans Affairs Medical Center, San Francisco, CAUSA
| | - Diana O Perkins
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
| | - Ming T Tsuang
- Department of Psychiatry, University of California, San Diego, CA, USA
| | - Scott W Woods
- Department of Psychiatry, Yale University, New Haven, CTUSA
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295
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Liu S, Guo Z, Cao H, Li H, Hu X, Cheng L, Li J, Liu R, Xu Y. Altered asymmetries of resting-state MRI in the left thalamus of first-episode schizophrenia. Chronic Dis Transl Med 2022; 8:207-217. [PMID: 36161199 PMCID: PMC9481880 DOI: 10.1002/cdt3.41] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Revised: 07/20/2022] [Accepted: 07/22/2022] [Indexed: 11/12/2022] Open
Abstract
Background Schizophrenia (SCZ) is a complex psychiatric disorder associated with widespread alterations in the subcortical brain structure. Hemispheric asymmetries are a fundamental organizational principle of the human brain and relate to human psychological and behavioral characteristics. We aimed to explore the state of thalamic lateralization of SCZ. Methods We used voxel-based morphometry (VBM) analysis, whole-brain analysis of low-frequency fluctuations (ALFF), fractional amplitude of low-frequency fluctuations (fALFF), and resting-state seed-based functional connectivity (FC) analysis to investigate brain structural and functional deficits in SCZ. Also, we applied Pearson's correlation analysis to validate the correlation between Positive and Negative Symptom Scale (PANSS) scores and them. Results Compared with healthy controls, SCZ showed increased gray matter volume (GMV) of the left thalamus (t = 2.214, p = 0.029), which positively correlated with general psychosis (r = 0.423, p = 0.010). SCZ also showed increased ALFF in the putamen, the caudate nucleus, the thalamus, fALFF in the nucleus accumbens (NAc), and the caudate nucleus, and decreased fALFF in the precuneus. The left thalamus showed significantly weaker resting-state FC with the amygdala and insula in SCZ. PANSS negative symptom scores were negatively correlated with the resting-state FC between the thalamus and the insula (r = -0.414, p = 0.025). Conclusions Collectively, these results suggest the possibility of aberrant laterality in the left thalamus and its FC with other related brain regions involved in the limbic system.
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Affiliation(s)
- Sha Liu
- Department of PsychiatryFirst Hospital/First Clinical Medical College of Shanxi Medical UniversityTaiyuanShanxiChina
- Shanxi Key Laboratory of Artificial Intelligence Assisted Diagnosis and Treatment for Mental DisorderFirst Hospital of Shanxi Medical UniversityTaiyuanShanxiChina
| | - Zhenglong Guo
- Department of PsychiatryFirst Hospital/First Clinical Medical College of Shanxi Medical UniversityTaiyuanShanxiChina
| | - Hongbao Cao
- School of Systems BiologyGeorge Mason UniversityManassasVirginiaUSA
| | - Hong Li
- Department of PsychiatryFirst Hospital/First Clinical Medical College of Shanxi Medical UniversityTaiyuanShanxiChina
- Shanxi Key Laboratory of Artificial Intelligence Assisted Diagnosis and Treatment for Mental DisorderFirst Hospital of Shanxi Medical UniversityTaiyuanShanxiChina
| | - Xiaodong Hu
- Department of PsychiatryFirst Hospital/First Clinical Medical College of Shanxi Medical UniversityTaiyuanShanxiChina
| | - Long Cheng
- Department of PsychiatryFirst Hospital/First Clinical Medical College of Shanxi Medical UniversityTaiyuanShanxiChina
| | - Jianying Li
- Department of PsychiatryFirst Hospital/First Clinical Medical College of Shanxi Medical UniversityTaiyuanShanxiChina
| | - Ruize Liu
- Stanley Center for Psychiatric ResearchBroad Institute of MIT and HarvardCambridgeMassachusettsUSA
| | - Yong Xu
- Department of PsychiatryFirst Hospital/First Clinical Medical College of Shanxi Medical UniversityTaiyuanShanxiChina
- Department of Mental HealthShanxi Medical UniversityTaiyuanShanxiChina
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296
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Regional and Sex-Specific Alterations in the Visual Cortex of Individuals With Psychosis Spectrum Disorders. Biol Psychiatry 2022; 92:396-406. [PMID: 35688762 DOI: 10.1016/j.biopsych.2022.03.023] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Revised: 03/10/2022] [Accepted: 03/29/2022] [Indexed: 11/23/2022]
