{"doi":"10.3390/diagnostics15233028","title":"Unsupervised Phenotyping of Asthma: Integrating Serum Periostin with Clinical and Inflammatory Profiles","abstract":"Background/Objectives: Asthma is a heterogeneous inflammatory airway disease. Periostin, a matricellular protein induced by interleukin-13, contributes to airway inflammation and remodeling. This study evaluated serum periostin as a diagnostic biomarker and explored multidimensional phenotypes in adult asthma. Methods: A cross-sectional study included 76 adults, with 25 healthy controls, 25 moderate, and 26 severe asthma patients, classified per Global Initiative for Asthma (GINA)-2020 guidelines. Serum periostin was measured using an enzyme-linked immunosorbent assay (ELISA). Diagnostic accuracy was assessed using receiver operating characteristic (ROC) analysis, Firth-penalized logistic regression, bootstrap calibration (1000 resamples), decision curve analysis (DCA), and gradient boosting machine (GBM) validation. Principal component analysis (PCA) followed by k-means clustering identified distinct phenotypes based on clinical, functional, and inflammatory variables. Results: Asthma patients had higher serum periostin than controls (median 52.9 vs. 32.5 pg/mL; p < 0.01), with excellent diagnostic accuracy (AUC = 0.987; sensitivity = 94.1%, specificity = 100%). Firth regression identified periostin as the only independent predictor of asthma diagnosis (β = 0.387; OR = 1.47; 95% CI 1.23–2.08; p < 0.001). Calibration showed minimal error (MAE = 0.042) and DCA demonstrated clear net benefit. GBM confirmed periostin as the dominant diagnostic predictor. PCA revealed three clusters: Cluster 1: younger, lower periostin, preserved lung function, good symptom control; Cluster 2: intermediate periostin, greater airflow limitation, poorer control; and Cluster 3: highest periostin, elevated systemic inflammation (NLR, PLR, SII), with moderate functional impairment. Conclusions: Serum periostin is a reliable diagnostic biomarker for asthma. Multidimensional clustering highlights clinically relevant phenotypes linked to periostin, inflammatory burden, and lung function, supporting its role in personalized asthma management.","journal":"Diagnostics","year":2025,"id":527675,"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":3,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.7818,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":909066,"name":"Mohammed Kaleem Ullah","orcid":"0000-0001-8470-3114","position":1,"is_corresponding":false},{"id":1151422,"name":"Medha Karnik","orcid":"0000-0002-1591-8004","position":2,"is_corresponding":false},{"id":1314348,"name":"Mandya Venkateshmurthy Greeshma","orcid":"0000-0003-2236-4588","position":3,"is_corresponding":false},{"id":1256584,"name":"N. Bansal","orcid":"0009-0003-8665-1313","position":4,"is_corresponding":false},{"id":1151420,"name":"Shreedhar Kulkarni","orcid":"0009-0009-0147-8376","position":5,"is_corresponding":false},{"id":1151421,"name":"Rekha Vaddarahalli ShankaraSetty","orcid":"0009-0008-6781-3627","position":6,"is_corresponding":false},{"id":668431,"name":"SubbaRao V. Madhunapantula","orcid":"0000-0001-9167-9271","position":7,"is_corresponding":false},{"id":909068,"name":"Jayaraj Biligere Siddaiah","orcid":"0000-0001-6055-4580","position":8,"is_corresponding":false},{"id":979766,"name":"Sindaghatta Krishnarao Chaya","orcid":"0000-0002-4898-9466","position":9,"is_corresponding":false},{"id":798830,"name":"Komarla Sundararaja Lokesh","orcid":"0000-0001-5651-1123","position":10,"is_corresponding":false},{"id":1404291,"name":"Shashi K. Ramaiah","orcid":"0009-0007-9105-9970","position":11,"is_corresponding":false},{"id":1404292,"name":"Sachith Srinivas","orcid":"0000-0002-8238-4903","position":12,"is_corresponding":false},{"id":1404293,"name":"Vikhnesh Padmakaran","orcid":"0009-0002-8510-1208","position":13,"is_corresponding":false},{"id":1404294,"name":"Malavika Shankar","orcid":"0000-0003-0462-3988","position":14,"is_corresponding":false},{"id":798829,"name":"Ashwaghosha Parthasarathi","orcid":"0000-0002-7270-0247","position":15,"is_corresponding":false},{"id":48868,"name":"P A Mahesh","orcid":"0000-0003-1632-5945","position":16,"is_corresponding":false},{"id":1151424,"name":"Sukanya Ravindran","orcid":"0009-0002-6507-8098","position":0,"is_corresponding":true}],"reference_count":51,"raw_metadata":null,"created_at":"2026-07-19T02:50:44.062153Z","pmid":"41374409","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":[]}