a.l Scientific Overview The Collaborative Study on the Genetics of Alcoholism (COGA) has been a remarkably productive collaboration. We have been very successful in identifying individual genes that influence the risk for alcoholism and genes that influence endophenotypes, including electrophysiological measures. Some of our key flndings have already been replicated by other groups. This is notable in this (or any) complex disease and attests to the robustness of COGA methodologies. We have been very successful in assembling and interviewing sample of over 1800 families of varying levels of risk for alcohol dependence, including a large number of densely affected (HIGH DENSITY) families. In the larger study, participants vary in ages from 7-72 years and have been carefully characterized using standardized clinical and neurophysiological assessments. Great care has been taken to ensure the reliability of all data collection and laboratory procedures across the participating data collection and analysis sites. This has given us a very rich dataset and repository of phenotypic and neurophysiological data, cell lines and DNA for current and future studies within COGA. Importantly, we have made this dataset available to the broader field of researchers to allow others to benefit from it. For example, this dataset has twice served as a test bed for developing genetic analysis tools as part of two Genetic Analysis Workshops (GAW-11 and GAW-14). Both phenotypic and biological samples and data are widely available to the scientific community through our NIAAA/COGA Sharing Repository, which has leveraged their value, in both scientific and monetary terms. We have developed new phenotypes and studied the relationships among them. We have successfully begun a prospective study of adolescents and young adults, from our well-characterized families, as they move into and pass through the prime age of risk for alcohol dependence. This will allow us to study how genetic variation that influences risk for or protection from alcoholism acts as a function of development, and to examine gene-environment interplay. The value of this prospective study is enriched In that many ofthe subjects come from the HIGH DENSITY families in which we have identified genes affecting the risk for alcoholism. COGA is a very successful collaboration, built upon complementary strengths of a strong team of scientists, to which younger colleagues have been added over the years. We have established paradigms for ascertainment and assessment that have become standards for the field;for example, the SSAGA interview that we developed has been adopted by many other groups both in the US and around the worid. Our sample collection and repository of transformed lymphoblastoid lines have been state-of-the-art;in fact, the Rutgers University Cell and DNA Repository, now a major resource used by many NIH institutes, was initially established as part of COGA. These data and samples have been made available to other scientists in the field. Our foresight in establishing cell lines from a large fraction of the COGA subjects now allows us to carry out studies on gene regulation and function in cells with the genetic variants we have identified. Our strategy of proceeding from linkage to assodation, by using many SNPs to analyze the variation within candidate genes, was innovative. We hypothesized eariy that large linkage peaks were the result of contributions from multiple genes, and we have demonstrated that in our studies. Our emphasis on endophenotypes, including electrophysiology, as part of our gene identiflcation strategy was also innovative and has proven to be a powerful tool in the search for genes affecting the susceptibility for alcoholism. As the technology has dramatically improved to test genetic association, we have also performed one of the flrst genome wide association studies for alcohol dependence.

Agency
National Institute of Health (NIH)
Institute
National Institute on Alcohol Abuse and Alcoholism (NIAAA)
Type
Cooperative Clinical Research--Cooperative Agreements (U10)
Project #
5U10AA008401-25
Application #
8537100
Study Section
Special Emphasis Panel (ZAA1-CC)
Project Start
Project End
Budget Start
2013-09-01
Budget End
2014-08-31
Support Year
25
Fiscal Year
2013
Total Cost
$1,156,710
Indirect Cost
$427,148
Name
Suny Downstate Medical Center
Department
Type
DUNS #
040796328
City
Brooklyn
State
NY
Country
United States
Zip Code
11203
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Dick, Danielle M (2018) Commentary for Special Issue of Prevention Science ""Using Genetics in Prevention: Science Fiction or Science Fact?"" Prev Sci 19:101-108
Liu, Dungang; Zhang, Heping (2018) Residuals and Diagnostics for Ordinal Regression Models: A Surrogate Approach. J Am Stat Assoc 113:845-854

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