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Quantification of Protein Interaction Network Dynamics using Multiplexed Co-Immunoprecipitation
Published on: August 21, 2019
Constructing a protein-protein interaction network for autoimmune liver diseases by integrating pQTL, rQTL, and
Dianzhe Tian1,2, Zuyi Yang2, Lvyuxing Zhao3
1Department of Liver Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No.1 Shuaifuyuan, Wangfujing, Dongcheng District, Beijing, 100730, China.
Abstract:
Autoimmune liver diseases (AILDs), including primary biliary cholangitis (PBC), primary sclerosing cholangitis (PSC), and autoimmune hepatitis (AIH), pose significant diagnostic and therapeutic challenges due to poorly understood mechanisms. While most studies focus on absolute protein levels, protein-protein ratios (PPRs), reflecting the relative abundance of paired plasma proteins, emerge as critical yet understudied biomarkers for decoding disease-specific network perturbations. To harness this potential, we integrated protein quantitative trait loci (pQTLs), ratio QTLs (rQTLs), and mediation Mendelian randomization (MR) to map causal proteomic networks, aiming to unravel pathogenic networks and identify therapeutic targets in AILDs. Using two-sample MR, we analyzed 2821 plasma PPRs and 2923 individual proteins from the UK Biobank Pharma Proteomics Project. The primary analysis employed the inverse-variance weighted (IVW) method, complemented by MR-Egger regression, weighted median, simple mode, and weighted mode methods, all within a random-effects model. Sensitivity analyses were performed to validate the findings, including Cochran's Q test, MR-Egger intercept analysis, MR-PRESSO, and Steiger filtering. Cross-trait linkage disequilibrium score regression (LDSC) quantified genetic correlations, while the MR approach based on Bayesian model averaging (MR-BMA) prioritized independent causal PPRs. Two-step mediation MR identified mechanistic pathways. Functional enrichment and protein-protein interaction (PPI) networks were constructed using STRING and the clusterProfiler package. Finally, we investigated the associations between the causal PPRs and AILD-related symptoms/complications, as well as the influence of modifiable lifestyle factors on these PPRs. CD74 exhibited dual roles in AILDs. Elevated plasma CD74 levels were associated with an increased risk of PSC (OR = 1.54, 95% CI 1.24-1.90), whereas CD74-PPRs exhibited robust protection. Specifically, CD74/JAM2 reduced risks of PSC (OR = 0.70, 95% CI 0.59-0.83) and AIH (OR = 0.53, 95% CI 0.39-0.71), while CD74/NPDC1 conferred protection against PSC (OR = 0.66, 95% CI 0.54-0.80). Mediation MR identified TRY3 as the dominant mediator of CD74/JAM2 in AIH (91.52% proportion mediated, P = 0.017), with GREM1 and TEK mediating CD74/NPDC1 effects in PSC. PPI networks implicated interactions among CD74, amyloid precursor protein (APP), and endoglin (ENG). Notably, CD74/JAM2 demonstrated cross-disease relevance, significantly lowering PSC-associated ulcerative colitis risk (OR = 0.35, 95% CI 0.22-0.54). This study pioneers the integration of pQTLs, rQTLs, and mediation MR to map dynamic proteomic interactions in AILDs. Our findings revealed the multifaceted impact of CD74 on AILDs: its direct elevation may promote disease, whereas its protein interactions appear to mitigate risk. These results advance understanding of AILD pathogenesis and pave the way for developing novel biomarkers and targeted therapies.
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