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Guo J, He C, Song H, Gao H, Yao S, Dong SS, Yang TL. Unveiling Promising Neuroimaging Biomarkers for Schizophrenia Through Clinical and Genetic Perspectives. Neurosci Bull 2024:10.1007/s12264-024-01214-1. [PMID: 38703276 DOI: 10.1007/s12264-024-01214-1] [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: 07/14/2023] [Accepted: 01/08/2024] [Indexed: 05/06/2024] Open
Abstract
Schizophrenia is a complex and serious brain disorder. Neuroscientists have become increasingly interested in using magnetic resonance-based brain imaging-derived phenotypes (IDPs) to investigate the etiology of psychiatric disorders. IDPs capture valuable clinical advantages and hold biological significance in identifying brain abnormalities. In this review, we aim to discuss current and prospective approaches to identify potential biomarkers for schizophrenia using clinical multimodal neuroimaging and imaging genetics. We first described IDPs through their phenotypic classification and neuroimaging genomics. Secondly, we discussed the applications of multimodal neuroimaging by clinical evidence in observational studies and randomized controlled trials. Thirdly, considering the genetic evidence of IDPs, we discussed how can utilize neuroimaging data as an intermediate phenotype to make association inferences by polygenic risk scores and Mendelian randomization. Finally, we discussed machine learning as an optimum approach for validating biomarkers. Together, future research efforts focused on neuroimaging biomarkers aim to enhance our understanding of schizophrenia.
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Affiliation(s)
- Jing Guo
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, China
| | - Changyi He
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, China
| | - Huimiao Song
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, China
| | - Huiwu Gao
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, China
| | - Shi Yao
- Guangdong Key Laboratory of Age-Related Cardiac and Cerebral Diseases, Affiliated Hospital of Guangdong Medical University, Zhanjiang, 524000, China
| | - Shan-Shan Dong
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, China.
| | - Tie-Lin Yang
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, China.
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2
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Prognostic associations of cortical gyrification in minimally medicated schizophrenia in an early intervention setting. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2022; 8:88. [PMID: 36309534 PMCID: PMC9617870 DOI: 10.1038/s41537-022-00296-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Accepted: 10/03/2022] [Indexed: 12/03/2022]
Abstract
The aberration in cortical gyrification seen in schizophrenia likely originates in the earliest phase of life, as gyrification begins in utero and reaches its peak in infancy. However, emerging observations have indicated a later reduction in gyrification, especially in early adulthood, may also occur in schizophrenia. At present, it is unclear whether the baseline and later gyrification reduction has any prognostic importance in schizophrenia. We address this question in a longitudinal design in patients minimally medicated at inception. About 108 minimally medicated (duration of medication = <14 days of antipsychotics) patients and 106 healthy controls underwent structural magnetic resonance imaging, with 34 patients being selectively re-scanned when clinically stable following antipsychotic treatment. The cortical surface from each structural image was reconstructed, and the local gyrification index and cortical thickness were computed for each vertex on the surface. We found minimally medicated schizophrenia patients during the first episode had a relatively higher gyrification in bilateral supramarginal, left superior temporal, and right posterior cingulate and paracentral regions. However, poor prognostic features were more likely in patients with lower baseline gyrification. Longitudinal reductions in left superior parietal and right precentral gyrification were associated with lower improvements in both positive and negative symptoms over time. The spatial pattern of longitudinal changes in gyrification was distinct from the changes in cortical thickness. These results indicated that schizophrenia is characterized by a relative hypergyrification in parieto-temporal and medial cortical areas at a group level at first presentation, but poor outcomes relate to lower-gyrification elsewhere both at the onset and during the early course. The early post-onset reduction of gyrification is rather limited in space and magnitude, but occurs unrelated to the progressive thinning, representing a distinct, prognostically important structural trajectory.
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3
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Wang M, Hu K, Fan L, Yan H, Li P, Jiang T, Liu B. Predicting Treatment Response in Schizophrenia With Magnetic Resonance Imaging and Polygenic Risk Score. Front Genet 2022; 13:848205. [PMID: 35186051 PMCID: PMC8847599 DOI: 10.3389/fgene.2022.848205] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Accepted: 01/12/2022] [Indexed: 11/15/2022] Open
Abstract
Background: Prior studies have separately demonstrated that magnetic resonance imaging (MRI) and schizophrenia polygenic risk score (PRS) are predictive of antipsychotic medication treatment outcomes in schizophrenia. However, it remains unclear whether MRI combined with PRS can provide superior prognostic performance. Besides, the relative importance of these measures in predictions is not investigated. Methods: We collected 57 patients with schizophrenia, all of which had baseline MRI and genotype data. All these patients received approximately 6 weeks of antipsychotic medication treatment. Psychotic symptom severity was assessed using the Positive and Negative Syndrome Scale (PANSS) at baseline and follow-up. We divided these patients into responders (N = 20) or non-responders (N = 37) based on whether their percentages of PANSS total reduction were above or below 50%. Nine categories of MRI measures and PRSs with 145 different p-value thresholding ranges were calculated. We trained machine learning classifiers with these baseline predictors to identify whether a patient was a responder or non-responder. Results: The extreme gradient boosting (XGBoost) technique was applied to build binary classifiers. Using a leave-one-out cross-validation scheme, we achieved an accuracy of 86% with all MRI and PRS features. Other metrics were also estimated, including sensitivity (85%), specificity (86%), F1-score (81%), and area under the receiver operating characteristic curve (0.86). We found excluding a single feature category of gray matter volume (GMV), amplitude of low-frequency fluctuation (ALFF), and surface curvature could lead to a maximum accuracy drop of 10.5%. These three categories contributed more than half of the top 10 important features. Besides, removing PRS features caused a modest accuracy drop (8.8%), which was not the least decrease (1.8%) among all feature categories. Conclusions: Our classifier using both MRI and PRS features was stable and not biased to predicting either responder or non-responder. Combining with MRI measures, PRS could provide certain extra predictive power of antipsychotic medication treatment outcomes in schizophrenia. PRS exhibited medium importance in predictions, lower than GMV, ALFF, and surface curvature, but higher than measures of cortical thickness, cortical volume, and surface sulcal depth. Our findings inform the contributions of PRS in predictions of treatment outcomes in schizophrenia.
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Affiliation(s)
- Meng Wang
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China
| | - Ke Hu
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China
| | - Lingzhong Fan
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China.,Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
| | - Hao Yan
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China.,Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing, China
| | - Peng Li
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China.,Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing, China
| | - Tianzi Jiang
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China.,Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China.,Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.,Innovation Academy for Artificial Intelligence, Chinese Academy of Sciences, Beijing, China
| | - Bing Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.,Chinese Institute for Brain Research, Beijing, China
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4
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Jiang R, Calhoun VD, Cui Y, Qi S, Zhuo C, Li J, Jung R, Yang J, Du Y, Jiang T, Sui J. Multimodal data revealed different neurobiological correlates of intelligence between males and females. Brain Imaging Behav 2021; 14:1979-1993. [PMID: 31278651 DOI: 10.1007/s11682-019-00146-z] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Intelligence is a socially and scientifically interesting topic because of its prominence in human behavior, yet there is little clarity on how the neuroimaging and neurobiological correlates of intelligence differ between males and females, with most investigations limited to using either mass-univariate techniques or a single neuroimaging modality. Here we employed connectome-based predictive modeling (CPM) to predict the intelligence quotient (IQ) scores for 166 males and 160 females separately, using resting-state functional connectivity, grey matter cortical thickness or both. The identified multimodal, IQ-predictive imaging features were then compared between genders. CPM showed high out-of-sample prediction accuracy (r > 0.34), and integrating both functional and structural features further improved prediction accuracy by capturing complementary information (r = 0.45). Male IQ demonstrated higher correlations with cortical thickness in the left inferior parietal lobule, and with functional connectivity in left parahippocampus and default mode network, regions previously implicated in spatial cognition and logical thinking. In contrast, female IQ was more correlated with cortical thickness in the right inferior parietal lobule, and with functional connectivity in putamen and cerebellar networks, regions previously implicated in verbal learning and item memory. Results suggest that the intelligence generation of males and females may rely on opposite cerebral lateralized key brain regions and distinct functional networks consistent with their respective superiority in cognitive domains. Promisingly, understanding the neural basis of gender differences underlying intelligence may potentially lead to optimized personal cognitive developmental programs and facilitate advancements in unbiased educational test design.
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Affiliation(s)
- Rongtao Jiang
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China.,University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Vince D Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, 30303, USA
| | - Yue Cui
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China.,University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Shile Qi
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, 30303, USA
| | - Chuanjun Zhuo
- Department of Psychiatric-Neuroimaging-Genetics and Morbidity Laboratory (PNGC-Lab), Tianjin Mental Health Center, Nankai University Affiliated Anding Hospital, Tianjin, 300222, China
| | - Jin Li
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China.,University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Rex Jung
- Department of Psychiatry and Neurosciences, University of New Mexico, Albuquerque, NM, 87131, USA
| | - Jian Yang
- Beijing Engineering Research Center of Mixed Reality and Advanced Display, School of Optics and Electronics, Beijing Institute of Technology, Beijing, 100081, China
| | - Yuhui Du
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, 30303, USA
| | - Tianzi Jiang
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China.,University of Chinese Academy of Sciences, Beijing, 100049, China.,University of Electronic Science and Technology of China, Chengdu, 610054, China.,Chinese Academy of Sciences Center for Excellence in Brain Science, Institute of Automation, Beijing, 100190, China
| | - Jing Sui
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China. .,University of Chinese Academy of Sciences, Beijing, 100049, China. .,Chinese Academy of Sciences Center for Excellence in Brain Science, Institute of Automation, Beijing, 100190, China.
