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Bandeira CE, Grevet EH, Vitola ES, da Silva BS, Cupertino RB, Picon FA, Ito LT, Tavares MEDA, Rovaris DL, Grimm O, Bau CHD. Exploring Neuroimaging Association Scores in adulthood ADHD and middle-age trajectories. J Psychiatr Res 2024; 176:348-353. [PMID: 38936238 DOI: 10.1016/j.jpsychires.2024.06.025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/17/2023] [Revised: 05/29/2024] [Accepted: 06/17/2024] [Indexed: 06/29/2024]
Abstract
Attention-Deficit/Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder associated with brain differences in children, but not in adults. A combined evaluation of the regional brain differences could improve statistical power and, consequently, allow the detection of possible effects in adults. Thus, our aim is to verify whether Neuroimaging Association Scores (NAS) are associated with adulthood ADHD and clinical trajectories of the disorder in midlife. Clinical and neuroimaging data were collected for 121 subjects with ADHD (mean age: 47.1 ± 10.5; 43% male) and 82 controls (mean age: 38.2 ± 9.0; 54.9% male). Cases were assessed seven and thirteen years after baseline diagnosis, and their clinical trajectories were classified as stable if they fulfilled ADHD diagnosis in all assessments or unstable if they presented remission and recurrence of symptoms. Neuroimaging data were acquired in the last clinical assessment (thirteen years after baseline) and NAS were calculated as a weighted sum of the associations previously reported by meta-analyses for three types of structural brain modalities: cortical thickness, cortical surface area, and subcortical volume. The NAS for cortical surface area was higher in cases compared to controls. No association was found for NAS and number of symptoms of ADHD or clinical trajectories. The fact that differences were restricted to ADHD diagnostic status suggests a susceptibility effect that is not extended to subtle aspects of the disorder. Our results also suggest that evaluating overall effects may have advantages especially when applied to adult ADHD samples.
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Affiliation(s)
- Cibele Edom Bandeira
- ADHD Outpatient Program, Clinical Research Center, Department of Psychiatry, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Laboratory of Physiological Genomics of Mental Health (PhysioGen Lab), Instituto de Ciencias Biomedicas da Universidade de São Paulo, São Paulo, Brazil
| | - Eugenio Horacio Grevet
- ADHD Outpatient Program, Clinical Research Center, Department of Psychiatry, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Laboratory of Developmental Psychiatry, Center of Experimental Research, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil; Department of Psychiatry, Faculty of Medicine, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Graduate Program in Psychiatry and Behavioral Sciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Eduardo Schneider Vitola
- ADHD Outpatient Program, Clinical Research Center, Department of Psychiatry, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Laboratory of Physiological Genomics of Mental Health (PhysioGen Lab), Instituto de Ciencias Biomedicas da Universidade de São Paulo, São Paulo, Brazil
| | - Bruna Santos da Silva
- ADHD Outpatient Program, Clinical Research Center, Department of Psychiatry, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Department of Basic Health Sciences, Federal University of Health Sciences of Porto Alegre (UFCSPA), Porto Alegre, Brazil
| | | | - Felipe Almeida Picon
- ADHD Outpatient Program, Clinical Research Center, Department of Psychiatry, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Lucas Toshio Ito
- Department of Biochemistry, Universidade Federal de São Paulo, São Paulo, Brazil; Laboratory of Integrative Neuroscience, Universidade Federal de São Paulo, São Paulo, Brazil
| | - Maria Eduarda de Araujo Tavares
- ADHD Outpatient Program, Clinical Research Center, Department of Psychiatry, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Laboratory of Developmental Psychiatry, Center of Experimental Research, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil; Graduate Program in Genetics and Molecular Biology, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Diego Luiz Rovaris
- ADHD Outpatient Program, Clinical Research Center, Department of Psychiatry, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Laboratory of Physiological Genomics of Mental Health (PhysioGen Lab), Instituto de Ciencias Biomedicas da Universidade de São Paulo, São Paulo, Brazil
| | - Oliver Grimm
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital, Goethe University, Frankfurt, Germany
| | - Claiton Henrique Dotto Bau
- ADHD Outpatient Program, Clinical Research Center, Department of Psychiatry, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Laboratory of Developmental Psychiatry, Center of Experimental Research, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil; Graduate Program in Psychiatry and Behavioral Sciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Graduate Program in Genetics and Molecular Biology, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Department of Genetics, Institute of Biosciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil.
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2
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Bergstrom JJD, Fu MM. Dysregulation of myelination-related genes in schizophrenia. J Neurochem 2024. [PMID: 39086020 DOI: 10.1111/jnc.16152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Revised: 06/03/2024] [Accepted: 06/05/2024] [Indexed: 08/02/2024]
Abstract
Schizophrenic individuals display disrupted myelination patterns, altered oligodendrocyte distribution, and abnormal oligodendrocyte morphology. Schizophrenia is linked with dysregulation of a variety of genes involved in oligodendrocyte function and myelin production. Single-nucleotide polymorphisms (SNPs) and rare mutations in myelination-related genes are observed in certain schizophrenic populations, representing potential genetic risk factors. Downregulation of myelination-related RNAs and proteins, particularly in frontal and limbic regions, is consistently associated with the disorder across multiple studies. These findings support the notion that disruptions in myelination may contribute to the cognitive and behavioral impairments experienced in schizophrenia, although further evidence of causation is needed.
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Affiliation(s)
| | - Meng-Meng Fu
- Department of Molecular and Cell Biology, UC Berkeley, Berkeley, California, USA
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Li N, Li Y, Yu T, Gou M, Chen W, Wang X, Tong J, Chen S, Tan S, Wang Z, Tian B, Li CSR, Tan Y. Immunosenescence-related T cell phenotypes and white matter in schizophrenia patients with tardive dyskinesia. Schizophr Res 2024; 269:36-47. [PMID: 38723519 DOI: 10.1016/j.schres.2024.04.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Revised: 03/18/2024] [Accepted: 04/22/2024] [Indexed: 06/17/2024]
Abstract
Schizophrenia patients with tardive dyskinesia (TD) are associated with accelerated biological aging, immunological dysfunction, and premature morbidity and mortality. Older individuals are particularly vulnerable to TD development. As a characteristic of immunosenescence, alterations in the relative proportions of naïve or memory T cell subpopulations may be negatively or positively associated with brain structure abnormalities; however, whether these changes are correlated with TD remains unclear. In this study, we investigated correlations between distributions of T cell phenotypes and brain structure abnormalities (especially white matter) in schizophrenia patients with (TD) and without (NTD) TD (n = 50 and 58, respectively) relative to healthy controls (HC, n = 41). Immune markers, including naïve (CD45RA+), memory (CD45RO+), and apoptotic (CD95+) CD4+ and CD8+ T cells, were examined by flow cytometry, as were the intracellular levels of cytokines (interferon (IFN)-γ, interleukin (IL)-6, IL-1β, and tumor necrosis factor (TNF)-α) in CD8 + CD45RA + CD95+ and CD8 + CD45RO + CD95+ T cells. MRI was employed to evaluate the fractional anisotropy (FA) of white matter tracts and subcortical volumes, following published routines. The percentage of CD8 + CD45RO + CD95+ T cells was higher in TD compared with NTD and HC groups and correlated with the choroid plexus volume in TD group. The intracellular level of IFN-γ in CD8 + CD45RO + CD95+ T cells, the FA of the fornix/stria terminalis, and the pallidum volume were correlated with orofacial TD, whereas the FAs of the inferior fronto-occipital fasciculus, cingulum, and superior longitudinal fasciculus were correlated with limb-truncal TD. These findings provide preliminary evidence that the association between immunosenescence-related T cell subpopulations and brain structure may underline the pathological process of TD.
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Affiliation(s)
- Na Li
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, PR China
| | - Yanli Li
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, PR China
| | - Ting Yu
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, PR China
| | - Mengzhuang Gou
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, PR China
| | - Wenjin Chen
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, PR China
| | - Xiaoying Wang
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, PR China
| | - Jinghui Tong
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, PR China
| | - Song Chen
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, PR China
| | - Shuping Tan
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, PR China
| | - Zhiren Wang
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, PR China
| | - Baopeng Tian
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, PR China
| | - Chiang-Shan R Li
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Yunlong Tan
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, PR China.
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Li YT, Zhang C, Han JC, Shang YX, Chen ZH, Cui GB, Wang W. Neuroimaging features of cognitive impairments in schizophrenia and major depressive disorder. Ther Adv Psychopharmacol 2024; 14:20451253241243290. [PMID: 38708374 PMCID: PMC11070126 DOI: 10.1177/20451253241243290] [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: 07/13/2023] [Accepted: 03/14/2024] [Indexed: 05/07/2024] Open
Abstract
Cognitive dysfunctions are one of the key symptoms of schizophrenia (SZ) and major depressive disorder (MDD), which exist not only during the onset of diseases but also before the onset, even after the remission of psychiatric symptoms. With the development of neuroimaging techniques, these non-invasive approaches provide valuable insights into the underlying pathogenesis of psychiatric disorders and information of cognitive remediation interventions. This review synthesizes existing neuroimaging studies to examine domains of cognitive impairment, particularly processing speed, memory, attention, and executive function in SZ and MDD patients. First, white matter (WM) abnormalities are observed in processing speed deficits in both SZ and MDD, with distinct neuroimaging findings highlighting WM connectivity abnormalities in SZ and WM hyperintensity caused by small vessel disease in MDD. Additionally, the abnormal functions of prefrontal cortex and medial temporal lobe are found in both SZ and MDD patients during various memory tasks, while aberrant amygdala activity potentially contributes to a preference to negative memories in MDD. Furthermore, impaired large-scale networks including frontoparietal network, dorsal attention network, and ventral attention network are related to attention deficits, both in SZ and MDD patients. Finally, abnormal activity and volume of the dorsolateral prefrontal cortex (DLPFC) and abnormal functional connections between the DLPFC and the cerebellum are associated with executive dysfunction in both SZ and MDD. Despite these insights, longitudinal neuroimaging studies are lacking, impeding a comprehensive understanding of cognitive changes and the development of early intervention strategies for SZ and MDD. Addressing this gap is critical for advancing our knowledge and improving patient prognosis.
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Affiliation(s)
- Yu-Ting Li
- Department of Radiology, Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University, Xi’an, Shaanxi, China
| | - Chi Zhang
- Department of Radiology, Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University, Xi’an, Shaanxi, China
- Shaanxi University of Chinese Medicine, Xianyang, Shaanxi, China
| | - Jia-Cheng Han
- Department of Radiology, Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University, Xi’an, Shaanxi, China
| | - Yu-Xuan Shang
- Department of Radiology, Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University, Xi’an, Shaanxi, China
| | - Zhu-Hong Chen
- Department of Radiology, Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University, Xi’an, Shaanxi, China
| | - Guang-Bin Cui
- Department of Radiology, Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University, 569 Xinsi Road, Xi’an 710038, Shaanxi, China
| | - Wen Wang
- Department of Radiology, Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University, 569 Xinsi Road, Xi’an 710038, Shaanxi, China
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Gou M, Li W, Tong J, Zhou Y, Xie T, Yu T, Feng W, Li Y, Chen S, Tian B, Tan S, Wang Z, Pan S, Luo X, Li CSR, Zhang P, Huang J, Tian L, Hong LE, Tan Y. Correlation of Immune-Inflammatory Response System (IRS)/Compensatory Immune-Regulatory Reflex System (CIRS) with White Matter Integrity in First-Episode Patients with Schizophrenia. Mol Neurobiol 2024; 61:2754-2763. [PMID: 37932545 DOI: 10.1007/s12035-023-03694-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Accepted: 10/04/2023] [Indexed: 11/08/2023]
Abstract
Several studies have reported compromised white matter integrity, and that some inflammatory mediators may underlie this functional dysconnectivity in the brain of patients with schizophrenia. The immune-inflammatory response system and compensatory immune-regulatory reflex system (IRS/CIRS) are novel biomarkers for exploring the role of immune imbalance in the pathophysiological mechanism of schizophrenia. This study aimed to explore the little-known area regarding the composite score of peripheral cytokines, the IRS/CIRS, and its correlation with white matter integrity and the specific microstructures most affected in schizophrenia. First-episode patients with schizophrenia (FEPS, n = 94) and age- and sex-matched healthy controls (HCs, n = 50) were enrolled in this study. Plasma cytokine levels were measured using enzyme-linked immunosorbent assay (ELISA), and psychopathology was assessed using the Positive and Negative Syndrome Scale (PANSS). The whole brain white matter integrity was measured by fractional anisotropy (FA) from diffusion tensor imaging (DTI) using a 3-T Prisma MRI scanner. The IRS/CIRS in FEPS was significantly higher than that in HCs (p = 1.5 × 10-5) and Cohen's d effect size was d = 0.74. FEPS had a significantly lower whole-brain white matter average FA (p = 0.032), which was negatively associated with IRS/CIRS (p = 0.029, adjusting for age, sex, years of education, BMI, and total intracranial volume), but not in the HCs (p > 0.05). Among the white matter microstructures, only the cortico-spinal tract was significantly correlated with IRS/CIRS in FEPS (r = - 0.543, p = 0.0009). Therefore, elevated IRS/CIRS may affect the white matter in FEPS.
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Affiliation(s)
- Mengzhuang Gou
- Beijing Huilongguan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Wei Li
- Beijing Huilongguan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Jinghui Tong
- Beijing Huilongguan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Yanfang Zhou
- Beijing Huilongguan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Ting Xie
- Beijing Huilongguan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Ting Yu
- Beijing Huilongguan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Wei Feng
- Beijing Huilongguan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Yanli Li
- Beijing Huilongguan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Song Chen
- Beijing Huilongguan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Baopeng Tian
- Beijing Huilongguan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Shuping Tan
- Beijing Huilongguan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Zhiren Wang
- Beijing Huilongguan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Shujuan Pan
- Beijing Huilongguan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Xingguang Luo
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Chiang-Shan R Li
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Ping Zhang
- Beijing Huilongguan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Junchao Huang
- Beijing Huilongguan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Li Tian
- Department of Physiology, Faculty of Medicine, Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, Estonia.
| | - L Elliot Hong
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, USA
| | - Yunlong Tan
- Beijing Huilongguan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China.
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Chen W, Tian Y, Gou M, Wang L, Tong J, Zhou Y, Feng W, Li Y, Chen S, Liu Y, Wang Z, Pan S, Zhang P, Huang J, Yang X, Li CSR, Tian L, Hong LE, Tan Y. Role of the immune-kynurenine pathway in treatment-resistant schizophrenia. Prog Neuropsychopharmacol Biol Psychiatry 2024; 130:110926. [PMID: 38147973 DOI: 10.1016/j.pnpbp.2023.110926] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 12/18/2023] [Accepted: 12/22/2023] [Indexed: 12/28/2023]
Abstract
BACKGROUND The immune-inflammatory response system (IRS) and kynurenine pathway (KP) have been implicated in the pathophysiology of schizophrenia. Studies have shown inflammation-related effects on KP metabolism in patients with schizophrenia. This study investigated the relationship between KP metabolites, IRS, and the compensatory immune-regulatory reflex system (CIRS) in patients with treatment-resistant schizophrenia (TRS). METHODS Patients with (n = 53) and without TRS (n = 47), and healthy controls (HCs, n = 49) were enrolled. We quantified plasma levels of pro-inflammatory cytokines (interleukin [IL]-1β, IL-2, IL-6, soluble(s)IL-6 receptor, IL-8, IL-12, IL-17, IL-18, interferon-γ, and tumor necrosis factor[TNF]-α) and anti-inflammatory cytokines (IL-1 receptor antagonist, IL-4, IL-10, tumor growth factor [TGF]-β1, TGF-β2, soluble (s) IL-2 receptor subunit α, sIL-2 receptor subunit β, and sTNF-α receptor 1) and calculated the IRS/CIRS ratio. We also tested serum metabolites of the KP, including kynurenine (KYN), kynurenic acid (KYNA), and quinolinic acid (QUIN), along with the QUIN/KYNA ratio. RESULTS Patients with TRS had significantly higher IRS/CIRS ratio than non-TRS patients (p = 0.002) and HCs (p = 0.007), and significantly lower KYN (p = 0.001) and KYNA (p = 0.01) levels than HCs. Binary logistic regression analysis revealed that a younger age at illness onset (odds ratio [OR] = 0.91, p = 0.02) and a higher IRS/CIRS ratio (OR = 1.22; p = 0.007) were risk factors for patients with TRS. After further adjusted for age of onset, the QUIN/KYNA ratio (β = 0.97; p = 0.02) significantly moderated the relationship between IRS/CIRS and TRS, showing that in the higher QUIN/KYNA condition, higher IRS/CIRS ratio were significantly and more likely to be associated with patients with TRS (β = 0.12, z = 3.19, p = 0.001), whereas in the low QUIN/KYNA condition, the association between IRS/CIRS ratio and TRS was weak and insignificant. CONCLUSIONS The peripheral immune response was imbalanced in TRS and was preferentially directed towards the IRS compared to patients without TRS and healthy controls, which is likely to play a role in neurotoxicity. Additionally, peripheral KP activation was also imbalanced, as evidenced by significantly reduced KYN and KYNA levels in patients with TRS compared to healthy controls, but none of KP metabolisms were significantly difference in non-TRS patients compared to healthy controls. QUIN/KYNA ratio involving to the degree of activation of NMDA receptors, indicated the neurotoxic level of the KP activation. The interaction between IRS/CIRS and QUIN/KYNA ratio was significant in predicting TRS, and our findings suggest a potential role for the immune-kynurenine pathway in TRS pathogenesis.
