Cluster analysis identifies three clinical patterns of patients with systemic autoimmune diseases and anti-Ku antibodies
Objective To determine distinct patterns of patients with autoimmune diseases harbouring anti-Ku antibodies and their respective prognosis.Methods Anti-Ku-positive patients were retrieved through four immunology departments. Clusters were derived from unsupervised multiple correspondence analysis, n...
Saved in:
| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMJ Publishing Group
2025-06-01
|
| Series: | RMD Open |
| Online Access: | https://rmdopen.bmj.com/content/11/2/e005191.full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849467739188494336 |
|---|---|
| author | Bruno Fautrel Zahir Amoura Yves Allenbach Olivier Benveniste Samuel Bitoun Xavier Mariette Luc Mouthon Benjamin Terrier Philippe Dieude François Chasset Brigitte Bader-Meunier Raphaele Seror Gaetane Nocturne Pascale Chretien Karim Sacre Yann Nguyen Victoire De Lastours Capucine Morélot-Panzini Yurdagül Uzunhan Veronique Le Guern Raphaël Borie Céline Comparon Olivier Sitbon Marc Humbert Cécile Goujard Marie Robert Glory Dingulu Perrine Dusser Mohamad Zaidan Elisabeth Aslangul Claire Goulvestre Jean-Luc Charuel Pascale Roland-Nicaise Marie Saillour |
| author_facet | Bruno Fautrel Zahir Amoura Yves Allenbach Olivier Benveniste Samuel Bitoun Xavier Mariette Luc Mouthon Benjamin Terrier Philippe Dieude François Chasset Brigitte Bader-Meunier Raphaele Seror Gaetane Nocturne Pascale Chretien Karim Sacre Yann Nguyen Victoire De Lastours Capucine Morélot-Panzini Yurdagül Uzunhan Veronique Le Guern Raphaël Borie Céline Comparon Olivier Sitbon Marc Humbert Cécile Goujard Marie Robert Glory Dingulu Perrine Dusser Mohamad Zaidan Elisabeth Aslangul Claire Goulvestre Jean-Luc Charuel Pascale Roland-Nicaise Marie Saillour |
| author_sort | Bruno Fautrel |
| collection | DOAJ |
| description | Objective To determine distinct patterns of patients with autoimmune diseases harbouring anti-Ku antibodies and their respective prognosis.Methods Anti-Ku-positive patients were retrieved through four immunology departments. Clusters were derived from unsupervised multiple correspondence analysis, not including the disease’s diagnosis, followed by hierarchical clustering. Baseline characteristics and risk of disease progression, defined as a composite of new organ involvement or the need for new immunosuppressants, were compared across the retrieved clusters.Results Among 154 anti-Ku-positive patients, three clusters were identified. At disease’s onset, all patients included in cluster 1 (n=42/154, 27%) had muscle involvement, 34% displayed cardiac manifestations. Inflammatory myopathies (n=35/42, 83%) and/or systemic sclerosis (n=17/42, 40%) were the most frequent diagnoses. Cluster 2 (n=69/154, 45%) included the lowest proportion of women (68% vs 83% and 84% in clusters 1 and 3), 54% of patients had lung involvement, and 25% fulfilled Sjögren’s disease criteria. Cluster 3 (n=43/154, 28%) included younger patients (median age 25 years), with 79% of them fulfilling systemic lupus erythematosus criteria. These three clusters have distinct outcomes (p=0.001): cluster 1 developed lung involvement and displayed the higher risk of disease progression, cluster 2 was prone to myositis development and cluster 3 developed various clinical manifestations. The proportion of patients with heart involvement doubled over time in all clusters, with a majority of myocarditis in cluster 1, pulmonary hypertension in cluster 2 and pericarditis in cluster 3.Conclusion Three distinct groups of anti-Ku-positive patients were identified; cardiac involvement should be carefully tracked throughout the follow-up in all of them. |
