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However, the transcriptomic features of AKI severity and its long-term effects are underexplored.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We performed bulk RNA sequencing on peripheral blood mononuclear cells from hospitalized patients with SARS-CoV-2 infection and complemented these findings with proteomic data from the same cohort. We compared the functional enrichment findings with historical sepsis\u2013AKI data and subsequently examined the association between molecular signatures and long-term kidney function changes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      In 283 patients, 57 had mild AKI (stage 1) and 49 had severe AKI (stage 2 or 3). After adjustments for age, sex, severity of infection, and preexisting CKD, we identified 6432 differentially expressed genes in the severe AKI versus control comparison, 840 in the mild AKI versus control comparison, and 1213 in the severe versus mild AKI comparison (false discovery rate &lt;0.05). Common pathways included unfolded protein response, cellular response to stress using eIF2, and IFN-\n                      <jats:italic toggle=\"yes\">\u03b3<\/jats:italic>\n                      \u2013mediated inflammatory response. Severe AKI was linked to pathways involved in mitochondrial dysfunction and endoplasmic reticulum stress. Proteomic analysis confirmed 40 established AKI and inflammation biomarkers, whereas gene-set enrichment of transcription regulators revealed additional biomarkers for severe AKI. Comparison with peripheral blood mononuclear cell transcriptomics from sepsis-related AKI showed significant functional overlap (30%). Analysis of postdischarge eGFR data in 115 patients identified 177 differentially expressed genes for severe AKI versus control, 106 for mild AKI versus control, and 46 for severe versus mild AKI. Key associations included kidney function decline related to carbohydrate and mitochondrial metabolism, inflammatory-response, and cardiovascular regulation.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>We demonstrate that severe AKI in SARS-CoV-2 infection is linked to mitochondrial dysfunction and endoplasmic reticulum stress. The functional overlap with sepsis\u2013AKI suggests potential broader therapeutic applicability. Long-term kidney dysfunction is influenced by disruptions in cellular energy metabolism and immune response.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.34067\/kid.0000000727","type":"journal-article","created":{"date-parts":[[2025,2,3]],"date-time":"2025-02-03T12:03:34Z","timestamp":1738584214000},"page":"921-936","update-policy":"https:\/\/doi.org\/10.1097\/lww.0000000000001000","source":"Crossref","is-referenced-by-count":7,"title":["Peripheral Transcriptomics in Acute and Long-Term Kidney Dysfunction in SARS-CoV-2 Infection"],"prefix":"10.34067","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1159-8354","authenticated-orcid":false,"given":"Pushkala","family":"Jayaraman","sequence":"first","affiliation":[{"name":"The Charles Bronfman Institute for Personalized Medicine (CBIPM), Icahn School of Medicine at Mount Sinai, New York, New York"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3553-2691","authenticated-orcid":false,"given":"Madhumitha","family":"Rajagopal","sequence":"additional","affiliation":[{"name":"The Barbara T Murphy Division of Nephrology, Samuel Bronfman Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7489-8322","authenticated-orcid":false,"given":"Ishan","family":"Paranjpe","sequence":"additional","affiliation":[{"name":"Department of Medicine, Stanford University, Stanford, California"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8712-3553","authenticated-orcid":false,"given":"Mayte","family":"Suarez-Farinas","sequence":"additional","affiliation":[{"name":"Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York"},{"name":"Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, New York"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lora E.","family":"Liharska","sequence":"additional","affiliation":[{"name":"Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0450-8181","authenticated-orcid":false,"given":"Ryan C.","family":"Thompson","sequence":"additional","affiliation":[{"name":"The Charles Bronfman Institute for Personalized Medicine (CBIPM), Icahn School of Medicine at Mount Sinai, New York, New York"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6983-5362","authenticated-orcid":false,"given":"Diane Marie","family":"Del Valle","sequence":"additional","affiliation":[{"name":"Department of Immunology and Immunotherapy, Icahn 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