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NIDA and NHGRI announce new PhenX measures for substance abuse and addiction

PhenX logo Genetic variants that are related to substance abuse and addiction are notoriously difficult to pinpoint. Part of the problem is that numerous genes might be implicated, each making a small but important contribution to substance abuse or addiction. Another factor is that researchers collect information on research participants' physical characteristics and environmental exposures in different ways, making it difficult to combine the data.

New standardized substance abuse and addiction measures, published February 24 on www.phenxtoolkit.org, will make it easier for researchers to combine studies and gain the much-needed statistical power to identify gene-gene or gene-environment interactions. The substance abuse and addiction measures are part of the Consensus Measures for Phenotype and eXposures Toolkit (PhenX). The National Human Genome Research Institute (NHGRI) and several other National Institutes of Health (NIH) institutes and centers provided funding for the PhenX Toolkit, which contains nearly 300 standardized measures and protocols across 21 different research areas. Of these measures, 15 were alcohol and substance abuse measures. The National Institute on Drug Abuse (NIDA) wanted a wider and deeper set of measures for grantees to increase collaboration and data comparability, so it turned to the PhenX Toolkit, which is led by Carol Hamilton, Ph.D., director of bioinformatics at RTI International, Research Triangle Park, N.C.

"The success of PhenX depends on its use by many different communities of researchers, such as those performing work of interest to NIDA. Their efforts will accelerate discovery of the genetic and environmental factors involved in common diseases," said Eric D. Green, M.D., Ph.D., NHGRI director.

The PhenX team used a consensus-based process to select and develop 43 additional high priority substance abuse and addiction measures. To do this, the PhenX team convened a Substance Abuse and Addiction Scientific Panel, a team of 10 outstanding academic and federal governmental scientists who provided input on the measures. The panel, chaired by Kenneth Sher, Ph.D., University of Missouri, identified collections to be developed, provided advice on three working groups, monitored their progress, and reviewed and approved recommendations for phenotype and environmental exposure measures. The three working groups identified measures for each of their two specialty areas, including:

    WG 1 (Substance Use) co-chaired by Drs. Harriet de Wit, Ph.D., University of Chicago, and Stephanie O'Malley, Ph.D., Yale University

    • Assessment of substance use and substance use disorders
    • Substance-specific intermediate phenotypes

    WG 2 (Risk Factors) chaired by Matt McGue, Ph.D., University of Minnesota

    • Substance use-related neurobehavioral and cognitive risk factors
    • Substance use-related psychosocial risk factors

    WG 3 (Community, Comorbidities and Outcomes) co-chaired by Frank Chaloupka, Ph.D., University of Illinois at Chicago, and Patrick Flynn, Ph.D., Texas Christian University

    • Substance use-related community factors
    • Substance use-related comorbidities and health-related outcomes

"NIDA is encouraging all grant applicants proposing human-subjects research to use the PhenX Toolkit to increase scientists' ability to combine data and work together across studies," said Kevin P. Conway, Ph.D., deputy director of NIDA's Division of Epidemiology, Services and Prevention Research. "The toolkit is a tremendous resource that provides access to standard measures of key biological, psychological and environmental constructs. By using common measures, researchers can readily combine datasets to improve statistical power to detect smaller, but important, effect sizes."

To help researchers use PhenX measures, NHGRI developed the webinar: The PhenX Toolkit — Get the Most from your Measures [youtube.com]. For general information about the PhenX program, please contact Heather Junkins, project analyst, at junkinsh@mail.nih.gov or 301-402-0343.

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Posted: February 24, 2012

Last updated: February 24, 2012