期刊
BIOLOGICAL PSYCHIATRY
卷 81, 期 4, 页码 336-346出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.biopsych.2016.04.017
关键词
DCC; MDD; NETRIN1; Pathway analysis; Polygenic risk score; Regional heritability
资金
- Wellcome Trust through a Strategic Award [104036/Z/14/Z]
- Dr. Mortimer and Theresa Sackler Foundation (T-KC and AMM)
- Medical Research Council (MRC)
- Biotechnology and Biological Sciences Research Council [BB/J004235/1]
- Scottish Government Health Department
- National Institutes of Health [UO1MH105630]
- China Scholarship Council
- MRC
- Dr. Mortimer and Theresa Sackler Foundation
- Chief Scientist Office [CZD/16/6]
- Pfizer
- Lilly
- Janssen
- BBSRC [BB/F019394/1, BB/J002844/1] Funding Source: UKRI
- MRC [MC_PC_U127561128, MC_PC_U127592696] Funding Source: UKRI
- Biotechnology and Biological Sciences Research Council [BB/F019394/1, BB/J002844/1] Funding Source: researchfish
- Chief Scientist Office [CZD/16/6/4] Funding Source: researchfish
- Medical Research Council [1292844, MC_PC_U127592696, MR/K026992/1, MC_PC_U127561128] Funding Source: researchfish
BACKGROUND: Genome-wide association studies (GWASs) of major depressive disorder (MDD) have identified few significant associations. Testing the aggregation of genetic variants, in particular biological pathways, may be more powerful. Regional heritability analysis can be used to detect genomic regions that contribute to disease risk. METHODS: We integrated pathway analysis and multilevel regional heritability analyses in a pipeline designed to identify MDD-associated pathways. The pipeline was applied to two independent GWAS samples [Generation Scotland: The Scottish Family Health Study (GS:SFHS, N = 6455) and Psychiatric Genomics Consortium (PGC:MDD) (N = 18,759)]. A polygenic risk score (PRS) composed of single nucleotide polymorphisms from the pathway most consistently associated with MDD was created, and its accuracy to predict MDD, using area under the curve, logistic regression, and linear mixed model analyses, was tested. RESULTS: In GS:SFHS, four pathways were significantly associated with MDD, and two of these explained a significant amount of pathway-level regional heritability. In PGC:MDD, one pathway was significantly associated with MDD. Pathway-level regional heritability was significant in this pathway in one subset of PGC:MDD. For both samples the regional heritabilities were further localized to the gene and subregion levels. The NETRIN1 signaling pathway showed the most consistent association with MDD across the two samples. PRSs from this pathway showed competitive predictive accuracy compared with the whole-genome PRSs when using area under the curve statistics, logistic regression, and linear mixed model. CONCLUSIONS: These post-GWAS analyses highlight the value of combining multiple methods on multiple GWAS data for the identification of risk pathways for MDD. The NETRIN1 signaling pathway is identified as a candidate pathway for MDD and should be explored in further large population studies.
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