Pub Date : 2024-02-27DOI: 10.1038/s41537-024-00439-3
Kalyani B Karunakaran, Sanjeev Jain, Samir K Brahmachari, N Balakrishnan, Madhavi K Ganapathiraju
Genome-wide association studies suggest significant overlaps in Parkinson's disease (PD) and schizophrenia (SZ) risks, but the underlying mechanisms remain elusive. The protein-protein interaction network ('interactome') plays a crucial role in PD and SZ and can incorporate their spatiotemporal specificities. Therefore, to study the linked biology of PD and SZ, we compiled PD- and SZ-associated genes from the DisGeNET database, and constructed their interactomes using BioGRID and HPRD. We examined the interactomes using clustering and enrichment analyses, in conjunction with the transcriptomic data of 26 brain regions spanning foetal stages to adulthood available in the BrainSpan Atlas. PD and SZ interactomes formed four gene clusters with distinct temporal identities (Disease Gene Networks or 'DGNs'1-4). DGN1 had unique SZ interactome genes highly expressed across developmental stages, corresponding to a neurodevelopmental SZ subtype. DGN2, containing unique SZ interactome genes expressed from early infancy to adulthood, correlated with an inflammation-driven SZ subtype and adult SZ risk. DGN3 contained unique PD interactome genes expressed in late infancy, early and late childhood, and adulthood, and involved in mitochondrial pathways. DGN4, containing prenatally-expressed genes common to both the interactomes, involved in stem cell pluripotency and overlapping with the interactome of 22q11 deletion syndrome (comorbid psychosis and Parkinsonism), potentially regulates neurodevelopmental mechanisms in PD-SZ comorbidity. Our findings suggest that disrupted neurodevelopment (regulated by DGN4) could expose risk windows in PD and SZ, later elevating disease risk through inflammation (DGN2). Alternatively, variant clustering in DGNs may produce disease subtypes, e.g., PD-SZ comorbidity with DGN4, and early/late-onset SZ with DGN1/DGN2.
{"title":"Parkinson's disease and schizophrenia interactomes contain temporally distinct gene clusters underlying comorbid mechanisms and unique disease processes.","authors":"Kalyani B Karunakaran, Sanjeev Jain, Samir K Brahmachari, N Balakrishnan, Madhavi K Ganapathiraju","doi":"10.1038/s41537-024-00439-3","DOIUrl":"10.1038/s41537-024-00439-3","url":null,"abstract":"<p><p>Genome-wide association studies suggest significant overlaps in Parkinson's disease (PD) and schizophrenia (SZ) risks, but the underlying mechanisms remain elusive. The protein-protein interaction network ('interactome') plays a crucial role in PD and SZ and can incorporate their spatiotemporal specificities. Therefore, to study the linked biology of PD and SZ, we compiled PD- and SZ-associated genes from the DisGeNET database, and constructed their interactomes using BioGRID and HPRD. We examined the interactomes using clustering and enrichment analyses, in conjunction with the transcriptomic data of 26 brain regions spanning foetal stages to adulthood available in the BrainSpan Atlas. PD and SZ interactomes formed four gene clusters with distinct temporal identities (Disease Gene Networks or 'DGNs'1-4). DGN1 had unique SZ interactome genes highly expressed across developmental stages, corresponding to a neurodevelopmental SZ subtype. DGN2, containing unique SZ interactome genes expressed from early infancy to adulthood, correlated with an inflammation-driven SZ subtype and adult SZ risk. DGN3 contained unique PD interactome genes expressed in late infancy, early and late childhood, and adulthood, and involved in mitochondrial pathways. DGN4, containing prenatally-expressed genes common to both the interactomes, involved in stem cell pluripotency and overlapping with the interactome of 22q11 deletion syndrome (comorbid psychosis and Parkinsonism), potentially regulates neurodevelopmental mechanisms in PD-SZ comorbidity. Our findings suggest that disrupted neurodevelopment (regulated by DGN4) could expose risk windows in PD and SZ, later elevating disease risk through inflammation (DGN2). Alternatively, variant clustering in DGNs may produce disease subtypes, e.g., PD-SZ comorbidity with DGN4, and early/late-onset SZ with DGN1/DGN2.