PubMed HealthSearch

PubMed · 39379962

Serum lncRNA ITGB2-AS1 and ICAM-1 as novel biomarkers for rheumatoid arthritis and osteoarthritis diagnosis.

Abstract

BACKGROUND: The complete circulating long non-coding RNAs (lncRNAs) signature of rheumatoid arthritis (RA) and osteoarthritis (OA) is still uncovered. The lncRNA integrin subunit beta 2 (ITGB2)-anti-sense RNA 1 (ITGB2-AS1) affects ITGB2 expression; however, there is a gap in knowledge regarding its expression and clinical usefulness in RA and OA. This study investigated the potential of serum ITGB2-AS1 as a novel diagnostic biomarker and its correlation with ITGB2 expression and its ligand intercellular adhesion molecule-1 (ICAM-1), disease activity, and severity in RA and primary knee OA patients. SUBJECTS: Forty-three RA patients, 35 knee OA patients, and 22 healthy volunteers were included. RESULTS: Compared with healthy controls, serum ITGB2-AS1 expression was upregulated in RA patients but wasn't significantly altered in knee OA patients, whereas serum ICAM-1 protein levels were elevated in both diseases. ITGB2-AS1 showed discriminative potential for RA versus controls (AUC = 0.772), while ICAM-1 displayed diagnostic potential for both RA and knee OA versus controls (AUC = 0.804, 0.914, respectively) in receiver-operating characteristic analysis. In the multivariate analysis, serum ITGB2-AS1 and ICAM-1 were associated with the risk of developing RA, while only ICAM-1 was associated with the risk of developing knee OA. A panel combining ITGB2-AS1 and ICAM-1 showed profound diagnostic power for RA (AUC = 0.9, sensitivity = 86.05%, and specificity = 91.67%). Interestingly, serum ITGB2-AS1 positively correlated with disease activity (DAS28) in RA patients and with ITGB2 mRNA expression in both diseases, while ICAM-1 positively correlated with ITGB2 expression in knee OA patients. CONCLUSION: Our study portrays serum ITGB2-AS1 as a novel potential diagnostic biomarker of RA that correlates with disease activity. A predictive panel combining ITGB2-AS1 and ICAM-1 could have clinical utility in RA diagnosis. We also spotlight the association of ICAM-1 with knee OA diagnosis. The correlation of serum ITGB2-AS1 with ITGB2 expression in both diseases may be insightful for further mechanistic studies.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Aliaa M Selim, Yumn A Elsabagh, Maha M El-Sawalhi, Nabila A Ismail, Mahmoud A Senousy. 2024-10-08. Serum lncRNA ITGB2-AS1 and ICAM-1 as novel biomarkers for rheumatoid arthritis and osteoarthritis diagnosis.. https://doi.org/10.1186/s12920-024-01993-6

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Global Genomic Surveillance.

Global genomic surveillance has emerged as a foundational pillar of public health in the twenty-first century, enabling real-time tracking of pathogen evolution and informing outbreak response. This chapter examines the strategic architecture of global genomic surveillance, focusing on its application to arboviruses such as chikungunya virus (CHIKV). It explores the integration of genomic data with epidemiological, clinical, and environmental information within a One Health framework, while addressing critical challenges in governance, equity, and interoperability. The discussion covers the entire genomic surveillance workflow, from sample collection and sequencing to bioinformatic analysis and phylogenetic inference, and highlights the transformative role of artificial intelligence (AI) in predictive surveillance. By analyzing global initiatives, operational barriers, and emerging technologies, this chapter underscores the necessity of sustainable, equitable, and interoperable genomic systems to proactively address current and future infectious disease threats.

Humans

Systematic Dissection of Key Driver Perturbation Signatures in Single Cells via ECCITE-seq.

CRISPR screens, such as expanded CRISPR-compatible cellular indexing of transcriptomes and epitopes by sequencing (ECCITE-seq), enable the simultaneous measurement of transcriptomes, gRNA identity, and cell-surface protein expression at single-cell resolution to systematically interrogate gene function. This platform provides a powerful and scalable experimental approach for validating disease-associated regulators identified by large-scale association studies and other computational methods, including network-based analyses of multi-omics data. Here, as an example application, we describe an ECCITE-seq framework to characterize the transcriptomic consequences of perturbing multiple neuronal key driver genes associated with Alzheimer's disease (AD) in human-induced pluripotent stem cell (hiPSC)-derived neurons. More broadly, by integrating customized pooled gRNA libraries with different CRISPR effectors across multiple cell types, this approach allows for the assessment of the regulatory impact of candidate genes implicated in development and disease processes.

Humans

Identification of Genome-Wide Chromatin Structural Aberration in Cancer by Hi-C Analysis.

Aberrant three-dimensional genome organization is a hallmark of cancer, often driving oncogene activation through mechanisms such as enhancer hijacking. High-throughput chromosome conformation capture (Hi-C) maps these interactions on a genome-wide scale. Unlike earlier dilution-based methods, in situ Hi-C performs proximity ligation within intact nuclei, minimizing random ligation noise and enabling fine-scale structure detection. This chapter describes an optimized in situ Hi-C protocol tailored for cancer cell lines using MboI digestion and biotin-mediated pull-down to generate high-complexity libraries. We further outline a computational workflow that extends beyond standard topological mapping of compartments and topologically associating domains to identify cancer-specific aberrations. Specifically, we focus on detecting chromosomal rearrangements (structural variants) and characterizing the distinct circular topology of extrachromosomal DNA. This integrated experimental and analytical framework provides the necessary tools to dissect the spatial dysregulation underlying tumor evolution.

Humans