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5
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Ren Z, Liu C, Meng J, Liu Q, Shi L, Wu X, Song L, Qiu J. Effects of the Openness to Experience Polygenic Score on Cortical Thickness and Functional Connectivity. Front Neurosci 2021; 14:607912. [PMID: 33505240 PMCID: PMC7829912 DOI: 10.3389/fnins.2020.607912] [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: 09/18/2020] [Accepted: 12/09/2020] [Indexed: 11/16/2022] Open
Abstract
Openness to experience (OTE) has relatively stable and heritable characteristics. Previous studies have used candidate gene approaches to explore the genetic mechanisms of OTE, but genome-wide polygenic scores have a greater genetic effect than other genetic analysis methods, and previous studies have never examined the potential effect of OTE on this cumulative effect at the level of the brain mechanism. In the present study, we aim to explore the associations between polygenic scores (PGSs) of OTE and brain structure and functions. First, the results of PGSs of OTE at seven different thresholds were calculated in a large Chinese sample (N = 586). Then, we determined the associations between PGSs of OTE and cortical thickness and functional connectivity. The results showed that PGSs of OTE was negatively correlated with the thickness of the fusiform gyrus, and PGSs of OTE were negatively associated with the functional connectivity between the left intraparietal sulcus (IPS) and the right posterior occipital lobe. These findings may suggest that the brain structure of fusiform gyrus and brain functions of IPS and posterior occipital lobe are partly regulated by OTE-related genetic factors.
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Affiliation(s)
- Zhiting Ren
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China
- Faculty of Psychology, Southwest University (SWU), Chongqing, China
| | - Cheng Liu
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China
- Faculty of Psychology, Southwest University (SWU), Chongqing, China
| | - Jie Meng
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China
- Faculty of Psychology, Southwest University (SWU), Chongqing, China
| | - Qiang Liu
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China
- Faculty of Psychology, Southwest University (SWU), Chongqing, China
| | - Liang Shi
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China
- Faculty of Psychology, Southwest University (SWU), Chongqing, China
| | - Xinran Wu
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China
- Faculty of Psychology, Southwest University (SWU), Chongqing, China
| | - Li Song
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China
- Faculty of Psychology, Southwest University (SWU), Chongqing, China
| | - Jiang Qiu
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China
- Faculty of Psychology, Southwest University (SWU), Chongqing, China
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6
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Evermann U, Gaser C, Besteher B, Langbein K, Nenadić I. Cortical Gyrification, Psychotic-Like Experiences, and Cognitive Performance in Nonclinical Subjects. Schizophr Bull 2020; 46:1524-1534. [PMID: 32691058 PMCID: PMC7707080 DOI: 10.1093/schbul/sbaa068] [Citation(s) in RCA: 8] [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: 01/04/2023]
Abstract
BACKGROUND Psychotic-like experiences (PLE) are present in nonclinical populations, yet their association with brain structural variation, especially markers of early neurodevelopment, is poorly understood. We tested the hypothesis that cortical surface gyrification, a putative marker of early brain development, is associated with PLE in healthy subjects. METHODS We analyzed gyrification from 3 Tesla MRI scans (using CAT12 software) and PLE (positive, negative, and depressive symptom dimensions derived from the Community Assessment of Psychic Experiences, CAPE) in 103 healthy participants (49 females, mean age 29.13 ± 9.37 years). A subsample of 63 individuals completed tasks from the Wechsler Adult Intelligence Scale and Controlled Oral Word Association Test. Estimated IQ and a composite neuropsychological score were used to explore mediation pathways via cognition. RESULTS Positive PLE distress was negatively associated with gyrification of the left precuneus. PLE depression dimension showed a negative association with gyrification in the right supramarginal and temporal region. There was no significant mediating effect of cognition on these associations. CONCLUSION Our results support a neurobiological psychosis spectrum, for the first time linking an early developmental imaging marker (rather than volume) to dimensional subclinical psychotic symptoms. While schizophrenia risk, neurodevelopment, and cognitive function might share genetic risk factors, additional mediation analyses did not confirm a mediating effect of cognition on the gyrification-psychopathology correlation.
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Affiliation(s)
- Ulrika Evermann
- Cognitive Neuropsychiatry Lab, Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| | - Christian Gaser
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
- Department of Neurology, Jena University Hospital, Jena, Germany
| | - Bianca Besteher
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
| | - Kerstin Langbein
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
| | - Igor Nenadić
- Cognitive Neuropsychiatry Lab, Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
- Marburg University Hospital – UKGM, Marburg, Germany
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7
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Li H, Zhang C, Cai X, Wang L, Luo F, Ma Y, Li M, Xiao X. Genome-wide Association Study of Creativity Reveals Genetic Overlap With Psychiatric Disorders, Risk Tolerance, and Risky Behaviors. Schizophr Bull 2020; 46:1317-1326. [PMID: 32133506 PMCID: PMC7505179 DOI: 10.1093/schbul/sbaa025] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Creativity represents one of the most important and partially heritable human characteristics, yet little is known about its genetic basis. Epidemiological studies reveal associations between creativity and psychiatric disorders as well as multiple personality and behavioral traits. To test whether creativity and these disorders or traits share genetic basis, we performed genome-wide association studies (GWAS) followed by polygenic risk score (PRS) analyses. Two cohorts of Han Chinese subjects (4,834 individuals in total) aged 18-45 were recruited for creativity measurement using typical performance test. After exclusion of the outliers with significantly deviated creativity scores and low-quality genotyping results, 4,664 participants were proceeded for GWAS. We conducted PRS analyses using both the classical pruning and thresholding (P+T) method and the LDpred method. The extent of polygenic risk was estimated through linear regression adjusting for the top 3 genotyping principal components. R2 was used as a measurement of the explained variance. PRS analyses demonstrated significantly positive genetic overlap, respectively, between creativity with schizophrenia ((P+T) method: R2(max) ~ .196%, P = .00245; LDpred method: R2(max) ~ .226%, P = .00114), depression ((P+T) method: R2(max) ~ .178%, P = .00389; LDpred method: R2(max) ~ .093%, P = .03675), general risk tolerance ((P+T) method: R2(max) ~ .177%, P = .00399; LDpred method: R2(max) ~ .305%, P = .00016), and risky behaviors ((P+T) method: R2(max) ~ .187%, P = .00307; LDpred method: R2(max) ~ .155%, P = .00715). Our results suggest that human creativity is probably a polygenic trait affected by numerous variations with tiny effects. Genetic variations that predispose to psychiatric disorders and risky behaviors may underlie part of the genetic basis of creativity, confirming the epidemiological associations between creativity and these traits.
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Affiliation(s)
- Huijuan Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Chuyi Zhang
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Xin Cai
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Lu Wang
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Fang Luo
- Faculty of Psychology, Beijing Normal University, Beijing, China
| | - Yina Ma
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Ming Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Xiao Xiao
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
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8
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Sun J, Yan W, Zhang XN, Lin X, Li H, Gong YM, Zhu XM, Zheng YB, Guo XY, Ma YD, Liu ZY, Liu L, Gao JH, Vitiello MV, Chang SH, Liu XG, Lu L. Polygenic evidence and overlapped brain functional connectivities for the association between chronic pain and sleep disturbance. Transl Psychiatry 2020; 10:252. [PMID: 32709872 PMCID: PMC7381677 DOI: 10.1038/s41398-020-00941-z] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Revised: 07/08/2020] [Accepted: 07/15/2020] [Indexed: 12/12/2022] Open
Abstract
Chronic pain and sleep disturbance are highly comorbid disorders, which leads to barriers to treatment and significant healthcare costs. Understanding the underlying genetic and neural mechanisms of the interplay between sleep disturbance and chronic pain is likely to lead to better treatment. In this study, we combined 1206 participants with phenotype data, resting-state functional magnetic resonance imaging (rfMRI) data and genotype data from the Human Connectome Project and two large sample size genome-wide association studies (GWASs) summary data from published studies to identify the genetic and neural bases for the association between pain and sleep disturbance. Pittsburgh sleep quality index (PSQI) score was used for sleep disturbance, pain intensity was measured by Pain Intensity Survey. The result showed chronic pain was significantly correlated with sleep disturbance (r = 0.171, p-value < 0.001). Their genetic correlation was rg = 0.598 using linkage disequilibrium (LD) score regression analysis. Polygenic score (PGS) association analysis showed PGS of chronic pain was significantly associated with sleep and vice versa. Nine shared functional connectivity (FCs) were identified involving prefrontal cortex, temporal cortex, precentral/postcentral cortex, anterior cingulate cortex, fusiform gyrus and hippocampus. All these FCs mediated the effect of sleep disturbance on pain and seven FCs mediated the effect of pain on sleep disturbance. The chronic pain PGS was positively associated with the FC between middle temporal gyrus and hippocampus, which further mediated the effect of chronic pain PGS on PSQI score. Mendelian randomization analysis implied a possible causal relationship from chronic pain to sleep disturbance was stronger than that of sleep disturbance to chronic pain. The results provided genetic and neural evidence for the association between pain and sleep disturbance, which may inform future treatment approaches for comorbid chronic pain states and sleep disturbance.
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Affiliation(s)
- Jie Sun
- grid.411642.40000 0004 0605 3760Center for Pain Medicine, Peking University Third Hospital, Beijing, 100191 China ,grid.11135.370000 0001 2256 9319Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191 China ,grid.411642.40000 0004 0605 3760Department of Anesthesiology, Peking University Third Hospital, Beijing, 100191 China
| | - Wei Yan
- grid.11135.370000 0001 2256 9319Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191 China
| | - Xing-Nan Zhang
- grid.11135.370000 0001 2256 9319Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191 China
| | - Xiao Lin
- grid.11135.370000 0001 2256 9319Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191 China
| | - Hui Li
- grid.11135.370000 0001 2256 9319Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191 China
| | - Yi-Miao Gong
- grid.11135.370000 0001 2256 9319Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191 China
| | - Xi-Mei Zhu
- grid.11135.370000 0001 2256 9319Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191 China
| | - Yong-Bo Zheng
- grid.11135.370000 0001 2256 9319Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191 China
| | - Xiang-Yang Guo
- grid.411642.40000 0004 0605 3760Department of Anesthesiology, Peking University Third Hospital, Beijing, 100191 China
| | - Yun-Dong Ma
- grid.11135.370000 0001 2256 9319Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191 China
| | - Zeng-Yi Liu
- grid.11135.370000 0001 2256 9319Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191 China
| | - Lin Liu
- grid.11135.370000 0001 2256 9319Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191 China
| | - Jia-Hong Gao
- grid.11135.370000 0001 2256 9319Center for MRI Research, Peking University, Beijing, 100871 China
| | - Michael V. Vitiello
- grid.34477.330000000122986657Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA 98195 USA
| | - Su-Hua Chang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China. .,Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China.
| | - Xiao-Guang Liu
- Center for Pain Medicine, Peking University Third Hospital, Beijing, 100191, China. .,Department of Orthopedics, Peking University Third Hospital, Beijing, 100191, China.
| | - Lin Lu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China. .,Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China.
