Background:Choosing the appropriate antipsychotic drug(APD)treatment for patients with schizophrenia(SCZ)can be challenging,as the treatment response to APD is highly variable and difficult to predict due to the lack ...Background:Choosing the appropriate antipsychotic drug(APD)treatment for patients with schizophrenia(SCZ)can be challenging,as the treatment response to APD is highly variable and difficult to predict due to the lack of effective biomarkers.Previous studies have indicated the association between treatment response and genetic and epigenetic factors,but no effective biomarkers have been identified.Hence,further research is imperative to enhance precision medicine in SCZ treatment.Methods:Participants with SCZ were recruited from two randomized trials.The discovery cohort was recruited from the CAPOC trial(n=2307)involved 6 weeks of treatment and equally randomized the participants to the Olanzapine,Risperidone,Quetiapine,Aripiprazole,Ziprasidone,and Haloperidol/Perphenazine(subsequently equally assigned to one or the other)groups.The external validation cohort was recruited from the CAPEC trial(n=1379),which involved 8 weeks of treatment and equally randomized the participants to the Olanzapine,Risperidone,and Aripiprazole groups.Additionally,healthy controls(n=275)from the local community were utilized as a genetic/epigenetic reference.The genetic and epigenetic(DNA methylation)risks of SCZ were assessed using the polygenic risk score(PRS)and polymethylation score,respectively.The study also examined the genetic-epigenetic interactions with treatment response through differential methylation analysis,methylation quantitative trait loci,colocalization,and promoteranchored chromatin interaction.Machine learning was used to develop a prediction model for treatment response,which was evaluated for accuracy and clinical benefit using the area under curve(AUC)for classification,R^(2) for regression,and decision curve analysis.Results:Six risk genes for SCZ(LINC01795,DDHD2,SBNO1,KCNG2,SEMA7A,and RUFY1)involved in cortical morphology were identified as having a genetic-epigenetic interaction associated with treatment response.The developed and externally validated prediction model,which incorporated clinical information,PRS,genetic risk score(GRS),and proxy methylation level(proxyDNAm),demonstrated positive benefits for a wide range of patients receiving different APDs,regardless of sex[discovery cohort:AUC=0.874(95%CI 0.867-0.881),R^(2)=0.478;external validation cohort:AUC=0.851(95%CI 0.841-0.861),R^(2)=0.507].Conclusions:This study presents a promising precision medicine approach to evaluate treatment response,which has the potential to aid clinicians in making informed decisions about APD treatment for patients with SCZ.Trial registration Chinese Clinical Trial Registry(https://www.chictr.org.cn/),18 Aug 2009 retrospectively registered:CAPOC-ChiCTR-RNC-09000521(https://www.chictr.org.cn/showproj.aspx?proj=9014),CAPEC-ChiCTRRNC-09000522(https://www.chictr.org.cn/showproj.aspx?proj=9013).展开更多
Autism spectrum disorders （ASD） are a group of neurodevelopmental disorders that affect up to 1.5% of population in the world. Recent large scale genomic studies show that genetic causes of ASD are very heterogeneou...Autism spectrum disorders （ASD） are a group of neurodevelopmental disorders that affect up to 1.5% of population in the world. Recent large scale genomic studies show that genetic causes of ASD are very heterogeneous. Gene ontology, pathway analysis and animal model studies have revealed several potential converging mechanisms including postsynaptic dysfunction of excitatory synapses. In this review, we focus on the structural and functional specializations of dendritic spines, and describe their defects in ASD. We use Fragile X syndrome, Rett syndrome and Phe- lan-McDermid syndrome, three of the most studied neurodevelopmental disorders with autism features, as examples to demonstrate the significant contribution made by mouse models towards the understanding of monogenic ASD. We envision that the development and application of new technologies to study the function ofdendritic spines in valid animal models wi l l eventually lead to innovative treatments for ASD.展开更多
Pathway analysis,also known as gene-set enrichment analysis,is a multilocus analytic strategy that integrates a priori,biological knowledge into the statistical analysis of high-throughput genetics data.Originally dev...Pathway analysis,also known as gene-set enrichment analysis,is a multilocus analytic strategy that integrates a priori,biological knowledge into the statistical analysis of high-throughput genetics data.Originally developed for the studies of gene expression data,it has become a powerful analytic procedure for indepth mining of genome-wide genetic variation data.Astonishing discoveries were made in the past years,uncovering genes and biological mechanisms underlying common and complex disorders.However,as massive amounts of diverse functional genomics data accrue,there is a pressing need for newer generations of pathway analysis methods that can utilize multiple layers of high-throughput genomics data.In this review,we provide an intellectual foundation of this powerful analytic strategy,as well as an update of the state-of-the-art in recent method developments.The goal of this review is threefold:(1)introduce the motivation and basic steps of pathway analysis for genome-wide genetic variation data;(2)review the merits and the shortcomings of classic and newly emerging integrative pathway analysis tools;and(3)discuss remaining challenges and future directions for further method developments.展开更多
