Gene discovery through imaging genetics: Identification of two novel genes associated with schizophrenia

S. G. Potkin; J. A. Turner; J. A. Fallon; A. Lakatos; D. B. Keator; G. Guffanti; F. Macciardi; John Lauriello; Juan Bastillo; Daniel O'Leary; Kelvin Lim; Gregory McCarthy; Judith Ford; Arthur Toga; Tyrone Cannon; Randy Gollub; Aysenil Belger; Dana Nguyen; Diane Highum

doi:10.1038/mp.2008.127

Gene discovery through imaging genetics: Identification of two novel genes associated with schizophrenia

S. G. Potkin, J. A. Turner, J. A. Fallon, A. Lakatos, D. B. Keator, G. Guffanti, F. Macciardi, John Lauriello, Juan Bastillo, Daniel O'Leary, Kelvin Lim, Gregory McCarthy, Judith Ford, Arthur Toga, Tyrone Cannon, Randy Gollub, Aysenil Belger, Dana Nguyen, Diane Highum

Psychiatry & Behavioral Sciences

Research output: Contribution to journal › Article › peer-review

86 Scopus citations

Abstract

We have discovered two genes, RSRC1 and ARHGAP18, associated with schizophrenia and in an independent study provided additional support for this association. We have both discovered and verified the association of two genes, RSRC1 and ARHGAP18, with schizophrenia. We combined a genome-wide screening strategy with neuroimaging measures as the quantitative phenotype and identified the single nucleotide polymorphisms (SNPs) related to these genes as consistently associated with the phenotypic variation. To control for the risk of false positives, the empirical P-value for association significance was calculated using permutation testing. The quantitative phenotype was Blood-Oxygen-Level Dependent (BOLD) Contrast activation in the left dorsal lateral prefrontal cortex measured during a working memory task. The differential distribution of SNPs associated with these two genes in cases and controls was then corroborated in a larger, independent sample of patients with schizophrenia (n=82) and healthy controls (n=91), thus suggesting a putative etiological function for both genes in schizophrenia. Up until now these genes have not been linked to any neuropsychiatric illness, although both genes have a function in prenatal brain development. We introduce the use of functional magnetic resonance imaging activation as a quantitative phenotype in conjunction with genome-wide association as a gene discovery tool.

Original language	English (US)
Pages (from-to)	416-428
Number of pages	13
Journal	Molecular psychiatry
Volume	14
Issue number	4
DOIs	https://doi.org/10.1038/mp.2008.127
State	Published - Apr 2009

Bibliographical note

Funding Information:
This research was supported by grants to the Transdisciplinary Imaging Genetics Center (TIGC-P20 RR020837-01) and to the Functional Imaging Biomedical Informatics Research Network (FBIRN-1 U24 RR021992) from the National Center for Research Resources (NCRR) at the National Institutes of Health (NIH) and by grants POCEMON (FP7-ICT-2007-216088), FIRB Italia-Israele (RBIN04SWHR) and HYPERGENES (HEALTH-F4-2007-201550) and by an anonymous foundation. The Broad Institute Center for Genotyping and Analysis is supported by grant U54 RR020278-01 from the NCRR. We acknowledge the help and support of Mita Mancini and Yann Legros from Illumina, as well as Cristina Barlassina, Chiara Dal Fiume, Alessandro Orro and Federica Torri (University of Milan) for performing the Human-Hap300 Bead Array procedures, as well as Liv Trondsen and Divya Rajpoot (UCI) for editorial support. We also acknowledge the recruitment, evaluation and SCID-based diagnostic assessment of healthy controls and schizophrenic subjects by FBIRN investigators: John Lauriello and Juan Bastillo, University of New Mexico; Daniel O’Leary, University of Iowa; Kelvin Lim, University of Minnesota; Gregory McCarthy, Judith Ford, Yale University; Arthur Toga, Tyrone Cannon, UCLA; Randy Gollub, Harvard University; Aysenil Belger, University of North Carolina; Dana Nguyen, Diane Highum, University of California, Irvine. We acknowledge the helpful comments of William E Bunney and Hal Stern. Author contributions: The fMRI task, imaging data from the discovery sample and imaging analyses for these results were programmed and implemented by Jessica Turner; the neuroanatomical and neuroscience expertize and genetic annotation was contributed by James Fallon; the genetic data analysis, PLINK and Eigenstrat analyses and genetic annotation were performed by Guia Guffanti and Fabio Macciardi; the in silico annotations were performed by Anita Lakatos; the visualization and gene viewer methods were developed by David Keator; the design and oversight of the experiments and analyses were the responsibility of Steven Potkin. Article preparation was a joint effort of all authors.