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Płonka O, Krześniak A, Adamczyk P. Analysis of local gyrification index using a novel shape-adaptive kernel and the standard FreeSurfer spherical kernel - evidence from chronic schizophrenia outpatients. Heliyon 2020; 6:e04172. [PMID: 32551394 PMCID: PMC7287247 DOI: 10.1016/j.heliyon.2020.e04172] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2020] [Revised: 05/19/2020] [Accepted: 06/04/2020] [Indexed: 12/20/2022] Open
Abstract
Schizophrenia can be considered a brain disconnectivity condition related to aberrant neurodevelopment that causes alterations in the brain structure, including gyrification of the cortex. Literature findings on cortical folding are incoherent: they report hypogyria in the frontal, superior-parietal and temporal cortices, but also frontal hypergyria. This discrepancy in local gyrification index (LGI) results could be due to the commonly used spherical kernel (Freesurfer), which is a method of analysis that is still not spatially precise enough. In this study we would like to test the spatial accuracy of a novel method based on a shape-adaptive kernel (Cmorph). The analysis of differences in gyrification between chronic schizophrenia outpatients (n = 30) and healthy controls (n = 30) was conducted with two methods: Freesurfer LGI and Cmorph LGI. Widespread differences in the LGI between schizophrenia outpatients and healthy controls were found using both methods. Freesurfer showed hypogyria in the superior temporal gyrus and the right temporal pole; it also showed hypergyria in the rostral-middle-frontal cortex in schizophrenia outpatients. In comparison, Cmorph revealed that hypergyria is equally represented as hypogyria in orbitofrontal and central brain regions. The clusters from Cmorph were smaller and distributed more broadly, covering all lobes of the brain. The presented evidence from disrupted cortical folding in schizophrenia indicates that the shape-adaptive kernel approach has a potential to improve the knowledge on the disrupted cortical folding in schizophrenia; therefore, it could be a valuable tool for further investigation on big sample size.
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Affiliation(s)
- Olga Płonka
- Institute of Psychology, Jagiellonian University, Krakow, Poland
| | - Alicja Krześniak
- Institute of Psychology, Jagiellonian University, Krakow, Poland.,Laboratory of Brain Imaging, Nencki Institute of Experimental Biology, Warsaw, Poland
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Nelson EA, Kraguljac NV, White DM, Jindal RD, Shin AL, Lahti AC. A Prospective Longitudinal Investigation of Cortical Thickness and Gyrification in Schizophrenia. CANADIAN JOURNAL OF PSYCHIATRY. REVUE CANADIENNE DE PSYCHIATRIE 2020; 65:381-391. [PMID: 32022594 PMCID: PMC7265602 DOI: 10.1177/0706743720904598] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
BACKGROUND Cortical thickness (CT) and gyrification are complementary indices that assess different aspects of gray matter structural integrity. Both neurodevelopment insults and acute tissue response to antipsychotic medication could underlie the known heterogeneity of treatment response and are well-suited for interrogation into the relationship between gray matter morphometry and clinical outcomes in schizophrenia (SZ). METHODS Using a prospective design, we enrolled 34 unmedicated patients with SZ and 23 healthy controls. Patients were scanned at baseline and after a 6-week trial with risperidone. CT and local gyrification index (LGI) values were quantified from structural MRI scans using FreeSurfer 5.3. RESULTS We found reduced CT and LGI in patients compared to controls. Vertex-wise analyses demonstrated that hypogyrification was most prominent in the inferior frontal cortex, temporal cortex, insula, pre/postcentral gyri, temporoparietal junction, and the supramarginal gyrus. Baseline CT was predictive of subsequent response to antipsychotic treatment, and increase in CT after 6 weeks was correlated with greater symptom reductions. CONCLUSIONS In summary, we report evidence of reduced CT and LGI in unmedicated patients compared to controls, suggesting involvement of different aspects of gray matter morphometry in the pathophysiology of SZ. Importantly, we found that lower CT at baseline and greater increase of CT following 6 weeks of treatment with risperidone were associated with better clinical response. Our results suggest that cortical thinning may normalize as a result of a good response to antipsychotic medication, possibly by alleviating potential neurotoxic processes underlying gray matter deterioration.
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Affiliation(s)
- Eric A. Nelson
- Department of Psychology, University of Alabama at Birmingham, AL, USA
| | - Nina V. Kraguljac
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, AL, USA
| | - David M. White
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, AL, USA
| | - Ripu D. Jindal
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, AL, USA
- Birmingham Veteran Affairs Medical Center, AL, USA
| | - Ah L. Shin
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, AL, USA
| | - Adrienne C. Lahti
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, AL, USA
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11
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Drobinin V, Van Gestel H, Zwicker A, MacKenzie L, Cumby J, Patterson VC, Vallis EH, Campbell N, Hajek T, Helmick CA, Schmidt MH, Alda M, Bowen CV, Uher R. Psychotic symptoms are associated with lower cortical folding in youth at risk for mental illness. J Psychiatry Neurosci 2020; 45:125-133. [PMID: 31674733 PMCID: PMC7828904 DOI: 10.1503/jpn.180144] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Cortical folding is essential for healthy brain development. Previous studies have found regional reductions in cortical folding in adult patients with psychotic illness. It is unknown whether these neuroanatomical markers are present in youth with subclinical psychotic symptoms. METHODS We collected MRIs and examined the local gyrification index in a sample of 110 youth (mean age ± standard deviation 14.0 ± 3.7 yr; range 9–25 yr) with a family history of severe mental illness: 48 with psychotic symptoms and 62 without. Images were processed using the Human Connectome Pipeline and FreeSurfer. We tested for group differences in local gyrification index using mixed-effects generalized linear models controlling for age, sex and familial clustering. Sensitivity analysis further controlled for intracranial volume, IQ, and stimulant and cannabis use. RESULTS Youth with psychotic symptoms displayed an overall trend toward lower cortical folding across all brain regions. After adjusting for multiple comparisons and confounders, regional reductions were localized to the frontal and occipital lobes. Specifically, the medial (B = –0.42, pFDR = 0.04) and lateral (B = –0.39, pFDR = 0.04) orbitofrontal cortices as well as the cuneus (B = –0.47, pFDR = 0.03) and the pericalcarine (B = –0.45, pFDR = 0.03) and lingual (B = –0.38, pFDR = 0.04) gyri. LIMITATIONS Inference about developmental trajectories was limited by the cross-sectional data. CONCLUSION Psychotic symptoms in youth are associated with cortical folding deficits, even in the absence of psychotic illness. The current study helps clarify the neurodevelopmental basis of psychosis at an early stage, before medication, drug use and other confounds have had a persistent effect on the brain.