Schizophrenia(SCH)is a complex and severe mental disorder with high prevalence,disability,mortality and carries a heavy disease burden,the lifetime prevalence of SCH is around 0.7%–1.0%,which has a profound impact on...Schizophrenia(SCH)is a complex and severe mental disorder with high prevalence,disability,mortality and carries a heavy disease burden,the lifetime prevalence of SCH is around 0.7%–1.0%,which has a profound impact on the individual and society.In the clinical practice of SCH,key problems such as subjective diagnosis,experiential treatment,and poor overall prognosis are still challenging.In recent years,some exciting discoveries have been made in the research on objective biomarkers of SCH,mainly focusing on genetic susceptibility genes,metabolic indicators,immune indices,brain imaging,electrophysiological characteristics.This review aims to summarize the biomarkers that may be used for the prediction and diagnosis of SCH.展开更多
Identical-by-descent(IBD)is a fundamental genomic characteristic in population genetics and has been widely used for population history reconstruction.However,limited by the nature of IBD,which could only capture the ...Identical-by-descent(IBD)is a fundamental genomic characteristic in population genetics and has been widely used for population history reconstruction.However,limited by the nature of IBD,which could only capture the relationship between two individuals/haplotypes,existing IBD-based history inference is constrained to two populations.In this study,we propose a framework by leveraging IBD sharing in multipopulation and develop a method,MatrixiBD,to reconstruct recent multi-population migration history.Specifically,we employ the structured coalescent theory to precisely model the genealogical process and then estimate the IBD sharing across multiple populations.Within our model,we establish a theoretical connection between migration history and IBD sharing.Our method is rigorously evaluated through simulations,revealing its remarkable accuracy and robustness.Furthermore,we apply MatrixiBD to Central and South Asia in the Human Genome Diversity Project and successfully reconstruct the recent migration history of three closely related populations in South Asia.By taking into account the IBD sharing across multiple populations simultaneously,MatrixlBD enables us to attain clearer and more comprehensive insights into the history of regions characterized by complex migration dynamics,providing a holistic perspective on intricate patterns embedded within the recent population migration history.展开更多
Background:Schizophrenia(SCZ)is a complex psychiatric disorder associated with widespread alterations in the subcortical brain structure.Hemispheric asymmetries are a fundamental organizational principle of the human ...Background:Schizophrenia(SCZ)is a complex psychiatric disorder associated with widespread alterations in the subcortical brain structure.Hemispheric asymmetries are a fundamental organizational principle of the human brain and relate to human psychological and behavioral characteristics.We aimed to explore the state of thalamic lateralization of SCZ.Methods:We used voxel-based morphometry(VBM)analysis,whole-brain analysis of low-frequency fluctuations(ALFF),fractional amplitude of low-frequency fluctuations(fALFF),and resting-state seed-based functional connectivity(FC)analysis to investigate brain structural and functional deficits in SCZ.Also,we applied Pearson’’s correlation analysis to validate the correlation between Positive and Negative Symptom Scale(PANSS)scores and them.Results:Compared with healthy controls,SCZ showed increased gray matter volume(GMV)of the left thalamus(t=2.214,p=0.029),which positively correlated with general psychosis(r=0.423,p=0.010).SCZ also showed increased ALFF in the putamen,the caudate nucleus,the thalamus,fALFF in the nucleus accumbens(NAc),and the caudate nucleus,and decreased fALFF in the precuneus.The left thalamus showed significantly weaker resting-state FC with the amygdala and insula in SCZ.PANSS negative symptom scores were negatively correlated with the resting-state FC between the thalamus and the insula(r=-0.414,p=0.025).Conclusions:Collectively,these results suggest the possibility of aberrant laterality in the left thalamus and its FC with other related brain regions involved in the limbic system.展开更多