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Affiliation(s)
- Wenjin Chen
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Yichang Tian
- Department of Human Reproductive Medicine, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing, China; Beijing Maternal and Child Health Care Hospital, Beijing, China
| | - Mengzhuang Gou
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Leilei Wang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Jinghui Tong
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Yanfang Zhou
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Wei Feng
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Yanli Li
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Song Chen
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Yongchang Liu
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Zhiren Wang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Shujuan Pan
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Ping Zhang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Junchao Huang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Xiaokui Yang
- Department of Human Reproductive Medicine, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing, China; Beijing Maternal and Child Health Care Hospital, Beijing, China
| | - Chiang-Shan R Li
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Li Tian
- Institute of Biomedicine and Translational Medicine, Department of Physiology, Faculty of Medicine, University of Tartu, Tartu, Estonia
| | - L Elliot Hong
- Department of Psychiatry and Behavioral Sciences, University of Texas Health Science Center, Houston, TX 77030, USA
| | - Yunlong Tan
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China.
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Xie Y, Li C, Guan M, Zhang T, Ma C, Wang Z, Ma Z, Wang H, Fang P. Low-frequency rTMS induces modifications in cortical structural connectivity - functional connectivity coupling in schizophrenia patients with auditory verbal hallucinations. Hum Brain Mapp 2024; 45:e26614. [PMID: 38375980 PMCID: PMC10878014 DOI: 10.1002/hbm.26614] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 01/09/2024] [Accepted: 01/19/2024] [Indexed: 02/21/2024] Open
Abstract
Auditory verbal hallucinations (AVH) are distinctive clinical manifestations of schizophrenia. While low-frequency repetitive transcranial magnetic stimulation (rTMS) has demonstrated potential in mitigating AVH, the precise mechanisms by which it operates remain obscure. This study aimed to investigate alternations in structural connectivity and functional connectivity (SC-FC) coupling among schizophrenia patients with AVH prior to and following treatment with 1 Hz rTMS that specifically targets the left temporoparietal junction. Initially, patients exhibited significantly reduced macroscopic whole brain level SC-FC coupling compared to healthy controls. Notably, SC-FC coupling increased significantly across multiple networks, including the somatomotor, dorsal attention, ventral attention, frontoparietal control, and default mode networks, following rTMS treatment. Significant alternations in SC-FC coupling were noted in critical nodes comprising the somatomotor network and the default mode network, such as the precentral gyrus and the ventromedial prefrontal cortex, respectively. The alternations in SC-FC coupling exhibited a correlation with the amelioration of clinical symptom. The results of our study illuminate the intricate relationship between white matter structures and neuronal activity in patients who are receiving low-frequency rTMS. This advances our understanding of the foundational mechanisms underlying rTMS treatment for AVH.
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Affiliation(s)
- Yuanjun Xie
- Military Medical Psychology SchoolFourth Military Medical UniversityXi'anChina
- Department of Radiology, Xijing HospitalFourth Military Medical UniversityXi'anChina
| | - Chenxi Li
- Military Medical Psychology SchoolFourth Military Medical UniversityXi'anChina
| | - Muzhen Guan
- Department of Mental HealthXi'an Medical CollegeXi'anChina
| | - Tian Zhang
- Military Medical Psychology SchoolFourth Military Medical UniversityXi'anChina
| | - Chaozong Ma
- Military Medical Psychology SchoolFourth Military Medical UniversityXi'anChina
| | - Zhongheng Wang
- Department of Psychiatry, Xijing HospitalFourth Military Medical UniversityXi'anChina
| | - Zhujing Ma
- Military Medical Psychology SchoolFourth Military Medical UniversityXi'anChina
| | - Huaning Wang
- Department of Psychiatry, Xijing HospitalFourth Military Medical UniversityXi'anChina
| | - Peng Fang
- Military Medical Psychology SchoolFourth Military Medical UniversityXi'anChina
- Shaanxi Provincial Key Laboratory of Bioelectromagnetic Detection and Intelligent PerceptionXi'anChina
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8
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van der Pluijm M, Alting M, Schrantee A, Edden RAE, Booij J, de Haan L, van de Giessen E. Glutamate and GABA levels in the anterior cingulate cortex in treatment resistant first episode psychosis patients. Schizophr Res 2024; 264:471-478. [PMID: 38277736 DOI: 10.1016/j.schres.2024.01.025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Revised: 12/12/2023] [Accepted: 01/14/2024] [Indexed: 01/28/2024]
Abstract
BACKGROUND Around 30 % of schizophrenia patients do not respond sufficiently to conventional antipsychotic treatment. Glutamate and γ-aminobutyric acid (GABA) may be implicated in treatment resistant (TR) patients. Some data indicate that TR patients show increased glutamate levels compared to responders, but findings are inconclusive and limited in the early disease stage. Furthermore, the two neurotransmitters have rarely been assessed in conjunction. We therefore aimed to investigate the role of GABA+ and glutamate in first episode TR patients and explore whether these neurometabolites could be potential predictive markers for TR schizophrenia. STUDY DESIGN We used proton magnetic resonance spectroscopy (MRS) to assess glutamate + glutamine (Glx) and GABA including macromolecules (GABA+) in the anterior cingulate cortex (ACC) of 58 first episode psychosis patients. At six months follow-up treatment response was determined and in a subgroup of 33 patients a follow-up MRS scan was acquired. STUDY RESULTS Glx and GABA+ levels were not significantly different between TR patients and responders at baseline and the levels did not change at six months follow-up. The groups differed in voxel fractions, which could have influenced our results even though we corrected for these differences. CONCLUSIONS Our findings do not provide evidence that ACC Glx or GABA+ levels are potential biomarkers for TR in first episode psychosis. Future research needs to take in to account voxel fractions and report potential differences. Comparison with previous literature suggests that illness duration, clozapine responsiveness and medication effects may partly explain the heterogeneous results on Glx and GABA+ levels in TR.
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Affiliation(s)
- Marieke van der Pluijm
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, the Netherlands; Department of Psychiatry, Amsterdam UMC, University of Amsterdam, the Netherlands.
| | - Maartje Alting
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, the Netherlands
| | - Anouk Schrantee
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, the Netherlands
| | - Richard A E Edden
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Jan Booij
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, the Netherlands
| | - Lieuwe de Haan
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, the Netherlands
| | - Elsmarieke van de Giessen
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, the Netherlands
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Boen R, Kaufmann T, van der Meer D, Frei O, Agartz I, Ames D, Andersson M, Armstrong NJ, Artiges E, Atkins JR, Bauer J, Benedetti F, Boomsma DI, Brodaty H, Brosch K, Buckner RL, Cairns MJ, Calhoun V, Caspers S, Cichon S, Corvin AP, Crespo-Facorro B, Dannlowski U, David FS, de Geus EJC, de Zubicaray GI, Desrivières S, Doherty JL, Donohoe G, Ehrlich S, Eising E, Espeseth T, Fisher SE, Forstner AJ, Fortaner-Uyà L, Frouin V, Fukunaga M, Ge T, Glahn DC, Goltermann J, Grabe HJ, Green MJ, Groenewold NA, Grotegerd D, Grøntvedt GR, Hahn T, Hashimoto R, Hehir-Kwa JY, Henskens FA, Holmes AJ, Håberg AK, Haavik J, Jacquemont S, Jansen A, Jockwitz C, Jönsson EG, Kikuchi M, Kircher T, Kumar K, Le Hellard S, Leu C, Linden DE, Liu J, Loughnan R, Mather KA, McMahon KL, McRae AF, Medland SE, Meinert S, Moreau CA, Morris DW, Mowry BJ, Mühleisen TW, Nenadić I, Nöthen MM, Nyberg L, Ophoff RA, Owen MJ, Pantelis C, Paolini M, Paus T, Pausova Z, Persson K, Quidé Y, Marques TR, Sachdev PS, Sando SB, Schall U, Scott RJ, Selbæk G, Shumskaya E, Silva AI, Sisodiya SM, Stein F, Stein DJ, Straube B, Streit F, Strike LT, Teumer A, Teutenberg L, Thalamuthu A, Tooney PA, Tordesillas-Gutierrez D, Trollor JN, van 't Ent D, van den Bree MBM, van Haren NEM, Vázquez-Bourgon J, Völzke H, Wen W, Wittfeld K, Ching CRK, Westlye LT, Thompson PM, Bearden CE, Selmer KK, Alnæs D, Andreassen OA, Sønderby IE. Beyond the Global Brain Differences: Intraindividual Variability Differences in 1q21.1 Distal and 15q11.2 BP1-BP2 Deletion Carriers. Biol Psychiatry 2024; 95:147-160. [PMID: 37661008 PMCID: PMC7615370 DOI: 10.1016/j.biopsych.2023.08.018] [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: 04/11/2023] [Revised: 07/25/2023] [Accepted: 08/21/2023] [Indexed: 09/05/2023]
Abstract
BACKGROUND Carriers of the 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants exhibit regional and global brain differences compared with noncarriers. However, interpreting regional differences is challenging if a global difference drives the regional brain differences. Intraindividual variability measures can be used to test for regional differences beyond global differences in brain structure. METHODS Magnetic resonance imaging data were used to obtain regional brain values for 1q21.1 distal deletion (n = 30) and duplication (n = 27) and 15q11.2 BP1-BP2 deletion (n = 170) and duplication (n = 243) carriers and matched noncarriers (n = 2350). Regional intra-deviation scores, i.e., the standardized difference between an individual's regional difference and global difference, were used to test for regional differences that diverge from the global difference. RESULTS For the 1q21.1 distal deletion carriers, cortical surface area for regions in the medial visual cortex, posterior cingulate, and temporal pole differed less and regions in the prefrontal and superior temporal cortex differed more than the global difference in cortical surface area. For the 15q11.2 BP1-BP2 deletion carriers, cortical thickness in regions in the medial visual cortex, auditory cortex, and temporal pole differed less and the prefrontal and somatosensory cortex differed more than the global difference in cortical thickness. CONCLUSIONS We find evidence for regional effects beyond differences in global brain measures in 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants. The results provide new insight into brain profiling of the 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants, with the potential to increase understanding of the mechanisms involved in altered neurodevelopment.
