Background/Purpose: Autoimmune and immune-mediated diseases (AIMDs) affect over 20 million Americans. Although AIMDs have distinct symptomatology, there is significant overlap in their treatment, suggesting overlap between their mechanisms of pathogenesis. While microbial factors have been previously investigated as a risk factor for AIMDs, most studies have considered AIMDs in isolation. Here, we hypothesize that integrative analysis across patients with different AIMDs will identify protective and pathogenic microbial biomarkers that are shared across AIMDs or specific to each disease, and that these features will correlate with host phenotype and clinical severity.

Methods: As a part of the Accelerating Medicines Partnership – Autoimmune and Immune Mediated Diseases (AMP AIM) program, we obtained, sequenced and analyzed stool samples from 126 subjects from new onset, biologic-naïve patients across six AIMDs: rheumatoid arthritis (RA; n=43), psoriasis (PsO=28), psoriatic arthritis (PsA=28), Sjögren’s syndrome (SJ=10), non-Sjögren’s SICCA (NSS=12), and systemic lupus erythematosus (SLE =5). In addition, we obtained samples from 6 healthy controls. Microbiome was characterized using 16S rRNA gene sequencing and analyzed with QIIME2 and the GreenGenes 2 reference taxonomy. Differential microbial features were identified via LEfSe and correlated with metadata using CUTIE.

Results: Compared to healthy controls, AIMD patients exhibited significantly lower alpha diversity (Kruskal-Wallis, p< 0.05 for all diseases) and different microbial composition (PERMANOVA p< 0.05 for PsA, SS, NSS; p< 0.10 for PsO, RA; p< 0.15 for SLE). Compared with healthy controls, we found several taxa differentially enriched in each disease, but none shared across all AIMDs: SS, Ruthenibacterium spp.; NSS, Coprococcus spp.; SLE, B. huniformis; RA; Prevotella spp. & A. indistinctus; PsO Oscillospirales order; PsA, C. innocuum. We observed a significant depletion of P.  faecium in all AIMDs (p=0.002). Correlation analyses between taxa and metrics of inflammation and clinical disease severity revealed that P. faecium was negatively correlated with serum CRP in PsA patients (p=0.017). In PsA and RA patients, P. copri was positively correlated with swollen and tender joint counts (p=0.005 and p=0.01).

Conclusion: Microbiome was significantly different in patients with AIMDs compared to healthy controls, with decreased diversity and distinct composition. We identified several taxa enriched in each AIMD (SS, Ruthenibacterium spp.; NSS, Coprococcus spp.; SLE, B. huniformis; RA; Prevotella spp. & A. indistinctus; PsO Oscillospirales order; PsA, C. innocuum), and a general depletion of P. faecium across all diseases. This short-chain fatty acid producer was negatively correlated with CRP, suggesting that the reduced abundance of this bacteria in AIMDs represents an impaired protective mechanism. Overall, our integrative analysis across AIMDs suggest that while the microbes that associate with pathogenesis are likely unique to each disease, mechanisms of protection (or their lack) tend to be shared. Future analyses will evaluate microbial pathways across AIMDs to further elucidate potential mechanisms of disease modulation.

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ACR Meeting Abstracts - https://acrabstracts.org/abstract/trans-disease-microbial-biomarkers-of-protection-and-pathogenesis-in-autoimmune-conditions-results-from-the-amp-aim-consortium/