Familial dysautonomia(FD), a hereditary sensory and autonomic neuropathy, is caused by a mutation in the Elongator complex protein 1(ELP1) gene that leads to a tissue-specific reduction of ELP1 protein. Our work to ge...Familial dysautonomia(FD), a hereditary sensory and autonomic neuropathy, is caused by a mutation in the Elongator complex protein 1(ELP1) gene that leads to a tissue-specific reduction of ELP1 protein. Our work to generate a phenotypic mouse model for FD headed to the discovery that homozygous deletion of the mouse Elp1 gene leads to embryonic lethality prior to mid-gestation. Given that FD is caused by a reduction, not loss, of ELP1, we generated two new mouse models by introducing different copy numbers of the human FD ELP1 transgene into the Elp1 knockout mouse(Elp1) and observed that human ELP1 expression rescues embryonic development in a dose-dependent manner. We then conducted a comprehensive transcriptome analysis in mouse embryos to identify genes and pathways whose expression correlates with the amount of ELP1. We found that ELP1 is essential for the expression of genes responsible for nervous system development. Further, gene length analysis of the differentially expressed genes showed that the loss of Elp1 mainly impacts the expression of long genes and that by gradually restoring Elongator, their expression is progressively rescued. Finally, through evaluation of co-expression modules, we identified gene sets with unique expression patterns that depended on ELP1 expression.展开更多
Schizophrenia is a life-long,complex mental illness that still lacks satisfactory treatments.In recent years,increasing numbers of candidate biomarkers of schizophrenia occurrences and drug responses to schizophrenia ...Schizophrenia is a life-long,complex mental illness that still lacks satisfactory treatments.In recent years,increasing numbers of candidate biomarkers of schizophrenia occurrences and drug responses to schizophrenia therapies have been successfully identified by many omics studies.This review discusses the latest discoveries regarding effective drug targets and relevant drug classifications in schizophrenia.It also assesses our understanding of biomarkers for drug efficacy and adverse drug reactions in current schizophrenia treatments using omics technologies.Future applications in clinical practice have been proposed based on these new findings,and are now considered highly promising strategies to better treat schizophrenia.Finally,we explore several novel approaches that aim to reveal additional genetic signatures of schizophrenia using multi-omics data,which are hoped to improve the diagnosis and treatment of this illness in the future.展开更多
基金supported by the National Natural Science Foundation of China(81825009,82071505,81901358)the Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences(2021-I2MC&T-B-099,2019-I2M-5–006)+2 种基金the Program of Chinese Institute for Brain Research Beijing(2020-NKX-XM-12)the King’s College London-Peking University Health Science Center Joint Institute for Medical Research(BMU2020KCL001,BMU2019LCKXJ012)the National Key R&D Program of China(2021YFF1201103,2016YFC1307000).
文摘Background:Choosing the appropriate antipsychotic drug(APD)treatment for patients with schizophrenia(SCZ)can be challenging,as the treatment response to APD is highly variable and difficult to predict due to the lack of effective biomarkers.Previous studies have indicated the association between treatment response and genetic and epigenetic factors,but no effective biomarkers have been identified.Hence,further research is imperative to enhance precision medicine in SCZ treatment.Methods:Participants with SCZ were recruited from two randomized trials.The discovery cohort was recruited from the CAPOC trial(n=2307)involved 6 weeks of treatment and equally randomized the participants to the Olanzapine,Risperidone,Quetiapine,Aripiprazole,Ziprasidone,and Haloperidol/Perphenazine(subsequently equally assigned to one or the other)groups.The external validation cohort was recruited from the CAPEC trial(n=1379),which involved 8 weeks of treatment and equally randomized the participants to the Olanzapine,Risperidone,and Aripiprazole groups.Additionally,healthy controls(n=275)from the local community were utilized as a genetic/epigenetic reference.The genetic and epigenetic(DNA methylation)risks of SCZ were assessed using the polygenic risk score(PRS)and polymethylation score,respectively.The study also examined the genetic-epigenetic interactions with treatment response through differential methylation analysis,methylation quantitative trait loci,colocalization,and promoteranchored chromatin interaction.Machine learning was used to develop a prediction model for treatment response,which was evaluated for accuracy and clinical benefit using the area under curve(AUC)for classification,R^(2) for regression,and decision curve analysis.Results:Six risk genes for SCZ(LINC01795,DDHD2,SBNO1,KCNG2,SEMA7A,and RUFY1)involved in cortical morphology were identified as having a genetic-epigenetic interaction associated with treatment response.The developed and externally validated prediction model,which incorporated clinical information,PRS,genetic risk score(GRS),and proxy methylation level(proxyDNAm),demonstrated positive benefits for a wide range of patients receiving different APDs,regardless of sex[discovery cohort:AUC=0.874(95%CI 0.867-0.881),R^(2)=0.478;external validation cohort:AUC=0.851(95%CI 0.841-0.861),R^(2)=0.507].Conclusions:This study presents a promising precision medicine approach to evaluate treatment response,which has the potential to aid clinicians in making informed decisions about APD treatment for patients with SCZ.Trial registration Chinese Clinical Trial Registry(https://www.chictr.org.cn/),18 Aug 2009 retrospectively registered:CAPOC-ChiCTR-RNC-09000521(https://www.chictr.org.cn/showproj.aspx?proj=9014),CAPEC-ChiCTRRNC-09000522(https://www.chictr.org.cn/showproj.aspx?proj=9013).
