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  • LSO-036 Cluster analysis and subphenotype stratification in lupus erythematosus based on data from the Asia Pacific lupus collaboration cohort (APLC-CASTLE)

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Short Oral Presentation
Short oral presentation session 6: SLE diagnosis and manifestations
LSO-036 Cluster analysis and subphenotype stratification in lupus erythematosus based on data from the Asia Pacific lupus collaboration cohort (APLC-CASTLE)
  1. Shirley Chiu Wai Chan1,
  2. Worawit Louthrenoo2,
  3. Alberta Hoi3,
  4. Shue Fen Luo4,
  5. Yeong-Jian Jan Wu4,
  6. Yi-Hsing Chen5,
  7. Jiacai Cho6,
  8. Aisha Lateef6,
  9. Laniyati Hamijoyo7,
  10. Sandra Navarra8,
  11. Leonid Zamora8,
  12. Sargunan Sockalingam9,
  13. Yuan An10,
  14. Zhanguo Li10,
  15. Yasuhiro Katsumata11,
  16. Masayoshi Harigai11,
  17. Yanjie Hao12,
  18. Zhuoli Zhang12,
  19. Jun Kikuchi13,
  20. Tsutomu Takeuchi13,
  21. BMDB Basnayake14,
  22. Madelynn Chan15,
  23. Kristine Ng16,
  24. Nicola Tugnet17,
  25. Sunil Kumar18,
  26. Shereen Oon19,
  27. Fiona Goldblatt20,
  28. Sean O’Neill21,
  29. Kathryn Gibson21,
  30. Naoaki Ohkubo22,
  31. Yoshiya Tanaka22,
  32. Sang-Cheol Bae23,
  33. Rangi Kandane-Rathnayake3,
  34. Mandana Nikpour19,
  35. Vera Golder3,
  36. Eric Morand3 and
  37. Chak Sing Lau1
  1. 1Medicine, University of Hong Kong, Hong Kong
  2. 2Internal Medicine, Chiang Mai University, Thailand
  3. 3Medicine Monash Health, Monash University, Australia
  4. 4Rheumatology, Allergy and Immunology, Chang Gung Memorial Hospital, Taiwan
  5. 5Internal Medicine, Taichung Veterans General Hospital, Taiwan
  6. 6Medicine, National University Hospital, Singapore
  7. 7Internal Medicine, Padjadjaran University, Indonesia
  8. 8Internal Medicine, University of Santo Tomas Hospital, Philippines
  9. 9Medicine, University of Malaya, Malaysia
  10. 10Rheumatology and Immunology, People’s Hospital, Peking University Health Science Center, China
  11. 11Internal Medicine, Tokyo Women’s Medical University, Japan
  12. 12Rheumatology and Clinical Immunology, Peking University First Hospital, China
  13. 13Internal Medicine, Keio University, Japan
  14. 14Medicine, National Hospital Kandy, SriLanka
  15. 15Rheumatology, Allergy and Immunology, Tan Tock Seng Hospital, Singapore
  16. 16Rheumatology, Waitemata District Health Board, New Zealand
  17. 17Rheumatology, Greenlane Clinical Centre, New Zealand
  18. 18Rheumatology, Middlemore Hospital, New Zealand
  19. 19Medicine, The University of Melbourne, Australia
  20. 20Rheumatology, Flinders Medical Centre, Australia
  21. 21Rheumatology, Liverpool Hospital, Australia
  22. 22The First Department of Internal Medicine, University of Occupational and Environmental Health, Japan
  23. 23Medicine, Hanyang University, Republic of Korea
  24. 24Medicine, University of the Philippines Manila, Philippines
  25. 25Rheumatology and Immunology, Singapore General Hospital, Singapore

Abstract

Background Systemic lupus erythematosus (SLE) is a complex disease with heterogenous manifestations.1 Clinical subphenotypes have been reported, but limited studies have evaluated their long-term impact.2 This study utilized the data from the Asia Pacific Lupus Collaboration (APLC) cohort to evaluate subphenotypes in SLE and differences in long term outcome.3

Methods Patient data from the APLC cohort collected between 2013 and 2020 were included. Two-step cluster analysis was conducted based on serological features (anti-dsDNA, anti-Sm, anti-phospholipid antibodies, direct coomb’s test, and hypocomplementemia). Clinical characteristics, LLDAS-50 attainment, and risk of damage accrual were compared.

Results Three clusters with distinct clinical and serological characteristics were identified (table 1). Cluster one included 1051 patients (29.1%); all patients were positive for anti-dsDNA but negative for other autoantibodies. Patients in cluster one had earlier age of SLE diagnosis and more frequent renal involvement (55.5%). Cluster two included 1537 patients (42.5%); most patients were positive for anti-dsDNA (83.9%) and anti-phospholipid antibodies (57.3%), had more frequent haematological involvements (62.6%) and serositis (19.8%). Cluster three included 1026 patients (28.4%); anti-dsDNA was the only autoantibody found in 474 patients (46.2%) and mucocutaneous involvements were the predominant features (84.5%).

Over a median of 2.5 years, damage accrual occurred in 20.8% patients and the risk was highest in cluster one (cluster 1 vs cluster 2: OR 1.34, P=0.008; cluster 1 vs cluster 3: OR 1.28, P=0.041). LLDAS-50 was most frequently achieved in cluster three (cluster 1: 49.6%, cluster 2: 48.7%, cluster 3: 59.1%) (figure 1). LLDAS-50 was associated with reduced risk of damage accrual across three clusters (cluster 1: OR 0.71, P=0.032; cluster 2: OR 0.63, P<0.001; cluster 3: OR 0.58, P<0.001).

Conclusions Three distinct subphenotypes were confirmed and associated with different risks of damage accrual. LLDAS-50 was an attainable target and associated with reduced risk of damage accrual across three clusters.

Abstract LSO-036 Figure 1
Abstract LSO-036 Figure 1

Percentage of patients with LLDAS-50 across three clusters

View this table:
Abstract LSO-036 Table 1

Cluster analyses based on autoantibody profile of 3614 SLE patients

References

  1. Kaul A, Gordon C, Crow MK, Touma Z, Urowitz MB, van Vollenhoven R, et al. Systemic lupus erythematosus. Nat Rev Dis Primers. 2016;2:16039.

  2. Li PH, Wong WH, Lee TL, Lau CS, Chan TM, Leung AM, et al. Relationship between autoantibody clustering and clinical subsets in SLE: cluster and association analyses in Hong Kong Chinese. Rheumatology (Oxford). 2013;52(2):337–45.

  • Cluster analysis
  • LLDAS-50
  • APLC
http://creativecommons.org/licenses/by-nc/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

http://dx.doi.org/10.1136/lupus-2023-KCR.77

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