</p>","PeriodicalId":74758,"journal":{"name":"Schizophrenia (Heidelberg, Germany)","volume":"10 1","pages":"26"},"PeriodicalIF":0.0,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10899210/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139984807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-22DOI: 10.1038/s41537-024-00433-9
Yuan-Jung Chen, Mong-Liang Lu, Yi-Hang Chiu, Chenyi Chen, Vitor Hugo Jesus Santos, Kah Kheng Goh
Childhood trauma has been linked to schizophrenia, but underlying biological mechanisms remain elusive. This study explored the potential role of plasma oxytocin as a mediator in the relationship between childhood trauma and the psychopathology of schizophrenia. 160 patients with schizophrenia and 80 age- and sex-matched healthy controls were assessed for childhood trauma experiences using the Childhood Trauma Questionnaire and structured interviews. Psychopathology was evaluated using the Positive and Negative Syndrome Scale and plasma oxytocin levels were measured. Results showed that patients with schizophrenia had lower oxytocin levels and higher childhood trauma scores than healthy controls. There was a significant correlation between childhood trauma scores and psychopathology, with plasma oxytocin levels being inversely associated with psychopathology, except for positive symptoms. Hierarchical regression analysis indicated that both childhood trauma scores and plasma oxytocin levels significantly predicted psychopathology. Plasma oxytocin levels partially mediated the relationship between childhood trauma and schizophrenia psychopathology. This study underscores the potential role of oxytocin in bridging the gap between childhood trauma and schizophrenia.
{"title":"Linking childhood trauma to the psychopathology of schizophrenia: the role of oxytocin.","authors":"Yuan-Jung Chen, Mong-Liang Lu, Yi-Hang Chiu, Chenyi Chen, Vitor Hugo Jesus Santos, Kah Kheng Goh","doi":"10.1038/s41537-024-00433-9","DOIUrl":"10.1038/s41537-024-00433-9","url":null,"abstract":"<p><p>Childhood trauma has been linked to schizophrenia, but underlying biological mechanisms remain elusive. This study explored the potential role of plasma oxytocin as a mediator in the relationship between childhood trauma and the psychopathology of schizophrenia. 160 patients with schizophrenia and 80 age- and sex-matched healthy controls were assessed for childhood trauma experiences using the Childhood Trauma Questionnaire and structured interviews. Psychopathology was evaluated using the Positive and Negative Syndrome Scale and plasma oxytocin levels were measured. Results showed that patients with schizophrenia had lower oxytocin levels and higher childhood trauma scores than healthy controls. There was a significant correlation between childhood trauma scores and psychopathology, with plasma oxytocin levels being inversely associated with psychopathology, except for positive symptoms. Hierarchical regression analysis indicated that both childhood trauma scores and plasma oxytocin levels significantly predicted psychopathology. Plasma oxytocin levels partially mediated the relationship between childhood trauma and schizophrenia psychopathology. This study underscores the potential role of oxytocin in bridging the gap between childhood trauma and schizophrenia.