Project description:Background: Schizophrenia is a severe, highly heritable, neuropsychiatric disorder characterized by episodic psychosis and altered cognitive function. Despite success in identifying genetic variants associated with schizophrenia, there remains uncertainty about the causal genes involved in disease pathogenesis and how their function is regulated. Insights into the functional complexity of the genome have focussed attention on the role of non-sequence-based genomic variation in health and disease. Although a better understanding of the molecular mechanisms underlying disease phenotypes is best achieved using an integrated functional genomics strategy, few studies have attempted to systematically integrate genetic and epigenetic epidemiological approaches. Results: We performed a multi-stage epigenome-wide association study (EWAS), quantifying genome-wide patterns of DNA methylation in a total of 1,801 individuals from three independent sample cohorts. We identified multiple differentially methylated positions (DMPs) and region (DMRs) associated with schizophrenia, independently of important confounders such as smoking, with consistent effects across the three independent cohorts. We also show that polygenic burden for schizophrenia is associated with epigenetic variation at multiple loci across the genome, independently of loci implicated in the analysis of diagnosed schizophrenia. Finally, we show how DNA methylation quantitative trait loci (mQTL) analyses can be used to annotate the extended genomic regions nominated by genetic studies of schizophrenia, with Bayesian co-localization analyses highlighting potential regulatory variation causally involved in disease. Conclusion: This study represents the first systematic integrated analysis of genetic and epigenetic variation in schizophrenia, introducing a methodological pipeline that can be used to inform EWAS analyses of other complex traits and diseases. We demonstrate the utility of using polygenic risk score (PRS) for identifying molecular variation associated with etiological variation, and mQTLs for refining the functional/regulatory variation associated with schizophrenia risk variants. Finally, we present strong evidence for the co-localization of genetic associations for schizophrenia and differential DNA methylation. 675 whole blood derived DNA samples (353 schizophrenia cases and 322 controls) representing phase 1 of our meta-analysis. Bisulfite converted DNA from these samples were hybridized to the Illumina Infinium 450k Human Methylation Beadchip v1.0.

Project description:Abstract Background: Schizophrenia is a severe, highly heritable, neuropsychiatric disorder characterized by episodic psychosis and altered cognitive function. Despite success in identifying genetic variants associated with schizophrenia, there remains uncertainty about the causal genes involved in disease pathogenesis and how their function is regulated. Insights into the functional complexity of the genome have focussed attention on the role of non-sequence-based genomic variation in health and disease. Although a better understanding of the molecular mechanisms underlying disease phenotypes is best achieved using an integrated functional genomics strategy, few studies have attempted to systematically integrate genetic and epigenetic epidemiological approaches. Results: We performed a multi-stage epigenome-wide association study (EWAS), quantifying genome-wide patterns of DNA methylation in a total of 1,801 individuals from three independent sample cohorts. We identified multiple differentially methylated positions (DMPs) and region (DMRs) associated with schizophrenia, independently of important confounders such as smoking, with consistent effects across the three independent cohorts. We also show that polygenic burden for schizophrenia is associated with epigenetic variation at multiple loci across the genome, independently of loci implicated in the analysis of diagnosed schizophrenia. Finally, we show how DNA methylation quantitative trait loci (mQTL) analyses can be used to annotate the extended genomic regions nominated by genetic studies of schizophrenia, with Bayesian co-localization analyses highlighting potential regulatory variation causally involved in disease. Conclusion: This study represents the first systematic integrated analysis of genetic and epigenetic variation in schizophrenia, introducing a methodological pipeline that can be used to inform EWAS analyses of other complex traits and diseases. We demonstrate the utility of using polygenic risk score (PRS) for identifying molecular variation associated with etiological variation, and mQTLs for refining the functional/regulatory variation associated with schizophrenia risk variants. Finally, we present strong evidence for the co-localization of genetic associations for schizophrenia and differential DNA methylation. 847 whole blood derived DNA samples (414 schizophrenia cases and 433 controls) representing phase 2 of our meta-analysis. Bisulfite converted DNA from these samples were hybridised to the Illumina Infinium 450k Human Methylation Beadchip v1.0.

