{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"medRxiv"}],"indexed":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T02:02:00Z","timestamp":1781661720190,"version":"3.54.5"},"posted":{"date-parts":[[2024,8,12]]},"group-title":"Allergy and Immunology","reference-count":90,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2024,8,12]],"date-time":"2024-08-12T00:00:00Z","timestamp":1723420800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2025,5,20]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                <jats:p>\n                  Genome-wide association studies (GWAS) have identified genetic links to autoimmune disorders, but lack detail on causal elements. We generated 3D genomic datasets of promoter-focused Capture-C, Hi-C, ATAC-seq, and RNA-seq across 57 human cell types integrated with GWAS of 16 autoimmune traits. These data allowed us to map disease-associated variants to their effector genes and identify impacted cell types more effectively than using 1D genomic features or eQTL approaches. Most variants implicated by 3D cis-regulatory architectures are trait-specific, while half the target genes are shared across multiple disorders and cell types, leading to enrichment of similar biological networks. This indicates complex genetic diversity converges on shared targets, yet unique pathways were identified offering avenues for targeted therapies. We pharmacologically validated squalene synthase, a cholesterol biosynthetic enzyme encoded by the\n                  <jats:italic>FDFT1<\/jats:italic>\n                  gene implicated by our approach and eQTL in multiple sclerosis and systemic lupus erythematosus, as a novel immunomodulatory drug target controlling T cell inflammatory cytokine production and aiding B cell antibody production in a human lymphoid organoid model. These data offer a comprehensive resource for understanding gene cis-regulatory mechanisms, and the analyses shed light on how autoimmune-associated variants regulate gene expression, function, and pathology across diverse tissues and cell types.\n                <\/jats:p>","DOI":"10.1101\/2024.08.12.24311676","type":"posted-content","created":{"date-parts":[[2024,8,13]],"date-time":"2024-08-13T00:05:23Z","timestamp":1723507523000},"source":"Crossref","is-referenced-by-count":2,"title":["3D chromatin-based variant-to-gene maps across 57 human cell types reveal the cellular and genetic architecture of autoimmune disease susceptibility"],"prefix":"10.64898","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9434-508X","authenticated-orcid":false,"given":"Khanh 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