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Affiliation(s)
- Vladislav Drobinin
- From the Department of Medical Neuroscience, Dalhousie University, Halifax, NS, Canada (Drobinin, Schmidt, Uher); the Nova Scotia Health Authority, Halifax, NS (Drobinin, van Gestel, Zwicker, MacKenzie, Cumby, Patterson, Vallis, Campbell, Helmick, Alda, Bowen, Uher); the Department of Pathology, Dalhousie University, Halifax, NS (Zwicker, Uher); the Department of Psychology and Neuroscience, Dalhousie University, Halifax, NS (MacKenzie, Patterson, Uher); the Department of Psychiatry, Dalhousie University, Halifax, NS (Vallis, Helmick, Alda, Uher); the Department of Medicine, Dalhousie University, Halifax, NS (Campbell); and the Department of Diagnostic Radiology, Dalhousie University, Halifax, NS (Bowen)
| | - Holly Van Gestel
- From the Department of Medical Neuroscience, Dalhousie University, Halifax, NS, Canada (Drobinin, Schmidt, Uher); the Nova Scotia Health Authority, Halifax, NS (Drobinin, van Gestel, Zwicker, MacKenzie, Cumby, Patterson, Vallis, Campbell, Helmick, Alda, Bowen, Uher); the Department of Pathology, Dalhousie University, Halifax, NS (Zwicker, Uher); the Department of Psychology and Neuroscience, Dalhousie University, Halifax, NS (MacKenzie, Patterson, Uher); the Department of Psychiatry, Dalhousie University, Halifax, NS (Vallis, Helmick, Alda, Uher); the Department of Medicine, Dalhousie University, Halifax, NS (Campbell); and the Department of Diagnostic Radiology, Dalhousie University, Halifax, NS (Bowen)
| | - Alyson Zwicker
- From the Department of Medical Neuroscience, Dalhousie University, Halifax, NS, Canada (Drobinin, Schmidt, Uher); the Nova Scotia Health Authority, Halifax, NS (Drobinin, van Gestel, Zwicker, MacKenzie, Cumby, Patterson, Vallis, Campbell, Helmick, Alda, Bowen, Uher); the Department of Pathology, Dalhousie University, Halifax, NS (Zwicker, Uher); the Department of Psychology and Neuroscience, Dalhousie University, Halifax, NS (MacKenzie, Patterson, Uher); the Department of Psychiatry, Dalhousie University, Halifax, NS (Vallis, Helmick, Alda, Uher); the Department of Medicine, Dalhousie University, Halifax, NS (Campbell); and the Department of Diagnostic Radiology, Dalhousie University, Halifax, NS (Bowen)
| | - Lynn MacKenzie
- From the Department of Medical Neuroscience, Dalhousie University, Halifax, NS, Canada (Drobinin, Schmidt, Uher); the Nova Scotia Health Authority, Halifax, NS (Drobinin, van Gestel, Zwicker, MacKenzie, Cumby, Patterson, Vallis, Campbell, Helmick, Alda, Bowen, Uher); the Department of Pathology, Dalhousie University, Halifax, NS (Zwicker, Uher); the Department of Psychology and Neuroscience, Dalhousie University, Halifax, NS (MacKenzie, Patterson, Uher); the Department of Psychiatry, Dalhousie University, Halifax, NS (Vallis, Helmick, Alda, Uher); the Department of Medicine, Dalhousie University, Halifax, NS (Campbell); and the Department of Diagnostic Radiology, Dalhousie University, Halifax, NS (Bowen)
| | - Jill Cumby
- From the Department of Medical Neuroscience, Dalhousie University, Halifax, NS, Canada (Drobinin, Schmidt, Uher); the Nova Scotia Health Authority, Halifax, NS (Drobinin, van Gestel, Zwicker, MacKenzie, Cumby, Patterson, Vallis, Campbell, Helmick, Alda, Bowen, Uher); the Department of Pathology, Dalhousie University, Halifax, NS (Zwicker, Uher); the Department of Psychology and Neuroscience, Dalhousie University, Halifax, NS (MacKenzie, Patterson, Uher); the Department of Psychiatry, Dalhousie University, Halifax, NS (Vallis, Helmick, Alda, Uher); the Department of Medicine, Dalhousie University, Halifax, NS (Campbell); and the Department of Diagnostic Radiology, Dalhousie University, Halifax, NS (Bowen)
| | - Victoria C. Patterson
- From the Department of Medical Neuroscience, Dalhousie University, Halifax, NS, Canada (Drobinin, Schmidt, Uher); the Nova Scotia Health Authority, Halifax, NS (Drobinin, van Gestel, Zwicker, MacKenzie, Cumby, Patterson, Vallis, Campbell, Helmick, Alda, Bowen, Uher); the Department of Pathology, Dalhousie University, Halifax, NS (Zwicker, Uher); the Department of Psychology and Neuroscience, Dalhousie University, Halifax, NS (MacKenzie, Patterson, Uher); the Department of Psychiatry, Dalhousie University, Halifax, NS (Vallis, Helmick, Alda, Uher); the Department of Medicine, Dalhousie University, Halifax, NS (Campbell); and the Department of Diagnostic Radiology, Dalhousie University, Halifax, NS (Bowen)
| | - Emily Howes Vallis
- From the Department of Medical Neuroscience, Dalhousie University, Halifax, NS, Canada (Drobinin, Schmidt, Uher); the Nova Scotia Health Authority, Halifax, NS (Drobinin, van Gestel, Zwicker, MacKenzie, Cumby, Patterson, Vallis, Campbell, Helmick, Alda, Bowen, Uher); the Department of Pathology, Dalhousie University, Halifax, NS (Zwicker, Uher); the Department of Psychology and Neuroscience, Dalhousie University, Halifax, NS (MacKenzie, Patterson, Uher); the Department of Psychiatry, Dalhousie University, Halifax, NS (Vallis, Helmick, Alda, Uher); the Department of Medicine, Dalhousie University, Halifax, NS (Campbell); and the Department of Diagnostic Radiology, Dalhousie University, Halifax, NS (Bowen)
| | - Niamh Campbell
- From the Department of Medical Neuroscience, Dalhousie University, Halifax, NS, Canada (Drobinin, Schmidt, Uher); the Nova Scotia Health Authority, Halifax, NS (Drobinin, van Gestel, Zwicker, MacKenzie, Cumby, Patterson, Vallis, Campbell, Helmick, Alda, Bowen, Uher); the Department of Pathology, Dalhousie University, Halifax, NS (Zwicker, Uher); the Department of Psychology and Neuroscience, Dalhousie University, Halifax, NS (MacKenzie, Patterson, Uher); the Department of Psychiatry, Dalhousie University, Halifax, NS (Vallis, Helmick, Alda, Uher); the Department of Medicine, Dalhousie University, Halifax, NS (Campbell); and the Department of Diagnostic Radiology, Dalhousie University, Halifax, NS (Bowen)
| | - Tomas Hajek
- From the Department of Medical Neuroscience, Dalhousie University, Halifax, NS, Canada (Drobinin, Schmidt, Uher); the Nova Scotia Health Authority, Halifax, NS (Drobinin, van Gestel, Zwicker, MacKenzie, Cumby, Patterson, Vallis, Campbell, Helmick, Alda, Bowen, Uher); the Department of Pathology, Dalhousie University, Halifax, NS (Zwicker, Uher); the Department of Psychology and Neuroscience, Dalhousie University, Halifax, NS (MacKenzie, Patterson, Uher); the Department of Psychiatry, Dalhousie University, Halifax, NS (Vallis, Helmick, Alda, Uher); the Department of Medicine, Dalhousie University, Halifax, NS (Campbell); and the Department of Diagnostic Radiology, Dalhousie University, Halifax, NS (Bowen)
| | - Carl A. Helmick
- From the Department of Medical Neuroscience, Dalhousie University, Halifax, NS, Canada (Drobinin, Schmidt, Uher); the Nova Scotia Health Authority, Halifax, NS (Drobinin, van Gestel, Zwicker, MacKenzie, Cumby, Patterson, Vallis, Campbell, Helmick, Alda, Bowen, Uher); the Department of Pathology, Dalhousie University, Halifax, NS (Zwicker, Uher); the Department of Psychology and Neuroscience, Dalhousie University, Halifax, NS (MacKenzie, Patterson, Uher); the Department of Psychiatry, Dalhousie University, Halifax, NS (Vallis, Helmick, Alda, Uher); the Department of Medicine, Dalhousie University, Halifax, NS (Campbell); and the Department of Diagnostic Radiology, Dalhousie University, Halifax, NS (Bowen)
| | - Matthias H. Schmidt
- From the Department of Medical Neuroscience, Dalhousie University, Halifax, NS, Canada (Drobinin, Schmidt, Uher); the Nova Scotia Health Authority, Halifax, NS (Drobinin, van Gestel, Zwicker, MacKenzie, Cumby, Patterson, Vallis, Campbell, Helmick, Alda, Bowen, Uher); the Department of Pathology, Dalhousie University, Halifax, NS (Zwicker, Uher); the Department of Psychology and Neuroscience, Dalhousie University, Halifax, NS (MacKenzie, Patterson, Uher); the Department of Psychiatry, Dalhousie University, Halifax, NS (Vallis, Helmick, Alda, Uher); the Department of Medicine, Dalhousie University, Halifax, NS (Campbell); and the Department of Diagnostic Radiology, Dalhousie University, Halifax, NS (Bowen)
| | - Martin Alda
- From the Department of Medical Neuroscience, Dalhousie University, Halifax, NS, Canada (Drobinin, Schmidt, Uher); the Nova Scotia Health Authority, Halifax, NS (Drobinin, van Gestel, Zwicker, MacKenzie, Cumby, Patterson, Vallis, Campbell, Helmick, Alda, Bowen, Uher); the Department of Pathology, Dalhousie University, Halifax, NS (Zwicker, Uher); the Department of Psychology and Neuroscience, Dalhousie University, Halifax, NS (MacKenzie, Patterson, Uher); the Department of Psychiatry, Dalhousie University, Halifax, NS (Vallis, Helmick, Alda, Uher); the Department of Medicine, Dalhousie University, Halifax, NS (Campbell); and the Department of Diagnostic Radiology, Dalhousie University, Halifax, NS (Bowen)
| | - Chris V. Bowen
- From the Department of Medical Neuroscience, Dalhousie University, Halifax, NS, Canada (Drobinin, Schmidt, Uher); the Nova Scotia Health Authority, Halifax, NS (Drobinin, van Gestel, Zwicker, MacKenzie, Cumby, Patterson, Vallis, Campbell, Helmick, Alda, Bowen, Uher); the Department of Pathology, Dalhousie University, Halifax, NS (Zwicker, Uher); the Department of Psychology and Neuroscience, Dalhousie University, Halifax, NS (MacKenzie, Patterson, Uher); the Department of Psychiatry, Dalhousie University, Halifax, NS (Vallis, Helmick, Alda, Uher); the Department of Medicine, Dalhousie University, Halifax, NS (Campbell); and the Department of Diagnostic Radiology, Dalhousie University, Halifax, NS (Bowen)
| | - Rudolf Uher
- From the Department of Medical Neuroscience, Dalhousie University, Halifax, NS, Canada (Drobinin, Schmidt, Uher); the Nova Scotia Health Authority, Halifax, NS (Drobinin, van Gestel, Zwicker, MacKenzie, Cumby, Patterson, Vallis, Campbell, Helmick, Alda, Bowen, Uher); the Department of Pathology, Dalhousie University, Halifax, NS (Zwicker, Uher); the Department of Psychology and Neuroscience, Dalhousie University, Halifax, NS (MacKenzie, Patterson, Uher); the Department of Psychiatry, Dalhousie University, Halifax, NS (Vallis, Helmick, Alda, Uher); the Department of Medicine, Dalhousie University, Halifax, NS (Campbell); and the Department of Diagnostic Radiology, Dalhousie University, Halifax, NS (Bowen)
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12
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Alnæs D, Kaufmann T, van der Meer D, Córdova-Palomera A, Rokicki J, Moberget T, Bettella F, Agartz I, Barch DM, Bertolino A, Brandt CL, Cervenka S, Djurovic S, Doan NT, Eisenacher S, Fatouros-Bergman H, Flyckt L, Di Giorgio A, Haatveit B, Jönsson EG, Kirsch P, Lund MJ, Meyer-Lindenberg A, Pergola G, Schwarz E, Smeland OB, Quarto T, Zink M, Andreassen OA, Westlye LT. Brain Heterogeneity in Schizophrenia and Its Association With Polygenic Risk. JAMA Psychiatry 2019; 76:739-748. [PMID: 30969333 PMCID: PMC6583664 DOI: 10.1001/jamapsychiatry.2019.0257] [Citation(s) in RCA: 155] [Impact Index Per Article: 31.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/07/2018] [Accepted: 01/14/2019] [Indexed: 12/28/2022]
Abstract
Importance Between-individual variability in brain structure is determined by gene-environment interactions, possibly reflecting differential sensitivity to environmental and genetic perturbations. Magnetic resonance imaging (MRI) studies have revealed thinner cortices and smaller subcortical volumes in patients with schizophrenia. However, group-level comparisons may mask considerable within-group heterogeneity, which has largely remained unnoticed in the literature. Objectives To compare brain structural variability between individuals with schizophrenia and healthy controls and to test whether respective variability reflects the polygenic risk score (PRS) for schizophrenia in an independent sample of healthy controls. Design, Setting, and Participants This case-control and polygenic risk analysis compared MRI-derived cortical thickness and subcortical volumes between healthy controls and patients with schizophrenia across 16 cohorts and tested for associations between PRS and MRI features in a control cohort from the UK Biobank. Data were collected from October 27, 2004, through April 12, 2018, and analyzed from December 3, 2017, through August 1, 2018. Main Outcomes and Measures Mean and dispersion parameters were estimated using double generalized linear models. Vertex-wise analysis was used to assess cortical thickness, and regions-of-interest analyses were used to assess total cortical volume, total surface area, and white matter, subcortical, and hippocampal subfield volumes. Follow-up analyses included within-sample analysis, test of robustness of the PRS threshold, population covariates, outlier removal, and control for image quality. Results A comparison of 1151 patients with schizophrenia (mean [SD] age, 33.8 [10.6] years; 68.6% male [n = 790] and 31.4% female [n = 361]) with 2010 healthy controls (mean [SD] age, 32.6 [10.4] years; 56.0% male [n = 1126] and 44.0% female [n = 884]) revealed higher heterogeneity in schizophrenia for cortical thickness and area (t = 3.34), cortical (t = 3.24) and ventricle (t range, 3.15-5.78) volumes, and hippocampal subfields (t range, 2.32-3.55). In the UK Biobank sample of 12 490 participants (mean [SD] age, 55.9 [7.5] years; 48.2% male [n = 6025] and 51.8% female [n = 6465]), higher PRS was associated with thinner frontal and temporal cortices and smaller left CA2/3 (t = -3.00) but was not significantly associated with dispersion. Conclusions and Relevance This study suggests that schizophrenia is associated with substantial brain structural heterogeneity beyond the mean differences. These findings may reflect higher sensitivity to environmental and genetic perturbations in patients, supporting the heterogeneous nature of schizophrenia. A higher PRS was associated with thinner frontotemporal cortices and smaller hippocampal subfield volume, but not heterogeneity. This finding suggests that brain variability in schizophrenia results from interactions between environmental and genetic factors that are not captured by the PRS. Factors contributing to heterogeneity in frontotemporal cortices and hippocampus are key to furthering our understanding of how genetic and environmental factors shape brain biology in schizophrenia.
