Evidence map›Paper›PMID 42573796›Full record

ArticleLung2026

Identification of ZNF331 as a Biomarker for Obstructive Sleep Apnea in Idiopathic Pulmonary Fibrosis Through Integrated Bioinformatics Analysis and Clinical Validation.

Shuo Wang, Yanwen Zhang, Jihong Feng, Jing Feng, Dan Liu

Abstract readValidation Study
PubMed Publisher
In one paragraph

Article in Lung, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

5 authors.

Shuo Wang *Department of Respiratory and Critical Care Medicine, Tianjin Medical University General Hospital, Tianjin, 300052, China.
Yanwen Zhang *Department of Respiratory and Critical Care Medicine, Tianjin Medical University General Hospital, Tianjin, 300052, China.
Jihong FengDepartment of Respiratory and Critical Care Medicine, The Second Affiliated Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, 300250, China.
Jing FengDepartment of Respiratory and Critical Care Medicine, Tianjin Medical University General Hospital, Tianjin, 300052, China. jingfeng_zyy@126.com.
Dan LiuDepartment of Respiratory and Critical Care Medicine, Tianjin Medical University General Hospital, Tianjin, 300052, China. liudan_nkdx@163.com.

Funding

Major and Refractory Diseases Integrated TCM-WM Clinical Collaboration Project ZDYN-2024-A-119 and ZDYN-2024-B-050National Natural Science Foundation of China 82300120 and 82474452National Science and Technology Major Project 2024ZD0522903Tianjin Key Medical Discipline Construction Project TJYXZDXK-3-004C
6 · The paper itself

Abstract

backgroundObstructive sleep apnea (OSA) is highly prevalent in patients with idiopathic pulmonary fibrosis (IPF), yet symptom-based screening frequently lacks reliability in this population. We aimed to identify a blood-based biomarker for detecting OSA in patients with IPF.

methodsPublic peripheral-blood transcriptomic datasets for OSA and IPF were analyzed to identify shared candidate genes. The leading candidate, ZNF331, was validated by reverse transcription-quantitative polymerase chain reaction in an independent clinical cohort comprising normal controls, patients with OSA, and non-oxygen-dependent patients with IPF. Diagnostic performance was assessed using receiver operating characteristic analysis and further corroborated through adjusted and internal validation analyses.

resultsZNF331 was prioritized as a shared candidate gene through the integrated bioinformatics analysis and was subsequently selected for clinical validation. In the validation cohort, ZNF331 expression exhibited an overall downward trend across the normal control, OSA, IPF, and IPF + OSA groups, reaching its lowest levels in patients with IPF complicated by OSA. ZNF331 demonstrated high diagnostic accuracy in differentiating IPF + OSA from IPF-only cases (area under the curve = 0.932, 95% confidence interval 0.874-0.990), whereas the Pittsburgh Sleep Quality Index and Epworth Sleepiness Scale showed limited diagnostic utility. The association between reduced ZNF331 expression and the IPF-OSA phenotype remained robust after propensity score matching and internal validation.

conclusionsZNF331 is a promising candidate blood-based biomarker for identifying OSA in patients with IPF. Its association with the IPF-OSA phenotype is supported by transcriptomic discovery, clinical validation, and robustness analyses. These findings suggest that ZNF331 may serve as a valuable screening biomarker for this population.

Indexed as

Idiopathic Pulmonary FibrosisSleep Apnea, ObstructiveAgedBiomarkersCase-Control StudiesComputational BiologyFemaleGene Expression ProfilingHumansMaleMiddle AgedPredictive Value of TestsReproducibility of ResultsROC CurveBiomarkersBiomarkerIdiopathic pulmonary fibrosisObstructive sleep apneaScreeningZNF331

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.