Frederick W Miller | PubMed Health

PubMed2026

Immunoproteomic Profiling of Autoantibodies and Antibodies against Infectious Agents in Autoimmune Diseases.

Prior research investigated limited antibody sets within individual autoimmune diseases. Using the Nucleic-Acid Programmable Protein Array platform, we measured antibodies against 280 human, 40 viral, and 15 bacterial antigens in serum from 237 patients with 8 autoimmune diseases, including autoimmune gastritis (AG), autoimmune thyroiditis (AT), celiac disease (CD), idiopathic inflammatory myopathies (IIM), type 1 diabetes mellitus (T1D), rheumatoid arthritis (RA), Sjögren's disease (SjD), and systemic lupus erythematosus (SLE), and 112 controls. Candidate antibodies were identified by combining Firth logistic regression and machine learning. We identified disease-specific antibodies, ranging from 3 in IIM to 13 in SLE for IgG and 1 in CD to 13 in AG for IgA. Additionally, 63 IgG and 44 IgA antibodies were shared across two or more diseases. Notably, two IgG autoantibodies overlapped in up to five diseases: directed against STNM4 (SLE, SjD, T1D, CD, and RA) and TRIM21 (SLE, SjD, IIM, CD, and RA); and three IgA antibodies in up to seven diseases: directed against H1N1 Influenza A virus NP (IIM, SjD, AG, T1D, CD, RA, and AT) and Coxsackievirus B3MK012537 and Enterovirus C PVgp1 (IIM, SjD, AG, T1D, CD, SLE, and RA). These findings underscore the potential of antibody profiling in autoimmune disease characterization and biomarker discovery.

Humans↗

PubMed2025

Genetic Architecture of Idiopathic Inflammatory Myopathies From Meta-Analyses.

OBJECTIVE: Idiopathic inflammatory myopathies (IIMs, myositis) are rare systemic autoimmune disorders that lead to muscle inflammation, weakness, and extramuscular manifestations, with a strong genetic component influencing disease development and progression. Previous genome-wide association studies identified loci associated with IIMs. In this study, we imputed data from two prior genome-wide myositis studies and analyzed the largest myositis data set to date to identify novel risk loci and susceptibility genes associated with IIMs and its clinical subtypes. METHODS: We performed association analyses on 14,903 individuals (3,206 patients and 11,697 controls) with genotypes and imputed data from the Trans-Omics for Precision Medicine reference panel. Fine-mapping and expression quantitative trait locus colocalization analyses in myositis-relevant tissues indicated potential causal variants. Functional annotation and network analyses using the random walk with restart (RWR) algorithm explored underlying genetic networks and drug repurposing opportunities. RESULTS: Our analyses identified novel risk loci and susceptibility genes, such as FCRLA, NFKB1, IRF4, DCAKD, and ATXN2 in overall IIMs; NEMP2 in polymyositis; ACBC11 in dermatomyositis; and PSD3 in myositis with anti-histidyl-transfer RNA synthetase autoantibodies (anti-Jo-1). We also characterized effects of HLA region variants and the role of C4. Colocalization analyses suggested putative causal variants in DCAKD in skin and muscle, HCP5 in lung, and IRF4 in Epstein-Barr virus (EBV)-transformed lymphocytes, lung, and whole blood. RWR further prioritized additional candidate genes, including APP, CD74, CIITA, NR1H4, and TXNIP, for future investigation. CONCLUSION: Our study uncovers novel genetic regions contributing to IIMs, advancing our understanding of myositis pathogenesis and offering new insights for future research.

Humans↗