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Affiliation(s)
- Dag Alnæs
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Norway
| | - Tobias Kaufmann
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Norway
| | - Dennis van der Meer
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Norway
| | - Aldo Córdova-Palomera
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Norway
| | - Jaroslav Rokicki
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Norway
| | - Torgeir Moberget
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Norway
| | - Francesco Bettella
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Norway
| | - Ingrid Agartz
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Norway
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Deanna M. Barch
- Department of Psychological and Brain Sciences, Washington University in Saint Louis, St Louis, Missouri
| | - Alessandro Bertolino
- Psychiatric Neuroscience Group, Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Christine L. Brandt
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Norway
| | - Simon Cervenka
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Srdjan Djurovic
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Norway
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
| | - Nhat Trung Doan
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Norway
| | - Sarah Eisenacher
- Central Institute of Mental Health, University of Heidelberg, Mannheim, Germany
| | - Helena Fatouros-Bergman
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Lena Flyckt
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Annabella Di Giorgio
- Psychiatric Neuroscience Group, Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
- Fondazione Istituto di Ricovero e Cura a Carattere Scientifico Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
| | - Beathe Haatveit
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Norway
| | - Erik G. Jönsson
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Norway
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Peter Kirsch
- Central Institute of Mental Health, University of Heidelberg, Mannheim, Germany
- Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Martina J. Lund
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Norway
| | - Andreas Meyer-Lindenberg
- Central Institute of Mental Health, University of Heidelberg, Mannheim, Germany
- Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Giulio Pergola
- Psychiatric Neuroscience Group, Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Emanuel Schwarz
- Central Institute of Mental Health, University of Heidelberg, Mannheim, Germany
| | - Olav B. Smeland
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Norway
| | - Tiziana Quarto
- Psychiatric Neuroscience Group, Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Mathias Zink
- Central Institute of Mental Health, University of Heidelberg, Mannheim, Germany
| | - Ole A. Andreassen
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Norway
| | - Lars T. Westlye
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
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13
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Mikhael SS, Pernet C. A controlled comparison of thickness, volume and surface areas from multiple cortical parcellation packages. BMC Bioinformatics 2019; 20:55. [PMID: 30691385 PMCID: PMC6348615 DOI: 10.1186/s12859-019-2609-8] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2018] [Accepted: 01/04/2019] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Cortical parcellation is an essential neuroimaging tool for identifying and characterizing morphometric and connectivity brain changes occurring with age and disease. A variety of software packages have been developed for parcellating the brain's cortical surface into a variable number of regions but interpackage differences can undermine reproducibility. Using a ground truth dataset (Edinburgh_NIH10), we investigated such differences for grey matter thickness (GMth), grey matter volume (GMvol) and white matter surface area (WMsa) for the superior frontal gyrus (SFG), supramarginal gyrus (SMG), and cingulate gyrus (CG) from 4 parcellation protocols as implemented in the FreeSurfer, BrainSuite, and BrainGyrusMapping (BGM) software packages. RESULTS Corresponding gyral definitions and morphometry approaches were not identical across the packages. As expected, there were differences in the bordering landmarks of each gyrus as well as in the manner in which variability was addressed. Rostral and caudal SFG and SMG boundaries differed, and in the event of a double CG occurrence, its upper fold was not always addressed. This led to a knock-on effect that was visible at the neighbouring gyri (e.g., knock-on effect at the SFG following CG definition) as well as gyral morphometric measurements of the affected gyri. Statistical analysis showed that the most consistent approaches were FreeSurfer's Desikan-Killiany-Tourville (DKT) protocol for GMth and BrainGyrusMapping for GMvol. Package consistency varied for WMsa, depending on the region of interest. CONCLUSIONS Given the significance and implications that a parcellation protocol will have on the classification, and sometimes treatment, of subjects, it is essential to select the protocol which accurately represents their regions of interest and corresponding morphometrics, while embracing cortical variability.
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Affiliation(s)
- Shadia S. Mikhael
- University of Edinburgh, Centre for Clinical Brain Sciences (CCBS), The Chancellor’s Building, 49 Little France Crescent, Edinburgh, EH16 4SB UK
| | - Cyril Pernet
- University of Edinburgh, Centre for Clinical Brain Sciences (CCBS), The Chancellor’s Building, 49 Little France Crescent, Edinburgh, EH16 4SB UK
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14
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Fonville L, Drakesmith M, Zammit S, Lewis G, Jones DK, David AS. MRI Indices of Cortical Development in Young People With Psychotic Experiences: Influence of Genetic Risk and Persistence of Symptoms. Schizophr Bull 2019; 45:169-179. [PMID: 29385604 PMCID: PMC6293214 DOI: 10.1093/schbul/sbx195] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Background Psychotic experiences (PEs) are considered part of an extended psychosis phenotype and are associated with an elevated risk of developing a psychotic disorder. Risk of transition increases with persistence of PEs, and this is thought to be modulated by genetic and environmental factors. However, it is unclear if persistence is associated with progressive schizophrenia-like changes in neuroanatomy. Methods We examined cortical morphometry using MRI in 247 young adults, from a population-based cohort, assessed for the presence of PEs at ages 18 and 20. We then incorporated a polygenic risk score for schizophrenia (PRS) to elucidate the effects of high genetic risk. Finally, we used atlas-based tractography data to examine the underlying white matter. Results Individuals with persisting PEs showed reductions in gyrification (local gyrification index: lGI) in the left temporal gyrus as well as atypical associations with brain volume (TBV) in the left occipital and right prefrontal gyri. No main effect was found for the PRS, but interaction effects with PEs were identified in the orbitofrontal, parietal, and temporal regions. Examination of underlying white matter did not provide strong evidence of further disturbances. Conclusions Disturbances in lGI were similar to schizophrenia but findings were mostly limited to those with persistent PEs. These could reflect subtle changes that worsen with impending psychosis or reflect an early vulnerability associated with the persistence of PEs. The lack of clear differences in underlying white matter suggests our findings reflect early disturbances in cortical expansion rather than progressive changes in brain structure.
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Affiliation(s)
- Leon Fonville
- Section of Cognitive Neuropsychiatry (Box 68), Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King ’s College London, UK
| | - Mark Drakesmith
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK
- Institute of Psychological Medicine and Clinical Neuroscience, School of Medicine, Cardiff University, Cardiff, UK
| | - Stanley Zammit
- Institute of Psychological Medicine and Clinical Neuroscience, School of Medicine, Cardiff University, Cardiff, UK
- Centre for Academic Mental Health, School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Glyn Lewis
- Division of Psychiatry, Faculty of Brain Sciences, University College London, London, UK
| | - Derek K Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK
- Institute of Psychological Medicine and Clinical Neuroscience, School of Medicine, Cardiff University, Cardiff, UK
| | - Anthony S David
- Section of Cognitive Neuropsychiatry (Box 68), Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King ’s College London, UK
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15
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Quezada S, Castillo-Melendez M, Walker DW, Tolcos M. Development of the cerebral cortex and the effect of the intrauterine environment. J Physiol 2018; 596:5665-5674. [PMID: 30325048 DOI: 10.1113/jp277151] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2018] [Accepted: 10/02/2018] [Indexed: 12/31/2022] Open
Abstract
The human brain is one of the most complex structures currently under study. Its external shape is highly convoluted, with folds and valleys over the entire surface of the cortex. Disruption of the normal pattern of folding is associated with a number of abnormal neurological outcomes, some serious for the individual. Most of our knowledge of the normal development and folding of the cerebral cortex (gyrification) focuses on the internal, biological (i.e. genetically driven) mechanisms of the brain that drive gyrification. However, the impact of an adverse intrauterine and maternal physiological environment on cortical folding during fetal development has been understudied. Accumulating evidence suggests that the state of the intrauterine and maternal environment can have a significant impact on gyrification of the fetal cerebral cortex. This review summarises our current knowledge of how development in a suboptimal intrauterine and maternal environment can affect the normal development of the folded cerebral cortex.