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Affiliation(s)
- Rune Boen
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway; Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
| | - Tobias Kaufmann
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health, University of Tübingen, Germany; German Center for Mental Health (DZPG), partner site Tübingen, Tübingen, Germany
| | - Dennis van der Meer
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, Netherlands
| | - Oleksandr Frei
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Centre for Bioinformatics, Department of Informatics, University of Oslo, Oslo, Norway
| | - Ingrid Agartz
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Clinical Research, Diakonhjemmet Hospital, Oslo, Norway; Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Health Care Services, Stockholm, Sweden
| | - David Ames
- University of Melbourne Academic Unit for Psychiatry of Old Age, St George's Hospital, Kew, Victoria, Australia; National Ageing Research Institute, Parkville, Victoria, Australia
| | - Micael Andersson
- Department of Integrative Medical Biology and Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden
| | - Nicola J Armstrong
- Department of Mathematics and Statistics, Curtin University, Perth, Western Australia, Australia
| | - Eric Artiges
- Institut National de la Santé et de la Recherche Médicale U1299, École Normale Supérieure Paris-Saclay, Université Paris Saclay, Gif-sur-Yvette, France; Établissement public de santé (EPS) Barthélemy Durand, Etampes, France
| | - Joshua R Atkins
- School of Biomedical Sciences and Pharmacy, College of Medicine, Health and Wellbeing, University of Newcastle, Callaghan, New South Wales, Australia; Precision Medicine Research Program, Hunter Medical Research Institute, Newcastle, New South Wales, Australia; Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Jochen Bauer
- University Clinic for Radiology, University of Münster, Münster, Germany
| | - Francesco Benedetti
- Psychiatry and Clinical Psychobiology Unit, Division of Neuroscience, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) San Raffaele Scientific Institute, Milan, Italy; Division of Neuroscience, Psychiatry and Clinical Psychobiology Unit, Istituto di Ricovero e Cura a Carattere Scientifico San Raffaele Scientific Institute, Milan, Italy
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Henry Brodaty
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, New South Wales, Australia
| | - Katharina Brosch
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Randy L Buckner
- Department of Psychology and Center for Brain Science, Harvard University, Cambridge, Massachusetts; Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts
| | - Murray J Cairns
- School of Biomedical Sciences and Pharmacy, College of Medicine, Health and Wellbeing, University of Newcastle, Callaghan, New South Wales, Australia; Precision Medicine Research Program, Hunter Medical Research Institute, Newcastle, New South Wales, Australia
| | - Vince Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University/Georgia Institute of Technology/Emory University, Atlanta, Georgia
| | - Svenja Caspers
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany; Institute for Anatomy I, Medical Faculty & University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Sven Cichon
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany; Department of Biomedicine, University of Basel, Basel, Switzerland; University Hospital Basel, Institute of Medical Genetics and Pathology, Basel, Switzerland
| | - Aiden P Corvin
- Department of Psychiatry, Trinity College Dublin, Dublin, Ireland
| | - Benedicto Crespo-Facorro
- Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocío/Centro superior de investigaciones científicas (CSIC), Sevilla, Spain; Centro de Investigación Biomédica en Red Salud Mental, Sevilla, Spain; Department of Psychiatry, University of Sevilla, Sevilla, Spain
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Friederike S David
- Institute of Human Genetics, University of Bonn, School of Medicine and University Hospital Bonn, Bonn, Germany
| | - Eco J C de Geus
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Greig I de Zubicaray
- School of Psychology and Counselling, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Sylvane Desrivières
- Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Joanne L Doherty
- Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom; Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, United Kingdom
| | - Gary Donohoe
- School of Psychology and Center for Neuroimaging, Cognition and Genomics, University of Galway, Galway, Ireland
| | - Stefan Ehrlich
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
| | - Else Eising
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands
| | - Thomas Espeseth
- Department of Psychology, University of Oslo, Oslo, Norway; Department of Psychology, Oslo New University College, Oslo, Norway
| | - Simon E Fisher
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands; Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands
| | - Andreas J Forstner
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany; Institute of Human Genetics, University of Bonn, School of Medicine and University Hospital Bonn, Bonn, Germany
| | - Lidia Fortaner-Uyà
- Psychiatry and Clinical Psychobiology Unit, Division of Neuroscience, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) San Raffaele Scientific Institute, Milan, Italy; Division of Neuroscience, Psychiatry and Clinical Psychobiology Unit, Istituto di Ricovero e Cura a Carattere Scientifico San Raffaele Scientific Institute, Milan, Italy
| | - Vincent Frouin
- Neurospin, Commissariat a l'Energie Atomique (CEA), Université Paris-Saclay, Gif-sur-Yvette, France
| | - Masaki Fukunaga
- Section of Brain Function Information, National Institute for Physiological Sciences, Okazaki, Japan
| | - Tian Ge
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts; Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - David C Glahn
- Department of Psychiatry and Behavioral Sciences, Boston Children's Hospital, Boston, Massachusetts; Department of Psychiatry, Harvard Medical School, Boston, Massachusetts
| | - Janik Goltermann
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Melissa J Green
- Discipline of Psychiatry and Mental Health, School of Clinical Medicine, University of New South Wales, Sydney, New South Wales, Australia; Neuroscience Research Australia, Sydney, New South Wales, Australia
| | - Nynke A Groenewold
- Department of Psychiatry and Mental Health, Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Gøril Rolfseng Grøntvedt
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway; Department of Neurology and Clinical Neurophysiology, University Hospital of Trondheim, Trondheim, Norway
| | - Tim Hahn
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Ryota Hashimoto
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, Tokyo, Japan
| | - Jayne Y Hehir-Kwa
- Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands
| | - Frans A Henskens
- School of Medicine and Public Health, University of Newcastle, Newcastle, New South Wales, Australia; Priority Research Centre for Health Behaviour, University of Newcastle, Newcastle, New South Wales, Australia
| | - Avram J Holmes
- Department of Psychiatry, Rutgers University, New Brunswick, New Jersey; Brain Health Institute, Rutgers University, Piscataway, New Jersey
| | - Asta K Håberg
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway; Department of Radiology and Nuclear Medicine, St. Olav's Hospital, Trondheim, Norway
| | - Jan Haavik
- Department of Biomedicine, University of Bergen, Bergen, Norway; Division of Psychiatry, Haukeland University Hospital, Bergen, Norway
| | - Sebastien Jacquemont
- Sainte Justine Hospital Research Center, Montreal, Quebec, Canada; Department of Pediatrics, University of Montreal, Montreal, Quebec, Canada
| | - Andreas Jansen
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany; Core-Facility Brainimaging and Department of Psychiatry, Faculty of Medicine, Philipps-University Marburg, Marburg, Germany
| | - Christiane Jockwitz
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany; Institute for Anatomy I, Medical Faculty & University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Erik G Jönsson
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Health Care Services, Stockholm Region, Stockholm, Sweden
| | - Masataka Kikuchi
- Department of Genome Informatics, Graduate School of Medicine, Osaka University, Osaka, Japan; Department of Computational Biology and Medical Sciences, Graduate School of Frontier Science, The University of Tokyo, Chiba, Japan
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Kuldeep Kumar
- Sainte Justine Hospital Research Center, Montreal, Quebec, Canada
| | - Stephanie Le Hellard
- Norwegian Centre for Mental Disorders Research, Department of Clinical Science, University of Bergen, Bergen, Norway; Dr. Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - Costin Leu
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom; Department of Neurology, McGovern Medical School, UTHealth Houston, Houston, Texas
| | - David E Linden
- Neuroscience and Mental Health Innovation Institute, Cardiff University, Cardiff, United Kingdom; School for Mental Health and Neuroscience, Department of Psychiatry and Neuropsychology, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, the Netherlands
| | - Jingyu Liu
- Department of Computer Science and Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Atlanta, Georgia
| | - Robert Loughnan
- Department of Cognitive Science and Population Neuroscience and Genetics Lab, University of California San Diego, La Jolla, California
| | - Karen A Mather
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, New South Wales, Australia
| | - Katie L McMahon
- School of Clinical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Allan F McRae
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
| | - Sarah E Medland
- Psychiatric Genetics, Queensland Institute of Medical Research (QIMR) Berghofer Medical Research Institute, Brisbane, Queensland, Australia; University of Queensland, Brisbane, Queensland, Australia; Queensland University of Technology, Brisbane, Queensland, Australia
| | - Susanne Meinert
- Institute for Translational Psychiatry, University of Münster, Münster, Germany; Institute for Translational Neuroscience, University of Münster, Münster, Germany
| | - Clara A Moreau
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Marina del Rey, California
| | - Derek W Morris
- Centre for Neuroimaging, Cognition and Genomics, School of Biological and Chemical Sciences, University of Galway, Galway, Ireland
| | - Bryan J Mowry
- Queensland Brain Institute and Queensland Centre for Mental Health Research, University of Queensland, Brisbane, Queensland, Australia
| | - Thomas W Mühleisen
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany; Institute for Anatomy I, Medical Faculty & University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Department of Biomedicine, University of Basel, Basel, Switzerland
| | - Igor Nenadić
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Markus M Nöthen
- Institute of Human Genetics, University of Bonn, School of Medicine and University Hospital Bonn, Bonn, Germany
| | - Lars Nyberg
- Departments of Radiation Sciences, Integrative Medical Biology and Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden
| | - Roel A Ophoff
- Department of Psychiatry, Erasmus University Medical Center, Rotterdam, the Netherlands; Semel Institute for Neuroscience and Human Behavior, Departments of Psychiatry and Biobehavioral Sciences and Psychology, University of California Los Angeles, Los Angeles, California
| | - Michael J Owen
- Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom; Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, United Kingdom
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne, Carlton South, Victoria, Australia; Western Centre for Health Research and Education, Sunshine Hospital, St Albans, Victoria, Australia
| | - Marco Paolini
- Psychiatry and Clinical Psychobiology Unit, Division of Neuroscience, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) San Raffaele Scientific Institute, Milan, Italy; Division of Neuroscience, Psychiatry and Clinical Psychobiology Unit, Istituto di Ricovero e Cura a Carattere Scientifico San Raffaele Scientific Institute, Milan, Italy
| | - Tomas Paus
- Departments of Psychiatry and Neuroscience, Faculty of Medicine and Sainte Justine Hospital Research Center, University of Montreal, Montreal, Quebec, Canada; Departments of Psychiatry and Psychology, University of Toronto, Toronto, Ontario, Canada
| | - Zdenka Pausova
- The Hospital for Sick Children, Toronto, Ontario, Canada; Department of Physiology, University of Toronto, Toronto, Ontario, Canada
| | - Karin Persson
- Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway; Norwegian National Centre for Ageing and Health, Vestfold Hospital Trust, Tønsberg, Norway
| | - Yann Quidé
- Neuroscience Research Australia, Sydney, New South Wales, Australia; School of Psychology, University of New South Wales, Sydney, New South Wales, Australia
| | - Tiago Reis Marques
- Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Perminder S Sachdev
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, New South Wales, Australia; Neuropsychiatric Institute, Prince of Wales Hospital, Sydney, New South Wales, Australia
| | - Sigrid B Sando
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway; Department of Neurology and Clinical Neurophysiology, University Hospital of Trondheim, Trondheim, Norway
| | - Ulrich Schall
- Hunter Medical Research Institute, Newcastle, New South Wales, Australia
| | - Rodney J Scott
- School of Biomedical Sciences and Pharmacy, College of Medicine, Health and Wellbeing, University of Newcastle, Callaghan, New South Wales, Australia; Hunter Medical Research Institute, Newcastle, New South Wales, Australia; Division of Molecular Medicine, New South Wales Health Pathology, Newcastle, New South Wales, Australia
| | - Geir Selbæk
- Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway; Norwegian National Centre for Ageing and Health, Vestfold Hospital Trust, Tønsberg, Norway; Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Elena Shumskaya
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands; Department of Human Genetics, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Ana I Silva
- Neuroscience and Mental Health Innovation Institute, Cardiff University, Cardiff, United Kingdom
| | - Sanjay M Sisodiya
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom; Chalfont Centre for Epilepsy, Chalfont St Peter, United Kingdom
| | - Frederike Stein
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Dan J Stein
- SA MRC Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Benjamin Straube
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Fabian Streit
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Lachlan T Strike
- Psychiatric Genetics, Queensland Institute of Medical Research (QIMR) Berghofer Medical Research Institute, Brisbane, Queensland, Australia; School of Psychology and Counselling, Faculty of Health, Queensland University of Technology, Brisbane, Australia
| | - Alexander Teumer
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany; Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany; German Centre for Cardiovascular Research, Greifswald, Germany
| | - Lea Teutenberg
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Anbupalam Thalamuthu
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, New South Wales, Australia
| | - Paul A Tooney
- School of Biomedical Sciences and Pharmacy, College of Medicine, Health and Wellbeing, University of Newcastle, Callaghan, New South Wales, Australia; Hunter Medical Research Institute, Newcastle, New South Wales, Australia
| | - Diana Tordesillas-Gutierrez
- Instituto de Física de Cantabria UC-CSIC, Santander, Spain; Department of Radiology, Marqués de Valdecilla University Hospital, Valdecilla Biomedical Research Institute, Instituto de Investigación Sanitaria Valdecilla, Santander, Spain
| | - Julian N Trollor
- Department of Developmental Disability Neuropsychiatry and Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, New South Wales, Australia
| | - Dennis van 't Ent
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Marianne B M van den Bree
- Institute of Psychological Medicine and Clinical Neurosciences and Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom; Institute for Translational Neuroscience, University of Münster, Münster, Germany
| | - Neeltje E M van Haren
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Centre, Rotterdam, the Netherlands; Department of Psychiatry, University Medical Centre Utrecht, Utrecht, the Netherlands
| | - Javier Vázquez-Bourgon
- Centro de Investigación Biomédica en Red Salud Mental, Sevilla, Spain; Department of Psychiatry, University Hospital Maqués de Valdecilla, Instituto de Investigación Sanitaria Valdecilla, Santander, Spain; Departamento de Medicina y Psiquiatría, Universidad de Cantabria, Santander, Spain
| | - Henry Völzke
- German Centre for Cardiovascular Research, Greifswald, Germany; Greifswald University Hospital, Greifswald, Germany
| | - Wei Wen
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, New South Wales, Australia
| | - Katharina Wittfeld
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Christopher R K Ching
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Marina del Rey, California
| | - Lars T Westlye
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Psychology, University of Oslo, Oslo, Norway; KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Marina del Rey, California
| | - Carrie E Bearden
- Semel Institute for Neuroscience and Human Behavior, Departments of Psychiatry and Biobehavioral Sciences and Psychology, University of California Los Angeles, Los Angeles, California
| | - Kaja K Selmer
- Department of Research and Innovation, Division of Clinical Neuroscience, Oslo University Hospital and the University of Oslo, Oslo, Norway
| | - Dag Alnæs
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Kristiania University College, Oslo, Norway
| | - Ole A Andreassen
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Ida E Sønderby
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway; Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
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Gou M, Chen W, Li Y, Chen S, Feng W, Pan S, Luo X, Tan S, Tian B, Li W, Tong J, Zhou Y, Li H, Yu T, Wang Z, Zhang P, Huang J, Kochunov P, Tian L, Li CSR, Hong LE, Tan Y. Immune-Inflammatory Response And Compensatory Immune-Regulatory Reflex Systems And White Matter Integrity in Schizophrenia. Schizophr Bull 2024; 50:199-209. [PMID: 37540273 PMCID: PMC10754202 DOI: 10.1093/schbul/sbad114] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 08/05/2023]
Abstract
BACKGROUND AND HYPOTHESIS Low-grade neural and peripheral inflammation are among the proposed pathophysiological mechanisms of schizophrenia. White matter impairment is one of the more consistent findings in schizophrenia but the underlying mechanism remains obscure. Many cerebral white matter components are sensitive to neuroinflammatory conditions that can result in demyelination, altered oligodendrocyte differentiation, and other changes. We tested the hypothesis that altered immune-inflammatory response system (IRS) and compensatory immune-regulatory reflex system (IRS/CIRS) dynamics are associated with reduced white matter integrity in patients with schizophrenia. STUDY DESIGN Patients with schizophrenia (SCZ, 70M/50F, age = 40.76 ± 13.10) and healthy controls (HCs, 38M/27F, age = 37.48 ± 12.31) underwent neuroimaging and plasma collection. A panel of cytokines were assessed using enzyme-linked immunosorbent assay. White matter integrity was measured by fractional anisotropy (FA) from diffusion tensor imaging using a 3-T Prisma MRI scanner. The cytokines were used to generate 3 composite scores: IRS, CIRS, and IRS/CIRS ratio. STUDY RESULTS The IRS/CIRS ratio in SCZ was significantly higher than that in HCs (P = .009). SCZ had a significantly lower whole-brain white matter average FA (P < .001), and genu of corpus callosum (GCC) was the most affected white matter tract and its FA was significantly associated with IRS/CIRS (r = 0.29, P = .002). FA of GCC was negatively associated with negative symptom scores in SCZ (r = -0.23, P = .016). There was no mediation effect taking FA of GCC as mediator, for that IRS/CIRS was not associated with negative symptom score significantly (P = .217) in SCZ. CONCLUSIONS Elevated IRS/CIRS might partly account for the severity of negative symptoms through targeting the integrity of GCC.
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Affiliation(s)
- Mengzhuang Gou
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Wenjin Chen
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Yanli Li
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Song Chen
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Wei Feng
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Shujuan Pan
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Xingguang Luo
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Shuping Tan
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Baopeng Tian
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Wei Li
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Jinghui Tong
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Yanfang Zhou
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Hongna Li
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Ting Yu
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Zhiren Wang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Ping Zhang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Junchao Huang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Li Tian
- Institute of Biomedicine and Translational Medicine, Department of Physiology, Faculty of Medicine, University of Tartu, Tartu, Estonia
| | - Chiang-Shan R Li
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - L Elliot Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Yunlong Tan
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
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11
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Kochunov P, Ma Y, Hatch KS, Gao S, Acheson A, Jahanshad N, Thompson PM, Adhikari BM, Bruce H, Van der Vaart A, Chiappelli J, Du X, Sotiras A, Kvarta MD, Ma T, Chen S, Hong LE. Ancestral, Pregnancy, and Negative Early-Life Risks Shape Children's Brain (Dis)similarity to Schizophrenia. Biol Psychiatry 2023; 94:332-340. [PMID: 36948435 PMCID: PMC10511664 DOI: 10.1016/j.biopsych.2023.03.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 03/07/2023] [Accepted: 03/07/2023] [Indexed: 03/24/2023]
Abstract
BACKGROUND Familial, obstetric, and early-life environmental risks for schizophrenia spectrum disorder (SSD) alter normal cerebral development, leading to the formation of characteristic brain deficit patterns prior to onset of symptoms. We hypothesized that the insidious effects of these risks may increase brain similarity to adult SSD deficit patterns in prepubescent children. METHODS We used data collected by the Adolescent Brain Cognitive Development (ABCD) Study (N = 8940, age = 9.9 ± 0.1 years, 4307/4633 female/male), including 727 (age = 9.9 ± 0.1 years, 351/376 female/male) children with family history of SSD, to evaluate unfavorable cerebral effects of ancestral SSD history, pre/perinatal environment, and negative early-life environment. We used a regional vulnerability index to measure the alignment of a child's cerebral patterns with the adult SSD pattern derived from a large meta-analysis of case-control differences. RESULTS In children with a family history of SSD, the regional vulnerability index captured significantly more variance in ancestral history than traditional whole-brain and regional brain measurements. In children with and without family history of SSD, the regional vulnerability index also captured more variance associated with negative pre/perinatal environment and early-life experiences than traditional brain measurements. CONCLUSIONS In summary, in a cohort in which most children will not develop SSD, familial, pre/perinatal, and early developmental risks can alter brain patterns in the direction observed in adult patients with SSD. Individual similarity to adult SSD patterns may provide an early biomarker of the effects of genetic and developmental risks on the brain prior to psychotic or prodromal symptom onset.