Project description:Abstract Background: Schizophrenia is a severe, highly heritable, neuropsychiatric disorder characterized by episodic psychosis and altered cognitive function. Despite success in identifying genetic variants associated with schizophrenia, there remains uncertainty about the causal genes involved in disease pathogenesis and how their function is regulated. Insights into the functional complexity of the genome have focussed attention on the role of non-sequence-based genomic variation in health and disease. Although a better understanding of the molecular mechanisms underlying disease phenotypes is best achieved using an integrated functional genomics strategy, few studies have attempted to systematically integrate genetic and epigenetic epidemiological approaches. Results: We performed a multi-stage epigenome-wide association study (EWAS), quantifying genome-wide patterns of DNA methylation in a total of 1,801 individuals from three independent sample cohorts. We identified multiple differentially methylated positions (DMPs) and region (DMRs) associated with schizophrenia, independently of important confounders such as smoking, with consistent effects across the three independent cohorts. We also show that polygenic burden for schizophrenia is associated with epigenetic variation at multiple loci across the genome, independently of loci implicated in the analysis of diagnosed schizophrenia. Finally, we show how DNA methylation quantitative trait loci (mQTL) analyses can be used to annotate the extended genomic regions nominated by genetic studies of schizophrenia, with Bayesian co-localization analyses highlighting potential regulatory variation causally involved in disease. Conclusion: This study represents the first systematic integrated analysis of genetic and epigenetic variation in schizophrenia, introducing a methodological pipeline that can be used to inform EWAS analyses of other complex traits and diseases. We demonstrate the utility of using polygenic risk score (PRS) for identifying molecular variation associated with etiological variation, and mQTLs for refining the functional/regulatory variation associated with schizophrenia risk variants. Finally, we present strong evidence for the co-localization of genetic associations for schizophrenia and differential DNA methylation.

Project description:Background: Schizophrenia is a severe, highly heritable, neuropsychiatric disorder characterized by episodic psychosis and altered cognitive function. Despite success in identifying genetic variants associated with schizophrenia, there remains uncertainty about the causal genes involved in disease pathogenesis and how their function is regulated. Insights into the functional complexity of the genome have focussed attention on the role of non-sequence-based genomic variation in health and disease. Although a better understanding of the molecular mechanisms underlying disease phenotypes is best achieved using an integrated functional genomics strategy, few studies have attempted to systematically integrate genetic and epigenetic epidemiological approaches. Results: We performed a multi-stage epigenome-wide association study (EWAS), quantifying genome-wide patterns of DNA methylation in a total of 1,801 individuals from three independent sample cohorts. We identified multiple differentially methylated positions (DMPs) and region (DMRs) associated with schizophrenia, independently of important confounders such as smoking, with consistent effects across the three independent cohorts. We also show that polygenic burden for schizophrenia is associated with epigenetic variation at multiple loci across the genome, independently of loci implicated in the analysis of diagnosed schizophrenia. Finally, we show how DNA methylation quantitative trait loci (mQTL) analyses can be used to annotate the extended genomic regions nominated by genetic studies of schizophrenia, with Bayesian co-localization analyses highlighting potential regulatory variation causally involved in disease. Conclusion: This study represents the first systematic integrated analysis of genetic and epigenetic variation in schizophrenia, introducing a methodological pipeline that can be used to inform EWAS analyses of other complex traits and diseases. We demonstrate the utility of using polygenic risk score (PRS) for identifying molecular variation associated with etiological variation, and mQTLs for refining the functional/regulatory variation associated with schizophrenia risk variants. Finally, we present strong evidence for the co-localization of genetic associations for schizophrenia and differential DNA methylation.