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Affiliation(s)
- Sebastian Quezada
- Monash University, Wellington Rd, Clayton, Melbourne, Australia, 3168.,The Ritchie Centre, Hudson Institute of Medical Research, 27-31 Wright St, Clayton, Melbourne, Australia, 3168
| | - Margie Castillo-Melendez
- Monash University, Wellington Rd, Clayton, Melbourne, Australia, 3168.,The Ritchie Centre, Hudson Institute of Medical Research, 27-31 Wright St, Clayton, Melbourne, Australia, 3168
| | - David W Walker
- School of Health & Biomedical Sciences, RMIT University, Plenty Rd., Bundoora, Melbourne, Australia, 3083
| | - Mary Tolcos
- School of Health & Biomedical Sciences, RMIT University, Plenty Rd., Bundoora, Melbourne, Australia, 3083
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16
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Luo N, Sui J, Chen J, Zhang F, Tian L, Lin D, Song M, Calhoun VD, Cui Y, Vergara VM, Zheng F, Liu J, Yang Z, Zuo N, Fan L, Xu K, Liu S, Li J, Xu Y, Liu S, Lv L, Chen J, Chen Y, Guo H, Li P, Lu L, Wan P, Wang H, Wang H, Yan H, Yan J, Yang Y, Zhang H, Zhang D, Jiang T. A Schizophrenia-Related Genetic-Brain-Cognition Pathway Revealed in a Large Chinese Population. EBioMedicine 2018; 37:471-482. [PMID: 30341038 PMCID: PMC6284414 DOI: 10.1016/j.ebiom.2018.10.009] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2018] [Revised: 09/23/2018] [Accepted: 10/02/2018] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND In the past decades, substantial effort has been made to explore the genetic influence on brain structural/functional abnormalities in schizophrenia, as well as cognitive impairments. In this work, we aimed to extend previous studies to explore the internal mediation pathway among genetic factor, brain features and cognitive scores in a large Chinese dataset. METHODS Gray matter (GM) volume, fractional amplitude of low-frequency fluctuations (fALFF), and 4522 schizophrenia-susceptible single nucleotide polymorphisms (SNP) from 905 Chinese subjects were jointly analyzed, to investigate the multimodal association. Based on the identified imaging-genetic pattern, correlations with cognition and mediation analysis were then conducted to reveal the potential mediation pathways. FINDINGS One linked imaging-genetic pattern was identified to be group discriminative, which was also associated with working memory performance. Particularly, GM reduction in thalamus, putamen and bilateral temporal gyrus in schizophrenia was associated with fALFF decrease in medial prefrontal cortex, both were also associated with genetic factors enriched in neuron development, synapse organization and axon pathways, highlighting genes including CSMD1, CNTNAP2, DCC, GABBR2 etc. This linked pattern was also replicated in an independent cohort (166 subjects), which although showed certain age and clinical differences with the discovery cohort. A further mediation analysis suggested that GM alterations significantly mediated the association from SNP to fALFF, while fALFF mediated the association from SNP and GM to working memory performance. INTERPRETATION This study has not only verified the impaired imaging-genetic association in schizophrenia, but also initially revealed a potential genetic-brain-cognition mediation pathway, indicating that polygenic risk factors could exert impact on phenotypic measures from brain structure to function, thus could further affect cognition in schizophrenia.
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Affiliation(s)
- Na Luo
- Brainnetome Center and National Laboratory of Pattern Recognition, Chinese Academy of Sciences, Institute of Automation, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jing Sui
- Brainnetome Center and National Laboratory of Pattern Recognition, Chinese Academy of Sciences, Institute of Automation, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China; The Mind Research Network & LBERI, Albuquerque, NM 87106, USA; CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Institute of Automation, Beijing 100190, China.
| | - Jiayu Chen
- The Mind Research Network & LBERI, Albuquerque, NM 87106, USA
| | | | - Lin Tian
- Wuxi Mental Health Center, Wuxi 214000, China
| | - Dongdong Lin
- The Mind Research Network & LBERI, Albuquerque, NM 87106, USA
| | - Ming Song
- Brainnetome Center and National Laboratory of Pattern Recognition, Chinese Academy of Sciences, Institute of Automation, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Vince D Calhoun
- The Mind Research Network & LBERI, Albuquerque, NM 87106, USA; Department of Electrical and Computer Engineer, The University of New, Albuquerque, NM 87131, USA
| | - Yue Cui
- Brainnetome Center and National Laboratory of Pattern Recognition, Chinese Academy of Sciences, Institute of Automation, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | | | - Fanfan Zheng
- Brainnetome Center and National Laboratory of Pattern Recognition, Chinese Academy of Sciences, Institute of Automation, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jingyu Liu
- The Mind Research Network & LBERI, Albuquerque, NM 87106, USA
| | - Zhenyi Yang
- Brainnetome Center and National Laboratory of Pattern Recognition, Chinese Academy of Sciences, Institute of Automation, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Nianming Zuo
- Brainnetome Center and National Laboratory of Pattern Recognition, Chinese Academy of Sciences, Institute of Automation, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Lingzhong Fan
- Brainnetome Center and National Laboratory of Pattern Recognition, Chinese Academy of Sciences, Institute of Automation, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Kaibin Xu
- Brainnetome Center and National Laboratory of Pattern Recognition, Chinese Academy of Sciences, Institute of Automation, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Shengfeng Liu
- Brainnetome Center and National Laboratory of Pattern Recognition, Chinese Academy of Sciences, Institute of Automation, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jian Li
- Brainnetome Center and National Laboratory of Pattern Recognition, Chinese Academy of Sciences, Institute of Automation, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yong Xu
- Department of Psychiatry, First Clinical Medical College, First Hospital of Shanxi Medical University, Taiyuan 030000, China
| | - Sha Liu
- Department of Psychiatry, First Clinical Medical College, First Hospital of Shanxi Medical University, Taiyuan 030000, China
| | - Luxian Lv
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang 453002, China; Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang 453002, China
| | - Jun Chen
- Department of Radiology, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Yunchun Chen
- Department of Psychiatry, Xijing Hospital, The Fourth Military Medical University, Xi'an 710032, China
| | - Hua Guo
- Zhumadian Psychiatric Hospital, Zhumadian 463000, China
| | - Peng Li
- Institute of Mental Health, Peking University Sixth Hospital, Beijing 100191, China; Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing 100191, China
| | - Lin Lu
- Institute of Mental Health, Peking University Sixth Hospital, Beijing 100191, China; Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing 100191, China
| | - Ping Wan
- Zhumadian Psychiatric Hospital, Zhumadian 463000, China
| | - Huaning Wang
- Department of Psychiatry, Xijing Hospital, The Fourth Military Medical University, Xi'an 710032, China
| | - Huiling Wang
- Department of Radiology, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Hao Yan
- Institute of Mental Health, Peking University Sixth Hospital, Beijing 100191, China; Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing 100191, China
| | - Jun Yan
- Institute of Mental Health, Peking University Sixth Hospital, Beijing 100191, China; Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing 100191, China
| | - Yongfeng Yang
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang 453002, China; Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang 453002, China,; Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Hongxing Zhang
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang 453002, China; Department of Psychology, Xinxiang Medical University, Xinxiang 453002, China
| | - Dai Zhang
- Institute of Mental Health, Peking University Sixth Hospital, Beijing 100191, China; Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing 100191, China; Center for Life Sciences, PKU-IDG, McGovern Institute for Brain Research, Peking University, Beijing 100871, China
| | - Tianzi Jiang
- Brainnetome Center and National Laboratory of Pattern Recognition, Chinese Academy of Sciences, Institute of Automation, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China; Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China; Queensland Brain Institute, University of Queensland, Brisbane, QLD 4072, Australia; CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Institute of Automation, Beijing 100190, China.
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17
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Avramopoulos D. Recent Advances in the Genetics of Schizophrenia. MOLECULAR NEUROPSYCHIATRY 2018; 4:35-51. [PMID: 29998117 PMCID: PMC6032037 DOI: 10.1159/000488679] [Citation(s) in RCA: 65] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2017] [Accepted: 03/21/2018] [Indexed: 12/27/2022]
Abstract
The last decade brought tremendous progress in the field of schizophrenia genetics. As a result of extensive collaborations and multiple technological advances, we now recognize many types of genetic variants that increase the risk. These include large copy number variants, rare coding inherited and de novο variants, and over 100 loci harboring common risk variants. While the type and contribution to the risk vary among genetic variants, there is concordance in the functions of genes they implicate, such as those whose RNA binds the fragile X-related protein FMRP and members of the activity-regulated cytoskeletal complex involved in learning and memory. Gene expression studies add important information on the biology of the disease and recapitulate the same functional gene groups. Studies of alternative phenotypes help us widen our understanding of the genetic architecture of mental function and dysfunction, how diseases overlap not only with each other but also with non-disease phenotypes. The challenge is to apply this new knowledge to prevention and treatment and help patients. The data generated so far and emerging technologies, including new methods in cell engineering, offer significant promise that in the next decade we will unlock the translational potential of these significant discoveries.