文摘Autism spectrum disorders （ASD） are a group of neurodevelopmental disorders that affect up to 1.5% of population in the world. Recent large scale genomic studies show that genetic causes of ASD are very heterogeneous. Gene ontology, pathway analysis and animal model studies have revealed several potential converging mechanisms including postsynaptic dysfunction of excitatory synapses. In this review, we focus on the structural and functional specializations of dendritic spines, and describe their defects in ASD. We use Fragile X syndrome, Rett syndrome and Phe- lan-McDermid syndrome, three of the most studied neurodevelopmental disorders with autism features, as examples to demonstrate the significant contribution made by mouse models towards the understanding of monogenic ASD. We envision that the development and application of new technologies to study the function ofdendritic spines in valid animal models wi l l eventually lead to innovative treatments for ASD.
基金supported by National Institutes of Health R00 MH101367 and R01 MH119243(to P.H.Lee)。
文摘Pathway analysis,also known as gene-set enrichment analysis,is a multilocus analytic strategy that integrates a priori,biological knowledge into the statistical analysis of high-throughput genetics data.Originally developed for the studies of gene expression data,it has become a powerful analytic procedure for indepth mining of genome-wide genetic variation data.Astonishing discoveries were made in the past years,uncovering genes and biological mechanisms underlying common and complex disorders.However,as massive amounts of diverse functional genomics data accrue,there is a pressing need for newer generations of pathway analysis methods that can utilize multiple layers of high-throughput genomics data.In this review,we provide an intellectual foundation of this powerful analytic strategy,as well as an update of the state-of-the-art in recent method developments.The goal of this review is threefold:(1)introduce the motivation and basic steps of pathway analysis for genome-wide genetic variation data;(2)review the merits and the shortcomings of classic and newly emerging integrative pathway analysis tools;and(3)discuss remaining challenges and future directions for further method developments.
基金supported by Academy of Medical Sciences Research Unit(2019-I2M-5-006)Chinese Institute for Brain Research at Beijing(2020-NKX-XM-12)+2 种基金Guizhou Province science and technology plan project([2020]4Y064)National Natural Science Foundation of China(81825009,http://dx.doi.org/10.13039/501100001809)PKUHSC-KCL Joint Medical Research(BMU2020KCL001).
文摘Schizophrenia(SCH)is a complex and severe mental disorder with high prevalence,disability,mortality and carries a heavy disease burden,the lifetime prevalence of SCH is around 0.7%–1.0%,which has a profound impact on the individual and society.In the clinical practice of SCH,key problems such as subjective diagnosis,experiential treatment,and poor overall prognosis are still challenging.In recent years,some exciting discoveries have been made in the research on objective biomarkers of SCH,mainly focusing on genetic susceptibility genes,metabolic indicators,immune indices,brain imaging,electrophysiological characteristics.This review aims to summarize the biomarkers that may be used for the prediction and diagnosis of SCH.
基金supported by the Fundamental Research Funds for the Central Universities(2023JBMC011)the National Natural Science Foundation of China(NSFC)Grant(12271026)the Beijing Natural Science Foundation Grant(L222051).
文摘Identical-by-descent(IBD)is a fundamental genomic characteristic in population genetics and has been widely used for population history reconstruction.However,limited by the nature of IBD,which could only capture the relationship between two individuals/haplotypes,existing IBD-based history inference is constrained to two populations.In this study,we propose a framework by leveraging IBD sharing in multipopulation and develop a method,MatrixiBD,to reconstruct recent multi-population migration history.Specifically,we employ the structured coalescent theory to precisely model the genealogical process and then estimate the IBD sharing across multiple populations.Within our model,we establish a theoretical connection between migration history and IBD sharing.Our method is rigorously evaluated through simulations,revealing its remarkable accuracy and robustness.Furthermore,we apply MatrixiBD to Central and South Asia in the Human Genome Diversity Project and successfully reconstruct the recent migration history of three closely related populations in South Asia.By taking into account the IBD sharing across multiple populations simultaneously,MatrixlBD enables us to attain clearer and more comprehensive insights into the history of regions characterized by complex migration dynamics,providing a holistic perspective on intricate patterns embedded within the recent population migration history.