Project description:Acute lymphoblastic leukemia (ALL), the commonest childhood malignancy, is characterized by recurring gross and submicroscopic structural genetic alterations that contribute to leukemogenesis. Disordered epigenetic regulation is a hallmark of many tumors, and while analysis of DNA methylation of limited numbers of genes or ALL samples suggests epigenetic alterations may also be important, a large-scale integrative genome-wide analysis evaluating DNA methylation in ALL has not been performed. Here, we report an integrated epigenomic, transcriptional and genetic analysis of 167 childhood ALL cases, comprising B-progenitor ALL with hyperdiploidy (N=26), ETV6-RUNX1 (N=27), TCF3-PBX1 (N=9), BCR-ABL1 (N=19), rearrangement of MLL (MLLr) (N=20), rearrangement of CRLF2 (N=11, CRLF2r), deletion of ERG (N=11), miscellaneous or normal karyotype (N=14), and T-lineage ALL (N=30), including 4 MLLr cases and 7 cases with early T-cell precursor immunophenotype. Genome-wide profiling of structural DNA alterations was performed for all cases using Affymetrix 500K and SNP 6.0 arrays. Affymetrix U133A gene expression profiling data was available for 154 cases. Genome-wide methylation profiling was performed using the HELP microarray assay, which measures methylation at approximately 50,000 CpGs distributed among 22,722 Refseq promoters. Methylation data was compared to that of normal pro-B (CD34+CD19+sIg-), pre-B (CD34-CD19+sIg-) and mature B (CD34-CD19+sIg+) cells FACS-sorted from bone marrow of 6 healthy individuals. Unsupervised hierarchical clustering of the top 4043 most variable methylation probesets identified 9 B-ALL clusters with significant correlation to specific genetic lesions including ETV6-RUNX1, MLLr, BCR-ABL1, CRLF2r, TCF3-PBX1 and ERG deletion. T-ALLs and hyperdiploid B-ALLs also defined specific DNA methylation clusters. Supervised analysis including limma and ANOVA identified distinct DNA methylation signatures for each subtype. Notably, the strength of these signatures was subtype dependent, with more differentially methylated genes observed in ALL cases with genetic alterations targeting transcriptional regulators (e.g. ETV6-RUNX1 and MLLr) and fewer genes in cases with alterations deregulating cytokine receptor signaling (e.g. CRLF2r). Aberrant DNA methylation affected specific and distinct biological processes in the various leukemia subtypes implicating epigenetic regulation of these pathways in the pathogenesis of these different forms of ALL (e.g. TGFB and TNF in ERG deleted leukemias; telomere and centriole regulation in BCR-ABL1 ALL). Aberrantly methylated genes were also enriched for binding sites of known or suspected oncogenic transcription factors that might represent cooperative influences in establishing the phenotype of the various B-ALL subtypes. Most importantly, an integrated analysis of methylation and gene expression of these ALL subtypes demonstrated striking inversely correlated expression of the corresponding gene transcripts. The methylation signatures of each subtype exhibited only partial overlap with those of normal B cells, indicating that the signatures do not simply reflect stage of lymphoid maturation. In a separate approach, we discovered that 81 genes showed consistent aberrant methylation across all ALL subtypes, including the tumor suppressor PDZD2, HOXA5, HOXA6 and MSH2. Inverse correlation with expression was confirmed in 66% of these genes. These data suggest the existence of a common epigenetic pathway underlying the malignant transformation of lymphoid precursor cells. Integrative genetic and epigenetic analysis revealed hypermethylation of genes on trisomic chromosomes that do not show increased expression, suggesting that epigenetic silencing may control genes within amplified regions and explain why only selected genes are overexpressed. Finally, analysis of individual genes targeted by recurring copy number alterations in ALL revealed a subset of genes also targeted by abnormal methylation, with corresponding changes in gene expression (e.g. ERG, GAB1), suggesting that such genes are inactivated far more frequently than suggested by genetic analyses alone. Collectively, the data support a key role of epigenetic gene regulation in the pathogenesis of ALL, and point towards a scenario where genetic and epigenetic lesions cooperatively determine disease phenotype. 154 Diagnostic ALL samples were analyzed. There are no replicates. This GEO submission contains only the U133A gene expression profile data described in the study summary.

