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Multimodal Integration of Protein Interactomes With Genomic and Molecular Data Discovers Distinct Rheumatoid
Javad Rahimikollu1,2,3, Priyamvada Guha Roy1,2,4, Akash Kishore1,2,3
1Center for Systems Immunology, Department of Immunology, University of Pittsburgh, Pittsburgh, Pennsylvania.
Objective:
Rheumatoid arthritis (RA) is a heterogeneous autoimmune disease characterized by clinical and molecular heterogeneity, notably in the presence of anti-cyclic citrullinated peptide (CCP) antibodies. Patients with CCP+ RA exhibit more severe disease progression and distinct treatment responses compared to patients with CCP- RA. Although previous studies have investigated cellular and molecular differences between these subtypes, their genetic differences are understudied.
Methods:
We leveraged the Rheumatoid Arthritis Comparative Effectiveness Research cohort, comprising 555 patients with CCP+/rheumatoid factor (RF)+ RA and 384 patients with CCP-/RF+ RA. Using a novel framework, we integrated a network-based genome-wide association study (GWAS) with multiomic data to uncover corresponding genetic and molecular differences.
Results:
We uncovered a significant heritability difference between these disease groups. Network-based GWAS uncovered 14 putative gene modules, including many genes outside the HLA loci, that explained genetic differences between CCP+/RF+ and CCP-/RF+ RA. Heritability partitioning and multivariate expression analyses validated four modules, highlighting novel genetic loci underlying phenotypic differences. Module functional significance was established using multiple orthogonal cohorts, underscoring their biologic relevance.
Conclusion:
Our findings demonstrate the use of network-based approaches in revealing differential genetic risk factors underlying CCP+/RF+ and CCP-/RF+ RA. Disease-associated gene modules detected in synovial tissue were also observed in peripheral blood, indicating joint-specific molecular programs are reflected systemically. This cross-tissue concordance highlights the potential for blood-based assays to capture pathogenic mechanisms active in the joints, enabling practical patient stratification. Our findings highlight why patients with CCP+/RF+ and CCP-/RF+ RA exhibit distinct clinical courses and therapeutic responses, supporting precision-guided treatment strategy development in RA.
Insights
Genetic differences between anti-cyclic citrullinated peptide antibody-positive (CCP+) and CCP-negative (CCP-) rheumatoid arthritis (RA) were identified using network-based genome-wide association studies. These findings reveal distinct genetic risk factors influencing RA subtypes and inform precision medicine strategies.
Area of Science:
- Genetics
- Immunology
- Rheumatology
Background:
- Rheumatoid arthritis (RA) is a heterogeneous autoimmune disease with distinct clinical and molecular subtypes, particularly anti-cyclic citrullinated peptide antibody-positive (CCP+) and CCP-negative (CCP-) RA.
- CCP+ RA patients often experience more severe disease and different treatment responses compared to CCP- RA patients.
- Genetic differences between these RA subtypes remain understudied despite known cellular and molecular variations.
Purpose of the Study:
- To investigate the understudied genetic differences between CCP+ and CCP- rheumatoid arthritis (RA) subtypes.
- To identify novel genetic risk factors and molecular pathways that differentiate these RA patient groups.
- To leverage network-based approaches integrating multi-omic data for comprehensive genetic analysis.
Main Methods:
- Utilized the Rheumatoid Arthritis Comparative Effectiveness Research (RACER) cohort, including CCP+/RF+ and CCP-/RF+ RA patients.
- Employed a novel framework integrating network-based genome-wide association study (GWAS) with multi-omic data.
- Performed heritability partitioning and multivariate expression analyses to validate identified gene modules.
Main Results:
- A significant difference in heritability was observed between CCP+ and CCP- RA groups.
- Network-based GWAS identified 14 putative gene modules, many outside HLA loci, explaining genetic disparities between RA subtypes.
- Four gene modules were validated, highlighting novel genetic loci associated with phenotypic differences, with functional significance confirmed across orthogonal cohorts.
Conclusions:
- Network-based approaches effectively reveal differential genetic risk factors for CCP+ and CCP- RA.
- Disease-associated gene modules in synovial tissue were also detected in peripheral blood, suggesting systemic reflection of joint-specific molecular programs.
- Findings support the potential for blood-based assays in stratifying RA patients and developing precision-guided treatment strategies based on distinct genetic underpinnings.
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