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Affiliation(s)
- Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland.
| | - Yizhou Ma
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Kathryn S Hatch
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Si Gao
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Ashley Acheson
- Department of Psychiatry, University of Arkansas for Medical Sciences, Little Rock, Arkansas
| | - Neda Jahanshad
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of University of the Sunshine Coast, Marina del Rey, California
| | - Paul M Thompson
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of University of the Sunshine Coast, Marina del Rey, California
| | - Bhim M Adhikari
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Heather Bruce
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Andrew Van der Vaart
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Joshua Chiappelli
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Xiaoming Du
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Aris Sotiras
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri
| | - Mark D Kvarta
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Tianzhou Ma
- Department of Epidemiology and Biostatistics, University of Maryland, College Park, Maryland
| | - Shuo Chen
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - L Elliot Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
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12
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Dolma S, Joshi A. The Node of Ranvier as an Interface for Axo-Glial Interactions: Perturbation of Axo-Glial Interactions in Various Neurological Disorders. J Neuroimmune Pharmacol 2023; 18:215-234. [PMID: 37285016 DOI: 10.1007/s11481-023-10072-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Accepted: 05/19/2023] [Indexed: 06/08/2023]
Abstract
The action potential conduction along the axon is highly dependent on the healthy interactions between the axon and myelin-producing glial cells. Myelin, which facilitates action potential, is the protective insulation around the axon formed by Schwann cells and oligodendrocytes in the peripheral (PNS) and central nervous system (CNS), respectively. Myelin is a continuous structure with intermittent gaps called nodes of Ranvier, which are the sites enriched with ion channels, transmembrane, scaffolding, and cytoskeletal proteins. Decades-long extensive research has identified a comprehensive proteome with strictly regularized localization at the node of Ranvier. Concurrently, axon-glia interactions at the node of Ranvier have gathered significant attention as the pathophysiological targets for various neurodegenerative disorders. Numerous studies have shown the alterations in the axon-glia interactions culminating in neurological diseases. In this review, we have provided an update on the molecular composition of the node of Ranvier. Further, we have discussed in detail the consequences of disruption of axon-glia interactions during the pathogenesis of various CNS and PNS disorders.
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Affiliation(s)
- Sonam Dolma
- Department of Pharmacy, Birla Institute of Technology and Sciences- Pilani, Hyderabad campus, Telangana state, India
| | - Abhijeet Joshi
- Department of Pharmacy, Birla Institute of Technology and Sciences- Pilani, Hyderabad campus, Telangana state, India.
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13
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Hatch KS, Gao S, Ma Y, Russo A, Jahanshad N, Thompson PM, Adhikari BM, Bruce H, Van der Vaart A, Sotiras A, Kvarta MD, Nichols TE, Schmaal L, Hong LE, Kochunov P. Brain deficit patterns of metabolic illnesses overlap with those for major depressive disorder: A new metric of brain metabolic disease. Hum Brain Mapp 2023; 44:2636-2653. [PMID: 36799565 PMCID: PMC10028678 DOI: 10.1002/hbm.26235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Revised: 01/30/2023] [Accepted: 02/01/2023] [Indexed: 02/18/2023] Open
Abstract
Metabolic illnesses (MET) are detrimental to brain integrity and are common comorbidities in patients with mental illnesses, including major depressive disorder (MDD). We quantified effects of MET on standard regional brain morphometric measures from 3D brain MRI as well as diffusion MRI in a large sample of UK BioBank participants. The pattern of regional effect sizes of MET in non-psychiatric UKBB subjects was significantly correlated with the spatial profile of regional effects reported by the largest meta-analyses in MDD but not in bipolar disorder, schizophrenia or Alzheimer's disease. We used a regional vulnerability index (RVI) for MET (RVI-MET) to measure individual's brain similarity to the expected patterns in MET in the UK Biobank sample. Subjects with MET showed a higher effect size for RVI-MET than for any of the individual brain measures. We replicated elevation of RVI-MET in a sample of MDD participants with MET versus non-MET. RVI-MET scores were significantly correlated with the volume of white matter hyperintensities, a neurological consequence of MET and age, in both groups. Higher RVI-MET in both samples was associated with obesity, tobacco smoking and frequent alcohol use but was unrelated to antidepressant use. In summary, MET effects on the brain were regionally specific and individual similarity to the pattern was more strongly associated with MET than any regional brain structural metric. Effects of MET overlapped with the reported brain differences in MDD, likely due to higher incidence of MET, smoking and alcohol use in subjects with MDD.
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Affiliation(s)
- Kathryn S Hatch
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Si Gao
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Yizhou Ma
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Alessandro Russo
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, California, USA
| | - Paul M Thompson
- Imaging Genetics Center, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, California, USA
| | - Bhim M Adhikari
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Heather Bruce
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Andrew Van der Vaart
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Aristeidis Sotiras
- Institute of Informatics, University of Washington, School of Medicine, St. Louis, Missouri, USA
- Department of Radiology, University of Washington, School of Medicine, St. Louis, Missouri, USA
| | - Mark D Kvarta
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Thomas E Nichols
- Nuffield Department of Population Health of the University of Oxford, Oxford, UK
| | - Lianne Schmaal
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
- Orygen, Parkville, Australia
| | - L Elliot Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
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14
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Tuovinen N, Hofer A. Resting-state functional MRI in treatment-resistant schizophrenia. FRONTIERS IN NEUROIMAGING 2023; 2:1127508. [PMID: 37554635 PMCID: PMC10406237 DOI: 10.3389/fnimg.2023.1127508] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Accepted: 03/17/2023] [Indexed: 08/10/2023]
Abstract
BACKGROUND Abnormalities in brain regions involved in the pathophysiology of schizophrenia (SCZ) may present insight into individual clinical symptoms. Specifically, functional connectivity irregularities may provide potential biomarkers for treatment response or treatment resistance, as such changes can occur before any structural changes are visible. We reviewed resting-state functional magnetic resonance imaging (rs-fMRI) findings from the last decade to provide an overview of the current knowledge on brain functional connectivity abnormalities and their associations to symptoms in treatment-resistant schizophrenia (TRS) and ultra-treatment-resistant schizophrenia (UTRS) and to look for support for the dysconnection hypothesis. METHODS PubMed database was searched for articles published in the last 10 years applying rs-fMRI in TRS patients, i.e., who had not responded to at least two adequate treatment trials with different antipsychotic drugs. RESULTS Eighteen articles were selected for this review involving 648 participants (TRS and control cohorts). The studies showed frontal hypoconnectivity before the initiation of treatment with CLZ or riluzole, an increase in frontal connectivity after riluzole treatment, fronto-temporal hypoconnectivity that may be specific for non-responders, widespread abnormal connectivity during mixed treatments, and ECT-induced effects on the limbic system. CONCLUSION Probably due to the heterogeneity in the patient cohorts concerning antipsychotic treatment and other clinical variables (e.g., treatment response, lifetime antipsychotic drug exposure, duration of illness, treatment adherence), widespread abnormalities in connectivity were noted. However, irregularities in frontal brain regions, especially in the prefrontal cortex, were noted which are consistent with previous SCZ literature and the dysconnectivity hypothesis. There were major limitations, as most studies did not differentiate between TRS and UTRS (i.e., CLZ-resistant schizophrenia) and investigated heterogeneous cohorts treated with mixed treatments (with or without CLZ). This is critical as in different subtypes of the disorder an interplay between dopaminergic and glutamatergic pathways involving frontal, striatal, and hippocampal brain regions in separate ways is likely. Better definitions of TRS and UTRS are necessary in future longitudinal studies to correctly differentiate brain regions underlying the pathophysiology of SCZ, which could serve as potential functional biomarkers for treatment resistance.
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Affiliation(s)
- Noora Tuovinen
- Division of Psychiatry I, Department of Psychiatry, Psychotherapy, Psychosomatics and Medical Psychology, Medical University of Innsbruck, Innsbruck, Austria
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15
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Wu XS, Kang XW, Li X, Bai LJ, Xi YB, Li Y, Xu YQ, Hu WZ, Yin H, Lv YL. Baseline white matter function predicts short-term treatment response in first-episode schizophrenia. J Neuroimaging 2023. [PMID: 36939186 DOI: 10.1111/jon.13101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Revised: 02/26/2023] [Accepted: 03/06/2023] [Indexed: 03/21/2023] Open
Abstract
BACKGROUND AND PURPOSE The detection and characterization of functional activities in the gray matter of schizophrenia (SZ) have been widely explored. However, the relationship between resting-state functional signals in the white matter of first-episode SZ and short-term treatment response remains unclear. METHODS Thirty-six patients with first-episode SZ and 44 matched healthy controls were recruited in this study. Patients were classified as nonresponders and responders based on response to antipsychotic medication during a single hospitalization. The fractional amplitude of low-frequency fluctuation (fALFF), regional homogeneity (ReHo), and functional connectivity (FC) of white matter were calculated. The relationships between functional changes and clinical features were analyzed. In addition, voxel-based morphometry was performed to analyze the white matter volume. RESULTS One-way analysis of variance showed significant differences of fALFF and ReHo in the left posterior thalamic radiation and left cingulum (hippocampus) in the patient group, and the areas were regarded as seeds. The FC was calculated between seeds and other white matter networks. Compared with responders, nonresponders showed significantly increased FC between the left cingulum (hippocampus) and left posterior thalamic radiation, splenium of corpus callosum, and left tapetum, and were associated with the changes of clinical assessment. However, there was no difference in white matter volume between groups. CONCLUSION Our work provides a novel insight that psycho-neuroimaging-based white matter function holds promise for influencing the clinical diagnosis and treatment of SZ.
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Affiliation(s)
- Xu-Sha Wu
- Department of Radiology, Xi'an People's Hospital (Xi'an Fourth Hospital), Xi'an, China
| | - Xiao-Wei Kang
- Department of Radiology, Xi'an People's Hospital (Xi'an Fourth Hospital), Xi'an, China
| | - Xuan Li
- The Key Laboratory of Biomedical Information Engineering, Ministry of Education, Department of Biomedical Engineering, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China
| | - Li-Jun Bai
- The Key Laboratory of Biomedical Information Engineering, Ministry of Education, Department of Biomedical Engineering, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China
| | - Yi-Bin Xi
- Department of Radiology, Xi'an People's Hospital (Xi'an Fourth Hospital), Xi'an, China
| | - Yan Li
- Department of Radiology, Xi'an People's Hospital (Xi'an Fourth Hospital), Xi'an, China.,School of Medical Technology, Shaanxi University of Chinese Medicine, Xianyang, China
| | - Yong-Qiang Xu
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Wen-Zhong Hu
- Department of Radiology, Xi'an People's Hospital (Xi'an Fourth Hospital), Xi'an, China.,Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Hong Yin
- Department of Radiology, Xi'an People's Hospital (Xi'an Fourth Hospital), Xi'an, China
| | - Ya-Li Lv
- Department of Neurology, Xi'an People's Hospital, Xi'an Fourth Hospital, Xi'an, China
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16
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Impact of low-frequency repetitive transcranial magnetic stimulation on functional network connectivity in schizophrenia patients with auditory verbal hallucinations. Psychiatry Res 2023; 320:114974. [PMID: 36587467 DOI: 10.1016/j.psychres.2022.114974] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 11/10/2022] [Accepted: 11/19/2022] [Indexed: 11/22/2022]
Abstract
Auditory verbal hallucinations (AVH) are a key symptom of schizophrenia. Low-frequency repetitive transcranial magnetic stimulation (rTMS) has shown potential in the treatment of AVH. However, the underlying neural mechanismof rTMS in the treatment of AVH remains largely unknown. In this study, we used a static and dynamic functional network connectivity approach to investigate the connectivity changes among the brain functional networks in schizophrenia patients with AVH receiving 1 Hz rTMS treatment. The static functional network connectivity (sFNC) analysis revealed that patients at baseline had significantly decreased connectivity between the default mode network (DMN) and language network (LAN), and within the executive control network (ECN) as well as within the auditory network (AUD) compared to controls. However, the abnormal network connectivity patterns were normalized or restored after rTMS treatment in patients, instead of increased connectivity between the ECN and LAN, as well as within the AUD. Moreover, the dynamic functional network connectivity (dFNC) analysis showed that the patients at baseline spent more time in this state that was characterized by strongly negative connectivity between the ENC and AUD, as well as within the AUD relative to controls. While after rTMS treatment, the patients showed a higher occurrence rate in this state that was characterized by strongly positive connectivity among the LAN, DMN, and ENC, as well as within the ECN. In addition, the altered static and dynamic connectivity properties were associated with reduced severity of clinical symptoms. Both sFNC and dFNC analyses provided complementary information and suggested that low-frequency rTMS treatment could induce intrinsic functional network alternations and contribute to improvements in clinical symptoms in patients with AVH.
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17
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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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18
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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: 0] [Impact Index Per Article: 0] [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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19
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Differences in white matter microstructure in first-episode schizophrenia spectrum disorders vs healthy volunteers and their association with cognition. Schizophr Res 2022; 250:196-202. [PMID: 36436499 DOI: 10.1016/j.schres.2022.11.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Revised: 05/06/2022] [Accepted: 11/15/2022] [Indexed: 11/27/2022]
Abstract
OBJECTIVE Both cognitive impairment and alterations in white matter tissue microstructure are well recognised in schizophrenia. We investigated whether differences in white matter microstructure underpin cognitive impairments in patients with first-episode schizophrenia spectrum disorders when controlling for multiple confounding factors. METHODS We employed a cross-sectional study design and compared fractional anisotropy (FA) between individuals diagnosed with first- episode schizophrenia spectrum disorders (FES) (n = 68) and matched healthy controls (n = 120). We conducted multiple analyses of covariance (ANCOVAs) to compare the mean FA values for patients and controls across 27 white matter tracts. We conducted exploratory correlation analyses to determine if white matter tract differences were associated with global cognitive impairment as well as deficits across seven cognitive domains. RESULTS We found widespread reductions in FA in patients compared to controls, after controlling for confounding variables, such as age, biological sex, education, substances, and childhood adversities. We found a significant positive correlation between the attention/vigilance domain and the splenium of the corpus collosum and external capsule after correction for multiple comparisons. In the control group we found no significant correlations between FA and cognition. CONCLUSION Our findings provide a neurobiological basis for attentional cognitive deficits in schizophrenia, highlighting a potential role for the splenium of the corpus collosum and external capsule.
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20
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White matter microstructure of superior longitudinal fasciculus II is associated with intelligence and treatment response of negative symptoms in patients with schizophrenia. SCHIZOPHRENIA 2022; 8:43. [PMID: 35853887 PMCID: PMC9262917 DOI: 10.1038/s41537-022-00253-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Accepted: 03/31/2022] [Indexed: 11/30/2022]
Abstract
Although the potential role of superior longitudinal fasciculus (SLF) in intellectual deficits and treatment response (TR) in patients with schizophrenia (SZ) has been previously described, little is known about the white-matter (WM) integrity of SLF subcomponents (SLF I, II, III, and arcuate fasciculus) and their particular relationships with the clinical presentations of the illness. This study examined the associations between fractional anisotropy (FA) of SLF subcomponents and intelligence level and 6-month treatment response (TR) of negative symptoms (NS) in patients with SZ. At baseline, 101 patients with SZ and 101 healthy controls (HCs) underwent structural magnetic resonance imaging. Voxel-wise group comparison analysis showed significant SLF FA reductions in patients with SZ compared with HCs. Voxel-wise correlation analyses revealed significant positive correlations of FAs of right SLF II with Korean–Wechsler Adult Intelligence Scale at baseline and the percentage reduction of negative syndrome subscale of the Positive and Negative Syndrome Scales at 6 months. These findings suggest that aberrance in WM microstructure in SLF II may be associated with intellectual deficits in patients with SZ and TR of NS, which may support the potential role of SLF II as a novel neuroimaging biomarker for clinical outcomes of the illness.
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21
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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: 2.0] [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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22
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Blazer A, Chengappa KNR, Foran W, Parr AC, Kahn CE, Luna B, Sarpal DK. Changes in corticostriatal connectivity and striatal tissue iron associated with efficacy of clozapine for treatment‑resistant schizophrenia. Psychopharmacology (Berl) 2022; 239:2503-2514. [PMID: 35435461 PMCID: PMC9013738 DOI: 10.1007/s00213-022-06138-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Accepted: 03/31/2022] [Indexed: 12/02/2022]
Abstract
RATIONALE Though numerous studies demonstrate the superiority of clozapine (CLZ) for treatment of persistent psychotic symptoms that are characteristic of treatment-refractory schizophrenia (TRS), what remains unknown are the neural and molecular mechanisms underlying CLZ's efficacy. Recent work implicates increased corticostriatal functional connectivity as a marker of response to non-CLZ, dopamine (DA) D2-receptor blocking antipsychotic drugs. However, it is undetermined whether this connectivity finding also relates to CLZ's unique efficacy, or if response to CLZ is associated with changes in striatal DA functioning. OBJECTIVE In a cohort of 22 individuals with TRS, we examined response to CLZ in relation to the following: (1) change in corticostriatal functional connectivity; and (2) change in a magnetic resonance-based measure of striatal tissue iron (R2'), which demonstrates utility as a proxy measure for elements of DA functioning. METHODS Participants underwent scanning while starting CLZ and after 12 weeks of CLZ treatment. We used both cortical and striatal regions of interest to examine changes in corticostriatal interactions and striatal R2' in relation to CLZ response (% reduction of psychotic symptoms). RESULTS We first found that response to CLZ was associated with an increase in corticostriatal connectivity between the dorsal caudate and regions of the frontoparietal network (P < 0.05, corrected). Secondly, we observed no significant changes in striatal R2' across CLZ treatment. CONCLUSION Overall, these results indicate that changes in corticostriatal networks without gross shifts in striatal DA functioning underlies CLZ response. Our results provide novel mechanistic insight into response to CLZ treatment.
