期刊
BIOLOGICAL PSYCHIATRY
卷 72, 期 4, 页码 311-317出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.biopsych.2011.12.031
关键词
Bipolar disorder; depression; GWAS; mania; networks; pathways; postsynaptic density; systems biology
资金
- European Community Health Seventh Framework Programme [259867]
- ALS Therapy Alliance
- Angel Fund
- ALS Association
- Motor Neurone Disease Association of Great Britainand Northern Ireland
- National Institute for Health Research Biomedical Research Centre for Mental Health at the South London
- Maudsley National Health Service Foundation Trust and Institute of Psychiatry, Kings College London
- Medical Research Council [G0701420]
- Wellcome Trust
- National Alliance for Research on Schizophrenia and Depression, and Biotechnology
- Biological Sciences Research Council
- German Federal Ministry of Education and Research, within the context of the National Genome Research Network 2
- National Genome Research Network plus
- Integrated Genome Research Network MooDS [01GS08144, 01GS08147]
- MRC [G0701420] Funding Source: UKRI
- Medical Research Council [G0701420, G9817803B] Funding Source: researchfish
Background: Despite high heritability, the genetic variants influencing bipolar disorder (BD) susceptibility remain largely unknown. Low statistical power to detect the small effect-size alleles believed to underlie much of the genetic risk and possible heterogeneity between cohorts are an increasing concern. Integrative biology approaches might offer advantages over genetic analysis alone by combining different genomic datasets at the higher level of biological processes rather than the level of specific genetic variants or genes. We employed this strategy to identify biological processes involved in BD etiopathology. Method: Three genome-wide association studies and a brain gene-expression study were combined with the Human Protein Reference Database protein-protein interaction network data. We used bioinformatic analysis to search for biological networks with evidence of association on the basis of enrichment among both genetic and differential-expression associations with BD. Results: We identified association with gene networks involved in transmission of nerve impulse, Wnt, and Notch signaling. Three features stand out among these genes: 1) they localized to the human postsynaptic density, which is crucial for neuronal function; 2) their mouse knockouts present altered behavioral phenotypes; and 3) some are known targets of the pharmacological treatments for BD. Conclusions: Genetic and gene-expression associations of BD cluster in discrete regions of the protein-protein interaction network. We found replicated evidence for association for networks involving several interlinked signaling pathways. These genes are promising candidates to generate animal models and pharmacological interventions. Our results demonstrate the potential advantage of integrative biology analyses of BD datasets.
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