TY - JOUR
T1 - Convergent functional genomics of schizophrenia
T2 - From comprehensive understanding to genetic risk prediction
AU - Ayalew, M.
AU - Le-Niculescu, H.
AU - Levey, D. F.
AU - Jain, N.
AU - Changala, B.
AU - Patel, S. D.
AU - Winiger, E.
AU - Breier, A.
AU - Shekhar, A.
AU - Amdur, R.
AU - Koller, D.
AU - Nurnberger, J. I.
AU - Corvin, A.
AU - Geyer, M.
AU - Tsuang, M. T.
AU - Salomon, D.
AU - Schork, N. J.
AU - Fanous, A. H.
AU - O'Donovan, M. C.
AU - Niculescu, A. B.
N1 - Funding Information:
This work is, in essence, a field-wide collaboration. We would like to acknowledge our debt of gratitude for the efforts and results of the many other groups, cited in our paper, who have conducted and published empirical studies (human and animal model, genetic and gene expression) in schizophrenia. With their arduous and careful work, a convergent approach such as ours is possible. We would particularly like to thank the ISC and GAIN consortia. We would also like to thank the subjects who participated in these studies, their families and their caregivers. Without their contribution, such work to advance the understanding of mental illness would not be possible. Finally, we would like to acknowledge Elyn Saks for her insightful memoir, which inspired the Yeats quote at the beginning of the paper. This work was supported by an NIH Directors’ New Innovator Award (1DP2OD007363) and a VA Merit Award (1I01CX000139-01) to ABN.
PY - 2012/9
Y1 - 2012/9
N2 - 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.
AB - 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.
KW - biomarkers
KW - convergent functional genomics
KW - genetic risk prediction
KW - pathways
KW - schizophrenia
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UR - http://www.scopus.com/inward/citedby.url?scp=84866372949&partnerID=8YFLogxK
U2 - 10.1038/mp.2012.37
DO - 10.1038/mp.2012.37
M3 - Article
C2 - 22584867
AN - SCOPUS:84866372949
SN - 1359-4184
VL - 17
SP - 887
EP - 905
JO - Molecular Psychiatry
JF - Molecular Psychiatry
IS - 9
ER -