</p>","PeriodicalId":74758,"journal":{"name":"Schizophrenia (Heidelberg, Germany)","volume":"10 1","pages":"24"},"PeriodicalIF":0.0,"publicationDate":"2024-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10883944/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139934599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Deficit schizophrenia (DS) is a subtype of schizophrenia (SCZ). The polygenic effects on the neuroimaging alterations in DS still remain unknown. This study aims to calculate the polygenic risk scores for schizophrenia (PRS-SCZ) in DS, and further explores the potential associations with functional features of brain. PRS-SCZ was calculated according to the Whole Exome sequencing and Genome-wide association studies (GWAS). Resting-state fMRI, as well as biochemical features and neurocognitive data were obtained from 33 DS, 47 NDS and 41 HCs, and association studies of genetic risk with neuroimaging were performed in this sample. The analyses of amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo) and functional connectivity (FC) were performed to detect the functional alterations between DS and NDS. In addition, correlation analysis was used to investigate the relationships between functional features (ALFF, ReHo, FC) and PRS-SCZ. The PRS-SCZ of DS was significantly lower than that in NDS and HC. Compared to NDS, there was a significant increase in the ALFF of left inferior temporal gyrus (ITG.L) and left inferior frontal gyrus (IFG.L) and a significant decrease in the ALFF of right precuneus (PCUN.R) and ReHo of right middle frontal gyrus (MFG.R) in DS. FCs were widely changed between DS and NDS, mainly concentrated in default mode network, including ITG, PCUN and angular gyrus (ANG). Correlation analysis revealed that the ALFF of left ITG, the ReHo of right middle frontal gyrus, the FC value between insula and ANG, left ITG and right corpus callosum, left ITG and right PCUN, as well as the scores of Trail Making Test-B, were associated with PRS-SCZ in DS. The present study demonstrated the differential polygenic effects on functional changes of brain in DS and NDS, providing a potential neuroimaging-genetic perspective for the pathogenesis of schizophrenia.
缺陷型精神分裂症(DS)是精神分裂症(SCZ)的一种亚型。多基因对缺陷型精神分裂症神经影像学改变的影响仍然未知。本研究旨在计算缺陷型精神分裂症的多基因风险评分(PRS-SCZ),并进一步探讨其与大脑功能特征的潜在关联。PRS-SCZ是根据全外显子组测序和全基因组关联研究(GWAS)计算得出的。研究获得了 33 名 DS、47 名 NDS 和 41 名 HC 的静息态 fMRI 以及生化特征和神经认知数据,并在这些样本中进行了遗传风险与神经影像学的关联研究。研究人员对低频波动幅度(ALFF)、区域同质性(ReHo)和功能连接性(FC)进行了分析,以检测DS和NDS之间的功能改变。此外,研究人员还使用相关性分析来探讨功能特征(ALFF、ReHo和FC)与PRS-SCZ之间的关系。DS的PRS-SCZ明显低于NDS和HC。与NDS相比,DS左侧颞下回(ITG.L)和左侧额下回(IFG.L)的ALFF显著增加,右侧楔前回(PCUN.R)的ALFF和右侧额中回(MFG.R)的ReHo显著减少。FCs在DS和NDS之间发生了广泛变化,主要集中在默认模式网络,包括ITG、PCUN和角回(ANG)。相关分析表明,左侧ITG的ALFF、右侧额中回的ReHo、脑岛与ANG、左侧ITG与右侧胼胝体、左侧ITG与右侧PCUN的FC值以及Trail Making Test-B的得分均与DS的PRS-SCZ相关。本研究证明了多基因对 DS 和 NDS 脑功能变化的不同影响,为精神分裂症的发病机制提供了一个潜在的神经影像遗传学视角。
{"title":"Polygenic effects on brain functional endophenotype for deficit and non-deficit schizophrenia.","authors":"Jin Fang, Yiding Lv, Yingying Xie, Xiaowei Tang, Xiaobin Zhang, Xiang Wang, Miao Yu, Chao Zhou, Wen Qin, Xiangrong Zhang","doi":"10.1038/s41537-024-00432-w","DOIUrl":"10.1038/s41537-024-00432-w","url":null,"abstract":"<p><p>Deficit schizophrenia (DS) is a subtype of schizophrenia (SCZ). The polygenic effects on the neuroimaging alterations in DS still remain unknown. This study aims to calculate the polygenic risk scores for schizophrenia (PRS-SCZ) in DS, and further explores the potential associations with functional features of brain. PRS-SCZ was calculated according to