Abstract
BACKGROUND Impairments of the visual system are implicated in psychotic disorders. However, studies exploring visual cortex (VC) morphology in this population are limited. Using data from the Bipolar-Schizophrenia Network on Intermediate Phenotypes consortium, we examined VC structure in psychosis probands and their first-degree relatives (RELs), sex differences in VC measures, and their relationships with cognitive and peripheral inflammatory markers. METHODS Cortical thickness, surface area, and volume of the primary (Brodmann area 17/V1) and secondary (Brodmann area 18/V2) visual areas and the middle temporal (V5/MT) region were quantified using FreeSurfer version 6.0 in psychosis probands (n = 530), first-degree RELs (n = 544), and healthy control subjects (n = 323). Familiality estimates were determined for probands and RELs. General cognition, response inhibition, and emotion recognition functions were assessed. Systemic inflammation was measured in a subset of participants. RESULTS Psychosis probands demonstrated significant area, thickness, and volume reductions in V1, V2, and MT, and their first-degree RELs demonstrated area and volume reductions in MT compared with control subjects. There was a higher degree of familiality for VC area than thickness. Area and volume reductions in V1 and V2 were sex dependent, affecting only female probands in a regionally specific manner. Reductions in some VC regions were correlated with poor general cognition, worse response inhibition, and increased C-reactive protein levels. CONCLUSIONS The visual cortex is a site of significant pathology in psychotic disorders, with distinct patterns of area and thickness changes, sex-specific and regional effects, potential contributions to cognitive impairments, and association with C-reactive protein levels.
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297
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The association between clinical and biological characteristics of depression and structural brain alterations. J Affect Disord 2022; 312:268-274. [PMID: 35760189 DOI: 10.1016/j.jad.2022.06.056] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 05/31/2022] [Accepted: 06/20/2022] [Indexed: 11/23/2022]
Abstract
BACKGROUND Structural brain alterations are observed in major depressive disorder (MDD). However, MDD is a highly heterogeneous disorder and specific clinical or biological characteristics of depression might relate to specific structural brain alterations. Clinical symptom subtypes of depression, as well as immuno-metabolic dysregulation associated with subtypes of depression, have been associated with brain alterations. Therefore, we examined if specific clinical and biological characteristics of depression show different brain alterations compared to overall depression. METHOD Individuals with and without depressive and/or anxiety disorders from the Netherlands Study of Depression and Anxiety (NESDA) (328 participants from three timepoints leading to 541 observations) and the Mood Treatment with Antidepressants or Running (MOTAR) study (123 baseline participants) were included. Symptom profiles (atypical energy-related profile, melancholic profile and depression severity) and biological indices (inflammatory, metabolic syndrome, and immuno-metabolic indices) were created. The associations of the clinical and biological profiles with depression-related structural brain measures (anterior cingulate cortex [ACC], orbitofrontal cortex, insula, and nucleus accumbens) were examined dimensionally in both studies and meta-analysed. RESULTS Depression severity was negatively associated with rostral ACC thickness (B = -0.55, pFDR = 0.03), and melancholic symptoms were negatively associated with caudal ACC thickness (B = -0.42, pFDR = 0.03). The atypical energy-related symptom profile and immuno-metabolic indices did not show a consistent association with structural brain measures across studies. CONCLUSION Overall depression- and melancholic symptom severity showed a dose-response relationship with reduced ACC thickness. No associations between immuno-metabolic dysregulation and structural brain alterations were found, suggesting that although both are associated with depression, distinct mechanisms may be involved.
