biostudies-literatureSrinivasan CCarnegie Mellon Computational Biology Department Lane Postdoctoral FellowshipNIDA NIH HHSHHS | NIH | National Institute of General Medical SciencesCarnegie Mellon Brainhub Presidential FellowshipHHS | NIH | National Institute on Drug AbuseAlfred P. Sloan FoundationNIGMS NIH HHSNational Science Foundation9008-9030https://www.ebi.ac.uk/biostudies/studies/S-EPMC8549541biostudies-literatureUnknown41(43)Recent large genome-wide association studies have identified multiple confident risk loci linked to addiction-associated behavioral traits. Most genetic variants linked to addiction-associated traits lie in noncoding regions of the genome, likely disrupting <i>cis</i>-regulatory element (CRE) function. CREs tend to be highly cell type-specific and may contribute to the functional development of the neural circuits underlying addiction. Yet, a systematic approach for predicting the impact of risk variants on the CREs of specific cell populations is lacking. To dissect the cell types and brain regions underlying addiction-associated traits, we applied stratified linkage disequilibrium score regression to compare genome-wide association studies to genomic regions collected from human and mousThe Journal of neuroscience : the official journal of the Society for NeuroscienceAddiction-Associated Genetic Variants Implicate Brain Cell Type- and Region-Specific Cis-Regulatory Elements in Addiction Neurobiology.PMC8549541DP1 DA0465851DP1DA046585DGE1745016F30 DA053020T32GM008208F30DA053020T32 GM008208Phan BNRamamurthy ELawler AJBrown ARSrinivasan CKleyman MKaplow IMWirthlin MEPfenning ARfalseAddiction-Associated Genetic Variants Implicate Brain Cell Type- and Region-Specific Cis-Regulatory Elements in Addiction Neurobiology.Recent large genome-wide association studies have identified multiple confident risk loci linked to addiction-associated behavioral traits. Most genetic variants linked to addiction-associated traits lie in noncoding regions of the genome, likely disrupting <i>cis</i>-regulatory element (CRE) function. CREs tend to be highly cell type-specific and may contribute to the functional development of the neural circuits underlying addiction. Yet, a systematic approach for predicting the impact of risk variants on the CREs of specific cell populations is lacking. To dissect the cell types and brain regions underlying addiction-associated traits, we applied stratified linkage disequilibrium score regression to compare genome-wide association studies to genomic regions collected from human and mous2021-01-01T00:00:00Z2021 Oct2026-06-17T06:24:16.085Z2025-02-19T01:26:08.985ZS-EPMC85495413446230610.1523/JNEUROSCI.2534-20.2021