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Cited by 397

The DOI matches its Crossref record; 288 of the 288 references it cites were found in a registry or an index.

Convergent functional genomics of schizophrenia: from comprehensive understanding to genetic risk prediction

Open access
Ayalew, M, Le-Niculescu, H, Levey, D F, Jain, N, Changala, B, Patel, S D, Winiger, E, Breier, A, Shekhar, A, Amdur, R, Koller, D, Nurnberger, J I, Corvin, A, Geyer, M, Tsuang, M T, Salomon, D, Schork, N J, Fanous, A H, O'Donovan, M C, Niculescu, A B·2012·Molecular Psychiatry
DOI 10.1038/mp.2012.37
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Abstract

We have used a translational convergent functional genomics (CFG) approach to identify and prioritize genes involved in schizophrenia, by gene-level integration of genome-wide association study data with other genetic and gene expression studies in humans and animal models. Using this polyevidence scoring and pathway analyses, we identify top genes (DISC1, TCF4, MBP, MOBP, NCAM1, NRCAM, NDUFV2, RAB18, as well as ADCYAP1, BDNF, CNR1, COMT, DRD2, DTNBP1, GAD1, GRIA1, GRIN2B, HTR2A, NRG1, RELN, SNAP-25, TNIK), brain development, myelination, cell adhesion, glutamate receptor signaling, G-protein-coupled receptor signaling and cAMP-mediated signaling as key to pathophysiology and as targets for therapeutic intervention. Overall, the data are consistent with a model of disrupted connectivity in schizophrenia, resulting from the effects of neurodevelopmental environmental stress on a background of genetic vulnerability. In addition, we show how the top candidate genes identified by CFG can be used to generate a genetic risk prediction score (GRPS) to aid schizophrenia diagnostics, with predictive ability in independent cohorts. The GRPS also differentiates classic age of onset schizophrenia from early onset and late-onset disease. We also show, in three independent cohorts, two European American and one African American, increasing overlap, reproducibility and consistency of findings from single-nucleotide polymorphisms to genes, then genes prioritized by CFG, and ultimately at the level of biological pathways and mechanisms. Finally, we compared our top candidate genes for schizophrenia from this analysis with top candidate genes for bipolar disorder and anxiety disorders from previous CFG analyses conducted by us, as well as findings from the fields of autism and Alzheimer. Overall, our work maps the genomic and biological landscape for schizophrenia, providing leads towards a better understanding of illness, diagnostics and therapeutics. It also reveals the significant genetic overlap with other major psychiatric disorder domains, suggesting the need for improved nosology.

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Metadata

Authors
Ayalew, M., Le-Niculescu, H., Levey, D. F., Jain, N., Changala, B., Patel, S. D., Winiger, E., Breier, A., Shekhar, A., Amdur, R., Koller, D., Nurnberger, J. I., Corvin, A., Geyer, M., Tsuang, M. T., Salomon, D., Schork, N. J., Fanous, A. H., O'Donovan, M. C., & Niculescu, A. B.
Venue
Molecular Psychiatry
Publisher
Springer Science and Business Media LLC
Published
2012-05-15
Volume
17
Issue
9
Pages
887-905
ISSN
  • 1359-4184 (ISSN-L)
  • 1476-5578
DOI
10.1038/mp.2012.37
OpenAlex
W2016854825
Cited by
397
References
288
FWCI
35.25
Type
journal article
Language
en
Open access
hybrid

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