COGA is a family-based study that has developed interview instruments and generated genetic data on a large number of individuals, the majority from families heavily affected by alcohol dependence. COGA welcomes qualified researchers who want to use these interview instruments and/or data. They can be accessed by collaboration or the data can be requested directly in several ways.
Accessing COGA Data
Please note that COGA data being currently collected are deposited in the NIAAA Data Archive (https://nda.nih.gov/niaaa).
(1) Collaborate directly with COGA investigators.
The advantage of this approach is that COGA collaborators can help navigate the extensive phenotypic and genotypic datasets. If you are interested in working with COGA on a project, start by identifying a COGA researcher with interests that map on to the project you would like to pursue or reach out to any one of the project leaders listed below and they can help you through this process. Your COGA data buddy can help you navigate the collaboration process, which will involve writing an abstract of the proposed work, presenting your work on a COGA call, and inviting other COGA collaborators with relevant expertise to be involved.
Genetics & Genomics: Arpana Agrawal (arpana@wustl.edu) & Yunlong Liu (yunliu@iu.edu)
Clinical and Behavioral Phenotypes: Victor Hesselbrock (hesselbrock@uchc.edu), Laura Bierut (laura@wustl.edu), Jessica Salvatore (jessica.salvatore@rutgers.edu)
EEG and Brain Function: Bernice Porjesz (bernice.porjesz@downstate.edu) & Jacquelyn Meyers (Jacquelyn.Meyers@downstate.edu)
Translational components: Danielle Dick (danielle.m.dick@rutgers.edu)
General data access questions: Sarah Hartz (hartzs@wustl.edu)
(2) Access data through dbGaP
GWAS data, along with limited phenotypic data, are available through NCBI (National Center for Biotechnology Information). For all datasets the subject ID is randomized and different than the ID used by COGA investigators, to protect against re-identification. Each of these datasets contains unique individuals, genotyped at different stages in the project, with the exception of 2-127 samples genotyped on at least two different arrays to assess quality. Links to dbGaP are in the table below. See Lai et al (2019) for more detail.
(3) Access experimental data from COGA induced pluripotent stem cells via GEO:
Access to Biomaterials
Rutgers University stores, maintains, and distributes biomaterials consisting of lymphoblastoid cell lines and DNA from participating subjects.
The table is a list of all iPSCs available from Sampled, Inc., our repository contractor. Please contact Dr. Ronald Hart (rhart@rutgers.edu) with questions.
COGA iPSC lines available through the NIAAA/COGA Sharing Repository. Use the Clone Inventory Code in the request. The Cell ID, Sex, and Group match cell line identifiers in publications denoted in the Study column (Popova: https://doi.org/10.1038/s41380-022-01818-x; Li: https://doi.org/10.1101/2024.02.19.581066). Matcode Source indicates the cell type used for reprogramming: CPL: cryopreserved lymphocytes; ERYB: erythroblasts; LCL: lymphocyte cell line. In most cases, multiple, reprogrammed iPSC were prepared and frozen but generally only the A clone was used in published studies.
COGA Instruments
COGA developed the Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA) interview, which we make freely available for researchers. The SSAGA is available in both adult and child forms. Different versions of the SSAGA have been administered across the different phases of data collection. To obtain the most recent version of the SSAGA, along with associated diagnostic algorithms, please contact Dr. Victor Hesselbrock.
Data Entry in Blaise
SSAGA-IV Entry Program – Instructions for downloading Blaise
Installation:
Users must obtain a Blaise license to download the dep.exe file. Once this is done, please email Sue Winkeler at winkeler@wustl.edu to obtain a password.
After downloading the Blaise executable file, dep.exe, unzip it to a folder of your choice. Note: If all files are unzipped to the same directory along with the dep.exe file, the specification pathnames will be simplified.
To Test:
Click on dep.exe in your folder. A window will open up. You will be prompted to enter the name of the data model. Paste or type the pathname for the test section chosen (e.g. tstDR.bdb) in the window.
On the first screen of the entry program, you will be prompted to enter the ID.
You may stop at this time during the data entry process and save the entered data. You may go back and change any previously entered responses. The program will enforce any changes to skip-out patterns associated with the changed responses.
Comments:
Some age checks are missing. This is intentional. These were omitted at the suggestion of the Assessment Committee.
CSSAGA-IV Entry Program
Electronic Data Entry using ASPECT with the SSAGA form heading