the Whole Exome sequencing and Genome-wide association studies (GWAS). Resting-state fMRI, as well as biochemical features and neurocognitive data were obtained from 33 DS, 47 NDS and 41 HCs, and association studies of genetic risk with neuroimaging were performed in this sample. The analyses of amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo) and functional connectivity (FC) were performed to detect the functional alterations between DS and NDS. In addition, correlation analysis was used to investigate the relationships between functional features (ALFF, ReHo, FC) and PRS-SCZ. The PRS-SCZ of DS was significantly lower than that in NDS and HC. Compared to NDS, there was a significant increase in the ALFF of left inferior temporal gyrus (ITG.L) and left inferior frontal gyrus (IFG.L) and a significant decrease in the ALFF of right precuneus (PCUN.R) and ReHo of right middle frontal gyrus (MFG.R) in DS. FCs were widely changed between DS and NDS, mainly concentrated in default mode network, including ITG, PCUN and angular gyrus (ANG). Correlation analysis revealed that the ALFF of left ITG, the ReHo of right middle frontal gyrus, the FC value between insula and ANG, left ITG and right corpus callosum, left ITG and right PCUN, as well as the scores of Trail Making Test-B, were associated with PRS-SCZ in DS. The present study demonstrated the differential polygenic effects on functional changes of brain in DS and NDS, providing a potential neuroimaging-genetic perspective for the pathogenesis of schizophrenia.</p>","PeriodicalId":74758,"journal":{"name":"Schizophrenia (Heidelberg, Germany)","volume":"10 1","pages":"18"},"PeriodicalIF":0.0,"publicationDate":"2024-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10873412/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139747936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-15DOI: 10.1038/s41537-024-00442-8
Stefan Leucht, Spyridon Siafis, Johannes Schneider-Thoma, Aran Tajika, Josef Priller, John M Davis, Toshi A Furukawa
A recent meta-epidemiological study did not reveal major differences between the results of blinded and open randomised-controlled trials (RCTs). Fewer patients may consent to double-blind RCTs than to open RCTs, compromising generalisability, making this question very important. However, the issue has not been addressed in schizophrenia. We used a database of randomised, acute-phase antipsychotic drug trials. Whenever at least one open and one blinded RCT was available for a comparison of two drugs, we contrasted the results by random-effects meta-analysis with subgroup tests. The primary outcome was overall symptoms as measured by the Positive and Negative Syndrome Scale, supplemented by seven secondary efficacy and side-effect outcomes. We also examined whether open RCTs were biased in favour of more recently introduced antipsychotics, less efficacious or more prone to side-effects antipsychotics, and pharmaceutical sponsors. 183 RCTs (155 blinded and 28 open) with 34715 participants comparing two active drugs were available. The results did not suggest general differences between open and blinded RCTs, which examined two active drugs. Only 12 out of 122 subgroup tests had a p-value below 0.1, four below 0.05, and if a Bonferroni correction for multiple tests had been applied, only one would have been significant. There were some exceptions which, however, did not always confirm the originally hypothesized direction of bias. Due to the relatively small number of open RCTs, our analysis is exploratory, but this fundamental question should be given more scientific attention. Currently, open RCTs should be excluded from meta-analyses, at least in sensitivity analyses.