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Affiliation(s)
- Annie Blazer
- Department of Psychiatry, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA
| | - K N Roy Chengappa
- Department of Psychiatry, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA
| | - William Foran
- Department of Psychiatry, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA
| | - Ashley C Parr
- Department of Psychiatry, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA
| | - Charles E Kahn
- Department of Psychiatry, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA
| | - Beatriz Luna
- Department of Psychiatry, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Deepak K Sarpal
- Department of Psychiatry, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA.
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23
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Thng G, Shen X, Stolicyn A, Harris MA, Adams MJ, Barbu MC, Kwong ASF, Frangou S, Lawrie SM, McIntosh AM, Romaniuk L, Whalley HC. Comparing personalized brain-based and genetic risk scores for major depressive disorder in large population samples of adults and adolescents. Eur Psychiatry 2022; 65:e44. [PMID: 35899848 PMCID: PMC9393914 DOI: 10.1192/j.eurpsy.2022.2301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Revised: 06/20/2022] [Accepted: 07/01/2022] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND Major depressive disorder (MDD) is a polygenic disorder associated with brain alterations but until recently, there have been no brain-based metrics to quantify individual-level variation in brain morphology. Here, we evaluated and compared the performance of a new brain-based 'Regional Vulnerability Index' (RVI) with polygenic risk scores (PRS), in the context of MDD. We assessed associations with syndromal MDD in an adult sample (N = 702, age = 59 ± 10) and with subclinical depressive symptoms in a longitudinal adolescent sample (baseline N = 3,825, age = 10 ± 1; 2-year follow-up N = 2,081, age = 12 ± 1). METHODS MDD-RVIs quantify the correlation of the individual's corresponding brain metric with the expected pattern for MDD derived in an independent sample. Using the same methodology across samples, subject-specific MDD-PRS and six MDD-RVIs based on different brain modalities (subcortical volume, cortical thickness, cortical surface area, mean diffusivity, fractional anisotropy, and multimodal) were computed. RESULTS In adults, MDD-RVIs (based on white matter and multimodal measures) were more strongly associated with MDD (β = 0.099-0.281, PFDR = 0.001-0.043) than MDD-PRS (β = 0.056-0.152, PFDR = 0.140-0.140). In adolescents, depressive symptoms were associated with MDD-PRS at baseline and follow-up (β = 0.084-0.086, p = 1.38 × 10-4-4.77 × 10-4) but not with any MDD-RVIs (β < 0.05, p > 0.05). CONCLUSIONS Our results potentially indicate the ability of brain-based risk scores to capture a broader range of risk exposures than genetic risk scores in adults and are also useful in helping us to understand the temporal origins of depression-related brain features. Longitudinal data, specific to the developmental period and on white matter measures, will be useful in informing risk for subsequent psychiatric illness.
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Affiliation(s)
- Gladi Thng
- Division of Psychiatry, University of Edinburgh, Kennedy Tower, Royal Edinburgh Hospital, Morningside Park, Edinburgh, United Kingdom
| | - Xueyi Shen
- Division of Psychiatry, University of Edinburgh, Kennedy Tower, Royal Edinburgh Hospital, Morningside Park, Edinburgh, United Kingdom
| | - Aleks Stolicyn
- Division of Psychiatry, University of Edinburgh, Kennedy Tower, Royal Edinburgh Hospital, Morningside Park, Edinburgh, United Kingdom
| | - Mathew A. Harris
- Division of Psychiatry, University of Edinburgh, Kennedy Tower, Royal Edinburgh Hospital, Morningside Park, Edinburgh, United Kingdom
| | - Mark J. Adams
- Division of Psychiatry, University of Edinburgh, Kennedy Tower, Royal Edinburgh Hospital, Morningside Park, Edinburgh, United Kingdom
| | - Miruna C. Barbu
- Division of Psychiatry, University of Edinburgh, Kennedy Tower, Royal Edinburgh Hospital, Morningside Park, Edinburgh, United Kingdom
| | - Alex S. F. Kwong
- Division of Psychiatry, University of Edinburgh, Kennedy Tower, Royal Edinburgh Hospital, Morningside Park, Edinburgh, United Kingdom
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Sophia Frangou
- Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, British Columbia, Canada
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Stephen M. Lawrie
- Division of Psychiatry, University of Edinburgh, Kennedy Tower, Royal Edinburgh Hospital, Morningside Park, Edinburgh, United Kingdom
| | - Andrew M. McIntosh
- Division of Psychiatry, University of Edinburgh, Kennedy Tower, Royal Edinburgh Hospital, Morningside Park, Edinburgh, United Kingdom
| | - Liana Romaniuk
- Division of Psychiatry, University of Edinburgh, Kennedy Tower, Royal Edinburgh Hospital, Morningside Park, Edinburgh, United Kingdom
| | - Heather C. Whalley
- Division of Psychiatry, University of Edinburgh, Kennedy Tower, Royal Edinburgh Hospital, Morningside Park, Edinburgh, United Kingdom
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24
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Xie S, Zhuo J, Song M, Chu C, Cui Y, Chen Y, Wang H, Li L, Jiang T. Tract-specific white matter microstructural alterations in subjects with schizophrenia and unaffected first-degree relatives. Brain Imaging Behav 2022; 16:2110-2119. [PMID: 35732912 DOI: 10.1007/s11682-022-00681-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/26/2022] [Indexed: 11/26/2022]
Abstract
White matter tracts alterations have been reported in schizophrenia (SZ), but whether such abnormalities are associated with the effects of the disorder itself and/or genetic vulnerability remains unclear. Moreover, the specific patterns of different parts of these altered tracts have been less well studied. Thus, diffusion-weighted images were acquired from 38 healthy controls (HCs), 48 schizophrenia patients, and 33 unaffected first-degree relatives of SZs (FDRs). Diffusion properties of the 25 major tracts automatically extracted with probabilistic tractography were calculated and compared among groups. Regarding the peripheral regions of the tracts, significantly higher diffusivity values in the left superior longitudinal fasciculus (SLF) and the left anterior thalamic radiation (ATR) were observed in SZs than in HCs and unaffected FDRs. However, there were no significant differences between HCs and FDRs in these two tracts. While no main effects of group with respect to the core regions of the 25 tracts survived multiple comparisons correction, FDRs had significantly higher diffusivity values in the left medial lemniscus and lower diffusivity values in the middle cerebellar peduncle than HCs and SZs. These findings enhance the understanding of the abnormal patterns in the peripheral and core regions of the tracts in SZs and those at high genetic risk for schizophrenia. Our results suggest that alterations in the peripheral regions of the left SLF and ATR are features of established illness rather than genetic predisposition, which may serve as critical neural substrates for the psychopathology of schizophrenia.
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Affiliation(s)
- Sangma Xie
- Institute of Biomedical Engineering and Instrumentation, School of Automation, Hangzhou Dianzi University, 310018, Hangzhou, China
| | - Junjie Zhuo
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, 570228, Haikou, China
| | - Ming Song
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China
- National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China
- University of Chinese Academy of Sciences, 100190, Beijing, China
| | - Congying Chu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China
| | - Yue Cui
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China
- National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China
- University of Chinese Academy of Sciences, 100190, Beijing, China
| | - Yunchun Chen
- Department of Psychiatry, Xijing Hospital, The Fourth Military Medical University, 710032, Xi'an, China
| | - Huaning Wang
- Department of Psychiatry, Xijing Hospital, The Fourth Military Medical University, 710032, Xi'an, China
| | - Lihua Li
- Institute of Biomedical Engineering and Instrumentation, School of Automation, Hangzhou Dianzi University, 310018, Hangzhou, China
| | - Tianzi Jiang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China.
- National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China.
- University of Chinese Academy of Sciences, 100190, Beijing, China.
- CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China.
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25
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Matrone M, Kotzalidis GD, Romano A, Bozzao A, Cuomo I, Valente F, Gabaglio C, Lombardozzi G, Trovini G, Amici E, Perrini F, De Persis S, Iasevoli F, De Filippis S, de Bartolomeis A. Treatment-resistant schizophrenia: Addressing white matter integrity, intracortical glutamate levels, clinical and cognitive profiles between early- and adult-onset patients. Prog Neuropsychopharmacol Biol Psychiatry 2022; 114:110493. [PMID: 34883221 DOI: 10.1016/j.pnpbp.2021.110493] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Revised: 11/05/2021] [Accepted: 11/29/2021] [Indexed: 01/30/2023]
Abstract
BACKGROUND Treatment-resistance in schizophrenia is 30-40%. Its neurobiology remains unclear; to explore it, we conducted a combined spectrometry/tractography/cognitive battery and psychopathological rating study on patients with treatment-resistant schizophrenia (TRS), dividing the sample into early-onset (N = 21) and adult-onset TRS (N = 20). Previous studies did not differentiate between early- (onset 13-18 years) and adult-onset (>18 years at formal diagnosis of schizophrenia) TRS. METHODS We evaluated cross-sectionally 41 TRS patients (26 male and 15 female) and 20 matched healthy controls (HCs) with psychopathological and cognitive testing prior to participating in brain imaging scanning using magnetic resonance spectroscopy and diffusion tensor imaging to determine the relationship between their symptoms and their glutamate levels and white matter integrity. RESULTS TRS patients scored lower than HCs on all cognitive domains; early-onset patients performed better than adult-onset patients only on the Symbol Coding domain. TRS correlated with symptom severity, especially negative symptoms. Glutamate levels and glutamate/creatine were increased in anterior cingulate cortex. Diffusion tensor imaging showed low fractional anisotropy in TRS patients in specific white matter tracts compared to HCs (bilateral anterior thalamic radiation, cortico-spinal tract, forceps minor, inferior fronto-occipital fasciculus, inferior longitudinal fasciculus, superior longitudinal fasciculus, and right uncinate fasciculus). CONCLUSIONS We identified specific magnetic resonance spectroscopy and diffusion tensor imaging alterations in TRS patients. Adult-onset TRS differed little from early-onset TRS on most measures; this points to alterations being present since the outset of schizophrenia and may constitute a biological signature of treatment-resistance.
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Affiliation(s)
- Marta Matrone
- Section of Psychiatry Laboratory of Molecular and Translational Psychiatry, Unit of Treatment Resistant Psychosis, Department of Neuroscience, Reproductive Science, and Odontostomatology, University of Naples Federico II, 80131 Naples, Italy; Clinica Neuropsichiatrica Villa von Siebenthal, Department of Neuropsychiatry, Via della Madonnina 1, 00045 Genzano di Roma, RM, Italy
| | - Georgios D Kotzalidis
- NESMOS (Neurosciences, Mental Health, and Sensory Organs) Department, Sapienza University of Rome, Faculty of Medicine and Psychology, Via di Grottarossa 1035-1039, 00189 Rome, Italy.
| | - Andrea Romano
- NESMOS (Neurosciences, Mental Health, and Sensory Organs) Department, Sapienza University of Rome, Faculty of Medicine and Psychology, Via di Grottarossa 1035-1039, 00189 Rome, Italy.
| | - Alessandro Bozzao
- NESMOS (Neurosciences, Mental Health, and Sensory Organs) Department, Sapienza University of Rome, Faculty of Medicine and Psychology, Via di Grottarossa 1035-1039, 00189 Rome, Italy.
| | - Ilaria Cuomo
- UOC SM I Distretto ASL ROMA 1, C.C. Regina Cœli, Via della Lungara 29, 00165 Rome, Italy.
| | - Francesca Valente
- Clinica Neuropsichiatrica Villa von Siebenthal, Department of Neuropsychiatry, Via della Madonnina 1, 00045 Genzano di Roma, RM, Italy; Department of Human Neurosciences, Institute of Child and Adolescent Neuropsychiatry, Sapienza University of Rome, Italy.
| | - Chiara Gabaglio
- Clinica Neuropsichiatrica Villa von Siebenthal, Department of Neuropsychiatry, Via della Madonnina 1, 00045 Genzano di Roma, RM, Italy
| | - Ginevra Lombardozzi
- Clinica Neuropsichiatrica Villa von Siebenthal, Department of Neuropsychiatry, Via della Madonnina 1, 00045 Genzano di Roma, RM, Italy
| | - Giada Trovini
- Clinica Neuropsichiatrica Villa von Siebenthal, Department of Neuropsychiatry, Via della Madonnina 1, 00045 Genzano di Roma, RM, Italy
| | - Emanuela Amici
- Clinica Neuropsichiatrica Villa von Siebenthal, Department of Neuropsychiatry, Via della Madonnina 1, 00045 Genzano di Roma, RM, Italy
| | - Filippo Perrini
- Clinica Neuropsichiatrica Villa von Siebenthal, Department of Neuropsychiatry, Via della Madonnina 1, 00045 Genzano di Roma, RM, Italy; UOC SMREE Distretto ASL ROMA 6, TSMREE, Via S. Biagio, 12, 00049, Velletri, Rome, Italy.
| | - Simone De Persis
- UOSD Attività Terapeutiche Riabilitative per i Disturbi da uso di Sostanze e nuove Dipendenze, ASL Rieti, Via Salaria per Roma 36, 02100 Rieti, Italy.
| | - Felice Iasevoli
- Section of Psychiatry Laboratory of Molecular and Translational Psychiatry, Unit of Treatment Resistant Psychosis, Department of Neuroscience, Reproductive Science, and Odontostomatology, University of Naples Federico II, 80131 Naples, Italy.
| | - Sergio De Filippis
- Clinica Neuropsichiatrica Villa von Siebenthal, Department of Neuropsychiatry, Via della Madonnina 1, 00045 Genzano di Roma, RM, Italy
| | - Andrea de Bartolomeis
- Section of Psychiatry Laboratory of Molecular and Translational Psychiatry, Unit of Treatment Resistant Psychosis, Department of Neuroscience, Reproductive Science, and Odontostomatology, University of Naples Federico II, 80131 Naples, Italy.
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26
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Luttenbacher I, Phillips A, Kazemi R, Hadipour AL, Sanghvi I, Martinez J, Adamson MM. Transdiagnostic role of glutamate and white matter damage in neuropsychiatric disorders: A Systematic Review. J Psychiatr Res 2022; 147:324-348. [PMID: 35151030 DOI: 10.1016/j.jpsychires.2021.12.042] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Revised: 12/08/2021] [Accepted: 12/19/2021] [Indexed: 12/09/2022]
Abstract
Neuropsychiatric disorders including generalized anxiety disorder (GAD), obsessive-compulsive disorder (OCD), major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SZ) have been considered distinct categories of diseases despite their overlapping characteristics and symptomatology. We aimed to provide an in-depth review elucidating the role of glutamate/Glx and white matter (WM) abnormalities in these disorders from a transdiagnostic perspective. The PubMed online database was searched for studies published between 2010 and 2021. After careful screening, 401 studies were included. The findings point to decreased levels of glutamate in the Anterior Cingulate Cortex in both SZ and BD, whereas Glx is elevated in the Hippocampus in SZ and MDD. With regard to WM abnormalities, the Corpus Callosum and superior Longitudinal Fascicle were the most consistently identified brain regions showing decreased fractional anisotropy (FA) across all the reviewed disorders, except GAD. Additionally, the Uncinate Fasciculus displayed decreased FA in all disorders, except OCD. Decreased FA was also found in the inferior Longitudinal Fasciculus, inferior Fronto-Occipital Fasciculus, Thalamic Radiation, and Corona Radiata in SZ, BD, and MDD. Decreased FA in the Fornix and Corticospinal Tract were found in BD and SZ patients. The Cingulum and Anterior Limb of Internal Capsule exhibited decreased FA in MDD and SZ patients. The results suggest a gradual increase in severity from GAD to SZ defined by the number of brain regions with WM abnormality which may be partially caused by abnormal glutamate levels. WM damage could thus be considered a potential marker of some of the main neuropsychiatric disorders.