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298
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Cattarinussi G, Kubera KM, Hirjak D, Wolf RC, Sambataro F. Neural Correlates of the Risk for Schizophrenia and Bipolar Disorder: A Meta-analysis of Structural and Functional Neuroimaging Studies. Biol Psychiatry 2022; 92:375-384. [PMID: 35523593 DOI: 10.1016/j.biopsych.2022.02.960] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Revised: 01/28/2022] [Accepted: 02/23/2022] [Indexed: 11/19/2022]
Abstract
BACKGROUND Clinical features and genetics overlap in schizophrenia (SCZ) and bipolar disorder (BD). Identifying brain alterations associated with genetic vulnerability for SCZ and BD could help to discover intermediate phenotypes, quantifiable biological traits with greater prevalence in unaffected relatives (RELs), and early recognition biomarkers in ultrahigh risk populations. However, a comprehensive meta-analysis of structural and functional magnetic resonance imaging (MRI) studies examining relatives of patients with SCZ and BD has not been performed yet. METHODS We systematically searched PubMed, Scopus, and Web of Science for structural and functional MRI studies investigating relatives and healthy control subjects. A total of 230 eligible neuroimaging studies (6274 SCZ-RELs, 1900 BD-RELs, 10,789 healthy control subjects) were identified. We conducted coordinate-based activation likelihood estimation meta-analyses on 26 structural MRI and 81 functional MRI investigations, including stratification by task type. We also meta-analyzed regional and global volumetric changes. Finally, we performed a meta-analysis of all MRI studies combined. RESULTS Reduced thalamic volume was present in both SCZ and BD RELs. Moreover, SCZ-RELs showed alterations in corticostriatal-thalamic networks, spanning the dorsolateral prefrontal cortex and temporal regions, while BD-RELs showed altered thalamocortical and limbic regions, including the ventrolateral prefrontal, superior parietal, and medial temporal cortices, with frontoparietal alterations in RELs of BD type I. CONCLUSIONS Familiarity for SCZ and BD is associated with alterations in the thalamocortical circuits, which may be the expression of the shared genetic mechanism underlying both disorders. Furthermore, the involvement of different prefrontocortical and temporal nodes may be associated with a differential symptom expression in the two disorders.
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Affiliation(s)
- Giulia Cattarinussi
- Department of Neuroscience, Università degli studi di Padova, Padova, Italy; Padova Neuroscience Center, Università degli studi di Padova, Padova, Italy
| | - Katharina M Kubera
- Department of General Psychiatry, Center for Psychosocial Medicine, Heidelberg University, Heidelberg, Germany
| | - Dusan Hirjak
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Robert C Wolf
- Department of General Psychiatry, Center for Psychosocial Medicine, Heidelberg University, Heidelberg, Germany
| | - Fabio Sambataro
- Department of Neuroscience, Università degli studi di Padova, Padova, Italy; Padova Neuroscience Center, Università degli studi di Padova, Padova, Italy.
