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Understanding how genetic variation influences complex traits and disease risk remains a major challenge in human genomics. Although genome-wide association studies (GWAS) have identified tens of thousands of risk loci, most lie in non-coding regions 6 , complicating interpretation. One common approach to bridge this gap is to map molecular QTLs (molQTLs), identifying genetic variants that affect intermediate molecular phenotypes such as gene expression or chromatin accessibility, and then test for colocalization with GWAS loci to infer potential regulatory mechanisms 7 . Most molQTL studies have focused on eQTLs derived from bulk RNA sequencing (RNA-seq), which have low sensitivity for cell-type-specific effects 8 , 9 . Recently, well-powered single-cell RNA-seq (scRNA-seq) studies have shown that genetic regulation of gene expression varies across cell types and states 10 , 11 , 12 , 13 , 14 .…