{ "abstract": "Per- and polyfluoroalkyl substances (PFAS) are persistent environmental pollutants with bioaccumulation potential, but their associations with kidney diseases remain incompletely understood. This study integrated Mendelian randomization and computational toxicology to examine associations between genetically predicted circulating PFAS levels and kidney disease outcomes and to prioritize candidate toxicogenomic pathway themes. Genetically predicted higher PFOA levels were inversely associated with IgA nephropathy (OR = 0.21, P = 0.004), but positively associated with hypertensive nephropathy (OR = 1.20, P < 0.001) and calculus of kidney (OR = 1.24, P = 0.016). Genetically predicted higher PFOS levels were inversely associated with IgA nephropathy (OR = 0.27, P = 0.046) and urinary tract infection (OR = 0.94, P = 0.003). A primary association was also observed between PFOA and membranous nephropathy (OR = 1.56, P = 0.028), but this association was not retained after targeted SNP-exclusion analyses and was therefore not interpreted as a robust or established causal association. Computational toxicology analyses prioritized database-derived candidate targets and pathway themes related to immune response, inflammation, oxidative stress, and apoptosis. Network-prioritized candidate nodes included CTNNB1, TP53, and EGFR in the PFOA–calculus of kidney network, IGF1 in the PFOA–hypertensive nephropathy network, and CCL2, TLR4, MMP9, and IFNG in the PFOA/PFOS–IgA nephropathy networks. In contrast, IL1B, TNF, and IL6 were observed as shared inflammatory nodes across multiple nephropathy-related networks. These candidates should be interpreted as database-derived and network-prioritized targets rather than experimentally validated causal mediators of kidney disease. Overall, this study provides a hypothesis-generating framework for exploring associations among genetically predicted PFAS-related traits, kidney disease outcomes, and candidate toxicogenomic pathway themes that require experimental validation. Author summary: Per- and polyfluoroalkyl substances (PFAS) are a group of persistent environmental chemicals widely detected in water, food, consumer products, and human blood. Because the kidneys are involved in filtration, tubular handling, and chemical elimination, they may be particularly relevant to long-term PFAS-related biological effects. However, it remains challenging to determine how circulating PFAS-related traits are associated with specific kidney disease outcomes and which molecular pathway themes warrant further study. In this study, we combined genetic epidemiology with computational toxicology to investigate associations between genetically predicted circulating PFAS-related traits and several kidney disease outcomes. Our genetic analyses suggested that PFOA and PFOS were associated with different kidney diseases in distinct directions. We then used computational approaches to prioritize database-derived candidate protein targets and pathway themes related to immune regulation, inflammation, oxidative stress, and apoptosis. By integrating population-level genetic evidence with computational target prioritization, this study provides a hypothesis-generating framework for future experimental studies on PFAS-related kidney health.", "abstract_shown": true, "affiliations": [ "Department of Urology, The Second Xiangya Hospital at Central South University, Changsha, Hunan, China", "Department of Nephrology, The Second Xiangya Hospital at Central South University, Changsha, Hunan, China", "Xiangya School of Medicine, Central South University, Changsha, Hunan, China", "The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, Henan, China", "Department of General Surgery, The Second Xiangya Hospital at Central South University, Changsha, Hunan, China" ], "article_type": "Research Article", "arxiv": null, "author_total": 6, "authors": [ { "affs": [ 0 ], "name": "Dianjie Zeng" }, { "affs": [ 1 ], "name": "Yuxi Wang" }, { "affs": [ 2 ], "name": "Yinhuai Wang" }, { "affs": [ 3 ], "name": "Guoqiang Li" }, { "affs": [ 4 ], "name": "Wenpeng Wang" }, { "name": "Zhongkun Zuo" } ], "bibtex": "https://research.draconitic.com/paper/32nt7n8jn7zsr.bib", "cited_by": 0, "doi": "10.1371/journal.pcbi.1014665", "fulltext_url": "https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1014665", "id": "32nt7n8jn7zsr", "issns": [ "1553-7358" ], "landing_url": "https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1014665", "language": null, "licence": "CC-BY-4.0", "licence_label": "CC BY 4.0", "licence_source": "journal", "licence_url": "https://creativecommons.org/licenses/by/4.0/", "metadata_licence": null, "native_subjects": [ [ "openalex", "2304|Per- and polyfluoroalkyl substances research" ], [ "plos", "/Biology and life sciences/Anatomy/Renal system/Kidneys" ], [ "plos", "/Biology and life sciences/Genetics/Genetics of disease" ], [ "plos", "/Biology and life sciences/Toxicology/Predictive toxicology" ], [ "plos", "/Computer and information sciences/Network analysis/Signaling networks" ], [ "plos", "/Medicine and health sciences/Anatomy/Renal system/Kidneys" ], [ "plos", "/Medicine and health sciences/Epidemiology/Genetic epidemiology" ], [ "plos", "/Medicine and health sciences/Medical conditions/Inflammatory diseases" ], [ "plos", "/Medicine and health sciences/Nephrology/Kidney stones" ], [ "plos", "/Medicine and health sciences/Pathology and laboratory medicine/Toxicology/Predictive toxicology" ], [ "plos", "/Medicine and health sciences/Urology/Genitourinary infections/Urinary tract infections" ], [ "plos", "/Medicine and health sciences/Urology/Kidney stones" ] ], "openalex": "W7213472956", "pdf_url": "https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1014665&type=printable", "pmcid": null, "pmid": null, "published": "2026-09-17", "publisher": "Public Library of Science", "ris": "https://research.draconitic.com/paper/32nt7n8jn7zsr.ris", "sources": [ { "first_seen": "2026-10-30T12:17:49Z", "native_id": "10.1371/journal.pcbi.1014665", "source": "plos", "url": "https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1014665" } ], "subjects": [ { "field": "biology", "origin": "plos:genetics", "subfield": "genetics-genomics" }, { "field": "medicine", "origin": "plos:toxicology", "subfield": "pharmacology-toxicology" }, { "field": "medicine", "origin": "plos:anatomy", "subfield": "physiology" } ], "title": "Per- and polyfluoroalkyl substances and kidney disease: Genetic associations and computational prioritization of candidate toxicogenomic pathways", "title_text": "Per- and polyfluoroalkyl substances and kidney disease: Genetic associations and computational prioritization of candidate toxicogenomic pathways", "type": "peer-reviewed", "updated_at": "2026-10-30T12:17:49Z", "url": "https://research.draconitic.com/paper/32nt7n8jn7zsr", "venue": "PLOS Computational Biology", "versions": [] }