Integrative Clinical, Molecular, and Computational Analysis Identify Novel Biomarkers and Differential Profiles of Anti-TNF Response in Rheumatoid Arthritis.

doi:10.3389/fimmu.2021.631662

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Community

Back to search

Article

Integrative Clinical, Molecular, and Computational Analysis Identify Novel Biomarkers and Differential Profiles of Anti-TNF Response in Rheumatoid Arthritis.

Frontiers in immunology - 1 Jan 2021

Luque-Tévar Maria, Perez-Sanchez Carlos, Patiño-Trives Alejandra Mª, Barbarroja Nuria, Arias de la Rosa Ivan, Abalos-Aguilera Mª Carmen, Marin-Sanz Juan Antonio, Ruiz-Vilchez Desiree, Ortega-Castro Rafaela, Font Pilar, Lopez-Medina Clementina, Romero-Gomez Montserrat, Rodriguez-Escalera Carlos, Perez-Venegas Jose, Ruiz-Montesinos Mª Dolores, Dominguez Carmen, Romero-Barco Carmen, Fernandez-Nebro Antonio, Mena-Vazquez Natalia, Marenco Jose Luis, Uceda-Montañez Julia, Toledo-Coello Mª Dolores, Aguirre M Angeles, Escudero-Contreras Alejandro, Collantes-Estevez Eduardo, Lopez-Pedrera Chary

Abstract excerpt

Background: This prospective multicenter study developed an integrative clinical and molecular longitudinal study in Rheumatoid Arthritis (RA) patients to explore changes in serologic parameters following anti-TNF therapy (TNF inhibitors, TNFi) and built on machine-learning algorithms aimed at the prediction of TNFi response, based on clinical and molecular profiles of RA patients. Methods: A total of 104 RA...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Antirheumatic Agents

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Arthritis, Rheumatoid

Share to Extracellular Traps

Share to Inflammation

Share to Longitudinal Studies

Share to Machine Learning

Share to Oxidative Stress

Share to Predictive Value of Tests

Source

Open in PubMed Open full text

Identifiers

PMID: 33833756
DOI: 10.3389/fimmu.2021.631662
PMCID: PMC8022208

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 6 Sept 2026. Manifest publication-graph-cohort-2026-09-06.1.

Source receipt: pubmed, retrieved 6 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Integrative Clinical, Molecular, and Computational Analysis Identify Novel Biomarkers and Differential Profiles of Anti-TNF Response in Rheumatoid Arthritis.PMID 33833756Read ↗

Early Prediction of Clinical Response to Anti-TNF Treatment using Multi-omics and Machine Learning in Rheumatoid ArthritisSemantic proximity Read ↗

Identification of a novel transcriptome signature for predicting the response to anti-TNF-α treatment in rheumatoid arthritis patientsSemantic proximity Read ↗

Integration of Known DNA, RNA and Protein Biomarkers Provides Prediction of Anti-TNF Response in Rheumatoid Arthritis: Results from the COMBINE StudySemantic proximity Read ↗

Pharmacogenomics of Anti-TNF Treatment Response Marks a New Era of Tailored Rheumatoid Arthritis Therapy.Semantic proximity Read ↗

Predicting Clinical Response to Monoclonal TNF Inhibitors in Rheumatoid Arthritis: A Transcriptomic Approach Based on Transmembrane TNF Reverse Signaling and NRF2 ActivationSemantic proximity Read ↗

Compendium of Synovial Signatures Identifies Pathologic Characteristics for Predicting Treatment Response in Rheumatoid ArthritisSemantic proximity Read ↗

A Combined Transcriptomic and Genomic Analysis Identifies a Gene Signature Associated With the Response to Anti-TNF Therapy in Rheumatoid ArthritisSemantic proximity Read ↗

Systematic review and meta-analysis: pharmacogenetics of anti-TNF treatment response in rheumatoid arthritis.Semantic proximity Read ↗

Harnessing gene-gene interactions via an RNA-Sequencing network analysis framework improves precision medicine prediction in rheumatoid arthritisSemantic proximity Read ↗

A compendium of mitochondrial molecular characteristics provides novel perspectives on the treatment of rheumatoid arthritis patientsSemantic proximity Read ↗

Genome-wide association analysis of anti-TNF drug response in patients with rheumatoid arthritis.Semantic proximity Read ↗

Deep phenotyping of synovial molecular signatures by integrative systems analysis in rheumatoid arthritis.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.