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Affiliation(s)
- Dimitrios Avramopoulos
- Institute of Genetic Medicine, Johns Hopkins University, Baltimore, Maryland, USA
- Department of Psychiatry, Johns Hopkins University, Baltimore, Maryland, USA
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18
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Bogdan R, Baranger DAA, Agrawal A. Polygenic Risk Scores in Clinical Psychology: Bridging Genomic Risk to Individual Differences. Annu Rev Clin Psychol 2018; 14:119-157. [PMID: 29579395 PMCID: PMC7772939 DOI: 10.1146/annurev-clinpsy-050817-084847] [Citation(s) in RCA: 90] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Genomewide association studies (GWASs) across psychiatric phenotypes have shown that common genetic variants generally confer risk with small effect sizes (odds ratio < 1.1) that additively contribute to polygenic risk. Summary statistics derived from large discovery GWASs can be used to generate polygenic risk scores (PRS) in independent, target data sets to examine correlates of polygenic disorder liability (e.g., does genetic liability to schizophrenia predict cognition?). The intuitive appeal and generalizability of PRS have led to their widespread use and new insights into mechanisms of polygenic liability. However, when currently applied across traits they account for small amounts of variance (<3%), are relatively uninformative for clinical treatment, and, in isolation, provide no insight into molecular mechanisms. Larger GWASs are needed to increase the precision of PRS, and novel approaches integrating various data sources (e.g., multitrait analysis of GWASs) may improve the utility of current PRS.
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Affiliation(s)
- Ryan Bogdan
- BRAINLab, Department of Psychological and Brain Sciences, and Division of Biology and Biomedical Sciences, Washington University in St. Louis, St. Louis, Missouri 63110, USA;
| | - David A A Baranger
- BRAINLab, Department of Psychological and Brain Sciences, and Division of Biology and Biomedical Sciences, Washington University in St. Louis, St. Louis, Missouri 63110, USA;
| | - Arpana Agrawal
- Department of Psychiatry, Washington University in St. Louis School of Medicine, St. Louis, Missouri 63110, USA
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19
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Abstract
The cerebral cortex of the human brain has a complex morphological structure consisting of folded or smooth cortical surfaces. These morphological features are referred to as cortical gyrification and are characterized by the gyrification index (GI). A number of cortical gyrification studies have been published using the manual tracing GI, automated GI, and local GI in patients with schizophrenia. In this review, we highlighted abnormal cortical gyrification in patients with schizophrenia, first-episode schizophrenia, siblings of patients, and high-risk and at-risk individuals. Previous researches also indicated that abnormalities in cortical gyrification may underlie the severity of clinical symptoms, neurological soft signs, and executive functions. A substantial body of research has been conducted; however, some researches showed an increased GI, which is called as "hypergyria," and others showed a decreased GI, which is called as "hypogyria." We discussed that different GI methods and a wide variety of characteristics, such as age, sex, stage, and severity of illness, might be important reasons for the conflicting findings. These issues still need to be considered, and future studies should address them.
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Affiliation(s)
- Yukihisa Matsuda
- Faculty of Pharmacy and Pharmaceutical Sciences, Fukuyama University, Hiroshima, Japan
| | - Kazutaka Ohi
- Department of Neuropsychiatry, Kanazawa Medical University, Ishikawa, Japan, .,Medical Research Institute, Kanazawa Medical University, Ishikawa, Japan,
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20
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Yue W, Yu X, Zhang D. Progress in genome-wide association studies of schizophrenia in Han Chinese populations. NPJ SCHIZOPHRENIA 2017; 3:24. [PMID: 28798405 PMCID: PMC5552785 DOI: 10.1038/s41537-017-0029-1] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/01/2017] [Revised: 04/29/2017] [Accepted: 05/03/2017] [Indexed: 01/01/2023]
Abstract
Since 2006, genome-wide association studies of schizophrenia have led to the identification of numerous novel risk loci for this disease. However, there remains a geographical imbalance in genome-wide association studies, which to date have primarily focused on Western populations. During the last 6 years, genome-wide association studies in Han Chinese populations have identified both the sharing of susceptible loci across ethnicities and genes unique to Han Chinese populations. Here, we review recent progress in genome-wide association studies of schizophrenia in Han Chinese populations. Researchers have identified and replicated the sharing of susceptible genes, such as within the major histocompatibility complex, microRNA 137 (MIR137), zinc finger protein 804A (ZNF804A), vaccinia related kinase 2 (VRK2), and arsenite methyltransferase (AS3MT), across both European and East Asian populations. Several copy number variations identified in European populations have also been validated in the Han Chinese, including duplications at 16p11.2, 15q11.2-13.1, 7q11.23, and VIPR2 and deletions at 22q11.2, 1q21.1-q21.2, and NRXN1. However, these studies have identified some potential confounding factors, such as genetic heterogeneity and the effects of natural selection on tetraspanin 18 (TSPAN18) or zinc finger protein 323 (ZNF323), which may explain the population differences in genome-wide association studies. In the future, genome-wide association studies in Han Chinese populations should include meta-analyzes or mega-analyses with enlarged sample sizes across populations, deep sequencing, precision medicine treatment, and functional exploration of the risk genes for schizophrenia.
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Affiliation(s)
- Weihua Yue
- Institute of Mental Health, the Sixth Hospital, Peking University, 100191, Beijing, China.
- Key Laboratory of Mental Health, Ministry of Health & National Clinical Research Center for Mental Disorders (Peking University), 100191, Beijing, China.
| | - Xin Yu
- Institute of Mental Health, the Sixth Hospital, Peking University, 100191, Beijing, China
- Key Laboratory of Mental Health, Ministry of Health & National Clinical Research Center for Mental Disorders (Peking University), 100191, Beijing, China
| | - Dai Zhang
- Institute of Mental Health, the Sixth Hospital, Peking University, 100191, Beijing, China
- Key Laboratory of Mental Health, Ministry of Health & National Clinical Research Center for Mental Disorders (Peking University), 100191, Beijing, China
- Peking-Tsinghua Joint Center for Life Sciences & PKU-IDG/McGovern Institute for Brain Research, Peking University, 100871, Beijing, China
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21
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Chung YS, Hyatt CJ, Stevens MC. Adolescent maturation of the relationship between cortical gyrification and cognitive ability. Neuroimage 2017; 158:319-331. [PMID: 28676299 DOI: 10.1016/j.neuroimage.2017.06.082] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2017] [Revised: 06/12/2017] [Accepted: 06/30/2017] [Indexed: 12/31/2022] Open
Abstract
There are changes to the degree of cortical folding from gestation through adolescence into young adulthood. Recent evidence suggests that degree of cortical folding is linked to individual differences in general cognitive ability in healthy adults. However, it is not yet known whether age-related cortical folding changes are related to maturation of specific cognitive abilities in adolescence. To address this, we examined the relationship between frontoparietal cortical folding as measured by a Freesurfer-derived local gyrification index (lGI) and performance on subtests from the Wechsler Abbreviated Scale of Intelligence and scores from Conner's Continuous Performance Test-II in 241 healthy adolescents (ages 12-25 years). We hypothesized that age-related lGI changes in the frontoparietal cortex would contribute to cognitive development. A secondary goal was to explore if any gyrification-cognition relationships were either test-specific or sex-specific. Consistent with previous studies, our results showed a reduction of frontoparietal local gyrification with age. Also, as predicted, all cognitive test scores (i.e., Vocabulary, Matrix Reasoning, the CPT-II Commission, Omission, Variabiltiy, d') showed age × cognitive ability interaction effects in frontoparietal and temporoparietal brain regions. Mediation analyses confirmed a causal role of age-related cortical folding changes only for CPT-II Commission errors. Taken together, the results support the functional significance of cortical folding, as well as provide the first evidence that cortical folding maturational changes play a role in cognitive development.
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Affiliation(s)
- Yu Sun Chung
- Clinical Neuroscience and Development Laboratory, Olin Neuropsychiatry Research Center, 200 Retreat Avenue, Whitehall Building, Institute of Living, Hartford, CT 06106, USA
| | - Christopher J Hyatt
- Clinical Neuroscience and Development Laboratory, Olin Neuropsychiatry Research Center, 200 Retreat Avenue, Whitehall Building, Institute of Living, Hartford, CT 06106, USA
| | - Michael C Stevens
- Clinical Neuroscience and Development Laboratory, Olin Neuropsychiatry Research Center, 200 Retreat Avenue, Whitehall Building, Institute of Living, Hartford, CT 06106, USA; Department of Psychiatry, Yale University School of Medicine, 300 George St., Suite 901, New Haven, CT 06511, USA.
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22
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Effects of environmental risks and polygenic loading for schizophrenia on cortical thickness. Schizophr Res 2017; 184:128-136. [PMID: 27989645 DOI: 10.1016/j.schres.2016.12.011] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/14/2016] [Revised: 12/09/2016] [Accepted: 12/11/2016] [Indexed: 01/21/2023]
Abstract
There are established differences in cortical thickness (CT) in schizophrenia (SCZ) and bipolar (BD) patients when compared to healthy controls (HC). However, it is unknown to what extent environmental or genetic risk factors impact on CT in these populations. We have investigated the effect of Environmental Risk Scores (ERS) and Polygenic Risk Scores for SCZ (PGRS-SCZ) on CT. Structural MRI scans were acquired at 3T for patients with SCZ or BD (n=57) and controls (n=41). Cortical reconstructions were generated in FreeSurfer (v5.3). The ERS was created by determining exposure to cannabis use, childhood adverse events, migration, urbanicity and obstetric complications. The PGRS-SCZ were generated, for a subset of the sample (Patients=43, HC=32), based on the latest PGC GWAS findings. ANCOVAs were used to test the hypotheses that ERS and PGRS-SCZ relate to CT globally, and in frontal and temporal lobes. An increase in ERS was negatively associated with CT within temporal lobe for patients. A higher PGRS-SCZ was also related to global cortical thinning for patients. ERS effects remained significant when including PGRS-SCZ as a fixed effect. No relationship which survived FDR correction was found for ERS and PGRS-SCZ in controls. Environmental risk for SCZ was related to localised cortical thinning in patients with SCZ and BD, while increased PGRS-SCZ was associated with global cortical thinning. Genetic and environmental risk factors for SCZ appear therefore to have differential effects. This provides a mechanistic means by which different risk factors may contribute to the development of SCZ and BD.
