Prevalence of a large panel of systemic autoantibodies in the Bavarian adult population

Rohm, Florian; Kling, Elisabeth; Hoffmann, Reinhard; Meisinger, Christine und Linseisen, Jakob (2024): Prevalence of a large panel of systemic autoantibodies in the Bavarian adult population. In: Frontiers in Immunology, Bd. 15, 1355905

Abstract

Objective: Autoimmune diseases commonly feature the presence of specific humoral autoantibodies. However, the prevalence of a large panel of systemic autoantibodies has never been assessed in the general population. We, therefore, described the prevalence of about 50 humoral systemic autoantibodies in a sample of the general Bavarian adult population.

Methods: Non-fasting venous serum samples from 331 participants were analyzed for 7 autoantibody screening tests (nuclear, cytoplasmic, and mitotic ANA, ANCA, cANCA and pANCA, anti-ENA autoantibodies) and 44 different monospecific humoral non-organ specific/systemic autoantibodies using indirect immunofluorescence tests, ELISAs, and line blots. In order to assess associations between sex, age, BMI, education level, smoking status and the presence of systemic autoantibodies, logistic regression analyses were conducted.

Results: At least one screening test was positive in 29.9% of the participants, and 42.3% of the participants were seropositive for at least one monospecific autoantibody. The most frequently found monospecific autoantibodies were rheumatoid factor (35.6%), ß2-glycoprotein 1 IgM (4.8%), and cardiolipin IgG (1.8%). Only few associations between sex, age, BMI, education, smoking status and autoantibody frequencies were observed.

Conclusion: Systemic autoantibodies are common in the general Bavarian population, and largely independent of sex, age, BMI, education, or smoking status. The study results may give orientation to clinicians about the occurrence of autoantibodies in the population, not (yet) associated with clinical symptoms.

• Dokumententyp: Zeitschriftenartikel
• Fakultät: Medizin > Institut für Medizinische Informationsverarbeitung, Biometrie und Epidemiologie
• Themengebiete: 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit
• ISSN: 1664-3224
• Sprache: Englisch