The Consortium on the Genetics of Schizophrenia (COGS-2) is a 6-site collaborative linked R01 study that aims to understand the genetic architecture of functionally important quantitative neurophysiological and neurocognitive endophenotypes and the qualitative phenotype of schizophrenia in 2,000 patients and 1,000 community comparison subjects (CCS). During the initial support period, the COGS-1 project developed a robust research platform for subject recruitment, careful clinical characterization, acquisition, quality assurance, and analysis of these endophenotypes in probands (N=305), clinically unaffected family members (N=1,014) and CCS (N=505). In addition, COGS-1 developed novel statistical genetics methods that take full advantage of the unique findings that have emerged to date. The COGS-2 renewal will extend the use of the original 3 neurophysiological and 3 neurocognitive endophenotypes, as well as additional heritable endophenotypes derived from COGS-1 using the Computerized Neurocognitive Battery (CNB). Given the increased importance of the relationship of these endophenotypes to functional outcome, COGS-2 will also add a functional status assessment battery, consisting of observer-based, surrogate and real-world functional status. COGS-2 will complete the originally proposed linkage analysis in the COGS-1 sample, as well as conduct a candidate gene study from the COGS-1 database using the custom COGS 1536 SNP Chip. COGS-2 will focus on ascertaining, testing and obtaining DNA from new samples of 2,000 schizophrenia patients and 1,000 CCS recruited via Specific Aim 1.
In Specific Aim 2, a genome wide association study (GWAS) using the current and most informative platform at the Center for Inherited Disease Research (CIDR) will be performed using the COGS-2 case-control data on the 9 COGS-2 quantitative endophenotypes and the qualitative diagnosis of schizophrenia. A complementary association study, using many strong-inference derived SNPs not included in the CIDR platform, will utilize the COGS SNP Chip array (94 candidate genes, 1536 SNPs) to assess SNP and copy-number variations (CNVs) associated with endophenotype deficits in schizophrenia as well as schizophrenia itself.
In Specific Aim 3, SNPs and CNVs associated with these endophenotypes and schizophrenia will be compared with those in publicly available databases (e.g., GAIN, CATIE, BROAD). Furthermore, we will continue to develop the COGS platform and related innovative statistical genetics methods to identify and interrogate crucial genetic data in order to enhance the search for schizophrenia vulnerability genes, enhance the endophenotype strategy and ultimately identify molecular targets for the treatment and improved function of schizophrenia patients.

Public Health Relevance

Schizophrenia is a devastating brain disorder that strikes young adults and carries with it a profound and devastating disease burden, often for the lifetime of the patient. The Consortium on the Genetics of Schizophrenia (""""""""COGS-2"""""""") project entitled, """"""""The Genetics of Endophenotypes and Schizophrenia"""""""", examines the genetic basis of impairments in core neurophysiological and neurocognitive processes in schizophrenia patients. Once we understand the genetic architecture of these abnormalities, new medications that aim to improve the functioning and quality of life of schizophrenia patients can be developed.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
2R01MH065571-06A2
Application #
7886929
Study Section
Special Emphasis Panel (ZRG1-PSE-E (60))
Program Officer
Koester, Susan E
Project Start
2003-04-04
Project End
2014-01-31
Budget Start
2010-04-16
Budget End
2011-01-31
Support Year
6
Fiscal Year
2010
Total Cost
$833,656
Indirect Cost
Name
University of California San Diego
Department
Psychiatry
Type
Schools of Medicine
DUNS #
804355790
City
La Jolla
State
CA
Country
United States
Zip Code
92093
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Light, Gregory A; Swerdlow, Neal R (2015) Future clinical uses of neurophysiological biomarkers to predict and monitor treatment response for schizophrenia. Ann N Y Acad Sci 1344:105-19

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