A combined pathway and regional heritability analysis indicates NETRIN1 pathway is associated with major depressive disorder

Zeng, Yanni, Navarro, Pau, Fernandez-Pujals, Ana M., Hall, Lynsey S., Clarke, Toni-Kim, Thomson, Pippa A., Smith, Blair H., Hocking, Lynne J., Padmanabhan, Sandosh, Hayward, Caroline, MacIntyre, Donald J., Wray, Naomi R., Deary, Ian J., Porteous, David J., Haley, Chris S. and McIntosh, Andrew M. (2016) A combined pathway and regional heritability analysis indicates NETRIN1 pathway is associated with major depressive disorder. Biological Psychiatry, 81 4: 336-346. doi:10.1016/j.biopsych.2016.04.017


Author Zeng, Yanni
Navarro, Pau
Fernandez-Pujals, Ana M.
Hall, Lynsey S.
Clarke, Toni-Kim
Thomson, Pippa A.
Smith, Blair H.
Hocking, Lynne J.
Padmanabhan, Sandosh
Hayward, Caroline
MacIntyre, Donald J.
Wray, Naomi R.
Deary, Ian J.
Porteous, David J.
Haley, Chris S.
McIntosh, Andrew M.
Title A combined pathway and regional heritability analysis indicates NETRIN1 pathway is associated with major depressive disorder
Journal name Biological Psychiatry   Check publisher's open access policy
ISSN 0006-3223
1873-2402
Publication date 2016-05-02
Sub-type Article (original research)
DOI 10.1016/j.biopsych.2016.04.017
Open Access Status DOI
Volume 81
Issue 4
Start page 336
End page 346
Total pages 11
Place of publication Philadelphia, PA, United States
Publisher Elsevier
Language eng
Abstract 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.
Formatted abstract
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.
Keyword MDD
Pathway analysis
Regional heritability
NETRIN1
DCC
Polygenic risk score
Q-Index Code C1
Q-Index Status Provisional Code
Grant ID 104036
MC_PC_U127592696
MC_PC_U127561128
U01 MH105630
BB/J002844/1
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: HERDC Pre-Audit
Queensland Brain Institute Publications
Institute for Molecular Bioscience - Publications
 
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Created: Mon, 05 Dec 2016, 20:43:45 EST by Kirstie Asmussen on behalf of School of Music