{"title":"Are the results of open randomised controlled trials comparing antipsychotic drugs in schizophrenia biased? Exploratory meta- and subgroup analysis.","authors":"Stefan Leucht, Spyridon Siafis, Johannes Schneider-Thoma, Aran Tajika, Josef Priller, John M Davis, Toshi A Furukawa","doi":"10.1038/s41537-024-00442-8","DOIUrl":"10.1038/s41537-024-00442-8","url":null,"abstract":"<p><p>A recent meta-epidemiological study did not reveal major differences between the results of blinded and open randomised-controlled trials (RCTs). Fewer patients may consent to double-blind RCTs than to open RCTs, compromising generalisability, making this question very important. However, the issue has not been addressed in schizophrenia. We used a database of randomised, acute-phase antipsychotic drug trials. Whenever at least one open and one blinded RCT was available for a comparison of two drugs, we contrasted the results by random-effects meta-analysis with subgroup tests. The primary outcome was overall symptoms as measured by the Positive and Negative Syndrome Scale, supplemented by seven secondary efficacy and side-effect outcomes. We also examined whether open RCTs were biased in favour of more recently introduced antipsychotics, less efficacious or more prone to side-effects antipsychotics, and pharmaceutical sponsors. 183 RCTs (155 blinded and 28 open) with 34715 participants comparing two active drugs were available. The results did not suggest general differences between open and blinded RCTs, which examined two active drugs. Only 12 out of 122 subgroup tests had a p-value below 0.1, four below 0.05, and if a Bonferroni correction for multiple tests had been applied, only one would have been significant. There were some exceptions which, however, did not always confirm the originally hypothesized direction of bias. Due to the relatively small number of open RCTs, our analysis is exploratory, but this fundamental question should be given more scientific attention. Currently, open RCTs should be excluded from meta-analyses, at least in sensitivity analyses.</p>","PeriodicalId":74758,"journal":{"name":"Schizophrenia (Heidelberg, Germany)","volume":"10 1","pages":"17"},"PeriodicalIF":0.0,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10866997/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139736886","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Bipolar disorder (BD) showed the highest suicide rate of all psychiatric disorders, and its underlying causative genes and effective treatments remain unclear. During diagnosis, BD is often confused with schizophrenia (SC) and major depressive disorder (MDD), due to which patients may receive inadequate or inappropriate treatment, which is detrimental to their prognosis. This study aims to establish a diagnostic model to distinguish BD from SC and MDD in multiple public datasets through bioinformatics and machine learning and to provide new ideas for diagnosing BD in the future. Three brain tissue datasets containing BD, SC, and MDD were chosen from the Gene Expression Omnibus database (GEO), and two peripheral blood datasets were selected for validation. Linear Models for Microarray Data (Limma) analysis was carried out to identify differentially expressed genes (DEGs). Functional enrichment analysis and machine learning were utilized to identify. Least absolute shrinkage and selection operator (LASSO) regression was employed for identifying candidate immune-associated central genes, constructing protein-protein interaction networks (PPI), building artificial neural networks (ANN) for validation, and plotting receiver operating characteristic curve (ROC curve) for differentiating BD from SC and MDD and creating immune cell infiltration to study immune cell dysregulation in the three diseases. RBM10 was obtained as a candidate gene to distinguish BD from SC. Five candidate genes (LYPD1, HMBS, HEBP2, SETD3, and ECM2) were obtained to distinguish BD from MDD. The validation was performed by ANN, and ROC curves were plotted for diagnostic value assessment. The outcomes exhibited the prediction model to have a promising diagnostic value. In the immune infiltration analysis, Naive B, Resting NK, and Activated Mast Cells were found to be substantially different between BD and SC. Naive B and Memory B cells were prominently variant between BD and MDD. In this study, RBM10 was found as a candidate gene to distinguish BD from SC; LYPD1, HMBS, HEBP2, SETD3, and ECM2 serve as five candidate genes to distinguish BD from MDD. The results obtained from the ANN network showed that these candidate genes could perfectly distinguish BD from SC and MDD (76.923% and 81.538%, respectively).