| format | Article |
| id | doaj-art-e66abf2d2ad94fa29ebe9800189701cf |
| institution | Kabale University |
| issn | 2056-5933 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | BMJ Publishing Group |
| record_format | Article |
| series | RMD Open |
| spelling | doaj-art-e66abf2d2ad94fa29ebe9800189701cf2025-08-20T03:26:05ZengBMJ Publishing GroupRMD Open2056-59332025-06-0111210.1136/rmdopen-2024-005191Cluster analysis identifies three clinical patterns of patients with systemic autoimmune diseases and anti-Ku antibodiesBruno Fautrel0Zahir Amoura1Yves Allenbach2Olivier Benveniste3Samuel Bitoun4Xavier Mariette5Luc Mouthon6Benjamin Terrier7Philippe Dieude8François Chasset9Brigitte Bader-Meunier10Raphaele Seror11Gaetane Nocturne12Pascale Chretien13Karim Sacre14Yann Nguyen15Victoire De Lastours16Capucine Morélot-Panzini17Yurdagül Uzunhan18Veronique Le Guern19Raphaël Borie20Céline Comparon21Olivier Sitbon22Marc Humbert23Cécile Goujard24Marie Robert25Glory Dingulu26Perrine Dusser27Mohamad Zaidan28Elisabeth Aslangul29Claire Goulvestre30Jean-Luc Charuel31Pascale Roland-Nicaise32Marie Saillour33Department of Rheumatology, Hôpital Pitié-Salpêtrière, Assistance Publique – Hôpitaux de Paris, Sorbonne Université, Paris, FranceDepartment of Internal Medicine 2, Hôpital Pitié-Salpêtrière, Assistance Publique – Hôpitaux de Paris, Sorbonne Université, Paris, FranceDepartment of Internal Medicine and Clinical Immunology, Hôpital Pitié-Salpêtrière, Assistance Publique – Hôpitaux de Paris, Sorbonne Université, Paris, FranceDepartment of Internal Medicine and Clinical Immunology, Hôpital Pitié-Salpêtrière, Assistance Publique – Hôpitaux de Paris, Sorbonne Université, Paris, FranceDepartment of Rheumatology, Université Paris Saclay, FHU CARE, INSERM UMR1184, AP-HP, Le Kremlin Bicêtre, FranceDepartment of Rheumatology, Hôpital Bicêtre, Assistance Publique – Hôpitaux de Paris, Université Paris-Saclay, Le Kremlin-Bicetre, FranceDepartment of Internal Medicine, Hôpital Cochin, Assistance Publique – Hôpitaux de Paris, Université Paris-Cité, Paris, FranceDepartment of Internal Medicine, Hôpital Cochin, Assistance Publique – Hôpitaux de Paris, Université Paris-Cité, Paris, FranceDepartment of Rheumatology, Hôpital Bichat, Assistance Publique – Hôpitaux de Paris, Université Paris-Cité, Paris, FranceDepartment of Dermatology, Hôpital Tenon, Assistance Publique – Hôpitaux de Paris, Sorbonne Université, Faculté de médecine, INSERM U1135, CIMI, Paris, FranceDepartment of Paediatric Rheumatology and Immunology, Hôpital Necker-Enfants malades, Assistance Publique – Hôpitaux de Paris, Inserm U163 Institut Imagine, Université Paris-Cité, Paris, FranceDepartment of Rheumatology, Hôpital Bicêtre, Assistance Publique – Hôpitaux de Paris, Université Paris-Saclay, Le Kremlin-Bicetre, FranceDepartment of Rheumatology, Hôpital Bicêtre, Assistance Publique – Hôpitaux de Paris, Université Paris-Saclay, Le Kremlin-Bicetre, FranceImmunology Laboratory, Hôpital Bicêtre, Assistance Publique – Hôpitaux de Paris, Université Paris-Saclay, Le Kremlin-Bicetre, FranceDepartment of Internal Medicine, Hôpital Bichat, Assistance Publique – Hôpitaux de Paris, Université