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Anti-Ku syndrome with elevated CK and anti-Ku syndrome with anti-dsDNA are two distinct entities with different outcomes
  1. Lionel Spielmann1,
  2. Benoit Nespola2,
  3. François Séverac3,4,
  4. Emmanuel Andres5,
  5. Romain Kessler6,
  6. Aurélien Guffroy7,8,9,
  7. Vincent Poindron7,8,
  8. Thierry Martin7,8,9,
  9. Bernard Geny9,10,
  10. Jean Sibilia8,9,11,
  11. Alain Meyer8,9,10,11
  1. 1 Service de Rhumatologie, hôpitaux civils de Colmar, Colmar, France
  2. 2 Laboratoire d'immunologie, hôpitaux universitaires de Strasbourg, Strasbourg, France
  3. 3 Service de Santé Publique, GMRC, hôpitaux universitaires de Strasbourg, Strasbourg, France
  4. 4 ICube, UMR 7357, université de Strasbourg, Strasbourg, France
  5. 5 Service de médecine interne, hôpitaux universitaires de Strasbourg, Strasbourg, France
  6. 6 Service de pneumologie, hôpitaux universitaires de Strasbourg, Strasbourg, France
  7. 7 Service d'immunologie clinique, hôpitaux universitaires de Strasbourg, Strasbourg, France
  8. 8 Centre de référence national des maladies auto-immunes rares, Strasbourg, France
  9. 9 Fédération de médecine translationnelle de Strasbourg, FRU 6702, université de Strasbourg, Strasbourg, France
  10. 10 Service de physiologie et d’explorations fonctionnelles, hôpitaux universitaires de Strasbourg et EA 3072, Strasbourg, France
  11. 11 Service de rhumatologie, hôpitaux universitaires de Strasbourg, Strasbourg, France
  1. Correspondence to Dr Lionel Spielmann, Service de Rhumatologie, Hôpitaux civils de Colmar, Colmar 68024, France; lionel.spielmann{at}ch-colmar.fr

Abstract

Objective To refine the spectrum of anti-Ku-associated disease, a condition that is equivocally described by current diagnostic criteria for connective tissue diseases.

Methods Among 42 consecutive patients harbouring anti-Ku antibodies, subgroups with similar phenotypes and prognosis were delineated without an a priori diagnosis using hierarchical clustering analysis of the cumulative clinico-biological features recorded during the follow-up. Features present at baseline that most efficiently predicted the outcomes were then identified using a sensitivity–specificity sum maximisation approach.

Results Clinico-biological features were clustered into three groups. Glomerulonephritis and ILD, the two fatal complications in this cohort, were unequally distributed between the three clusters that additionally differed on six clinico-biological features.

Among features present at baseline, elevated serum level of creatine kinase (CK) and anti-dsDNA antibodies were generally mutually exclusive and most efficiently predicted the cluster belonging at last follow-up. Anti-Ku patients with elevated CK had a 22-fold higher risk of ILD while anti-Ku patients with anti-dsDNA antibodies had a 13-fold higher risk of glomerulonephritis

Conclusion “Anti-Ku with elevated CK” syndrome and “anti-Ku with anti-dsDNA” syndrome represent two distinct entities that are important to recognise in order to best tailor patient care.

  • autoantibodies
  • autoimmune diseases
  • autoimmunity
  • Dermatomyositis
  • Polymyositis
  • Inflammatory myopathies
  • Inflammatory myopathy
  • Myositis
  • Necrotizing myopathy
  • necrotizing myopathies
  • Inflammatory skeletal muscle
  • Antisynthetase
  • Interstitial lung disease
  • Systemic lupus erythematosus
  • Systemic sclerosis
  • scleroderma
  • Classification
  • Anti-Ku antibodies
  • Undifferentiated connective tissue disease
  • Mixed connective tissue disease
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Footnotes

  • Handling editor Josef S Smolen

  • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

  • Competing interests None declared.

  • Patient consent for publication Not required.

  • Ethics approval The study was approved by the Commission nationale de l’informatique et des libertés (CNIL—French national data protection authority) under No. 912027.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data sharing statement All data relevant to the study are included in the article or uploaded as supplementary information.

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