{"doi":"10.3389/fimmu.2022.910993","title":"Exploring urine:serum fractional excretion ratios as potential biomarkers for lupus nephritis","abstract":"Objectives The goal of this exploratory study is to determine if urine:serum fractional excretion ratios can outperform the corresponding urinary biomarker proteins in identifying active renal disease in systemic lupus erythematosus (SLE). Methods Thirty-six adult SLE patients and twelve healthy controls were examined for serum and urine levels of 8 protein markers, namely ALCAM, calpastatin, hemopexin, peroxiredoxin 6 (PRDX6), platelet factor 4 (PF4), properdin, TFPI and VCAM-1, by ELISA. Fractional excretion of analyzed biomarkers was calculated after normalizing both the urine and serum biomarker levels against creatinine. A further validation cohort of fifty SLE patients was included to validate the initial findings. Results The FE ratios of all 8 proteins interrogated outperformed conventional disease activity markers such as anti-dsDNA, C3 and C4 in identifying renal disease activity. All but VCAM-1 FE were superior to the corresponding urine biomarkers levels in differentiating LN activity, exhibiting positive correlation with renal SLEDAI. ALCAM FE , PF4 FE and properdin FE ratios exhibited the highest accuracy (AUC>0.9) in distinguishing active LN from inactive SLE. Four of the FE ratios exhibited perfect sensitivity (calpastatin, PRDX6, PF4 and properdin), while ALCAM FE , PF4 FE and properdin FE exhibited the highest specificity values for active LN. In addition, several of these novel biomarkers were associated with higher renal pathology activity indices. In the validation cohort ALCAM FE , PF4 FE and properdin FE once again exhibited higher accuracy metrics, surpassing corresponding urine and serum biomarkers levels, with ALCAM FE exhibiting 95% accuracy in distinguishing active LN from inactive SLE. Conclusions With most of the tested proteins, urine:serum fractional excretion ratios outperformed corresponding urine and serum protein measurements in identifying active renal involvement in SLE. Hence, this novel class of biomarkers in SLE ought to be systemically evaluated in larger independent cohorts for their diagnostic utility in LN assessment.","journal":"Frontiers in Immunology","year":2022,"id":271087,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":13,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9624,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":280204,"name":"Samantha Stanley","orcid":null,"position":1,"is_corresponding":false},{"id":278760,"name":"Kamala Vanarsa","orcid":"0000-0002-7602-4709","position":2,"is_corresponding":false},{"id":894569,"name":"Faten Ismail","orcid":null,"position":3,"is_corresponding":false},{"id":278766,"name":"Chi Chiu Mok","orcid":"0000-0003-3696-1228","position":4,"is_corresponding":false},{"id":278769,"name":"Chandra Mohan","orcid":"0000-0001-7896-5740","position":5,"is_corresponding":false},{"id":894568,"name":"Samar A. Soliman","orcid":null,"position":0,"is_corresponding":true}],"reference_count":54,"raw_metadata":null,"created_at":"2026-07-19T00:27:35.206187Z","pmid":"36091001","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}