Data Sheet 1_Integrative multi-omic profiling in blood reveals distinct immune and metabolic signatures between ACPA-negative and ACPA-positive rheumatoid arthritis.zip

Data Sheet 1_Integrative multi-omic profiling in blood reveals distinct immune and metabolic signatures between ACPA-negative and ACPA-positive rheumatoid arthritis.zip

Objective<p>To investigate whether patients with ACPA-negative (ACPA–) and ACPA-positive (ACPA+) rheumatoid arthritis (RA) exhibit distinct immune and metabolic profiles in blood, using integrative proteomic and metabolomic analyses. By uncovering subgroup-specific molecular signatures, we aim...

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Bibliographic Details
Main Author: Benjamin Hur (3446447) (author)
Other Authors: Vinod K. Gupta (9962110) (author), Minsik Oh (3897688) (author), Hu Zeng (5819990) (author), Cynthia S. Crowson (9512878) (author), Kenneth J. Warrington (10943677) (author), Elena Myasoedova (9512875) (author), Vanessa L. Kronzer (7070621) (author), John M. Davis (7922228) (author), Jaeyun Sung (437557) (author)
Published: 2025
Subjects:
Genetic Immunology
biomarker discovery
multi-omic profiling
ACPA-negative and ACPA-positive rheumatoid arthritis
proteomics
metabolomics
plasma
machine learning
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