W7. MASSIVELY PARALLEL CHARACTERIZATION OF COMMON GENETIC RISK VARIANTS FOR MENTAL HEALTH DISORDERS IN GLUTAMATERGIC NEURONS

Background Mental health disorders such as schizophrenia, bipolar disorder, attention deficit hyperactivity disorder, and autism spectrum disorder are highly heritable conditions that strongly impact patients’ quality of life. Recent genome-wide association studies (GWAS) have identified thousands of associated risk variants, the majority of which are located in non-coding regions of the genome. However, the functional consequences of these variants remain largely unclear. Here, we investigated the enhancer activity of psychiatric risk variants using massively parallel reporter assays (MPRAs) in human iPSC-derived NGN2-induced glutamatergic neurons. Methods We selected approximately 40,000 common risk variants associated with the disorders mentioned above from recent GWAS datasets. For each variant, 270 base pair oligonucleotides containing either the reference or risk allele were synthesized, with the variant positioned in the center of the sequence. In addition, alternative oligonucleotide designs with shifted variant positions were generated based on chromatin accessibility predictions from ChromBPNet a deep learning model trained on ATAC-seq data from NGN2-induced neurons. Oligonucleotides were linked to unique barcodes, cloned upstream of a minimal promoter driving GFP expression, and packaged into lentivirus for transduction into human iPSC-derived NGN2-induced glutamatergic neurons. DNA and RNA were isolated, barcode abundance was quantified by sequencing, and enhancer activity was calculated as the RNA/DNA barcode ratio. MPRA activity and allelic effects were assessed using MPRAnalyze and complementary statistical approaches. Results Preliminary analyses demonstrated high reproducibility between biological replicates and clear separation between positive and negative control elements, supporting robust assay performance. Using MPRAnalyze, we identified 275 significant active regulatory elements and 324 variants with significant allelic regulatory effects between risk and reference alleles. Most regulatory effects were modest in magnitude, consistent with the polygenic architecture of psychiatric disorders. Integration of activity and allelic analyses identified candidate expression-modulating variants with potential causal regulatory roles at psychiatric GWAS loci. Discussion The identification of active and allelic regulatory variants provides insight into the molecular mechanisms linking non-coding genetic variation to psychiatric disease risk. Future analyses will integrate MPRA results with epigenomic annotations, GWAS fine-mapping, transcription factor motif disruption, and disease-associated gene networks, while comparing regulatory effects at shared and disorder-specific risk loci to identify convergent and distinct molecular mechanisms across psychiatric disorders.