{"title":"A diagnostic model based on bioinformatics and machine learning to differentiate bipolar disorder from schizophrenia and major depressive disorder.","authors":"Jing Shen, Chenxu Xiao, Xiwen Qiao, Qichen Zhu, Hanfei Yan, Julong Pan, Yu Feng","doi":"10.1038/s41537-023-00417-1","DOIUrl":"10.1038/s41537-023-00417-1","url":null,"abstract":"<p><p>Bipolar disorder (BD) showed the highest suicide rate of all psychiatric disorders, and its underlying causative genes and effective treatments remain unclear. During diagnosis, BD is often confused with schizophrenia (SC) and major depressive disorder (MDD), due to which patients may receive inadequate or inappropriate treatment, which is detrimental to their prognosis. This study aims to establish a diagnostic model to distinguish BD from SC and MDD in multiple public datasets through bioinformatics and machine learning and to provide new ideas for diagnosing BD in the future. Three brain tissue datasets containing BD, SC, and MDD were chosen from the Gene Expression Omnibus database (GEO), and two peripheral blood datasets were selected for validation. Linear Models for Microarray Data (Limma) analysis was carried out to identify differentially expressed genes (DEGs). Functional enrichment analysis and machine learning were utilized to identify. Least absolute shrinkage and selection operator (LASSO) regression was employed for identifying candidate immune-associated central genes, constructing protein-protein interaction networks (PPI), building artificial neural networks (ANN) for validation, and plotting receiver operating characteristic curve (ROC curve) for differentiating BD from SC and MDD and creating immune cell infiltration to study immune cell dysregulation in the three diseases. RBM10 was obtained as a candidate gene to distinguish BD from SC. Five candidate genes (LYPD1, HMBS, HEBP2, SETD3, and ECM2) were obtained to distinguish BD from MDD. The validation was performed by ANN, and ROC curves were plotted for diagnostic value assessment. The outcomes exhibited the prediction model to have a promising diagnostic value. In the immune infiltration analysis, Naive B, Resting NK, and Activated Mast Cells were found to be substantially different between BD and SC. Naive B and Memory B cells were prominently variant between BD and MDD. In this study, RBM10 was found as a candidate gene to distinguish BD from SC; LYPD1, HMBS, HEBP2, SETD3, and ECM2 serve as five candidate genes to distinguish BD from MDD. The results obtained from the ANN network showed that these candidate genes could perfectly distinguish BD from SC and MDD (76.923% and 81.538%, respectively).</p>","PeriodicalId":74758,"journal":{"name":"Schizophrenia (Heidelberg, Germany)","volume":"10 1","pages":"16"},"PeriodicalIF":3.0,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10866880/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139736885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-12DOI: 10.1038/s41537-024-00441-9
Alisa L A Schormann, Katja Butschbach, Tania M Lincoln, Marcel Riehle
We examined the association between causal attributions and self-reported motivational negative symptoms (amotivation) in a German online community sample (n = 251). Bivariate correlations revealed significant associations between amotivation and attribution of success to external, variable, and specific causes. No associations between amotivation and failure attributions were found. Our data suggest that demotivational causal attributions of success could be a feature of amotivation and a promising target for research and intervention.
{"title":"Dysfunctional attributions of success as a distinct feature of amotivation.","authors":"Alisa L A Schormann, Katja Butschbach, Tania M Lincoln, Marcel Riehle","doi":"10.1038/s41537-024-00441-9","DOIUrl":"10.1038/s41537-024-00441-9","url":null,"abstract":"<p><p>We examined the association between causal attributions and self-reported motivational negative symptoms (amotivation) in a German online community sample (n = 251). Bivariate correlations revealed significant associations between amotivation and attribution of success to external, variable, and specific causes. No associations between amotivation and failure attributions were found. Our data suggest that demotivational causal attributions of success could be a feature of amotivation and a promising target for research and intervention.</p>","PeriodicalId":74758,"journal":{"name":"Schizophrenia (Heidelberg, Germany)","volume":"10 1","pages":"15"},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10861587/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139725309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-10DOI: 10.1038/s41537-024-00440-w
Mahbod Ebrahimi, Kowsar Teymouri, Cheng C Chen, Ayeshah G Mohiuddin, Jennie G Pouget, Vanessa F Goncalves, Arun K Tiwari, Clement C Zai, James L Kennedy