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23
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Ritchie SJ, Tucker-Drob EM, Cox SR, Dickie DA, Del C Valdés Hernández M, Corley J, Royle NA, Redmond P, Muñoz Maniega S, Pattie A, Aribisala BS, Taylor AM, Clarke TK, Gow AJ, Starr JM, Bastin ME, Wardlaw JM, Deary IJ. Risk and protective factors for structural brain ageing in the eighth decade of life. Brain Struct Funct 2017; 222:3477-3490. [PMID: 28424895 PMCID: PMC5676817 DOI: 10.1007/s00429-017-1414-2] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2016] [Accepted: 03/27/2017] [Indexed: 11/06/2022]
Abstract
Individuals differ markedly in brain structure, and in how this structure degenerates during ageing. In a large sample of human participants (baseline n = 731 at age 73 years; follow-up n = 488 at age 76 years), we estimated the magnitude of mean change and variability in changes in MRI measures of brain macrostructure (grey matter, white matter, and white matter hyperintensity volumes) and microstructure (fractional anisotropy and mean diffusivity from diffusion tensor MRI). All indices showed significant average change with age, with considerable heterogeneity in those changes. We then tested eleven socioeconomic, physical, health, cognitive, allostatic (inflammatory and metabolic), and genetic variables for their value in predicting these differences in changes. Many of these variables were significantly correlated with baseline brain structure, but few could account for significant portions of the heterogeneity in subsequent brain change. Physical fitness was an exception, being correlated both with brain level and changes. The results suggest that only a subset of correlates of brain structure are also predictive of differences in brain ageing.
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Affiliation(s)
- Stuart J Ritchie
- Department of Psychology, The University of Edinburgh, Edinburgh, UK. .,Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, Edinburgh, UK.
| | | | - Simon R Cox
- Department of Psychology, The University of Edinburgh, Edinburgh, UK.,Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, Edinburgh, UK
| | - David Alexander Dickie
- Brain Research Imaging Centre, The University of Edinburgh, Edinburgh, UK.,Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK.,Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
| | - Maria Del C Valdés Hernández
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, Edinburgh, UK.,Brain Research Imaging Centre, The University of Edinburgh, Edinburgh, UK.,Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK.,Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
| | - Janie Corley
- Department of Psychology, The University of Edinburgh, Edinburgh, UK.,Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, Edinburgh, UK
| | - Natalie A Royle
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, Edinburgh, UK.,Brain Research Imaging Centre, The University of Edinburgh, Edinburgh, UK.,Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK.,Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
| | - Paul Redmond
- Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - Susana Muñoz Maniega
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, Edinburgh, UK.,Brain Research Imaging Centre, The University of Edinburgh, Edinburgh, UK.,Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK.,Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
| | - Alison Pattie
- Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - Benjamin S Aribisala
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, Edinburgh, UK.,Brain Research Imaging Centre, The University of Edinburgh, Edinburgh, UK.,Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK.,Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK.,Computer Science Department, Faculty of Science, Lagos State University, Lagos, Nigeria
| | - Adele M Taylor
- Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - Toni-Kim Clarke
- Division of Psychiatry, The University of Edinburgh, Edinburgh, UK
| | - Alan J Gow
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, Edinburgh, UK.,Department of Psychology, Heriot-Watt University, Edinburgh, UK
| | - John M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, Edinburgh, UK.,Alzheimer Scotland Dementia Research Centre, The University of Edinburgh, Edinburgh, UK
| | - Mark E Bastin
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, Edinburgh, UK.,Brain Research Imaging Centre, The University of Edinburgh, Edinburgh, UK.,Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK.,Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
| | - Joanna M Wardlaw
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, Edinburgh, UK.,Brain Research Imaging Centre, The University of Edinburgh, Edinburgh, UK.,Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK.,Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
| | - Ian J Deary
- Department of Psychology, The University of Edinburgh, Edinburgh, UK.,Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, Edinburgh, UK
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24
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Polygenic risk for five psychiatric disorders and cross-disorder and disorder-specific neural connectivity in two independent populations. NEUROIMAGE-CLINICAL 2017; 14:441-449. [PMID: 28275544 PMCID: PMC5328751 DOI: 10.1016/j.nicl.2017.02.011] [Citation(s) in RCA: 47] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/05/2016] [Revised: 02/10/2017] [Accepted: 02/11/2017] [Indexed: 12/21/2022]
Abstract
Major psychiatric disorders, including attention deficit hyperactivity disorder (ADHD), autism (AUT), bipolar disorder (BD), major depressive disorder (MDD), and schizophrenia (SZ), are highly heritable and polygenic. Evidence suggests that these five disorders have both shared and distinct genetic risks and neural connectivity abnormalities. To measure aggregate genetic risks, the polygenic risk score (PGRS) was computed. Two independent general populations (N = 360 and N = 323) were separately examined to investigate whether the cross-disorder PGRS and PGRS for a specific disorder were associated with individual variability in functional connectivity. Consistent altered functional connectivity was found with the bilateral insula: for the left supplementary motor area and the left superior temporal gyrus with the cross-disorder PGRS, for the left insula and right middle and superior temporal lobe associated with the PGRS for autism, for the bilateral midbrain, posterior cingulate, cuneus, and precuneus associated with the PGRS for BD, and for the left angular gyrus and the left dorsolateral prefrontal cortex associated with the PGRS for schizophrenia. No significant functional connectivity was found associated with the PGRS for ADHD and MDD. Our findings indicated that genetic effects on the cross-disorder and disorder-specific neural connectivity of common genetic risk loci are detectable in the general population. Our findings also indicated that polygenic risk contributes to the main neurobiological phenotypes of psychiatric disorders and that identifying cross-disorder and specific functional connectivity related to polygenic risks may elucidate the neural pathways for these disorders. Altered cross-disorder functional connectivity related to PGRSs is detected. Altered disorder-specific functional connectivity related to PGRSs is detected. Altered functional connectivity related to PGRSs is involved in brain networks. Polygenic risk contributes to neurobiological phenotypes of psychiatric disorders.
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25
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Reus LM, Shen X, Gibson J, Wigmore E, Ligthart L, Adams MJ, Davies G, Cox SR, Hagenaars SP, Bastin ME, Deary IJ, Whalley HC, McIntosh AM. Association of polygenic risk for major psychiatric illness with subcortical volumes and white matter integrity in UK Biobank. Sci Rep 2017; 7:42140. [PMID: 28186152 PMCID: PMC5301496 DOI: 10.1038/srep42140] [Citation(s) in RCA: 54] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2016] [Accepted: 01/03/2017] [Indexed: 12/11/2022] Open
Abstract
Major depressive disorder (MDD), schizophrenia (SCZ) and bipolar disorder (BP) are common, disabling and heritable psychiatric diseases with a complex overlapping polygenic architecture. Individuals with these disorders, as well as their unaffected relatives, show widespread structural differences in corticostriatal and limbic networks. Structural variation in many of these brain regions is also heritable and polygenic but whether their genetic architecture overlaps with that of major psychiatric disorders is unknown. We sought to address this issue by examining the impact of polygenic risk of MDD, SCZ, and BP on subcortical brain volumes and white matter (WM) microstructure in a large single sample of neuroimaging data; the UK Biobank Imaging study. The first release of UK Biobank imaging data comprised participants with overlapping genetic data and subcortical volumes (N = 978) and WM measures (N = 816). The calculation of polygenic risk scores was based on genome-wide association study results generated by the Psychiatric Genomics Consortium. Our findings indicated no statistically significant associations between either subcortical volumes or WM microstructure, and polygenic risk for MDD, SCZ or BP. These findings suggest that subcortical brain volumes and WM microstructure may not be closely linked to the genetic mechanisms of major psychiatric disorders.
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Affiliation(s)
- L. M. Reus
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, United Kingdom
| | - X. Shen
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, United Kingdom
| | - J. Gibson
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, United Kingdom
| | - E. Wigmore
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, United Kingdom
| | - L. Ligthart
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, the Netherlands
| | - M. J. Adams
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, United Kingdom
| | - G. Davies
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, United Kingdom
| | - S. R. Cox
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, United Kingdom
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, United Kingdom
| | - S. P. Hagenaars
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, United Kingdom
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, United Kingdom
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, United Kingdom
| | - M. E. Bastin
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, United Kingdom
| | - I. J. Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, United Kingdom
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, United Kingdom
| | - H. C. Whalley
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, United Kingdom
| | - A. M. McIntosh
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, United Kingdom
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, United Kingdom
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26
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Neurogenetics of developmental dyslexia: from genes to behavior through brain neuroimaging and cognitive and sensorial mechanisms. Transl Psychiatry 2017; 7:e987. [PMID: 28045463 PMCID: PMC5545717 DOI: 10.1038/tp.2016.240] [Citation(s) in RCA: 60] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/13/2016] [Accepted: 10/15/2016] [Indexed: 01/18/2023] Open
Abstract
Developmental dyslexia (DD) is a complex neurodevelopmental deficit characterized by impaired reading acquisition, in spite of adequate neurological and sensorial conditions, educational opportunities and normal intelligence. Despite the successful characterization of DD-susceptibility genes, we are far from understanding the molecular etiological pathways underlying the development of reading (dis)ability. By focusing mainly on clinical phenotypes, the molecular genetics approach has yielded mixed results. More optimally reduced measures of functioning, that is, intermediate phenotypes (IPs), represent a target for researching disease-associated genetic variants and for elucidating the underlying mechanisms. Imaging data provide a viable IP for complex neurobehavioral disorders and have been extensively used to investigate both morphological, structural and functional brain abnormalities in DD. Performing joint genetic and neuroimaging studies in humans is an emerging strategy to link DD-candidate genes to the brain structure and function. A limited number of studies has already pursued the imaging-genetics integration in DD. However, the results are still not sufficient to unravel the complexity of the reading circuit due to heterogeneous study design and data processing. Here, we propose an interdisciplinary, multilevel, imaging-genetic approach to disentangle the pathways from genes to behavior. As the presence of putative functional genetic variants has been provided and as genetic associations with specific cognitive/sensorial mechanisms have been reported, new hypothesis-driven imaging-genetic studies must gain momentum. This approach would lead to the optimization of diagnostic criteria and to the early identification of 'biologically at-risk' children, supporting the definition of adequate and well-timed prevention strategies and the implementation of novel, specific remediation approach.
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