Complex genetic mechanisms underlie susceptibility to schizophrenia. The goal of this proposed collaborative R01 project, submitted as part of the Clinical Studies of Mental Disorders (CSMD) program, is to combine genetic and neurobiologic paradigms enabling detection and localization of genes that modulate susceptibility to schizophrenia and related phenotypes. As part of a major collaborative effort between the University of Pennsylvania (UPENN, Dr. R. Gur, P.I.), the University of Pittsburgh (UPITT, Dr. V. Nimgaonkar, P.I.) And the Southwest Foundation for Biomedical Research (SFBR, Dr. L. Almasy, Dr. J. Blangero, P.Is.), we propose to shift the focus on the genetic basis of schizophrenia to the detailed dissection of correlated endophenotypes. We anticipate that these continuously distributed phenotypes related to brain function will serve as reliably measured risk factors and indicators of schizophrenia liability in a way that is similar to the multiple risk factors that are routinely assessed as indicators of chronic common diseases (e.g., the relationship of cholesterol measures to risk of atherosclerosis). It is likely that neurocognitive endophenotypes are more proximal functions of gene action than schizophrenia itself and therefore any contributing genetic loci should be substantially easier to localize and characterize. A combined sample of 50 multiplex multigenerational families with about 1000 members will be ascertained at the UPENN and the UPITT. Comprehensive diagnostic assessment will include the DIGS, the FIGS and scales for dimensionalizing symptoms. DSM-IV diagnoses will be made by consensus best-estimate procedures. Quantitative neurocognitive measures will be obtained using efficient computerized testing that produces a neurocognitive profile of endophenotypic markers leading to characterization of brain function. SFBR will provide the expertise in genetics of complex traits and carry out the molecular and statistical genetic analyses. Using highly polymorphic genetic markers spaced at approximately 10 cM intervals, we will localize quantitative trait loci (QTLs) influencing phenotypic variation in te neurocognitive endophenotypes employing a novel oligogenic linkage analysis method. Additionally, multivariate linkage analysis will localize pleiotropic genes that jointly influence endophenotypic variation and schizophrenia liability. All collected data will become part of the NIMH-sponsored archival database for schizophrenia.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
5R01MH061622-05
Application #
6920663
Study Section
Special Emphasis Panel (ZRG1-GNM (04))
Program Officer
Lehner, Thomas
Project Start
2001-07-24
Project End
2007-06-30
Budget Start
2005-07-01
Budget End
2007-06-30
Support Year
5
Fiscal Year
2005
Total Cost
$422,331
Indirect Cost
Name
Texas Biomedical Research Institute
Department
Type
DUNS #
007936834
City
San Antonio
State
TX
Country
United States
Zip Code
78245
Kos, Mark Z; Carless, Melanie A; Peralta, Juan et al. (2017) Exome sequences of multiplex, multigenerational families reveal schizophrenia risk loci with potential implications for neurocognitive performance. Am J Med Genet B Neuropsychiatr Genet 174:817-827
Kos, Mark Z; Carless, Melanie A; Peralta, Juan et al. (2016) Exome Sequence Data From Multigenerational Families Implicate AMPA Receptor Trafficking in Neurocognitive Impairment and Schizophrenia Risk. Schizophr Bull 42:288-300
Roalf, David R; Vandekar, Simon N; Almasy, Laura et al. (2015) Heritability of subcortical and limbic brain volume and shape in multiplex-multigenerational families with schizophrenia. Biol Psychiatry 77:137-46
Roalf, David R; Ruparel, Kosha; Gur, Raquel E et al. (2014) Neuroimaging predictors of cognitive performance across a standardized neurocognitive battery. Neuropsychology 28:161-76
Glahn, David C; Knowles, Emma E M; McKay, D Reese et al. (2014) Arguments for the sake of endophenotypes: examining common misconceptions about the use of endophenotypes in psychiatric genetics. Am J Med Genet B Neuropsychiatr Genet 165B:122-30
Roalf, David R; Gur, Ruben C; Almasy, Laura et al. (2013) Neurocognitive performance stability in a multiplex multigenerational study of schizophrenia. Schizophr Bull 39:1008-17
Da Silva, Felipe N; Irani, Farzin; Richard, Jan et al. (2012) More than just tapping: index finger-tapping measures procedural learning in schizophrenia. Schizophr Res 137:234-40
Yokley, Jessica L; Prasad, Konasale M; Chowdari, Kodavali V et al. (2012) Genetic associations between neuregulin-1 SNPs and neurocognitive function in multigenerational, multiplex schizophrenia families. Psychiatr Genet 22:70-81
Tarbox, Sarah I; Almasy, Laura; Gur, Raquel E et al. (2012) The nature of schizotypy among multigenerational multiplex schizophrenia families. J Abnorm Psychol 121:396-406
Drago, Antonio; Giegling, Ina; Schäfer, Martin et al. (2012) No association of a set of candidate genes on haloperidol side effects. PLoS One 7:e44853

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