Mapping the genetic regulation of long non-coding RNAs across cellular contexts advances understanding of complex brain diseases

Long non-coding RNAs (lncRNAs) play essential roles in the pathogenesis of neurological disease, but the cellular heterogeneity of their genetic regulation remains poorly understood, with a key barrier being the resolution–power trade-off between bulk and single-nucleus eQTL studies. Here, we profiled 17,541 lncRNAs including both GENCODE-annotated and newly assembled transcripts in the dorsolateral prefrontal cortex (DLPFC) of 2,443 individuals and performed interaction eQTL (ieQTL) mapping based on computational deconvolution. We identified 3,763 interaction-effect lncRNAs (ieLncRNAs) across brain cell types, including 2,783 (74%) previously unannotated in GENCODE and 3,262 (86%) not captured in current single-nucleus eQTL resources. Integration of lncRNA-ieQTLs with GWAS data of brain-related diseases indicated that nearly two-thirds of colocalization signals were missed by bulk eQTL analyses, underscoring the added interpretive resolution afforded by modeling cellular context. We further illustrate this with representative loci, including AC096667.1 and lncRNAs overlapping NRGN, which show cell-context–dependent colocalization with neuroticism and schizophrenia risk, respectively, refining the cellular interpretation of genetic risk. Collectively, this resource advances our understanding of lncRNA contributions to brain disease by uncovering regulatory effects that are obscured in bulk tissues and not captured by single-nucleus eQTL resources.