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Affiliation(s)
- Ines Luttenbacher
- Department of Social & Behavioral Sciences, University of Amsterdam, Amsterdam, Netherlands; Rehabilitation Service, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA
| | - Angela Phillips
- Rehabilitation Service, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA; Department of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Reza Kazemi
- Department of Cognitive Psychology, Institute for Cognitive Science Studies, Tehran, Iran
| | - Abed L Hadipour
- Department of Cognitive Sciences, University of Messina, Messina, Italy
| | - Isha Sanghvi
- Rehabilitation Service, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA; Department of Neuroscience, University of Southern California, Los Angeles, CA, USA
| | - Julian Martinez
- Rehabilitation Service, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA; Palo Alto University, Palo Alto, CA, USA
| | - Maheen M Adamson
- Rehabilitation Service, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA; Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, USA.
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27
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Yang K, Longo L, Narita Z, Cascella N, Nucifora FC, Coughlin JM, Nestadt G, Sedlak TW, Mihaljevic M, Wang M, Kenkare A, Nagpal A, Sethi M, Kelly A, Di Carlo P, Kamath V, Faria A, Barker P, Sawa A. A multimodal study of a first episode psychosis cohort: potential markers of antipsychotic treatment resistance. Mol Psychiatry 2022; 27:1184-1191. [PMID: 34642460 PMCID: PMC9001745 DOI: 10.1038/s41380-021-01331-7] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/11/2020] [Revised: 09/17/2021] [Accepted: 09/29/2021] [Indexed: 11/13/2022]
Abstract
Treatment resistant (TR) psychosis is considered to be a significant cause of disability and functional impairment. Numerous efforts have been made to identify the clinical predictors of TR. However, the exploration of molecular and biological markers is still at an early stage. To understand the TR condition and identify potential molecular and biological markers, we analyzed demographic information, clinical data, structural brain imaging data, and molecular brain imaging data in 7 Tesla magnetic resonance spectroscopy from a first episode psychosis cohort that includes 136 patients. Age, gender, race, smoking status, duration of illness, and antipsychotic dosages were controlled in the analyses. We found that TR patients had a younger age at onset, more hospitalizations, more severe negative symptoms, a reduction in the volumes of the hippocampus (HP) and superior frontal gyrus (SFG), and a reduction in glutathione (GSH) levels in the anterior cingulate cortex (ACC), when compared to non-TR patients. The combination of multiple markers provided a better classification between TR and non-TR patients compared to any individual marker. Our study shows that ACC-GSH, HP and SFG volumes, and age at onset, could potentially be biomarkers for TR diagnosis, while hospitalization and negative symptoms could be used to evaluate the progression of the disease. Multimodal cohorts are essential in obtaining a comprehensive understanding of brain disorders.
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Affiliation(s)
- Kun Yang
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Luisa Longo
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
- Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Zui Narita
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Nicola Cascella
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Frederick C Nucifora
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Jennifer M Coughlin
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Gerald Nestadt
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Thomas W Sedlak
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Marina Mihaljevic
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Min Wang
- Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
- College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Anshel Kenkare
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Anisha Nagpal
- Department of Public Health Studies, Johns Hopkins University Zanvyl Krieger School of Arts and Sciences, Baltimore, MD, 21218, USA
| | - Mehk Sethi
- Department of Applied Math and Statistics, Johns Hopkins University Whiting School of Engineering, Baltimore, MD, 21218, USA
| | - Alexandra Kelly
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Pasquale Di Carlo
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
- Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Vidyulata Kamath
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Andreia Faria
- Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Peter Barker
- Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, 21205, USA
| | - Akira Sawa
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA.
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA.
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA.
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA.
- Department of Mental Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, 21205, USA.
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28
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Serum kynurenine metabolites might not be associated with risk factors of treatment-resistant schizophrenia. J Psychiatr Res 2022; 145:339-346. [PMID: 34776248 DOI: 10.1016/j.jpsychires.2021.11.002] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/08/2021] [Revised: 10/11/2021] [Accepted: 11/02/2021] [Indexed: 11/23/2022]
Abstract
BACKGROUND About a third of patients with schizophrenia do not respond adequately to currently available antipsychotics and thus experiences symptoms of greater severity, known as treatment-resistant schizophrenia (TRS). Some evidence suggests that the tryptophan (TRP) pathway (comprising 5-HT and kynurenine sub-pathways) has an important influence on response to antipsychotics. We therefore hypothesized that TRS is linked to metabolites of TRP pathway. METHODS We measured TRP metabolites in 54 patients with TRS and compared them to 49 age- and sex-matched patients who responded to antipsychotics (NTRS), and 62 healthy controls using liquid chromatography-tandem mass spectrometry. Psychopathology and clinical symptoms were assessed by means of schizophrenia positive and negative scales. Working memory abilities, cortical thickness and white matter diffusion tensor imaging fractional anisotropy were appraised in enrolled subjects by neurophysiological tests, as spatial span and digital sequencing tests, and 3T magnetic resonance imaging. RESULTS Patients with TRS had a significantly higher 5-HT/TRP ratio (p = 0.009) than patients with NTRS. However, the two groups did not differ in kynurenine-pathway metabolites or ratios. Additionally, 5-HT/TRP was positively correlated with disorganized symptoms in TRS (r = 0.59, p < 0.001), and negatively correlated with digit-sequencing test scores (r = -0.34, p = 0.02). These correlations were insignificant among patients with NTRS and healthy controls. In patients with TRS, 5-HT/TRP was strongly linked to the right supramarginal cortex (t = -3.2, p = 0.003), and in healthy controls, to the right transverse temporal (t = 3.40, p = 0.001), but significance disappeared after FDR correction. CONCLUSIONS Present results indicate that an upregulated 5-HT biosynthetic pathway can be associated to TRS, suggesting that targeting mechanisms of 5-HT conversion from tryptophan could shed light on the development of new pharmacological approaches of TRS.
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29
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Li H, Chen W, Gou M, Li W, Tong J, Zhou Y, Xie T, Yu T, Feng W, Li Y, Chen S, Tian B, Tan S, Wang Z, Pan S, Li N, Luo X, Zhang P, Huang J, Tian L, Li CSR, Tan Y. The relationship between TLR4/NF-κB/IL-1β signaling, cognitive impairment, and white-matter integrity in patients with stable chronic schizophrenia. Front Psychiatry 2022; 13:966657. [PMID: 36051545 PMCID: PMC9424630 DOI: 10.3389/fpsyt.2022.966657] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/11/2022] [Accepted: 07/22/2022] [Indexed: 01/10/2023] Open
Abstract
OBJECTIVE Previous studies have implicated intricate interactions between innate immunity and the brain in schizophrenia. Monocytic Toll-like receptor (TLR) 4 signaling, a crucial "sensor" of innate immunity, was reported to be over-activated in link with cognitive impairment in schizophrenia. As TLR4 is predominantly expressed on gliocytes prior to expression in neurons, we hypothesized that higher TLR4 levels may contribute to cognitive deterioration by affecting white matter microstructure. METHODS Forty-four patients with stable chronic schizophrenia (SCS) and 59 healthy controls (HCs) were recruited in this study. The monocytic function was detected with lipopolysaccharide (LPS) stimulation to simulate bacterial infection. Basal and LPS- stimulated levels of TLR4, nuclear factor-kappa B (NF-κB), and interleukin (IL)-1β were quantified with flow cytometry. Cognitive function was assessed by the MATRICS Consensus Cognitive Battery (MCCB) and psychopathological symptoms were evaluated by the Positive and Negative Syndrome Scale (PANSS). We employed diffusion tensor imaging with a 3-T scanner and evaluated white-matter integrity with fractional anisotropy (FA). Subcortical volume and cortical thickness were also assessed. RESULTS The TLR4/NF-κB/IL-1β signaling pathway was activated in patients with SCS, but responded sluggishly to LPS stimulation when compared with HCs. Furthermore, monocytic TLR4 expressions were inversely correlated with cognitive function and white matter FA, but not with cortical thickness or subcortical gray matter volume in schizophrenia. CONCLUSION Our findings support altered TLR4 signaling pathway activity in association with deficits in cognition and white matter integrity in schizophrenia.
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Affiliation(s)
- Hongna Li
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Wenjin Chen
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Mengzhuang Gou
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Wei Li
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Jinghui Tong
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Yanfang Zhou
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Ting Xie
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Ting Yu
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Wei Feng
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Yanli Li
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Song Chen
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Baopeng Tian
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Shuping Tan
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Zhiren Wang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Shujuan Pan
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Na Li
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Xingguang Luo
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States
| | - Ping Zhang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Junchao Huang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Li Tian
- Department of Physiology, Faculty of Medicine, Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, Estonia
| | - Chiang-Shan R Li
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States
| | - Yunlong Tan
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
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30
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Kochunov P, Hong LE, Dennis EL, Morey RA, Tate DF, Wilde EA, Logue M, Kelly S, Donohoe G, Favre P, Houenou J, Ching CRK, Holleran L, Andreassen OA, van Velzen LS, Schmaal L, Villalón-Reina JE, Bearden CE, Piras F, Spalletta G, van den Heuvel OA, Veltman DJ, Stein DJ, Ryan MC, Tan Y, van Erp TGM, Turner JA, Haddad L, Nir TM, Glahn DC, Thompson PM, Jahanshad N. ENIGMA-DTI: Translating reproducible white matter deficits into personalized vulnerability metrics in cross-diagnostic psychiatric research. Hum Brain Mapp 2022; 43:194-206. [PMID: 32301246 PMCID: PMC8675425 DOI: 10.1002/hbm.24998] [Citation(s) in RCA: 41] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2019] [Revised: 03/06/2020] [Accepted: 03/17/2020] [Indexed: 12/25/2022] Open
Abstract
The ENIGMA-DTI (diffusion tensor imaging) workgroup supports analyses that examine the effects of psychiatric, neurological, and developmental disorders on the white matter pathways of the human brain, as well as the effects of normal variation and its genetic associations. The seven ENIGMA disorder-oriented working groups used the ENIGMA-DTI workflow to derive patterns of deficits using coherent and coordinated analyses that model the disease effects across cohorts worldwide. This yielded the largest studies detailing patterns of white matter deficits in schizophrenia spectrum disorder (SSD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), posttraumatic stress disorder (PTSD), traumatic brain injury (TBI), and 22q11 deletion syndrome. These deficit patterns are informative of the underlying neurobiology and reproducible in independent cohorts. We reviewed these findings, demonstrated their reproducibility in independent cohorts, and compared the deficit patterns across illnesses. We discussed translating ENIGMA-defined deficit patterns on the level of individual subjects using a metric called the regional vulnerability index (RVI), a correlation of an individual's brain metrics with the expected pattern for a disorder. We discussed the similarity in white matter deficit patterns among SSD, BD, MDD, and OCD and provided a rationale for using this index in cross-diagnostic neuropsychiatric research. We also discussed the difference in deficit patterns between idiopathic schizophrenia and 22q11 deletion syndrome, which is used as a developmental and genetic model of schizophrenia. Together, these findings highlight the importance of collaborative large-scale research to provide robust and reproducible effects that offer insights into individual vulnerability and cross-diagnosis features.
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Affiliation(s)
- Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - L Elliot Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Emily L Dennis
- Psychiatry Neuroimaging Laboratory, Brigham & Women's Hospital, Boston, Massachusetts, USA
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, California, USA
- Department of Neurology, University of Utah School of Medicine, Salt Lake City, Utah, USA
- George E. Wahlen VA, Salt Lake City, Utah, USA
| | - Rajendra A Morey
- Brain Imaging and Analysis Center, Duke University, Durham, North Carolina, USA
| | - David F Tate
- Department of Neurology, University of Utah School of Medicine, Salt Lake City, Utah, USA
- George E. Wahlen VA, Salt Lake City, Utah, USA
| | - Elisabeth A Wilde
- Department of Neurology, University of Utah School of Medicine, Salt Lake City, Utah, USA
- George E. Wahlen VA, Salt Lake City, Utah, USA
| | - Mark Logue
- VA Boston Healthcare System, National Center for PTSD, Boston, Massachusetts, USA
- Boston University School of Medicine, Department of Psychiatry, Boston, Massachusetts, USA
- Boston University School of Medicine, Biomedical Genetics, Boston, Massachusetts, USA
- Boston University School of Public Health, Department of Biostatistics, Boston, Massachusetts, USA
| | - Sinead Kelly
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, California, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Gary Donohoe
- Centre for Neuroimaging and Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, National University of Ireland Galway, Galway, Ireland
| | - Pauline Favre
- Neurospin, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
- INSERM Unit U955, team "Translational Neuro-Psychiatry", Créteil, France
| | - Josselin Houenou
- Neurospin, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
- INSERM Unit U955, team "Translational Neuro-Psychiatry", Créteil, France
- Psychiatry Department, Assistance Publique-Hôpitaux de Paris (AP-HP), CHU Mondor, Créteil, France
- Faculté de Médecine, Université Paris Est Créteil, Créteil, France
| | - Christopher R K Ching
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, California, USA
| | - Laurena Holleran
- Centre for Neuroimaging and Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, National University of Ireland Galway, Galway, Ireland
| | - Ole A Andreassen
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Laura S van Velzen
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Australia
- Orygen, The National Centre of Excellence in Youth Mental Health, Parkville, Australia
| | - Lianne Schmaal
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Australia
- Orygen, The National Centre of Excellence in Youth Mental Health, Parkville, Australia
| | - Julio E Villalón-Reina
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, California, USA
| | - Carrie E Bearden
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California at Los Angeles, Los Angeles, California, USA
- Department of Psychology, University of California at Los Angeles, Los Angeles, California, USA
| | - Fabrizio Piras
- Laboratory of Neuropsychiatry, Department of Clinical and Behavioral Neurology, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Gianfranco Spalletta
- Laboratory of Neuropsychiatry, Department of Clinical and Behavioral Neurology, IRCCS Santa Lucia Foundation, Rome, Italy
- Division of Neuropsychiatry, Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas, USA
| | - Odile A van den Heuvel
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Psychiatry, Department of Anatomy & Neurosciences, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Dick J Veltman
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Psychiatry, Department of Anatomy & Neurosciences, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Dan J Stein
- Department of Psychiatry & Neuroscience Institute, University of Cape Town, SA MRC Unit on Risk & Resilience in Mental Disorders, Cape Town, South Africa
| | - Meghann C Ryan
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Yunlong Tan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, China
| | - Theo G M van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry, University of California Irvine, Irvine, California, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, Irvine, California, USA
| | - Jessica A Turner
- Department of Psychology and Neuroscience Institute, Georgia State University, Atlanta, Georgia, USA
| | - Liz Haddad
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, California, USA
| | - Talia M Nir
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, California, USA
| | - David C Glahn
- Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, Boston, Massachusetts, USA
- Olin Neuropsychiatric Research Center, Hartford Hospital, Hartford, Connecticut, USA
| | - Paul M Thompson
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, California, USA
| | - Neda Jahanshad
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, California, USA
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White matter in prolonged glucocorticoid response to psychological stress in schizophrenia. Neuropsychopharmacology 2021; 46:2312-2319. [PMID: 34211106 PMCID: PMC8580975 DOI: 10.1038/s41386-021-01077-4] [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: 03/05/2021] [Revised: 06/17/2021] [Accepted: 06/21/2021] [Indexed: 02/06/2023]
Abstract
Stress is implicated in psychosis etiology and exacerbation, but pathogenesis toward brain network alterations in schizophrenia remain unclear. White matter connects limbic and prefrontal regions responsible for stress response regulation, and white matter tissues are also vulnerable to glucocorticoid aberrancies. Using a novel psychological stressor task, we studied cortisol stress responses over time and white matter microstructural deficits in schizophrenia spectrum disorder (SSD). Cortisol was measured at baseline, 0-, 20-, and 40-min after distress induction by a psychological stressor task in 121 SSD patients and 117 healthy controls (HC). White matter microstructural integrity was measured by 64-direction diffusion tensor imaging. Fractional anisotropy (FA) in white matter tracts were related to cortisol responses and then compared to general patterns of white matter tract deficits in SSD identified by mega-analysis. Differences between 40-min post-stress and baseline, but not acute reactivity post-stress, was significantly elevated in SSD vs HC, time × diagnosis interaction F2.3,499.9 = 4.1, p = 0.013. All SSD white matter tracts were negatively associated with prolonged cortisol reactivity but all tracts were positively associated with prolonged cortisol reactivity in HC. Individual tracts most strongly associated with prolonged cortisol reactivity were also most impacted in schizophrenia in general as established by the largest schizophrenia white matter study (r = -0.56, p = 0.006). Challenged with psychological stress, SSD and HC mount similar cortisol responses, and impairments arise in the resolution timeframe. Prolonged cortisol elevations are associated with the white matter deficits in SSD, in a pattern previously associated with schizophrenia in general.
