{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,13]],"date-time":"2026-05-13T16:27:38Z","timestamp":1778689658574,"version":"3.51.4"},"reference-count":45,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,11,17]],"date-time":"2025-11-17T00:00:00Z","timestamp":1763337600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Genet."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Psoriasis is a chronic immune-mediated skin disorder characterized by excessive keratinocyte proliferation and localized inflammation. A comprehensive understanding of its molecular mechanisms is crucial for improving disease management and developing targeted therapies.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>This study aimed to investigate the molecular mechanisms underlying psoriasis by integrating single-cell RNA sequencing with Mendelian randomization (MR) analysis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Single-cell transcriptomic data from 174 skin samples (92 from psoriasis patients and 82 from healthy controls) were obtained from the GEO database. Data processing was conducted using the Seurat package, including quality control, normalization, dimensionality reduction, and cell-type annotation, ultimately identifying 11 distinct cell populations. MR analysis was then performed using summary statistics from the EBI database (n = 484,598) to assess the putative relationships between candidate genes and psoriasis risk.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Seven genetically informed candidate genes were identified as being significantly associated with psoriasis susceptibility. Among them, BIN2 and CAPN12 were linked to an increased risk, while genes such as CXXC5 and KLRD1 were associated with decreased risk. These genes were predominantly expressed in CD4\n                      <jats:sup>+<\/jats:sup>\n                      T cells. Functional enrichment analyses, including Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA), revealed their involvement in critical immune-related pathways, such as the IL-17 signaling and NOD-like receptor signaling pathways. Immune infiltration analysis demonstrated an elevated abundance of various immune cell types in psoriasis lesions. Moreover, transcription factor regulatory network analysis suggested that specific transcription factors may regulate the expression of these core genes, thereby contributing to psoriasis pathogenesis.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>\n                      By integrating single-cell RNA sequencing with MR analysis, we identified seven psoriasis-related genes (BIN2, CAPN12, CXXC5, KLRC1, KLRD1, PRF1, and SLFN5) that are highly expressed in CD4\n                      <jats:sup>+<\/jats:sup>\n                      T cells. These genes hold promise as potential biomarkers for psoriasis diagnosis and as novel therapeutic targets.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fgene.2025.1634874","type":"journal-article","created":{"date-parts":[[2025,11,17]],"date-time":"2025-11-17T01:59:51Z","timestamp":1763344791000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Potential marker genes for psoriasis revealed based on single-cell sequencing and Mendelian randomization analysis"],"prefix":"10.3389","volume":"16","author":[{"given":"Ying","family":"Dong","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hong-Song","family":"Ge","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rui-Xue","family":"Chang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jing","family":"Chu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2025,11,17]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"e1463","DOI":"10.1002\/cti2.1463","article-title":"A unique cytotoxic CD4+ T cell-signature defines critical COVID-19","volume":"12","author":"Baird","year":"2023","journal-title":"Clin. 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