基金National Natural Science Foundation of China(Grant/Award Number:81701326)National Key Research and Development Program of China(Grant/Award Number:2016YFC1307004)+3 种基金Multidisciplinary Team for Cognitive Impairment of Shanxi Science and Technology Innovation Training Team(Grant/Award Number:201705D131027)Special Project of Scientific Research Plan Talents of Shanxi Provincial Health Commission(Grant/Award Number:2020081)Shanxi Provincial Science and Technology Achievements Transformation and Guidance Project(Grant/Award Numbers:201904D131020,81971601)Shanxi Province Overseas Students Science and Technology Activity Funding Project(Grant/Award Number:20200038)。
文摘Background:Schizophrenia(SCZ)is a complex psychiatric disorder associated with widespread alterations in the subcortical brain structure.Hemispheric asymmetries are a fundamental organizational principle of the human brain and relate to human psychological and behavioral characteristics.We aimed to explore the state of thalamic lateralization of SCZ.Methods:We used voxel-based morphometry(VBM)analysis,whole-brain analysis of low-frequency fluctuations(ALFF),fractional amplitude of low-frequency fluctuations(fALFF),and resting-state seed-based functional connectivity(FC)analysis to investigate brain structural and functional deficits in SCZ.Also,we applied Pearson’’s correlation analysis to validate the correlation between Positive and Negative Symptom Scale(PANSS)scores and them.Results:Compared with healthy controls,SCZ showed increased gray matter volume(GMV)of the left thalamus(t=2.214,p=0.029),which positively correlated with general psychosis(r=0.423,p=0.010).SCZ also showed increased ALFF in the putamen,the caudate nucleus,the thalamus,fALFF in the nucleus accumbens(NAc),and the caudate nucleus,and decreased fALFF in the precuneus.The left thalamus showed significantly weaker resting-state FC with the amygdala and insula in SCZ.PANSS negative symptom scores were negatively correlated with the resting-state FC between the thalamus and the insula(r=-0.414,p=0.025).Conclusions:Collectively,these results suggest the possibility of aberrant laterality in the left thalamus and its FC with other related brain regions involved in the limbic system.
基金supported by National Institutes of Health grants (R37NS095640 to S.A.S.)the Francis Crick Institute (to PC and JQS)
文摘Familial dysautonomia(FD), a hereditary sensory and autonomic neuropathy, is caused by a mutation in the Elongator complex protein 1(ELP1) gene that leads to a tissue-specific reduction of ELP1 protein. Our work to generate a phenotypic mouse model for FD headed to the discovery that homozygous deletion of the mouse Elp1 gene leads to embryonic lethality prior to mid-gestation. Given that FD is caused by a reduction, not loss, of ELP1, we generated two new mouse models by introducing different copy numbers of the human FD ELP1 transgene into the Elp1 knockout mouse(Elp1) and observed that human ELP1 expression rescues embryonic development in a dose-dependent manner. We then conducted a comprehensive transcriptome analysis in mouse embryos to identify genes and pathways whose expression correlates with the amount of ELP1. We found that ELP1 is essential for the expression of genes responsible for nervous system development. Further, gene length analysis of the differentially expressed genes showed that the loss of Elp1 mainly impacts the expression of long genes and that by gradually restoring Elongator, their expression is progressively rescued. Finally, through evaluation of co-expression modules, we identified gene sets with unique expression patterns that depended on ELP1 expression.
基金This work was supported by grants from the 863 Program(No.2012AA02A515,2012AA021802)the National Natural Science Foundation of China(No.81773818,81273596,30900799,81671326)+3 种基金the National Key Research and Development Program of China(No.2017YFC0909303,2016YFC0905000,2016YFC0905002,2016YFC1200200,2016YFC0906400)the 4th Three-year Action Plan for Public Health of Shanghai,China(No.15GWZK0101)Shanghai Pujiang Program,China(No.17PJD020)Shanghai Key Laboratory of Psychotic Disorders,China(No.13dz2260500).
文摘Schizophrenia is a life-long,complex mental illness that still lacks satisfactory treatments.In recent years,increasing numbers of candidate biomarkers of schizophrenia occurrences and drug responses to schizophrenia therapies have been successfully identified by many omics studies.This review discusses the latest discoveries regarding effective drug targets and relevant drug classifications in schizophrenia.It also assesses our understanding of biomarkers for drug efficacy and adverse drug reactions in current schizophrenia treatments using omics technologies.Future applications in clinical practice have been proposed based on these new findings,and are now considered highly promising strategies to better treat schizophrenia.Finally,we explore several novel approaches that aim to reveal additional genetic signatures of schizophrenia using multi-omics data,which are hoped to improve the diagnosis and treatment of this illness in the future.