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299
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Patterson TK, Nuechterlein KH, Subotnik KL, Castel AD, Knowlton BJ. Value-directed remembering in first-episode schizophrenia. Neuropsychology 2022; 36:540-551. [PMID: 35737534 PMCID: PMC9945935 DOI: 10.1037/neu0000840] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Abstract
OBJECTIVE Memory deficits in individuals with schizophrenia are well-established, but less is known about how schizophrenia affects metacognitive processes such as metamemory. We investigated metamemory ability using the value-directed remembering task, which assesses the degree to which participants use value cues to guide their learning of a list of items (i.e., their memory selectivity). METHOD Participants were patients undergoing treatment following a recent first episode of schizophrenia (n = 20) and demographically comparable healthy controls (n = 18). Participants viewed six lists of 24 words where each word was paired with either a low value (1-3 points) or a high value (10-12 points), and they were instructed to maximize their score on free recall tests given after each list. After the final free recall test, participants completed a recognition test where they gave remember/know judgments. RESULTS On tests of free recall, patients showed reduced memory selectivity relative to healthy controls. On the recognition test, patients failed to show an effect of value on recognition of nonrecalled words, in contrast to healthy controls, who showed a significant value effect that was characterized by greater "remember" judgments. Patients initially overestimated their memory capacity but were able to adjust their estimates to be more accurate based on task experience. Patients' self-reports of memory selectivity were unrelated to their actual memory selectivity. CONCLUSIONS Patients with first-episode schizophrenia had substantial impairments on the value-directed remembering task, but areas of preserved metamemory ability were also observed. These findings have potential implications for cognitive training interventions. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
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Affiliation(s)
| | - Keith H. Nuechterlein
- Department of Psychology, University of California, Los Angeles
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles
| | - Kenneth L. Subotnik
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles
| | - Alan D. Castel
- Department of Psychology, University of California, Los Angeles
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300
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Li Z, Li D, He Y, Wang K, Ma X, Chen X. Cross-Disorder Analysis of Shared Genetic Components Between Cortical Structures and Major Psychiatric Disorders. Schizophr Bull 2022; 48:1145-1154. [PMID: 35265999 PMCID: PMC9434450 DOI: 10.1093/schbul/sbac019] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
BACKGROUND AND HYPOTHESIS Although large-scale neuroimaging studies have demonstrated similar patterns of structural brain abnormalities across major psychiatric disorders, the underlying genetic etiology behind these similar cross-disorder patterns is not well understood. STUDY DESIGN We quantified the extent of shared genetic components between cortical structures and major psychiatric disorders (CS-MPD) by using genome-wide association study (GWAS) summary statistics of 70 cortical structures (surface area and thickness of the whole cortex and 34 cortical regions) and five major psychiatric disorders, consisting of attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), and schizophrenia (SCZ). Cross-disorder analyses were then conducted to estimate the degree of similarity in CS-MPD shared genetic components among these disorders. STUDY RESULTS The CS-MPD shared genetic components have medium-to-strong positive correlations in ADHD, BD, MDD, and SCZ (r = 0.415 to r = 0.806) while ASD was significantly correlated with ADHD, BD, and SCZ (r = 0.388 to r = 0.403). These pairwise correlations of CS-MPD shared genetic components among disorders were significantly associated with corresponding cross-disorder similarities in cortical structural abnormalities (r = 0.668), accounting for 44% variance. In addition, one latent shared factor consisted primarily of BD, MDD, and SCZ, explaining 62.47% of the total variance in CS-MPD shared genetic components of all disorders. CONCLUSIONS The current results bridge the gap between shared cross-disorder heritability and shared structural brain abnormalities in major psychiatric disorders, providing important implications for a shared genetic basis of cortical structures in these disorders.
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Affiliation(s)
- Zongchang Li
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, PR China.,National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital, Central South University, Changsha, PR China.,China National Technology Institute on Mental Disorders & Hunan Key Laboratory of Psychiatry and Mental Health, Mental Health Institute, The Second Xiangya Hospital, Central South University, Changsha, PR China
| | - David Li
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, PR China
| | - Ying He
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, PR China.,National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital, Central South University, Changsha, PR China.,China National Technology Institute on Mental Disorders & Hunan Key Laboratory of Psychiatry and Mental Health, Mental Health Institute, The Second Xiangya Hospital, Central South University, Changsha, PR China
| | - Kangli Wang
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, PR China
| | - Xiaoqian Ma
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, PR China
| | - Xiaogang Chen
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, PR China.,National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital, Central South University, Changsha, PR China.,China National Technology Institute on Mental Disorders & Hunan Key Laboratory of Psychiatry and Mental Health, Mental Health Institute, The Second Xiangya Hospital, Central South University, Changsha, PR China
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