New research uncovers gut microbiome links to lupus and IBD, pointing to potential biomarkers and personalized treatment options.
Study: Lupus and inflammatory bowel disease share a common set of microbiome features distinct from other autoimmune disorders. Image Credit: SewCreamStudio/Shutterstock.com
In a recent study published in Annals of Rheumatic Diseases, researchers identified the microbial profiles linked with autoimmune illnesses, including inflammatory bowel disease (IBD) and systemic lupus erythematosus (SLE).
They linked these microbiome patterns to colorectal cancer (CRC) to uncover shared microbial processes and distinct biomarkers.
Introduction
The gut microbiota is critical in autoimmune illnesses, with some species associated with specific ailments. Dysbiosis, or severe instability in the gut microbiota, is unique among people, demonstrating a direct relationship between gut composition and clinical symptoms of autoimmune diseases.
More extensive studies are required to find biomarkers and understand the processes by which the microbiome impacts autoimmune diseases.
Metagenomic investigations provide comprehensive species and functional capabilities that differ between illness states. However, further study is required to determine the cause and specificity of each condition.
About the study
The present study used microbiome profiling to discover possible biomarkers and molecular pathways underlying autoimmune disorders, including SLE and IBD.
Researchers collected 78 fecal samples, 32 from SLE patients (n=14) and 46 from sex- and age-matched controls (n=22) from Yale University Medical. They recruited individuals over two years. Participant Systemic Lupus Erythematosus Disease Activity Index (SLEDAI) scores were determined.
Over three visits, participants provided diet and medical histories and samples of whole blood, in addition to fecal, oral, and skin microbiome samples.
Deoxyribonucleic acid (DNA) extracted from fecal samples underwent high-throughput metagenomic sequencing. Researchers analyzed the taxonomic and functional profiles aligned with the Kyoto Encyclopedia of Genes and Genomes (KEGG) database.
They also analyzed metagenomic datasets of patients with autoimmune conditions such as IBD, myasthenia gravis, multiple sclerosis, ankylosing spondylitis, or Graves disease. They contrasted these with colorectal cancer metagenomes to identify disease-specific microbial features. The study excluded samples with fewer than 107 reads.
To investigate effector-like proteins and their targets in main signaling pathways, researchers used protein-protein interactions (PPI) analysis and pathway enrichment. PPIs have helped predict microbial roles in autoimmune disorders and give functional insights into species-level variations, notably in IBD and SLE.
Co-immunoprecipitation assays used human embryonic kidney 293T (HEK293T) cells to demonstrate in vivo protein binding to anticipated bacterial interactors.
Generalized linear regressions detected differentially abundant microbial features between patients and healthy controls, adjusting for gender and age. Models trained on protein family (PFAM) composition in each cohort's microbiomes predicted microbial gene families associated with autoimmune disorders.
Results
The study showed that gut microorganisms can regulate disease processes, with IBD and SLE having enriched pathways for glucocorticoid receptor signaling, interleukin (IL)-12, 13, and phosphatidylinositol 3-kinase/protein kinase B (PI3K/AKT) signaling.
PPIs in the host microbiome connected to the nuclear receptor subfamily 3 group C member 1 (NR3C1) glucocorticoid receptor protein were significantly correlated with IBD and SLE, indicating oxidative stress-induced inflammation.
Experimental validations showed connections between NR3C1 and gut bacteria-derived proteins, implying potential therapeutic applications for inflammatory illnesses such as IBD and SLE.
Gemella haemolysans, Clostridium innocuu, and Streptococcus oralis were more prevalent in individuals with IBD and SLE than in controls. Parvimonas micra, Peptostreptococcus stomatis, Fusobacterium nucleatum, Gemella morbillorum, Hungatella hathewayi, and Solobacterium moorei were the most common bacteria found in CRC patients. Controls had higher abundances of Anaerostipes hadrus, Fusicatenibacter saccharivorans, Eubacterium sp. CAG_38, Gemmiger formicilis, C. leptum, and Asaccharobacter celatus than SLE or IBD patients.
PFAMs such as the Dockerin domain type I, 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 considerably overexpressed in individuals with various autoimmune disorders and CRC.
Genes for glucan endo-1,3-β-glucosidase (GH17), endo-β−1,4-galactanase (GH53), and endo-α−1,4-polygalactosaminidase (GH114) were more numerous in controls. The findings suggest that CAZymes may be potential biomarkers for diagnosing autoimmune disorders such as IBD and SLE.
The study found a significant metabolic difference between healthy controls and SLE/IBD patients, notably in acetyl-CoA and pyruvate metabolism. SLE or IBD patients concentrate on enzymes like pyruvate kinase and pyruvate dehydrogenase, which may impact illness development via gut microbiome changes.
Healthy controls, on the other hand, have a strong acetyl-CoA metabolism that supports the tricarboxylic acid (TCA) cycle.
Patients also have elevated levels of acetate CoA transferase, which may influence microbiome composition and tissue inflammation. Short-chain fatty acids (SCFAs) may alter immunological responses and inflammatory diseases.
Conclusions
The study identified microbial markers and common pathways in autoimmune illnesses such as IBD and SLE, pointing to the microbiome as a possible therapeutic target.
The findings support the development of microbiome-based therapies such as dietary changes, tailored probiotics, prebiotics, fecal microbiota transplantation, and host-microbiome PPI regulation.
PPIs involving NR3C1 may enhance diagnosis and allow for more customized therapy for autoimmune disorders.
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