Schizophrenia is a severe mental illness and a major risk factor for suicide, with approximately 50% of schizophrenia patients attempting and 10% dying from suicide. Although genetic components play a significant role in schizophrenia risk, the underlying genetic risk factors for suicide are poorly understood. The complement component C4 gene, an immune gene involved in the innate immune system and located in the major histocompatibility complex (MHC) region, has been identified to be strongly associated with schizophrenia risk. In addition, recent findings have also suggested that the MHC region has been associated with suicide risk across disorders, making C4 a potential candidate of interest for studying suicidality in schizophrenia patients. Despite growing interest in investigating the association between the C4 gene and schizophrenia, to our knowledge, no work has been done to examine the potential of C4 variants as suicide risk factors in patients with schizophrenia. In this study, we investigated the association between different C4 copy number variants and predicted C4 brain expression with suicidal outcomes (suicide attempts/suicidal ideation). We directly genotyped 434 schizophrenia patients to determine their C4A and C4B copy number variants. We found the C4AS copy number to be marginally and negatively associated with suicide risk, potentially being protective against suicide attempts (OR = 0.49; p = 0.05) and suicidal ideation (OR = 0.65; p = 0.07). Furthermore, sex-stratified analyses revealed that there are no significant differences between males and females. Our preliminary findings encourage additional studies of C4 and potential immune dysregulation in suicide.
{"title":"Association study of the complement component C4 gene and suicide risk in schizophrenia.","authors":"Mahbod Ebrahimi, Kowsar Teymouri, Cheng C Chen, Ayeshah G Mohiuddin, Jennie G Pouget, Vanessa F Goncalves, Arun K Tiwari, Clement C Zai, James L Kennedy","doi":"10.1038/s41537-024-00440-w","DOIUrl":"10.1038/s41537-024-00440-w","url":null,"abstract":"<p><p>Schizophrenia is a severe mental illness and a major risk factor for suicide, with approximately 50% of schizophrenia patients attempting and 10% dying from suicide. Although genetic components play a significant role in schizophrenia risk, the underlying genetic risk factors for suicide are poorly understood. The complement component C4 gene, an immune gene involved in the innate immune system and located in the major histocompatibility complex (MHC) region, has been identified to be strongly associated with schizophrenia risk. In addition, recent findings have also suggested that the MHC region has been associated with suicide risk across disorders, making C4 a potential candidate of interest for studying suicidality in schizophrenia patients. Despite growing interest in investigating the association between the C4 gene and schizophrenia, to our knowledge, no work has been done to examine the potential of C4 variants as suicide risk factors in patients with schizophrenia. In this study, we investigated the association between different C4 copy number variants and predicted C4 brain expression with suicidal outcomes (suicide attempts/suicidal ideation). We directly genotyped 434 schizophrenia patients to determine their C4A and C4B copy number variants. We found the C4AS copy number to be marginally and negatively associated with suicide risk, potentially being protective against suicide attempts (OR = 0.49; p = 0.05) and suicidal ideation (OR = 0.65; p = 0.07). Furthermore, sex-stratified analyses revealed that there are no significant differences between males and females. Our preliminary findings encourage additional studies of C4 and potential immune dysregulation in suicide.</p>","PeriodicalId":74758,"journal":{"name":"Schizophrenia (Heidelberg, Germany)","volume":"10 1","pages":"14"},"PeriodicalIF":0.0,"publicationDate":"2024-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10858919/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139716736","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-27DOI: 10.1038/s41537-024-00434-8
Naok Kang, Subin Chung, Sang-Hyuk Lee, Minji Bang
Although the role of the cerebellum in schizophrenia has gained attention, its contribution to cognitive impairment remains unclear. We aimed to investigate volumetric alterations in the cerebro-cerebellar gray matter (GM) in patients with recent-onset schizophrenia (ROS) and chronic schizophrenia (CS) compared with healthy controls (HCs). Seventy-two ROS, 43 CS, and 127 HC participants were recruited, and high-resolution T1-weighted structural magnetic resonance images of the brain were acquired. We compared cerebellar GM volumes among the groups using voxel-based morphometry and examined the cerebro-cerebellar GM volumetric correlations in participants with schizophrenia. Exploratory correlation analysis investigated the functional relevance of cerebro-cerebellar GM volume alterations to cognitive function in the schizophrenia group. The ROS and CS participants demonstrated smaller cerebellar GM volumes, particularly in Crus I and II, than HCs. Extracted cerebellar GM volumes demonstrated significant positive correlations with the cerebral GM volume in the fronto-temporo-parietal association areas engaged in higher-order association. The exploratory analysis showed that smaller cerebellar GM in the posterior lobe regions was associated with poorer cognitive performance in participants with schizophrenia. Our study suggests that cerebellar pathogenesis is present in the early stages of schizophrenia and interconnected with structural abnormalities in the cerebral cortex. Integrating the cerebellum into the pathogenesis of schizophrenia will help advance our understanding of the disease and identify novel treatment targets concerning dysfunctional cerebro-cerebellar interactions.
