3/7 Psychiatric Genomics Consortium: Finding actionable variation
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ABSTRACT:
PROVIDER: PRJNA906253 | ENA |
REPOSITORIES: ENA
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Project description:3/7 Psychiatric Genomics Consortium: Finding actionable variation
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Project description:Lung Genomics Research Consortium
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Project description:This SuperSeries is composed of the SubSeries listed below. Consortium contacts: Maria Pedersen: mpedersen@nygenome.org Hemali Phatnani: hphatnani@nygenome.org NYGC ALS Consortium: cgndhelp@nygenome.org
2019-09-20 | GSE137810 | GEO
Project description:These subjects were diagnosed as being controls or having interstitial lung disease (ILD) or chronic obstructive pulmonary disease (COPD) as determined by clinical history, CT scan, and surgical pathology. There was no intervention, these are cross-sectional data. All samples are from the Lung Tissue Research Consortium (LTRC) and are indexed by their LTRC tissue label.
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Project description:Congenital malformations in facial bones significantly impact the overall representation of face. Establishing a correlation between gene expression and morphogenesis of craniofacial structures may lead to new discoveries of molecular mechanisms of craniofacial development. Thus in the present investigation we will generate gene expression profiles of different facial bones at different time intervals over a period of 5 years to establish their roles in regulating craniofacial development. To perform global gene expression profiling analysis of mandible and maxilla development and integrate these datasets with cell lineage and quantitative 3D dynamic imaging analyses. In collaboration with the ontology group within the FaceBase consortium, we will define anatomical landmarks and morphometric parameters of the developing mandible and maxilla.
2016-03-24 | E-GEOD-67985 | biostudies-arrayexpress
Project description:Anorexia nervosa (AN), bulimia nervosa (BN), and obsessive-compulsive disorder (OCD) are complex psychiatric disorders with shared obsessive features, thought to arise from the interaction of multiple genes of small effect with environmental factors. Potential candidate genes for AN, BN, and OCD have been identified through clinical association and neuroimaging studies; however, recent genome-wide association studies of eating disorders (ED) so far have failed to report significant findings. Additionally, few if any studies have interrogated postmortem brain tissue for evidence of eQTLs associated with candidate genes, which has particular promise as an approach to elucidating molecular mechanisms of association. We therefore selected single nucleotide polymorphisms (SNPs) based on candidate gene studies for AN, BN, and OCD from the literature, and examined the association of these SNPs with gene expression across the lifespan in prefrontal cortex of a non-psychiatric control cohort (N=268). Several risk-predisposing SNPs were significantly associated with gene expression among control subjects. We then measured gene expression in the prefrontal cortex of cases previously diagnosed with obsessive psychiatric disorders, e.g., eating disorders (ED; N=15), and obsessive-compulsive disorder/obsessive-compulsive personality disorder or tics (OCD/OCPD/Tic; N=16), and non-psychiatric controls (N=102) and identified 6 and 286 genes that were differentially expressed between ED compared to controls and OCD cases compared to controls, respectively (FDR < 5%). However, none of the clinical risk SNPs were among the eQTLs and none were significantly associated with gene expression within the broad obsessive cohort, suggesting larger sample sizes or other brain regions may be required to identify candidate molecular mechanisms of clinical association in postmortem brain datasets. Gene expression data from the dorsolateral prefrontal cortex (DLPFC) from postmortem tissue on 133 subjects - 15 eating disorder (ED) patients, 16 obessive compulsive disorder (OCD) patients, and 102 non-psychiatric controls - run on the Illumina HumanHT-12 v3 microarray
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Project description:The Mammalian Methylation Consortium aimed to characterize the relationship between cytosine methylation levels and a) species characteristics such as maximum lifespan and b) individual sample characteristics such as age, sex, tissue type. Both supervised machine learning approaches and unsupervised machine learning approaches were applied to the data as described in the citations. To facilitate comparative analyses across species, the mammalian methylation consortium applied a single measurement platform (the mammalian methylation array, GPL28271) to n=15216 DNA samples derived from 70 tissue types of 348 different mammalian species (331 eutherian-, 15 marsupial-, and 2 monotreme species). Most of the CpGs are located in highly conserved stretches of DNA but not all CpGs apply to all species as detailed in the description of the platform, GPL28271 and on https://github.com/shorvath/MammalianMethylationConsortium/.
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Project description:COVID-19 Genomics UK (COG-UK) consortium
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