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Preprint WatchModerateSeptember 19th, 2026

Newly identified COPD GWAS protein interactors reveal a potential disease network module

Deritei, D.; Inuzuka, H.; Zhang, C.; Castaldi, P. J.; Asara, J. M.; Madha-Krause, S.; Moritz, R. L.; Cho, M. H.; Glass, K.; Wei, W.; Silverman, E. K.

Affinity purification mass spectrometry of six established COPD GWAS gene products identified a tightly connected eight-protein core disease network module that includes TGM2 alongside AGER, FAM13A, HHIP, FBXO38, MFAP2, CAVIN1 and HSPA1A.

Moderate contradiction

1 prior failure

Two documented clinical failures match this mechanism, or a single Phase 3 failure is on record.

This is a network membership claim rather than a therapeutic one, and it lands on the same day Claidex recorded the first clinical failure on this target. GSK3915393, an oral transglutaminase 2 inhibitor, met futility at a pre-planned interim in idiopathic pulmonary fibrosis (gsk3915393-tgm2-idiopathic-pulmonary-fibrosis-transform-phase2-futility-termination), a programme whose weakest link was human target-disease evidence, with an Open Targets association of 0.0793 built from literature alone. Placing TGM2 in a protein interaction module anchored on COPD GWAS gene products is the kind of human-anchored evidence that pairing lacked, but it is evidence in a different lung disease, it comes from interaction proteomics in two cell lines rather than from genetics of TGM2 itself, and network centrality has repeatedly failed to predict drug response. Read as encouragement to re-enter fibrotic lung disease on this target, the flag is a caution. Read as a prompt to ask whether TGM2 has any human genetic signal in an obstructive rather than fibrotic phenotype, it is worth following.

Abstract excerpt

Background: Chronic obstructive pulmonary disease (COPD) is a complex, heterogeneous disease influenced by genetic and environmental factors. However, the interactions between COPD risk genes and their collective role in COPD susceptibility remain largely elusive. We hypothesize that the protein-protein interaction (PPI) network of genes associated with COPD risk can provide molecular insight into the mechanisms of COPD pathogenesis. Methods: We used affinity purification mass spectrometry (AP-MS) to detect protein-protein interactions of six well-established COPD GWAS gene products (AGER, FAM13A, FBXO38, HHIP, IREB2, MFAP2) in two relevant lung cell lines (IMR90, 16HBE). These genes are located in significant COPD GWAS regions, and their physiological role in COPD has been previously confirmed by functional studies. We analyzed the impact of the newly identified interactions in contextual, cell type-specific PPI networks built from the combination of publicly available PPI data (HUBRIS) and cell type-specific gene expression data. Results: Using AP-MS, we identified 482 unique interactors across 701 newly identified protein interactions with the six GWAS gene products in at least one of the cell lines (AGER: 122, FAM13A: 83, FBXO38: 71, HHIP: 108, IREB2: 8, MFAP2: 309). Subsequent network analysis incorporating these new PPIs with public PPI databases revealed: (1) the new interactions significantly reduce the network distance between known COPD GWAS gene products; (2) 5.2% of the newly identified interactors are differentially abundant between COPD cases and controls in lung proteomic data from the Lung Tissue Research Consortium (LTRC); and (3) 41 (14.3%) of the newly identified interactors were directly connected to more than one of the six COPD GWAS genes. We identified a tightly connected core network of COPD GWAS gene products and protein biomarkers with intersecting signals; this network consists of 8 proteins, including 5 of the 6 GWAS gene products (AGER, FAM13A, HHIP, FBXO38, and MFAP2) as well as CAVIN1, TGM2, and HSPA1A. Conclusions: By combining AP-MS experimental data, multiple types of "omics" data, and network analysis, we have constructed a disease network module for COPD. This module can be a foundation for understanding the collective influence of COPD GWAS gene products in disease pathogenesis.

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This is an automated contradiction flag, not an editorial judgment on the preprint's quality. Flags identify where the preclinical literature and the clinical failure record diverge.