New research reveals gut microbiome connections to lupus and IBD, pointing to potential biomarkers and personalized treatment options.
Study: Lupus and inflammatory bowel disease share a common set of microbiome characteristics distinct from other autoimmune disorders. Image credit: SewCreamStudio/Shutterstock.com
In a recent study published in Annals of Rheumatic Diseasesresearchers identified the microbial profiles associated with autoimmune diseases such as inflammatory bowel disease (IBD) and systemic lupus erythematosus (SLE).
They linked these microbiome patterns to colorectal cancer (CRC) to reveal common microbial processes and distinct biomarkers.
Import
The gut microbiota is critical in autoimmune diseases, with certain species associated with specific conditions. Dysbiosis, or severe instability in the gut microbiota, is unique among humans, demonstrating a direct link between gut composition and clinical symptoms of autoimmune diseases.
More extensive studies are needed to find biomarkers and understand the processes by which the microbiome influences autoimmune diseases.
Metagenomic investigations provide comprehensive species and functional capacities that differ between disease states. However, further study is needed to determine the cause and specificity of each condition.
About the study
The present study used microbiome profiling to discover potential biomarkers and molecular pathways underlying autoimmune disorders, including SLE and IBD.
The researchers collected 78 stool samples, 32 from SLE patients (n=14) and 46 from sex- and age-matched controls (n=22) from Yale University Medical School. They hired people over two years. Systemic Lupus Erythematosus Disease Activity Index (SLEDAI) scores were determined.
At three visits, participants provided dietary and medical histories and whole blood samples, in addition to stool, oral microbiota, and skin samples.
Deoxyribonucleic acid (DNA) extracted from stool samples was subjected to high-throughput metagenomic sequencing. The researchers analyzed the taxonomic and functional profiles aligned to the Kyoto Encyclopedia of Genes and Genomes (KEGG) database.
They also analyzed metagenomic datasets of patients with autoimmune diseases such as IBD, myasthenia gravis, multiple sclerosis, ankylosing spondylitis or Graves’ disease. They contrasted these with colon cancer metagenomes to identify microbial features specific to the disease. The study excluded samples with fewer than 107 is reading.
To investigate effector-like proteins and their targets in major signaling pathways, the researchers used protein-protein interactions (PPI) analysis and pathway enrichment. PPIs have helped predict microbial roles in autoimmune disorders and provide functional insights into species-level variations, particularly in IBD and SLE.
Co-immunoprecipitation assays used human embryonic kidney 293T (HEK293T) cells to demonstrate in vivo protein binding to expected bacterial interactors.
Generalized linear regressions detected differentially abundant microbial traits between patients and healthy controls, adjusting for gender and age. Models trained on protein family composition (PFAM) in the microbiomes of each cohort predicted microbial gene families associated with autoimmune disorders.
Results
The study showed that gut microbes can modulate disease processes, with IBD and SLE having enriched pathways for glucocorticoid receptor signaling, interleukin (IL)-12, 13, and phosphatidylinositol 3-kinase/protein kinase B signaling ( PI3K/AKT).
PPIs in the host microbiome that bind to the group C nuclear receptor subfamily 3 (NR3C1) glucocorticoid receptor protein were significantly associated with IBD and SLE, indicating oxidative stress-mediated inflammation.
Experimental validations showed connections between NR3C1 and proteins derived from gut bacteria, implying potential therapeutic applications for inflammatory diseases such as IBD and SLE.
Gemella haemolysans, Clostridium innocuuand Streptococcus oralis were more prevalent in subjects with IBD and SLE than in controls. Parvimonas micra, Peptostreptococcus stomatis, Fusobacterium nucleatum, Gemella morbillorum, Hungatella hathewayiand Solobacterium moorei were the most common bacteria found in CRC patients. Controls had higher abundance Anaerostipes hadrus, Fusicatenibacter saccharivorans, Eubacterium sp. CAG_38, Gemmiger foricilis, C. leptumand Asaccharobacter celatus from patients with SLE or IBD.
PFAMs such as Dockerin type I domain, glycoside hydrolase 44, and anaphase-promoting subunit 2 were significantly more prevalent in controls. Carbohydrate-active enzymes (CAZymes), such as N-acetylglucosaminyltransferase and peptidoglycan hydrolase, were significantly overexpressed in subjects with various autoimmune disorders and CRC.
Genes for glycan endo-1,3-β-glucosidase (GH17), endo-β-1,4-galactanase (GH53) and endo-α-1,4-polygalactosaminidase (GH114) were more abundant in witnesses. The findings suggest that CAZymes may be potential biomarkers for the diagnosis of autoimmune disorders such as IBD and SLE.
The study found a significant metabolic difference between healthy controls and SLE/IBD patients, particularly in acetyl-CoA and pyruvate metabolism. Patients with SLE or IBD focus on enzymes such as pyruvate kinase and pyruvate dehydrogenase, which may affect disease development through changes in the gut microbiome.
Healthy controls, on the other hand, have robust acetyl-CoA metabolism that supports the tricarboxylic acid (TCA) cycle.
Patients also have elevated levels of CoA acetate transferase, which can affect microbiome composition and tissue inflammation. Short-chain fatty acids (SCFAs) may alter immune responses and inflammatory diseases.
conclusions
The study identified microbial markers and common pathways in autoimmune diseases such as IBD and SLE, pointing to the microbiome as a potential therapeutic target.
The findings support the development of microbiome-based therapies such as dietary changes, tailored probiotics, prebiotics, faecal microbial transplantation, and host microbiome PPI modulation.
PPIs involving NR3C1 may enhance diagnosis and allow more tailored therapy for autoimmune disorders.