Project description:Acute lymphoblastic leukemia (ALL), the commonest childhood malignancy, is characterized by recurring gross and submicroscopic structural genetic alterations that contribute to leukemogenesis. Disordered epigenetic regulation is a hallmark of many tumors, and while analysis of DNA methylation of limited numbers of genes or ALL samples suggests epigenetic alterations may also be important, a large-scale integrative genome-wide analysis evaluating DNA methylation in ALL has not been performed. Here, we report an integrated epigenomic, transcriptional and genetic analysis of 167 childhood ALL cases, comprising B-progenitor ALL with hyperdiploidy (N=26), ETV6-RUNX1 (N=27), TCF3-PBX1 (N=9), BCR-ABL1 (N=19), rearrangement of MLL (MLLr) (N=20), rearrangement of CRLF2 (N=11, CRLF2r), deletion of ERG (N=11), miscellaneous or normal karyotype (N=14), and T-lineage ALL (N=30), including 4 MLLr cases and 7 cases with early T-cell precursor immunophenotype. Genome-wide profiling of structural DNA alterations was performed for all cases using Affymetrix 500K and SNP 6.0 arrays. Affymetrix U133A gene expression profiling data was available for 154 cases [GEO Series GSE26281]. Genome-wide methylation profiling was performed using the HELP microarray assay, which measures methylation at approximately 50,000 CpGs distributed among 22,722 Refseq promoters. Methylation data was compared to that of normal pro-B (CD34+CD19+sIg-), pre-B (CD34-CD19+sIg-) and mature B (CD34-CD19+sIg+) cells FACS-sorted from bone marrow of 6 healthy individuals. Unsupervised hierarchical clustering of the top 4043 most variable methylation probesets identified 9 B-ALL clusters with significant correlation to specific genetic lesions including ETV6-RUNX1, MLLr, BCR-ABL1, CRLF2r, TCF3-PBX1 and ERG deletion. T-ALLs and hyperdiploid B-ALLs also defined specific DNA methylation clusters. Supervised analysis including limma and ANOVA identified distinct DNA methylation signatures for each subtype. Notably, the strength of these signatures was subtype dependent, with more differentially methylated genes observed in ALL cases with genetic alterations targeting transcriptional regulators (e.g. ETV6-RUNX1 and MLLr) and fewer genes in cases with alterations deregulating cytokine receptor signaling (e.g. CRLF2r). Aberrant DNA methylation affected specific and distinct biological processes in the various leukemia subtypes implicating epigenetic regulation of these pathways in the pathogenesis of these different forms of ALL (e.g. TGFB and TNF in ERG deleted leukemias; telomere and centriole regulation in BCR-ABL1 ALL). Aberrantly methylated genes were also enriched for binding sites of known or suspected oncogenic transcription factors that might represent cooperative influences in establishing the phenotype of the various B-ALL subtypes. Most importantly, an integrated analysis of methylation and gene expression of these ALL subtypes demonstrated striking inversely correlated expression of the corresponding gene transcripts. The methylation signatures of each subtype exhibited only partial overlap with those of normal B cells, indicating that the signatures do not simply reflect stage of lymphoid maturation. In a separate approach, we discovered that 81 genes showed consistent aberrant methylation across all ALL subtypes, including the tumor suppressor PDZD2, HOXA5, HOXA6 and MSH2. Inverse correlation with expression was confirmed in 66% of these genes. These data suggest the existence of a common epigenetic pathway underlying the malignant transformation of lymphoid precursor cells. Integrative genetic and epigenetic analysis revealed hypermethylation of genes on trisomic chromosomes that do not show increased expression, suggesting that epigenetic silencing may control genes within amplified regions and explain why only selected genes are overexpressed. Finally, analysis of individual genes targeted by recurring copy number alterations in ALL revealed a subset of genes also targeted by abnormal methylation, with corresponding changes in gene expression (e.g. ERG, GAB1), suggesting that such genes are inactivated far more frequently than suggested by genetic analyses alone. Collectively, the data support a key role of epigenetic gene regulation in the pathogenesis of ALL, and point towards a scenario where genetic and epigenetic lesions cooperatively determine disease phenotype. 186 samples were analyzed by DNA methylation on the HELP array, including 167 Diagnostic ALL samples and 19 Normal Bone Marrow B cells. There are no replicates

