Genetic Overlap between Metabolic and Psychiatric disease
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ABSTRACT:
PROVIDER: EGAS00001002723 | EGA |
REPOSITORIES: EGA
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Project description:Agilent custom designed array comparative genomic hybridization (CGH) was performed on 235 samples with a dual diagnosis of schizophrenia and epilepsy and 80 samples with a dual diagnosis of bipolar and epilpsy. ArrayCGH on 191 psychiatric screened controls was also performed. A common male reference was used for all samples and controls. Samples and controls were obtained from the NIMH cell line repositories. 235 samples with a dual diagnosis of schizophrenia and epilepsy, 80 samples with a dual diagnosis of bipolar and epilepsy, and 191 psychiatric screened controls
2010-12-31 | E-GEOD-23703 | biostudies-arrayexpress
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Project description:Schizophrenia (SZ) and bipolar disorder (BD) are severe psychiatric conditions, with a lifetime prevalence of about 1%. Both disorders have a neurodevelopment component, with onset of symptoms occurring most frequently during late adolescence or early adulthood. Genetic findings indicate the existence of an overlap in genetic susceptibility across the disorders. These gene expression profiles were used to identify the molecular mechanisms that differentiate SZ and BP from healthy controls but also that distinguish both from healthy individuals. They were also used to expand an analysis from an experiment that searched molecular alterations in human induced pluripotent stem cells derived from fibroblasts from control subject and individual with schizophrenia and further differentiated to neuron to identify genes relevant for the development of schizophrenia (GSE62105). Brain tissue (frontal cortex) from 30 healthy controls, 29 bipolar disorder patients and 29 schizophrenia patients were analyzed. The reference is an in-house pool of RNA extracted from 15 human cell lines.
2014-10-11 | E-GEOD-62191 | biostudies-arrayexpress
Project description:Metabolomics analysis of plasma collected from patients with schizophrenia and non-psychiatric control subjects.
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Project description:Gene expression in peripheral blood is shown sufficient to differentiate patients with metabolic disorders from control. The signatures of metabolic syndrome, coronary artery disease and type 2 diabetes also have significant overlap. Microarrays were performed on 35 subjects in the following groups: control (n=9), rheumatoid arthritis (n=6), metabolic syndrome (n= 6), coronary artery disease (n=6) and type 2 diabetes (n=8). Intensity values for each array were normalized to a sum of 10,000.
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Project description:Gene expression in peripheral blood is shown sufficient to differentiate patients with metabolic disorders from control. The signatures of metabolic syndrome, coronary artery disease and type 2 diabetes also have significant overlap.
2010-08-12 | GSE23561 | GEO
Project description:Hsu Y, Nacu E, Liu R, Kim A, Tsafou K, Petrossian N, Crotty W, Suh JM, Pintacuda G, Riseman J, Martin J, Malolepsza E, Li T, Singh T, Ge T, Egri SB, Tanenbaum B, Stanclift CR, Apffel AM, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Stanley Global Asia Initiatives, Carr SA, Schenone M, Jaffe J, Fornelos N, Huang H, Eggan KC, Lage K. 2021. Genetics have nominated many schizophrenia risk genes that lack functional interpretation. To empower such interpretation, we executed interaction proteomics for six risk genes in human induced neurons and found the resulting protein network to be enriched for common variant risk of schizophrenia in Europeans and East Asians. The network is down-regulated in layer 5/6 cortical neurons of patients and can complement fine-mapping and eQTL data to prioritize additional genes in GWAS loci. A sub-network centered on HCN1 is enriched for common variant risk and also contains proteins (HCN4 and AKAP11) enriched for rare protein-truncating mutations in patients with schizophrenia and bipolar disease. Our findings establish brain cell-type-specific interactomes as an organizing framework to facilitate interpretation of genetic and transcriptomic data in schizophrenia and psychiatric diseases.
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Project description:Schizophrenia is a severe psychiatric illness that affects ~1% of the population and has a strong genetic underpinning. Recently, genome wide analysis of copy number variation (CNV) has implicated rare and de novo events as important in schizophrenia. Here we report a genome-wide analysis of 245 schizophrenia cases and 490 controls, all of Ashkenazi Jewish descent. Since many studies have found an excess burden of large, rare deletions in cases, we limited our analysis to deletions over 500 kb in size. We observed seven large, rare deletions in cases with 57% of these being de novo. We focused on one 836 kb de novo deletion at chromosome 3q29 that falls within a 1.3–1.6 Mb deletion previously identified in children with intellectual disability (ID) and autism, as increasing evidence suggests an overlap of specific rare CNVs between autism and schizophrenia. By combining our data with prior CNV studies of schizophrenia and analysis of the data of the Genetic Association Information Network (GAIN), we identified six 3q29 deletions among 7,545 schizophrenic subjects and one among 39,748 controls, resulting in a statistically significant association with schizophrenia (p = 0.02) and an odds ratio estimate of 17 (95% CI: 1.36–1198.4). Moreover, this 3q29 deletion region contains two linkage peaks from prior schizophrenia family studies, and the minimal deletion interval implicates 20 annotated genes, including PAK2 and DLG1, both paralogous to X-linked ID genes and now strong candidates for schizophrenia susceptibility. Copy Number alanysis was performed on 245 cases and 490 controls of Ashkenazi Jewish descent. Samples were analyzed for deletions greater than 500 kb, with 20 or more snps in the interval. Three algorithms were used for analysis, GADA, GLAD and BEAST. The reference was created by using all samples processed here as the reference.
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Project description:DNA methylation (DNAm) is important in brain development, and potentially in schizophrenia. We characterized DNAm in prefrontal cortex from 335 non-psychiatric controls across the lifespan and 191 patients with schizophrenia, and identified widespread changes in the transition from prenatal to postnatal life. These DNAm changes manifest in the transcriptome, correlate strongly with a shifting cellular landscape, and overlap regions of genetic risk for schizophrenia. A quarter of published GWAS-suggestive loci (4,208/15,930, p<10-20) manifest as significant methylation quantitative trait loci (meQTLs), including 59.6% of GWAS-positive schizophrenia loci. We identified 2,104 CpGs that differ between schizophrenia patients and controls, enriched for genes related to development and neurodifferentiation. The schizophrenia-associated CpGs strongly correlate with changes related to the prenatal-postnatal transition and show slight enrichment for GWAS risk loci, while not corresponding to CpGs differentiating adolescence from later adult life. These data implicate an epigenetic component to the developmental origins of this disorder.
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