Paris-Cité, Paris, FranceCentre for Research Epidemiology and Statistics, INSERM U1153, Paris, FranceDepartment of Internal Medicine, Hôpital Beaujon, Assistance Publique – Hôpitaux de Paris, Université Paris-Cité, Clichy, FranceDepartment of Pneumology, département R3S, Hôpital Pitié-Salpêtrière, Assistance Publique – Hôpitaux de Paris, Sorbonne Université, Paris, FranceDepartment of Pneumology, Hôpital Avicenne, Assistance Publique – Hôpitaux de Paris, Université Sorbonne Paris Nord, Bobigny, FranceDepartment of Internal Medicine, Hôpital Cochin, Assistance Publique – Hôpitaux de Paris, Université Paris-Cité, Paris, FranceService de Pneumologie A, Centre constitutif du centre de référence des Maladies Pulmonaires Rares, FHU APOLLO, Hopital Bichat, AP-HP, Paris, FranceDepartment of Internal Medicine, Hôpital Avicenne, Assistance Publique – Hôpitaux de Paris, Sorbonne Université, Bobigny, FranceService de Pneumologie et Soins Intensifs Respiratoires, Hôpital Bicêtre, Université Paris–Saclay, INSERM UMR_S 999, Assistance Publique Hôpitaux de Paris, Le Kremlin-Bicetre, FranceService de Pneumologie et Soins Intensifs Respiratoires, Hôpital Bicêtre, Université Paris–Saclay, INSERM UMR_S 999, Assistance Publique Hôpitaux de Paris, Le Kremlin-Bicetre, FranceDepartment of Internal Medicine, Hôpital Bicêtre, Assistance Publique – Hôpitaux de Paris, Université Paris-Saclay, Le Kremlin-Bicetre, FranceDepartment of Rheumatology, Hôpital Bicêtre, Assistance Publique – Hôpitaux de Paris, Université Paris-Saclay, Le Kremlin-Bicetre, FranceDepartment of Paediatrics, Hôpital Robert Debré, Assistance Publique – Hôpitaux de Paris, Centre de référence Rhumatismes et Auto-immunité systémique de l’enfant (RAISE), Université Paris-Cité, Paris, FranceDepartment of Paediatric Rheumatology, Hôpital Bicêtre, Assistance Publique – Hôpitaux de Paris, Université Paris-Saclay, Le Kremlin-Bicetre, FranceDepartment of Nephrology, Hôpital Bicêtre, Assistance Publique – Hôpitaux de Paris, Université Paris-Saclay, Le Kremlin-Bicetre, FranceDepartment of Internal Medicine, Hôpital Louis-Mourier, Assistance Publique – Hôpitaux de Paris, Université Paris-Cité, Colombes, FranceImmunology Laboratory, Hôpital Cochin, Assistance Publique – Hôpitaux de Paris, Université Paris-Cité, Paris, FranceImmunology Department, Hôpital Pitié-Salpêtrière, Assistance Publique – Hôpitaux de Paris, Sorbonne Université, Paris, FranceClinical Immunology Laboratory, Hôpital Bichat, Assistance Publique – Hôpitaux de Paris, Université Paris-Cité, Paris, FranceDepartment of Pneumology, Hôpital Louis-Mourier, Assistance Publique – Hôpitaux de Paris, Université Paris-Cité, Colombes, FranceObjective To determine distinct patterns of patients with autoimmune diseases harbouring anti-Ku antibodies and their respective prognosis.Methods Anti-Ku-positive patients were retrieved through four immunology departments. Clusters were derived from unsupervised multiple correspondence analysis, not including the disease’s diagnosis, followed by hierarchical clustering. Baseline characteristics and risk of disease progression, defined as a composite of new organ involvement or the need for new immunosuppressants, were compared across the retrieved clusters.Results Among 154 anti-Ku-positive patients, three clusters were identified. At disease’s onset, all patients included in cluster 1 (n=42/154, 27%) had muscle involvement, 34% displayed cardiac manifestations. Inflammatory myopathies (n=35/42, 83%) and/or systemic sclerosis (n=17/42, 40%) were the most frequent diagnoses. Cluster 2 (n=69/154, 45%) included the lowest proportion of women (68% vs 83% and 84% in clusters 1 and 3), 54% of patients had lung involvement, and 25% fulfilled Sjögren’s disease criteria. Cluster 3 (n=43/154, 28%) included younger patients (median age 25 years), with 79% of them fulfilling systemic lupus erythematosus criteria. These three clusters have distinct outcomes (p=0.001): cluster 1 developed lung involvement and displayed the higher risk of disease progression, cluster 2 was prone to myositis development and cluster 3 developed various clinical manifestations. The proportion of patients with heart involvement doubled over time in all clusters, with a majority of myocarditis in cluster 1, pulmonary hypertension in cluster 2 and pericarditis in cluster 3.Conclusion Three distinct groups of anti-Ku-positive patients were identified; cardiac involvement should be carefully tracked throughout the follow-up in all of them.https://rmdopen.bmj.com/content/11/2/e005191.full |
| spellingShingle | Bruno Fautrel Zahir Amoura Yves Allenbach Olivier Benveniste Samuel Bitoun Xavier Mariette Luc Mouthon Benjamin Terrier Philippe Dieude François Chasset Brigitte Bader-Meunier Raphaele Seror Gaetane Nocturne Pascale Chretien Karim Sacre Yann Nguyen Victoire De Lastours Capucine Morélot-Panzini Yurdagül Uzunhan Veronique Le Guern Raphaël Borie Céline Comparon Olivier Sitbon Marc Humbert Cécile Goujard Marie Robert Glory Dingulu Perrine Dusser Mohamad Zaidan Elisabeth Aslangul Claire Goulvestre Jean-Luc Charuel Pascale Roland-Nicaise Marie Saillour Cluster analysis identifies three clinical patterns of patients with systemic autoimmune diseases and anti-Ku antibodies RMD Open |
| title | Cluster analysis identifies three clinical patterns of patients with systemic autoimmune diseases and anti-Ku antibodies |
| title_full | Cluster analysis identifies three clinical patterns of patients with systemic autoimmune diseases and anti-Ku antibodies |
| title_fullStr | Cluster analysis identifies three clinical patterns of patients with systemic autoimmune diseases and anti-Ku antibodies |
| title_full_unstemmed | Cluster analysis identifies three clinical patterns of patients with systemic autoimmune diseases and anti-Ku antibodies |
| title_short | Cluster analysis identifies three clinical patterns of patients with systemic autoimmune diseases and anti-Ku antibodies |
| title_sort | cluster analysis identifies three clinical patterns of patients with systemic autoimmune diseases and anti ku antibodies |
| url | https://rmdopen.bmj.com/content/11/2/e005191.full |
| work_keys_str_mv | AT brunofautrel clusteranalysisidentifiesthreeclinicalpatternsofpatientswithsystemicautoimmunediseasesandantikuantibodies AT zahiramoura clusteranalysisidentifiesthreeclinicalpatternsofpatientswithsystemicautoimmunediseasesandantikuantibodies AT yvesallenbach clusteranalysisidentifiesthreeclinicalpatternsofpatientswithsystemicautoimmunediseasesandantikuantibodies AT olivierbenveniste clusteranalysisidentifiesthreeclinicalpatternsofpatientswithsystemicautoimmunediseasesandantikuantibodies AT samuelbitoun clusteranalysisidentifiesthreeclinicalpatternsofpatientswithsystemicautoimmunediseasesandantikuantibodies AT xaviermariette clusteranalysisidentifiesthreeclinicalpatternsofpatientswithsystemicautoimmunediseasesandantikuantibodies AT lucmouthon