Project description:Acute lymphoblastic leukemia (ALL), the commonest childhood malignancy, is characterized by recurring gross and submicroscopic structural genetic alterations that contribute to leukemogenesis. Disordered epigenetic regulation is a hallmark of many tumors, and while analysis of DNA methylation of limited numbers of genes or ALL samples suggests epigenetic alterations may also be important, a large-scale integrative genome-wide analysis evaluating DNA methylation in ALL has not been performed. Here, we report an integrated epigenomic, transcriptional and genetic analysis of 167 childhood ALL cases, comprising B-progenitor ALL with hyperdiploidy (N=26), ETV6-RUNX1 (N=27), TCF3-PBX1 (N=9), BCR-ABL1 (N=19), rearrangement of MLL (MLLr) (N=20), rearrangement of CRLF2 (N=11, CRLF2r), deletion of ERG (N=11), miscellaneous or normal karyotype (N=14), and T-lineage ALL (N=30), including 4 MLLr cases and 7 cases with early T-cell precursor immunophenotype. Genome-wide profiling of structural DNA alterations was performed for all cases using Affymetrix 500K and SNP 6.0 arrays. Affymetrix U133A gene expression profiling data was available for 154 cases. Genome-wide methylation profiling was performed using the HELP microarray assay, which measures methylation at approximately 50,000 CpGs distributed among 22,722 Refseq promoters. Methylation data was compared to that of normal pro-B (CD34+CD19+sIg-), pre-B (CD34-CD19+sIg-) and mature B (CD34-CD19+sIg+) cells FACS-sorted from bone marrow of 6 healthy individuals. Unsupervised hierarchical clustering of the top 4043 most variable methylation probesets identified 9 B-ALL clusters with significant correlation to specific genetic lesions including ETV6-RUNX1, MLLr, BCR-ABL1, CRLF2r, TCF3-PBX1 and ERG deletion. T-ALLs and hyperdiploid B-ALLs also defined specific DNA methylation clusters. Supervised analysis including limma and ANOVA identified distinct DNA methylation signatures for each subtype. Notably, the strength of these signatures was subtype dependent, with more differentially methylated genes observed in ALL cases with genetic alterations targeting transcriptional regulators (e.g. ETV6-RUNX1 and MLLr) and fewer genes in cases with alterations deregulating cytokine receptor signaling (e.g. CRLF2r). Aberrant DNA methylation affected specific and distinct biological processes in the various leukemia subtypes implicating epigenetic regulation of these pathways in the pathogenesis of these different forms of ALL (e.g. TGFB and TNF in ERG deleted leukemias; telomere and centriole regulation in BCR-ABL1 ALL). Aberrantly methylated genes were also enriched for binding sites of known or suspected oncogenic transcription factors that might represent cooperative influences in establishing the phenotype of the various B-ALL subtypes. Most importantly, an integrated analysis of methylation and gene expression of these ALL subtypes demonstrated striking inversely correlated expression of the corresponding gene transcripts. The methylation signatures of each subtype exhibited only partial overlap with those of normal B cells, indicating that the signatures do not simply reflect stage of lymphoid maturation. In a separate approach, we discovered that 81 genes showed consistent aberrant methylation across all ALL subtypes, including the tumor suppressor PDZD2, HOXA5, HOXA6 and MSH2. Inverse correlation with expression was confirmed in 66% of these genes. These data suggest the existence of a common epigenetic pathway underlying the malignant transformation of lymphoid precursor cells. Integrative genetic and epigenetic analysis revealed hypermethylation of genes on trisomic chromosomes that do not show increased expression, suggesting that epigenetic silencing may control genes within amplified regions and explain why only selected genes are overexpressed. Finally, analysis of individual genes targeted by recurring copy number alterations in ALL revealed a subset of genes also targeted by abnormal methylation, with corresponding changes in gene expression (e.g. ERG, GAB1), suggesting that such genes are inactivated far more frequently than suggested by genetic analyses alone. Collectively, the data support a key role of epigenetic gene regulation in the pathogenesis of ALL, and point towards a scenario where genetic and epigenetic lesions cooperatively determine disease phenotype. 194 samples were analyzed by DNA methylation on the HELP array, including 167 Diagnostic ALL samples, 19 Normal Bone Marrow B cell samples, and 8 Normal T lymphocyte cell samples. There are no replicates.

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