{"title":"Cerebro-cerebellar gray matter abnormalities associated with cognitive impairment in patients with recent-onset and chronic schizophrenia.","authors":"Naok Kang, Subin Chung, Sang-Hyuk Lee, Minji Bang","doi":"10.1038/s41537-024-00434-8","DOIUrl":"10.1038/s41537-024-00434-8","url":null,"abstract":"<p><p>Although the role of the cerebellum in schizophrenia has gained attention, its contribution to cognitive impairment remains unclear. We aimed to investigate volumetric alterations in the cerebro-cerebellar gray matter (GM) in patients with recent-onset schizophrenia (ROS) and chronic schizophrenia (CS) compared with healthy controls (HCs). Seventy-two ROS, 43 CS, and 127 HC participants were recruited, and high-resolution T1-weighted structural magnetic resonance images of the brain were acquired. We compared cerebellar GM volumes among the groups using voxel-based morphometry and examined the cerebro-cerebellar GM volumetric correlations in participants with schizophrenia. Exploratory correlation analysis investigated the functional relevance of cerebro-cerebellar GM volume alterations to cognitive function in the schizophrenia group. The ROS and CS participants demonstrated smaller cerebellar GM volumes, particularly in Crus I and II, than HCs. Extracted cerebellar GM volumes demonstrated significant positive correlations with the cerebral GM volume in the fronto-temporo-parietal association areas engaged in higher-order association. The exploratory analysis showed that smaller cerebellar GM in the posterior lobe regions was associated with poorer cognitive performance in participants with schizophrenia. Our study suggests that cerebellar pathogenesis is present in the early stages of schizophrenia and interconnected with structural abnormalities in the cerebral cortex. Integrating the cerebellum into the pathogenesis of schizophrenia will help advance our understanding of the disease and identify novel treatment targets concerning dysfunctional cerebro-cerebellar interactions.</p>","PeriodicalId":74758,"journal":{"name":"Schizophrenia (Heidelberg, Germany)","volume":"10 1","pages":"11"},"PeriodicalIF":0.0,"publicationDate":"2024-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10851702/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139572292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-15DOI: 10.1038/s41537-024-00431-x
Pingping Wang, Xiaoni Guan, Xiuru Su, Fengchun Wu, Meihong Xiu
{"title":"Author Correction: A pilot study to examine the association between COX-2 rs5275 polymorphism and the response to repetitive transcranial stimulation in schizophrenia.","authors":"Pingping Wang, Xiaoni Guan, Xiuru Su, Fengchun Wu, Meihong Xiu","doi":"10.1038/s41537-024-00431-x","DOIUrl":"10.1038/s41537-024-00431-x","url":null,"abstract":"","PeriodicalId":74758,"journal":{"name":"Schizophrenia (Heidelberg, Germany)","volume":"10 1","pages":"9"},"PeriodicalIF":0.0,"publicationDate":"2024-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10851693/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139473173","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}