Keywords

Case-control study
Cognition
GWAS
Prefrontal cortex
Quantitative trait loci
fMRI

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Potkin, S. G., Turner, J. A., Fallon, J. A., Lakatos, A., Keator, D. B., Guffanti, G., Macciardi, F., Lauriello, J., Bastillo, J., O'Leary, D., Lim, K., McCarthy, G., Ford, J., Toga, A., Cannon, T., Gollub, R., Belger, A., Nguyen, D., & Highum, D. (2009). Gene discovery through imaging genetics: Identification of two novel genes associated with schizophrenia. Molecular psychiatry, 14(4), 416-428. https://doi.org/10.1038/mp.2008.127

Potkin, SG, Turner, JA, Fallon, JA, Lakatos, A, Keator, DB, Guffanti, G, Macciardi, F, Lauriello, J, Bastillo, J, O'Leary, D, Lim, K, McCarthy, G, Ford, J, Toga, A, Cannon, T, Gollub, R, Belger, A, Nguyen, D & Highum, D 2009, 'Gene discovery through imaging genetics: Identification of two novel genes associated with schizophrenia', Molecular psychiatry, vol. 14, no. 4, pp. 416-428. https://doi.org/10.1038/mp.2008.127

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abstract = "We have discovered two genes, RSRC1 and ARHGAP18, associated with schizophrenia and in an independent study provided additional support for this association. We have both discovered and verified the association of two genes, RSRC1 and ARHGAP18, with schizophrenia. We combined a genome-wide screening strategy with neuroimaging measures as the quantitative phenotype and identified the single nucleotide polymorphisms (SNPs) related to these genes as consistently associated with the phenotypic variation. To control for the risk of false positives, the empirical P-value for association significance was calculated using permutation testing. The quantitative phenotype was Blood-Oxygen-Level Dependent (BOLD) Contrast activation in the left dorsal lateral prefrontal cortex measured during a working memory task. The differential distribution of SNPs associated with these two genes in cases and controls was then corroborated in a larger, independent sample of patients with schizophrenia (n=82) and healthy controls (n=91), thus suggesting a putative etiological function for both genes in schizophrenia. Up until now these genes have not been linked to any neuropsychiatric illness, although both genes have a function in prenatal brain development. We introduce the use of functional magnetic resonance imaging activation as a quantitative phenotype in conjunction with genome-wide association as a gene discovery tool.",

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author = "Potkin, {S. G.} and Turner, {J. A.} and Fallon, {J. A.} and A. Lakatos and Keator, {D. B.} and G. Guffanti and F. Macciardi and John Lauriello and Juan Bastillo and Daniel O'Leary and Kelvin Lim and Gregory McCarthy and Judith Ford and Arthur Toga and Tyrone Cannon and Randy Gollub and Aysenil Belger and Dana Nguyen and Diane Highum",

note = "Funding Information: This research was supported by grants to the Transdisciplinary Imaging Genetics Center (TIGC-P20 RR020837-01) and to the Functional Imaging Biomedical Informatics Research Network (FBIRN-1 U24 RR021992) from the National Center for Research Resources (NCRR) at the National Institutes of Health (NIH) and by grants POCEMON (FP7-ICT-2007-216088), FIRB Italia-Israele (RBIN04SWHR) and HYPERGENES (HEALTH-F4-2007-201550) and by an anonymous foundation. The Broad Institute Center for Genotyping and Analysis is supported by grant U54 RR020278-01 from the NCRR. We acknowledge the help and support of Mita Mancini and Yann Legros from Illumina, as well as Cristina Barlassina, Chiara Dal Fiume, Alessandro Orro and Federica Torri (University of Milan) for performing the Human-Hap300 Bead Array procedures, as well as Liv Trondsen and Divya Rajpoot (UCI) for editorial support. We also acknowledge the recruitment, evaluation and SCID-based diagnostic assessment of healthy controls and schizophrenic subjects by FBIRN investigators: John Lauriello and Juan Bastillo, University of New Mexico; Daniel O{\textquoteright}Leary, University of Iowa; Kelvin Lim, University of Minnesota; Gregory McCarthy, Judith Ford, Yale University; Arthur Toga, Tyrone Cannon, UCLA; Randy Gollub, Harvard University; Aysenil Belger, University of North Carolina; Dana Nguyen, Diane Highum, University of California, Irvine. We acknowledge the helpful comments of William E Bunney and Hal Stern. Author contributions: The fMRI task, imaging data from the discovery sample and imaging analyses for these results were programmed and implemented by Jessica Turner; the neuroanatomical and neuroscience expertize and genetic annotation was contributed by James Fallon; the genetic data analysis, PLINK and Eigenstrat analyses and genetic annotation were performed by Guia Guffanti and Fabio Macciardi; the in silico annotations were performed by Anita Lakatos; the visualization and gene viewer methods were developed by David Keator; the design and oversight of the experiments and analyses were the responsibility of Steven Potkin. Article preparation was a joint effort of all authors.",

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AU - Guffanti, G.

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AU - Lauriello, John

AU - Bastillo, Juan

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Gene discovery through imaging genetics: Identification of two novel genes associated with schizophrenia

Abstract

Bibliographical note

Keywords

Access

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