NEW YORK (GenomeWeb News) – The National Institute on Drug Abuse sees great potential for applying genetic and genomic knowledge to addiction research, and plans to fund the creation of education programs to train scientists in ways to analyze and use genetic data in addiction research.
Under a new funding program, NIDA will award grants of up to $500,000 to encourage research education efforts that will focus on statistical and computational models to address genetics-based problems related to addiction.
NIDA has already prioritized genetic studies of addiction, with an emphasis on epigenetic and functional genetics; genetic epidemiology projects pursuing the hereditary aspects of addiction; molecular genetic studies of addiction to discover genes and variants that may be associated with substance abuse; and studies integrating genetics with neuroimaging, among others.
Such research is generating large amounts of complex genetic and phenotypic data that requires more sophisticated statistical and computational models for analysis. There currently is a shortage of individuals who are trained to generate innovative approaches in statistical genetics and computational models, according to NIDA, and new advancements in understanding and treating addiction will require that genomic information be used with other types of data and that new technologies, computational approaches, large-scale databases, and analytic methods are required to make sense and use of all this information. NIDA said.
The agency said that a new workforce for studying genetics and addiction will need to be trained in methods to develop algorithms for analyzing and interpreting this data, as well as ways to present genomic information to researchers. This new research education funding program seeks to support such statistical and computational training programs.
These research education projects may focus on gene-environment interplay; genetic epistasis; integration of genetic and imaging data; methods for analyzing gene variants and copy number variants associated with addiction, and other similar research areas.
Applicants may seek funding for education programs to use statistical and computational methods for a range of project types, such as analyzing data from genome-wide association studies and whole-genome sequence data; analyzing the genetic structure of populations; modeling and analyzing correlations among genetic, environmental, and developmental factors; improving software for complex trait analysis that incorporates GWAS, epigenomic data, and some gene expression data; meta-and mega-analysis of genetic studies of addiction, and other similar types of research.
NIDA wants the applicants to plan well-integrated research education and training programs that will result in new computational and statistical models that are relevant to the genetics of addiction.