clusteranalysisidentifiesthreeclinicalpatternsofpatientswithsystemicautoimmunediseasesandantikuantibodies AT benjaminterrier clusteranalysisidentifiesthreeclinicalpatternsofpatientswithsystemicautoimmunediseasesandantikuantibodies AT philippedieude clusteranalysisidentifiesthreeclinicalpatternsofpatientswithsystemicautoimmunediseasesandantikuantibodies AT francoischasset clusteranalysisidentifiesthreeclinicalpatternsofpatientswithsystemicautoimmunediseasesandantikuantibodies AT brigittebadermeunier clusteranalysisidentifiesthreeclinicalpatternsofpatientswithsystemicautoimmunediseasesandantikuantibodies AT raphaeleseror clusteranalysisidentifiesthreeclinicalpatternsofpatientswithsystemicautoimmunediseasesandantikuantibodies AT gaetanenocturne clusteranalysisidentifiesthreeclinicalpatternsofpatientswithsystemicautoimmunediseasesandantikuantibodies AT pascalechretien clusteranalysisidentifiesthreeclinicalpatternsofpatientswithsystemicautoimmunediseasesandantikuantibodies AT karimsacre clusteranalysisidentifiesthreeclinicalpatternsofpatientswithsystemicautoimmunediseasesandantikuantibodies AT yannnguyen clusteranalysisidentifiesthreeclinicalpatternsofpatientswithsystemicautoimmunediseasesandantikuantibodies AT victoiredelastours clusteranalysisidentifiesthreeclinicalpatternsofpatientswithsystemicautoimmunediseasesandantikuantibodies AT capucinemorelotpanzini clusteranalysisidentifiesthreeclinicalpatternsofpatientswithsystemicautoimmunediseasesandantikuantibodies AT yurdaguluzunhan clusteranalysisidentifiesthreeclinicalpatternsofpatientswithsystemicautoimmunediseasesandantikuantibodies AT veroniqueleguern clusteranalysisidentifiesthreeclinicalpatternsofpatientswithsystemicautoimmunediseasesandantikuantibodies AT raphaelborie clusteranalysisidentifiesthreeclinicalpatternsofpatientswithsystemicautoimmunediseasesandantikuantibodies AT celinecomparon clusteranalysisidentifiesthreeclinicalpatternsofpatientswithsystemicautoimmunediseasesandantikuantibodies AT oliviersitbon clusteranalysisidentifiesthreeclinicalpatternsofpatientswithsystemicautoimmunediseasesandantikuantibodies AT marchumbert clusteranalysisidentifiesthreeclinicalpatternsofpatientswithsystemicautoimmunediseasesandantikuantibodies AT cecilegoujard clusteranalysisidentifiesthreeclinicalpatternsofpatientswithsystemicautoimmunediseasesandantikuantibodies AT marierobert clusteranalysisidentifiesthreeclinicalpatternsofpatientswithsystemicautoimmunediseasesandantikuantibodies AT glorydingulu clusteranalysisidentifiesthreeclinicalpatternsofpatientswithsystemicautoimmunediseasesandantikuantibodies AT perrinedusser clusteranalysisidentifiesthreeclinicalpatternsofpatientswithsystemicautoimmunediseasesandantikuantibodies AT mohamadzaidan clusteranalysisidentifiesthreeclinicalpatternsofpatientswithsystemicautoimmunediseasesandantikuantibodies AT elisabethaslangul clusteranalysisidentifiesthreeclinicalpatternsofpatientswithsystemicautoimmunediseasesandantikuantibodies AT clairegoulvestre clusteranalysisidentifiesthreeclinicalpatternsofpatientswithsystemicautoimmunediseasesandantikuantibodies AT jeanluccharuel clusteranalysisidentifiesthreeclinicalpatternsofpatientswithsystemicautoimmunediseasesandantikuantibodies AT pascalerolandnicaise clusteranalysisidentifiesthreeclinicalpatternsofpatientswithsystemicautoimmunediseasesandantikuantibodies AT mariesaillour clusteranalysisidentifiesthreeclinicalpatternsofpatientswithsystemicautoimmunediseasesandantikuantibodies |