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32
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Lancaster TM, Dimitriadis SI, Perry G, Zammit S, O’Donovan MC, Linden DE. Morphometric Analysis of Structural MRI Using Schizophrenia Meta-analytic Priors Distinguish Patients from Controls in Two Independent Samples and in a Sample of Individuals With High Polygenic Risk. Schizophr Bull 2021; 48:524-532. [PMID: 34662406 PMCID: PMC8886591 DOI: 10.1093/schbul/sbab125] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
Schizophrenia (SCZ) is associated with structural brain changes, with considerable variation in the extent to which these cortical regions are influenced. We present a novel metric that summarises individual structural variation across the brain, while considering prior effect sizes, established via meta-analysis. We determine individual participant deviation from a within-sample-norm across structural MRI regions of interest (ROIs). For each participant, we weight the normalised deviation of each ROI by the effect size (Cohen's d) of the difference between SCZ/control for the corresponding ROI from the SCZ Enhancing Neuroimaging Genomics through Meta-Analysis working group. We generate a morphometric risk score (MRS) representing the average of these weighted deviations. We investigate if SCZ-MRS is elevated in a SCZ case/control sample (NCASE = 50; NCONTROL = 125), a replication sample (NCASE = 23; NCONTROL = 20) and a sample of asymptomatic young adults with extreme SCZ polygenic risk (NHIGH-SCZ-PRS = 95; NLOW-SCZ-PRS = 94). SCZ cases had higher SCZ-MRS than healthy controls in both samples (Study 1: β = 0.62, P < 0.001; Study 2: β = 0.81, P = 0.018). The high liability SCZ-PRS group also had a higher SCZ-MRS (Study 3: β = 0.29, P = 0.044). Furthermore, the SCZ-MRS was uniquely associated with SCZ status, but not attention-deficit hyperactivity disorder (ADHD), whereas an ADHD-MRS was linked to ADHD status, but not SCZ. This approach provides a promising solution when considering individual heterogeneity in SCZ-related brain alterations by identifying individual's patterns of structural brain-wide alterations.
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Affiliation(s)
- Thomas M Lancaster
- Department of Psychology, Bath University, Bath, UK,Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK,To whom correspondence should be addressed; Department of Psychology, Bath University, Bath, UK, tel.: +44-1225-384658, e-mail:
| | - Stavros I Dimitriadis
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK,MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff School of Medicine, Cardiff University, Cardiff, UK
| | - Gavin Perry
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK
| | - Stan Zammit
- MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff School of Medicine, Cardiff University, Cardiff, UK,Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Michael C O’Donovan
- MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff School of Medicine, Cardiff University, Cardiff, UK,Neuroscience and Mental Health Research Institute, Cardiff University, Cardiff, UK
| | - David E Linden
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK,MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff School of Medicine, Cardiff University, Cardiff, UK,Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK,School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
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Is treatment-resistant schizophrenia associated with distinct neurobiological callosal connectivity abnormalities? CNS Spectr 2021; 26:545-549. [PMID: 32772934 DOI: 10.1017/s1092852920001753] [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: 01/25/2023]
Abstract
BACKGROUND Resistance to antipsychotic treatment affects up to 30% of patients with schizophrenia. Although the time course of development of treatment-resistant schizophrenia (TRS) varies from patient to patient, the reasons for these variations remain unknown. Growing evidence suggests brain dysconnectivity as a significant feature of schizophrenia. In this study, we compared fractional anisotropy (FA) of brain white matter between TRS and non-treatment-resistant schizophrenia (non-TRS) patients. Our central hypothesis was that TRS is associated with reduced FA values. METHODS TRS was defined as the persistence of moderate to severe symptoms after adequate treatment with at least two antipsychotics from different classes. Diffusion-tensor brain MRI obtained images from 34 TRS participants and 51 non-TRS. Whole-brain analysis of FA and axial, radial, and mean diffusivity were performed using Tract-Based Spatial Statistics (TBSS) and FMRIB's Software Library (FSL), yielding a contrast between TRS and non-TRS patients, corrected for multiple comparisons using family-wise error (FWE) < 0.05. RESULTS We found a significant reduction in FA in the splenium of corpus callosum (CC) in TRS when compared to non-TRS. The antipsychotic dose did not relate to the splenium CC. CONCLUSION Our results suggest that the focal abnormality of CC may be a potential biomarker of TRS.
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White matter brain aging in relationship to schizophrenia and its cognitive deficit. Schizophr Res 2021; 230:9-16. [PMID: 33667860 PMCID: PMC8222174 DOI: 10.1016/j.schres.2021.02.003] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Revised: 01/26/2021] [Accepted: 02/18/2021] [Indexed: 11/21/2022]
Abstract
We hypothesized that cerebral white matter deficits in schizophrenia (SZ) are driven in part by accelerated white matter aging and are associated with cognitive deficits. We used a machine learning model to predict individual age from diffusion tensor imaging features and calculated the delta age (Δage) as the difference between predicted and chronological age. Through this approach, we translated multivariate white matter imaging features into an age-scaled metric and used it to test the temporal trends of accelerated aging-related white matter deficit in SZ and its association with the cognition. A feature selection procedure was first employed to choose fractional anisotropy values in 34 of 43 white fiber tracts. Using these features, a machine learning model was trained based on a training set consisted of 107 healthy controls (HC). The brain age of 166 SZs and 107 HCs in the testing set were calculated using this model. Then, we examined the SZ-HC group effect on Δage and whether this effect was moderated by chronological age using the regression spline model. The results showed that Δage was significantly elevated in the age > 30 group in patients (p < 0.001) but not in age ≤ 30 group (p = 0.364). Δage in patients was significantly and negatively associated with both working memory (β = -0.176, p = 0.007) and processing speed (β = -0.519, p = 0.035) while adjusting sex and chronological age. Overall, these findings indicate that the Δage is elevated in SZs and become significantly from the third decade of life; the increase of Δage in SZs is associated with the declined neurocognitive performance.
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Pretreatment abnormalities in white matter integrity predict one-year clinical outcome in first episode schizophrenia. Schizophr Res 2021; 228:241-248. [PMID: 33486391 DOI: 10.1016/j.schres.2020.12.011] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Revised: 08/17/2020] [Accepted: 12/06/2020] [Indexed: 02/05/2023]
Abstract
Schizophrenia is a serious mental illness for which the mainstay of treatment is antipsychotics. Up to 30% of schizophrenia patients show limited response to antipsychotics. Identifying these patients before treatment could guide individualized treatment for improving outcomes in those not likely to show robust benefit from antipsychotics. Diffusion tensor imaging was performed with 56 drug-naïve first-episode schizophrenia patients and 69 matched healthy controls. Patients were followed clinically after one-year of antipsychotic treatment and classified at that point into groups of 17 poor outcome and 39 good outcome patients based on whether they showed at least a 50% reduction of Positive and Negative Syndrome Scale (PANSS) scores from baseline. Tract-based spatial statistics were applied to assess white matter microstructure in the two patient subgroups and healthy controls. Poor outcome patients showed reduced pretreatment fractional anisotropy (FA) in left cingulum and anterior thalamic radiation and increased FA in right superior and inferior longitudinal fasciculus compared with good outcome patients. FA in each of these four tracts was decreased in both patient subgroups relative to healthy controls. Considered together, the four altered tracts showed promising ability to differentiate poor from good outcome patients (sensitivity = 74.4%, specificity = 95.2%, AUC = 0.90, p < 0.001), and superior prediction of clinical outcome to baseline PANSS scores (p < 0.015). Prediction of outcomes using DTI features was not related to duration of untreated psychosis. Baseline alterations in white matter integrity may identify schizophrenia patients less likely to respond to treatment, which could be useful information for stratification in clinical trials and for individualized treatment planning.
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36
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Tong J, Zhou Y, Huang J, Zhang P, Fan F, Chen S, Tian B, Cui Y, Tian L, Tan S, Wang Z, Feng W, Yang F, Hare S, Goldwaser EL, Bruce HA, Kvarta M, Chen S, Kochunov P, Tan Y, Hong LE. N-methyl-D-aspartate Receptor Antibody and White Matter Deficits in Schizophrenia Treatment-Resistance. Schizophr Bull 2021; 47:1463-1472. [PMID: 33515249 PMCID: PMC8379535 DOI: 10.1093/schbul/sbab003] [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] [Indexed: 01/08/2023]
Abstract
Insufficient or lack of response to antipsychotic medications in some patients with schizophrenia is a major challenge in psychiatry, but the underlying mechanisms remain unclear. Two seemingly unrelated observations, cerebral white matter and N-methyl-D-aspartate receptor (NMDAR) hypofunction, have been linked to treatment-resistant schizophrenia (TRS). As NMDARs are critical to axonal myelination and signal transduction, we hypothesized that NMDAR antibody (Ab), when present in schizophrenia, may impair NMDAR functions and white matter microstructures, contributing to TRS. In this study, 50 patients with TRS, 45 patients with nontreatment-resistant schizophrenia (NTRS), 53 patients with schizophrenia at treatment initiation schizophrenia (TIS), and 90 healthy controls were enrolled. Serum NMDAR Ab levels and white matter diffusion tensor imaging fractional anisotropy (FA) were assessed. The white matter specificity effects by NMDAR Ab were assessed by comparing with effects on cortical and subcortical gray matter. Serum NMDAR Ab levels of the TRS were significantly higher than those of the NTRS (P = .035). In patients with TRS, higher NMDAR Ab levels were significantly associated with reduced whole-brain average FA (r = -.37; P = .026), with the strongest effect at the genu of corpus callosum (r = -.50; P = .0021, significant after correction for multiple comparisons). Conversely, there was no significant correlation between whole-brain or regional cortical thickness or any subcortical gray matter structural volume and NMDAR Ab levels in TRS. Our finding highlights a potential NMDAR mechanism on white matter microstructure impairment in schizophrenia that may contribute to their treatment resistance to antipsychotic medications.
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Affiliation(s)
- Jinghui Tong
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, P. R. China
| | - Yanfang Zhou
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, P. R. China
| | - Junchao Huang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, P. R. China
| | - Ping Zhang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, P. R. China
| | - Fengmei Fan
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, P. R. China
| | - Song Chen
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, P. R. China
| | - Baopeng Tian
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, P. R. China
| | - Yimin Cui
- Department of Pharmacy, Peking University First Hospital, Beijing, P. R. China
| | - Li Tian
- Institute of Biomedicine and Translational Medicine, Department of Physiology, Faculty of Medicine, University of Tartu, Tartu, Estonia
| | - Shuping Tan
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, P. R. China
| | - Zhiren Wang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, P. R. China
| | - Wei Feng
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, P. R. China
| | - Fude Yang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, P. R. China
| | - Stephanie Hare
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Eric L Goldwaser
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Heather A Bruce
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Mark Kvarta
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Shuo Chen
- 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
| | - Yunlong Tan
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, P. R. China,To whom correspondence should be addressed; tel: +86-(10)-83024319, fax: +86-(10)-62710156, e-mail:
| | - L Elliot Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
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37
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Comparison of regional brain deficit patterns in common psychiatric and neurological disorders as revealed by big data. NEUROIMAGE-CLINICAL 2021; 29:102574. [PMID: 33530016 PMCID: PMC7851406 DOI: 10.1016/j.nicl.2021.102574] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Revised: 12/08/2020] [Accepted: 01/16/2021] [Indexed: 12/15/2022]
Abstract
RVI for MDD and AD was derived based on large meta-analytical findings. RVI-MDD and AD were significantly elevated in UKBB subjects with respective illnesses. There was no elevation of RVI-MDD in subjects with AD or RVI-AD in subjects with MDD. RVI captures neuroanatomic deviation patterns. RVI is a useful biomarker for assessing similarity to neuropsychiatric illnesses.
Neurological and psychiatric illnesses are associated with regional brain deficit patterns that bear unique signatures and capture illness-specific characteristics. The Regional Vulnerability Index (RVI) was developed to quantify brain similarity by comparing individual white matter microstructure, cortical gray matter thickness and subcortical gray matter structural volume measures with neuroanatomical deficit patterns derived from large-scale meta-analytic studies. We tested the specificity of the RVI approach for major depressive disorder (MDD) and Alzheimer’s disease (AD) in a large epidemiological sample of UK Biobank (UKBB) participants (N = 19,393; 9138 M/10,255F; age = 64.8 ± 7.4 years). Compared to controls free of neuropsychiatric disorders, participants with MDD (N = 2,248; 805 M/1443F; age = 63.4 ± 7.4) had significantly higher RVI-MDD values (t = 5.6, p = 1·10−8), but showed no detectable difference in RVI-AD (t = 2.0, p = 0.10). Subjects with dementia (N = 7; 4 M/3F; age = 68.6 ± 8.6 years) showed significant elevation in RVI-AD (t = 4.2, p = 3·10−5) but not RVI-MDD (t = 2.1, p = 0.10) compared to controls. Even within affective illnesses, participants with bipolar disorder (N = 54) and anxiety disorder (N = 773) showed no significant elevation in whole-brain RVI-MDD. Participants with Parkinson’s disease (N = 37) showed elevation in RVI-AD (t = 2.4, p = 0.01) while subjects with stroke (N = 247) showed no such elevation (t = 1.1, p = 0.3). In summary, we demonstrated elevation in RVI-MDD and RVI-AD measures in the respective illnesses with strong replicability that is relatively specific to the respective diagnoses. These neuroanatomic deviation patterns offer a useful biomarker for population-wide assessments of similarity to neuropsychiatric illnesses.
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Kochunov P, Zavaliangos-Petropulu A, Jahanshad N, Thompson PM, Ryan MC, Chiappelli J, Chen S, Du X, Hatch K, Adhikari B, Sampath H, Hare S, Kvarta M, Goldwaser E, Yang F, Olvera RL, Fox PT, Curran JE, Blangero J, Glahn DC, Tan Y, Hong LE. A White Matter Connection of Schizophrenia and Alzheimer's Disease. Schizophr Bull 2021; 47:197-206. [PMID: 32681179 PMCID: PMC7825012 DOI: 10.1093/schbul/sbaa078] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Schizophrenia (SZ) is a severe psychiatric illness associated with an elevated risk for developing Alzheimer's disease (AD). Both SZ and AD have white matter abnormalities and cognitive deficits as core disease features. We hypothesized that aging in SZ patients may be associated with the development of cerebral white matter deficit patterns similar to those observed in AD. We identified and replicated aging-related increases in the similarity between white matter deficit patterns in patients with SZ and AD. The white matter "regional vulnerability index" (RVI) for AD was significantly higher in SZ patients compared with healthy controls in both the independent discovery (Cohen's d = 0.44, P = 1·10-5, N = 173 patients/230 control) and replication (Cohen's d = 0.78, P = 9·10-7, N = 122 patients/64 controls) samples. The degree of overlap with the AD deficit pattern was significantly correlated with age in patients (r = .21 and .29, P < .01 in discovery and replication cohorts, respectively) but not in controls. Elevated RVI-AD was significantly associated with cognitive measures in both SZ and AD. Disease and cognitive specificities were also tested in patients with mild cognitive impairment and showed intermediate overlap. SZ and AD have diverse etiologies and clinical courses; our findings suggest that white matter deficits may represent a key intersecting point for these 2 otherwise distinct diseases. Identifying mechanisms underlying this white matter deficit pattern may yield preventative and treatment targets for cognitive deficits in both SZ and AD patients.
