Dataset Information

Whole Genome Association Study of Bipolar Disorder

ABSTRACT:

The goal of the project is to identify genes that make individuals more susceptible to bipolar disorder (manic depressive illness) and to better understand the brain pathways involved in the disease.

Dataset versioning

Version 1: European-American (EA) ancestry only
Version 2: Version 1 plus African-American (AA) ancestry
Version 3: EA and AA samples plus updated diagnostic criteria

Consent groups and participant set

General research use (GRU): 1767 controls (1081 EA controls, 686 AA controls)
This consent group includes all controls for the Bipolar study, which are a subset of controls for the Schizophrenia study (subset of Schizophrenia: GRU).
Bipolar and related disorders (BARD): 841 cases (691 EA cases, 150 AA cases)
This consent group includes a subset of the Bipolar cases.
Bipolar disorder only (BDO): 653 cases (388 EA cases, 265 AA cases)
This consent group includes a subset of the Bipolar cases.

PROVIDER: phs000017 | dbGaP |

SECONDARY ACCESSION(S): PRJNA75403PRJNA75401

REPOSITORIES: dbGaP

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Project description:Background/Purpose: Systemic lupus erythematosus (SLE) is a complex multi-system autoimmune disease of uncertain etiology. Patients from different ancestral backgrounds demonstrate differences in clinical manifestations and autoantibody profiles. In this study we examined genome-wide transcriptional patterns in major immune cell subsets across different ancestral backgrounds. Methods: Peripheral blood was collected from 21 African-American (AA) and 21 European-American (EA) SLE patients, 5 AA controls, and 5 EA controls. CD4+ T-cells, CD8+ T-cells, monocytes and B cells were purified by flow sorting. Each cell subset from each subject was run on an Illumina HumanHT-12 V4 expression BeadChip array (n=208 arrays). Differentially expressed genes (DEGs) were determined by comparing cases and controls of the same ancestral background. Results: The overlap in DEG lists between different cell types from the same ancestral background was very modest (<1%). Typically between 5-10% of DEGs were shared when comparing the same cell type between different ancestral backgrounds (for ex. CD20 AA vs. CD20 EA). Quantitative measurement of global IFN-stimulated gene (ISG) expression revealed that AA subjects demonstrated more concordance across all studied cell types. Two subgroups of patients were identified based on the ISG expression profiles. One subgroup showed higher ISGs expression in all cell types, and the other subgroup had higherISG expression only in T and B lymphocytes but not in monocytes. The correlation of ISG expression with medication data revealed that only the B cells had lower ISG expression in patients taking immunosuppressants, while ISG expression in the other cell types did not differ based upon medication use. Conclusion: We find striking differences in gene expression between different immune cell subsets and between ancestral backgrounds in SLE patients. The IFN signature is diverse, with different transcripts represented in different cell populations, and signature-positive cell subsets differed in EA vs. AA patients. We also find that treatment with the immunosuppressive agents correlates with the down-regulation of B cell ISG expression, and this was not observed in other cell types. Peripheral blood was collected from 21 African-American (AA) and 21 European-American (EA) SLE patients, 5 AA controls, and 5 EA controls. CD4+ T-cells, CD8+ T-cells, monocytes and B cells were purified by flow sorting. Each cell subset from each subject was run on an Illumina HumanHT-12 V4 expression BeadChip array (n=208 arrays).

Dataset Information

Whole Genome Association Study of Bipolar Disorder

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