Recent advances in human molecular genetics and genetic epidemiology can allow the successful genetic dissection of complex diseases. For disorders with an unknown biochemical basis, identification of the genes is a prerequisite to their understanding of its biological basis. Nowhere can this success be more helpful than in psychiatric diseases. This application for a Multi-Institutional Collaborative Research Project (MICRP) is designed to identify regions of the human genome involved in susceptibility to schizophrenia. It involves a collaborative effort between groups at the University of Pittsburgh and Case Western Reserve University. This research is proposed as a research paradigm for the genetic dissection of multigenic disorders. Schizophrenia is a severe psychiatric illness with a lifetime morbid risk of approximately 1 percent. Its precise etiology is unknown and treatment remains palliative. A significant inherited predisposition has been established, but the mode of inheritance is uncertain. In this application the investigators propose contemporary methods in research design, family ascertainment, genotyping and linkage/association analyses to dissect the genetic factors in schizophrenia. The investigators propose to ascertain a large sample of nuclear families with affected individuals. The families will include those with one ill individual, as well as those with two or more affected. Linkage analysis will be conducted initially using the affected sib-pairs. State-of-the-art genotyping of highly polymorphic anonymous markers spaced at 10 cM intervals throughout the genome and novel statistical genetic analysis will be used to identify regions spanning susceptibility loci. Such regions will be further investigated using more densely spaced markers and parents of probands. Subsequently, anonymous markers and those of candidate genes thought to be linked to the disease genes will be further evaluated using the haplotype relative risk (HRR) and transmission disequilibrium test (TDT) methods. The combined linkage and association approach are a powerful combination for investigating the genetic basis of disease.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Unknown (R10)
Project #
3R10MH056242-04S1
Application #
6448834
Study Section
Genome Study Section (GNM)
Program Officer
Moldin, Steven Owen
Project Start
1997-06-01
Project End
2002-05-31
Budget Start
2000-06-15
Budget End
2001-05-31
Support Year
4
Fiscal Year
2001
Total Cost
$27,582
Indirect Cost
Name
University of Pittsburgh
Department
Psychiatry
Type
Schools of Medicine
DUNS #
053785812
City
Pittsburgh
State
PA
Country
United States
Zip Code
15213
Bhatia, Triptish; Wood, Joel; Iyengar, Satish et al. (2018) Emotion discrimination in humans: Its association with HSV-1 infection and its improvement with antiviral treatment. Schizophr Res 193:161-167
Bhatia, Triptish; Gettig, Elizabeth A; Gottesman, Irving I et al. (2016) Stratifying empiric risk of schizophrenia among first degree relatives using multiple predictors in two independent Indian samples. Asian J Psychiatr 24:79-84
De, Sreeja; Bhatia, Triptish; Thomas, Pramod et al. (2013) Bizarre delusions: a qualitative study on Indian schizophrenia patients. Indian J Psychol Med 35:268-72
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Bhatia, Triptish; Agarwal, Akhilesh; Shah, Gyandeepak et al. (2012) Adjunctive cognitive remediation for schizophrenia using yoga: an open, non-randomized trial. Acta Neuropsychiatr 24:91-100
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
Thomas, Pramod; Chandra, Abha; Bhatia, Triptish et al. (2011) Clinical and genetic correlates of severity in schizophrenia in India: an ordinal logistic regression approach. Psychiatry Res 189:321-3
Chen, X; Lee, G; Maher, B S et al. (2011) GWA study data mining and independent replication identify cardiomyopathy-associated 5 (CMYA5) as a risk gene for schizophrenia. Mol Psychiatry 16:1117-29

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