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Affiliation(s)
- Peter Kochunov
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD
| | - Artemis Zavaliangos-Petropulu
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California of USC, Marina del Rey, CA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California of USC, Marina del Rey, CA
| | - Paul M Thompson
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California of USC, Marina del Rey, CA
| | - Meghann C Ryan
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD
| | - Joshua Chiappelli
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD
| | - Shuo Chen
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD
| | - Xiaoming Du
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD
| | - Kathryn Hatch
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD
| | - Bhim Adhikari
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD
| | - Hemalatha Sampath
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD
| | - Stephanie Hare
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD
| | - Mark Kvarta
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD
| | - Eric Goldwaser
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD
| | - Fude Yang
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Rene L Olvera
- Department of Psychiatry, University of Texas Health Science Center at San Antonio, San Antonio, TX
| | - Peter T Fox
- Research Imaging Institute, University of Texas Health Science Center at San Antonio, San Antonio, TX
| | - Joanne E Curran
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio Grande Valley, Brownsville, TX
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio Grande Valley, Brownsville, TX
| | - David C Glahn
- Department of Psychiatry, Boston Children’s Hospital, Harvard Medical School, Boston, MA
| | - Yunlong Tan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - L Elliot Hong
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD
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Adamczyk P, Płonka O, Kruk D, Jáni M, Błądziński P, Kalisz A, Castelein S, Cechnicki A, Wyczesany M. On the relation of white matter brain abnormalities and the asociality symptoms in schizophrenia outpatients - a DTI study. Acta Neurobiol Exp (Wars) 2021; 81:80-95. [PMID: 33949167 DOI: 10.21307/ane-2021-009] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Accepted: 01/29/2021] [Indexed: 11/11/2022]
Abstract
Recent MRI studies have shown that abnormal functional connections in schizophrenia coexist with subtle changes in the structure of axons in the brain. However, there is a discrepancy in the literature concerning the relationship between white matter abnormalities and the occurrence of negative psychopathological symptoms. In the present study, we investigate the relationship between the altered white matter structure and specific psychopathology symptoms, i.e., subscales of Positive and Negative Syndrome Scale (PANSS) and Brief Negative Symptoms Scale (BNSS) in a sample of schizophrenia outpatients. For investigation on white matter abnormalities in schizophrenia, the diffusion tensor imaging analysis of between-group differences in main diffusion parameters by tract-based spatial statistics was conducted on schizophrenia outpatients and healthy controls. Hence, the correlation of PANSS and BNSS psychopathology subscales in the clinical group with fractional anisotropy was analyzed in the 17 selected cortical regions of interest. Presented between-group results revealed widespread loss of white matter integrity located across the brain in schizophrenia outpatients. Results on the white matter relationship with psychopathology revealed the negative correlation between fractional anisotropy in the left orbital prefrontal cortex, right Heschl's gyrus, bilateral precuneus and posterior cingulate cortex and the severity of asociality, as assessed with the BNSS. In conclusion, the presented study confirms the previous evidence on the widespread white matter abnormalities in schizophrenia outpatients and indicates the existence of the subtle but specific association between fractional anisotropy in the fronto-temporo-parietal regions with the asociality. Recent MRI studies have shown that abnormal functional connections in schizophrenia coexist with subtle changes in the structure of axons in the brain. However, there is a discrepancy in the literature concerning the relationship between white matter abnormalities and the occurrence of negative psychopathological symptoms. In the present study, we investigate the relationship between the altered white matter structure and specific psychopathology symptoms, i.e., subscales of Positive and Negative Syndrome Scale (PANSS) and Brief Negative Symptoms Scale (BNSS) in a sample of schizophrenia outpatients. For investigation on white matter abnormalities in schizophrenia, the diffusion tensor imaging analysis of between-group differences in main diffusion parameters by tract-based spatial statistics was conducted on schizophrenia outpatients and healthy controls. Hence, the correlation of PANSS and BNSS psychopathology subscales in the clinical group with fractional anisotropy was analyzed in the 17 selected cortical regions of interest. Presented between-group results revealed widespread loss of white matter integrity located across the brain in schizophrenia outpatients. Results on the white matter relationship with psychopathology revealed the negative correlation between fractional anisotropy in the left orbital prefrontal cortex, right Heschl’s gyrus, bilateral precuneus and posterior cingulate cortex and the severity of asociality, as assessed with the BNSS. In conclusion, the presented study confirms the previous evidence on the widespread white matter abnormalities in schizophrenia outpatients and indicates the existence of the subtle but specific association between fractional anisotropy in the fronto-temporo-parietal regions with the asociality.
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Affiliation(s)
| | - Olga Płonka
- Institute of Psychology , Jagiellonian University , Krakow , Poland
| | - Dawid Kruk
- Psychosis Research and Psychotherapy Unit , Association for the Development of Community Psychiatry and Care , Krakow , Poland ; Community Psychiatry and Psychosis Research Center , Chair of Psychiatry , Medical College , Jagiellonian University , Krakow , Poland
| | - Martin Jáni
- Institute of Psychology , Jagiellonian University , Krakow , Poland ; Department of Psychiatry , Faculty of Medicine , Masaryk University and University Hospital Brno , Brno , Czech Republic
| | - Piotr Błądziński
- Community Psychiatry and Psychosis Research Center , Chair of Psychiatry , Medical College , Jagiellonian University , Krakow , Poland
| | - Aneta Kalisz
- Community Psychiatry and Psychosis Research Center , Chair of Psychiatry , Medical College , Jagiellonian University , Krakow , Poland
| | - Stynke Castelein
- Lentis Research , Lentis Psychiatric Institute , Groningen , The Netherlands ; Faculty of Behavioural and Social Sciences , University of Groningen , Groningen , The Netherlands
| | - Andrzej Cechnicki
- Psychosis Research and Psychotherapy Unit , Association for the Development of Community Psychiatry and Care , Krakow , Poland ; Community Psychiatry and Psychosis Research Center , Chair of Psychiatry , Medical College , Jagiellonian University , Krakow , Poland
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Zhou CH, Xue SS, Xue F, Liu L, Liu JC, Ma QR, Qin JH, Tan QR, Wang HN, Peng ZW. The impact of quetiapine on the brain lipidome in a cuprizone-induced mouse model of schizophrenia. Biomed Pharmacother 2020; 131:110707. [PMID: 32905942 DOI: 10.1016/j.biopha.2020.110707] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Revised: 08/25/2020] [Accepted: 08/28/2020] [Indexed: 12/12/2022] Open
Abstract
The antipsychotic effect of Quetiapine (Que) has been extensively studied and growing evidence suggests that Que has a beneficial effect, improving cognitive functions and promoting myelin repair. However, the effects of Que on the brain lipidome and the association between Que-associated cognitive improvement and changes in lipids remain elusive. In the present study, we assessed the cognitive protective effects of Que treatment and used a mass spectrometry-based lipidomic approach to evaluated changes in lipid composition in the hippocampus, prefrontal cortex (PFC), and striatum in a mouse model of cuprizone (CPZ)-induced demyelination. CPZ induces cognitive impairment and remarkable lipid changes in the brain, specifically in lipid species of glycerophospholipids and sphingolipids. Moreover, the changes in lipid classes of the PFC were more extensive than those observed in the hippocampus and striatum. Notably, Que treatment ameliorated cuprizone-induced cognitive impairment and partly normalized CPZ-induced lipid changes. Taken together, our data suggest that Que may rescue cognitive behavioral changes from CPZ-induced demyelination through modulation of the brain lipidome, providing new insights into the pharmacological mechanism of Que for schizophrenia.
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Affiliation(s)
- Cui-Hong Zhou
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China; Department of Toxicology, Shaanxi Key Lab of Free Radical Biology and Medicine, The Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, School of Public Health, Fourth Military Medical University, Xi'an, 710032, China
| | - Shan-Shan Xue
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China; Department of Toxicology, Shaanxi Key Lab of Free Radical Biology and Medicine, The Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, School of Public Health, Fourth Military Medical University, Xi'an, 710032, China
| | - Fen Xue
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China
| | - Ling Liu
- Institute of Neuroscience, Fourth Military Medical University, Xi'an, 710032, China
| | - Jun-Chang Liu
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China
| | - Quan-Rui Ma
- Department of Pediatrics, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China; Department of Human Anatomy and Histology and Embryology, Basic Medical College, Ningxia Medical University, 750004, China
| | - Jun-Hui Qin
- State Key Laboratory of Cancer Biology, Department of Pathology, Xijing Hospital and School of Basic Medicine, Fourth Military Medical University, Xi'an, 710032, China
| | - Qing-Rong Tan
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China
| | - Hua-Ning Wang
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China.
| | - Zheng-Wu Peng
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China; Department of Toxicology, Shaanxi Key Lab of Free Radical Biology and Medicine, The Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, School of Public Health, Fourth Military Medical University, Xi'an, 710032, China.
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Ochi R, Noda Y, Tsuchimoto S, Tarumi R, Honda S, Matsushita K, Tsugawa S, Plitman E, Masuda F, Ogyu K, Wada M, Miyazaki T, Fujii S, Chakravarty MM, Graff-Guerrero A, Uchida H, Mimura M, Nakajima S. White matter microstructural organizations in patients with severe treatment-resistant schizophrenia: A diffusion tensor imaging study. Prog Neuropsychopharmacol Biol Psychiatry 2020; 100:109871. [PMID: 31962187 DOI: 10.1016/j.pnpbp.2020.109871] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/15/2019] [Revised: 11/19/2019] [Accepted: 01/15/2020] [Indexed: 01/29/2023]
Abstract
Previous diffusion tensor imaging (DTI) studies have reported white matter alterations in patients with schizophrenia. Notably, one third of this population does not respond to first-line antipsychotics and is thus referred to as treatment-resistant schizophrenia (TRS). Despite potentially distinct neural bases between TRS and non-TRS, few studies have compared white matter integrity between these groups. In order to reflect clinical picture of TRS, we enrolled TRS patients who had severe symptoms. According to the consensus criteria for TRS. TRS was defined by severe positive symptomatology despite optimal antipsychotic treatment. Fractional anisotropy (FA), an index of white matter integrity, was examined by DTI and analyzed with tract-based spatial statistics in 24 TRS patients (mean PANSS = 108.9), 28 non-TRS patients (mean PANSS = 50.0), and 27 healthy controls (HCs) for group comparison. Additionally, correlation analyses were conducted between FA values and symptomatology. The TRS group had lower FA values in multiple tracts (cerebral peduncle, corona radiata, corpus callosum, external and internal capsules, posterior thalamic radiation, sagittal stratum, superior longitudinal fasciculus, tapetum, and uncinate fasciculus) compared to the HC group as well as the non-TRS group (p < .05; family-wise error-corrected), while no differences were found between the non-TRS and HC groups. In the TRS group, FA values in most of the tracts (other than the left anterior limb of internal capsule, left cerebral peduncle, and right uncinate fasciculus) were negatively correlated with the Positive and Negative Syndrome Scale total scores, and negative and general symptom scores. No such relationships were found in the non-TRS group. The identified white matter integrity deficits may reflect the pathophysiology of TRS.
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Affiliation(s)
- Ryo Ochi
- Faculty of Environment and Information Studies, Keio University, Fujisawa, Japan
| | - Yoshihiro Noda
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Shohei Tsuchimoto
- Graduate School of Science and Technology, Keio University, Yokohama, Japan
| | - Ryosuke Tarumi
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan; Department of Psychiatry, Komagino Hospital, Tokyo, Japan
| | - Shiori Honda
- Graduate School of Media and Governance, Keio University, Fujisawa, Japan
| | - Karin Matsushita
- Faculty of Environment and Information Studies, Keio University, Fujisawa, Japan
| | - Sakiko Tsugawa
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Eric Plitman
- Cerebral Imaging Centre, Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada; Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - Fumi Masuda
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Kamiyu Ogyu
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Masataka Wada
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Takahiro Miyazaki
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Shinya Fujii
- Faculty of Environment and Information Studies, Keio University, Fujisawa, Japan
| | - M Mallar Chakravarty
- Cerebral Imaging Centre, Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada; Department of Psychiatry, McGill University, Montreal, QC, Canada; Department of Biomedical Engineering, McGill University, Montreal, QC, Canada
| | - Ariel Graff-Guerrero
- Campbell Institute Research Program, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Hiroyuki Uchida
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan; Campbell Institute Research Program, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Masaru Mimura
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Shinichiro Nakajima
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan; Campbell Institute Research Program, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.
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42
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Kochunov P, Fan F, Ryan MC, Hatch KS, Tan S, Jahanshad N, Thompson PM, van Erp TGM, Turner JA, Chen S, Du X, Adhikari B, Bruce H, Hare S, Goldwaser E, Kvarta M, Huang J, Tong J, Cui Y, Cao B, Tan Y, Hong LE. Translating ENIGMA schizophrenia findings using the regional vulnerability index: Association with cognition, symptoms, and disease trajectory. Hum Brain Mapp 2020; 43:566-575. [PMID: 32463560 PMCID: PMC8675428 DOI: 10.1002/hbm.25045] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2019] [Revised: 05/11/2020] [Accepted: 05/11/2020] [Indexed: 12/17/2022] Open
Abstract
Patients with schizophrenia have patterns of brain deficits including reduced cortical thickness, subcortical gray matter volumes, and cerebral white matter integrity. We proposed the regional vulnerability index (RVI) to translate the results of Enhancing Neuro Imaging Genetics Meta-Analysis studies to the individual level. We calculated RVIs for cortical, subcortical, and white matter measurements and a multimodality RVI. We evaluated RVI as a measure sensitive to schizophrenia-specific neuroanatomical deficits and symptoms and studied the timeline of deficit formations in: early (≤5 years since diagnosis, N = 45, age = 28.8 ± 8.5); intermediate (6-20 years, N = 30, age 43.3 ± 8.6); and chronic (21+ years, N = 44, age = 52.5 ± 5.2) patients and healthy controls (N = 76, age = 38.6 ± 12.4). All RVIs were significantly elevated in patients compared to controls, with the multimodal RVI showing the largest effect size, followed by cortical, white matter and subcortical RVIs (d = 1.57, 1.23, 1.09, and 0.61, all p < 10-6 ). Multimodal RVI was significantly correlated with multiple cognitive variables including measures of visual learning, working memory and the total score of the MATRICS consensus cognitive battery, and with negative symptoms. The multimodality and white matter RVIs were significantly elevated in the intermediate and chronic versus early diagnosis group, consistent with ongoing progression. Cortical RVI was stable in the three disease-duration groups, suggesting neurodevelopmental origins of cortical deficits. In summary, neuroanatomical deficits in schizophrenia affect the entire brain; the heterochronicity of their appearance indicates both the neurodevelopmental and progressive nature of this illness. These deficit patterns may be useful for early diagnosis and as quantitative targets for more effective treatment strategies aiming to alter these neuroanatomical deficit patterns.
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Affiliation(s)
- Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Fengmei Fan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, People's Republic of China
| | - Meghann C Ryan
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Kathryn S Hatch
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Shuping Tan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, People's Republic of China
| | - Neda Jahanshad
- Imaging Genetics Center, Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine of USC, Los Angeles, California, USA
| | - Paul M Thompson
- Imaging Genetics Center, Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine of USC, Los Angeles, California, USA
| | - Theo G M van Erp
- Department of Psychiatry, University of California Irvine, Irvine, California, USA
| | - Jessica A Turner
- Department of Psychology and Neuroscience Institute, Georgia State University, Atlanta, Georgia, USA
| | - Shuo Chen
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Xiaoming Du
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Bhim Adhikari
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Heather Bruce
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Stephanie Hare
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Eric Goldwaser
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Mark Kvarta
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Junchao Huang
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, People's Republic of China
| | - Jinghui Tong
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, People's Republic of China
| | - Yimin Cui
- Department of Pharmacy, Peking University First Hospital, Beijing, China
| | - Baopeng Cao
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, People's Republic of China
| | - Yunlong Tan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, People's Republic of China
| | - L Elliot Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
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43
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Kalin NH. Gaining Ground on Schizophrenia: Conceptualizing How to Use Neuroimaging and Genomics in Its Diagnosis and Treatment. Am J Psychiatry 2019; 176:771-773. [PMID: 31569991 DOI: 10.1176/appi.ajp.2019.19080828] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Ned H Kalin
- Department of Psychiatry, University of Wisconsin School of Medicine and Public Health, Madison
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