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| Funder | NATIONAL INSTITUTE ON DRUG ABUSE |
|---|---|
| Recipient Organization | University of Maryland, College Park |
| Country | United States |
| Start Date | Sep 01, 2024 |
| End Date | Aug 31, 2028 |
| Duration | 1,460 days |
| Number of Grantees | 1 |
| Roles | Principal Investigator |
| Data Source | NIH (US) |
| Grant ID | 10984753 |
ABSTRACT Substance use disorders (SUDs) are complex and heritable mental disorders and serious public health challenge with uncontrolled use of substances like tobacco, alcohol and cannabis. SUDs are highly heritable (h2~40-70%), with multiple replicable genetic loci associated with SUDs reported by large-scale Genome Wide
Association Studies (GWAS). Neuroimaging studies using magnetic resonance imaging (MRI) techniques showed alterations in both gray and white matter structural and functional signatures of addiction, however, the pathway from genes to brain alternations to addiction remained unclear. In this project, we focus on brain
functional connectivity (FC) data and hypothesize that genes impact addiction partially via modification in brain FC. My goal in seeking this Mentored Research Scientist Development K01 Award is to have protected time and acquire the necessary training from the mentoring team in (1) analysis of functional MRI data; (2)
understanding clinical and neurobiology of nicotine and cannabis addiction; (3) exploration of large-scale imaging genetics linked to addiction behavioral data; (4) developing grant writing and management skills. The knowledge and hands-on experience gained from this project will help the PI develop into a leading
independent investigator in the field leveraging various types of big data (e.g. neuroimaging, multi-omics) to improve the mechanistic understanding of addiction and mental illness and contribute to his long-term career success. GWAS identify gene-trait association at SNP level, but do not yield direct evidence on gene function
or the underlying biological mechanisms. Transcriptome-wide association studies (TWAS) fill this gap by using GWAS data and expression quantitative trait loci (eQTL) to perform gene-level association analyses that informs potential tissue-dependent functions of candidate loci. The proposed project will combine the PI’s
background in statistical genetics with the additional training in neuroimaging and neurobiology of addiction to advance novel TWAS methods development to identify genes associated with brain FC changes as well as pleiotropic genes associated with both brain FC and addiction, which is a critical first step to our understanding
of the hypothesized gene->FC-> addiction causal mediation pathway. Specifically, in Aim 1, we will develop a new TWAS method with robust statistics for cross-sectional genetic-rsFC studies on nicotine addiction and identify pleiotropic genes associated with both FC and nicotine addiction; in Aim 2, we will perform TWAS for
genetic-rsFC studies on cannabis use and identify pleiotropic genes associated with both FC and cannabis use; in Aim 3, we will develop software package to implement the methods and a FC- addiction-TWAS database with curated knowledge. Successful completion of this project will provide the PI with the new
skillsets and preliminary data to develop a subsequent R01 application. 1
University of Maryland, College Park
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