Autoantibody clustering of lupus-associated pulmonary hypertension

Mizus, Marisa; Li, Jessica; Petri, Michelle

doi:10.1136/lupus-2019-000356

Cited by 10 publications

(8 citation statements)

References 36 publications

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“…Another study of 74 SLE patients has shown a higher percentage of seropositivity of rheumatoid factor (RF) in SLE patients with PH than in those without PH [ 46 ]. Other factors, including the presence of anti-ET-1 [ 47 ], anti-U1 RNP [ 14 ], anti-topoisomerase I (anti-Scl-70) [ 48 ], anti-SmD1 [ 49 ], and anti-Smith (Sm) [ 50 ], low erythrocyte sedimentation rate (ESR) [ 18 ] and hypocomplementemia [ 50 ] have also been associated with the presence of PH in SLE. Thus, it would be clinically meaningful to apply serum biomarkers for the early detection of PH in SLE patients.…”

Section: Diagnosismentioning

confidence: 99%

Systemic Lupus Erythematosus and Pulmonary Hypertension

Parperis

Velidakis

Khattab

et al. 2023

IJMS

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Pulmonary Hypertension (PH) is a common manifestation in patients with Systemic Lupus Erythematosus (SLE) and varies from asymptomatic to life-threatening disease. PH can result not only from immune system dysregulation, but also from various conditions, including cardiorespiratory disorders and thromboembolic diseases. Most commonly, SLE-related PH presents with non-specific symptoms, such as progressive dyspnea on exertion, generalized fatigue and weakness and eventually dyspnea at rest. Prompt diagnosis of SLE-related PH and early identification of the underlying pathogenetic mechanisms is demanded in order to introduce targeted therapy to prevent irreversible pulmonary vascular damage. In most cases the management of PH in SLE patients is similar to idiopathic pulmonary arterial hypertension (PAH). Furthermore, specific diagnostic tools like biomarkers or screening protocols, to establish early diagnosis seem to be not available yet. Although, the survival rates for patients with SLE-related PH vary between studies, it is evident that PH presence negatively affects the survival of SLE patients.

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Section: Diagnosismentioning

confidence: 99%

Systemic Lupus Erythematosus and Pulmonary Hypertension

Parperis

Velidakis

Khattab

et al. 2023

IJMS

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“…To better understand SLE's underlying biology and how it relates to prognosis, attempts have been made to stratify SLE patients into endotypes including patient clusters based on common autoantibody profiles. [1][2][3][4][5][6][7][8][9][10][11] SLE pathogenesis is multifaceted, but certain autoantibodies are a hallmark of SLE and have proven useful as diagnostic and predictive biomarkers for disease manifestations and activity.…”

Section: Introductionmentioning

confidence: 99%

Machine learning identifies clusters of longitudinal autoantibody profiles predictive of systemic lupus erythematosus disease outcomes

Choi

Chen

Clarke

et al. 2023

Annals of the Rheumatic Diseases

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ObjectivesA novel longitudinal clustering technique was applied to comprehensive autoantibody data from a large, well-characterised, multinational inception systemic lupus erythematosus (SLE) cohort to determine profiles predictive of clinical outcomes.MethodsDemographic, clinical and serological data from 805 patients with SLE obtained within 15 months of diagnosis and at 3-year and 5-year follow-up were included. For each visit, sera were assessed for 29 antinuclear antibodies (ANA) immunofluorescence patterns and 20 autoantibodies. K-means clustering on principal component analysis-transformed longitudinal autoantibody profiles identified discrete phenotypic clusters. One-way analysis of variance compared cluster enrolment demographics and clinical outcomes at 10-year follow-up. Cox proportional hazards model estimated the HR for survival adjusting for age of disease onset.ResultsCluster 1 (n=137, high frequency of anti-Smith, anti-U1RNP, AC-5 (large nuclear speckled pattern) and high ANA titres) had the highest cumulative disease activity and immunosuppressants/biologics use at year 10. Cluster 2 (n=376, low anti-double stranded DNA (dsDNA) and ANA titres) had the lowest disease activity, frequency of lupus nephritis and immunosuppressants/biologics use. Cluster 3 (n=80, highest frequency of all five antiphospholipid antibodies) had the highest frequency of seizures and hypocomplementaemia. Cluster 4 (n=212) also had high disease activity and was characterised by multiple autoantibody reactivity including to antihistone, anti-dsDNA, antiribosomal P, anti-Sjögren syndrome antigen A or Ro60, anti-Sjögren syndrome antigen B or La, anti-Ro52/Tripartite Motif Protein 21, antiproliferating cell nuclear antigen and anticentromere B). Clusters 1 (adjusted HR 2.60 (95% CI 1.12 to 6.05), p=0.03) and 3 (adjusted HR 2.87 (95% CI 1.22 to 6.74), p=0.02) had lower survival compared with cluster 2.ConclusionFour discrete SLE patient longitudinal autoantibody clusters were predictive of long-term disease activity, organ involvement, treatment requirements and mortality risk.

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“…Due to the heterogeneity and complexity of the underlying disease, pathogenesis, prevalence, risk factors, and the natural history of PAH in SLE remain poorly understood. 1 As a result, there are no definite guidelines for screening, managing, and monitoring pulmonary hypertension in SLE patients.…”

Section: Introductionmentioning

confidence: 99%

“…A recently published study from the Hopkins Lupus Cohort where lupus phenotype associated with PAH was defined using multiple autoantibodies. 1 Here clustering analysis was used for the first time to define five autoantibody clusters in lupus-PAH. In the present study, clustering analysis has been used to test the hypothesis that this technique would bring out unique phenotypic groups of PAH in Indian lupus patients.…”

Section: Introductionmentioning

confidence: 99%

Autoantibody Clustering in Systemic Lupus Erythematosus–Associated Pulmonary Arterial Hypertension

Baisya

Devarasetti

Murthy

et al. 2021

IJCDW

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Systemic lupus erythematous–associated pulmonary arterial hypertension (SLE-PAH) is one of the important causes of mortality in lupus patients. Different autoantibodies are associated with SLE-PAH which can predict its future development. The objective of the study was to identify distinct autoantibody-based clusters in SLE-PAH patients and to compare demographic characters, clinical phenotypes, and therapeutic strategy across the clusters. Three distinct autoantibody clusters were identified using k-means cluster analysis in 71 SLE-PAH patients. Cluster1 had predominant Sm-RNP, Smith, SS-A association; cluster 2 had no definite autoantibody association; and cluster 3 was associated with nucleosome, histone, dsDNA, and ribosomal P protein. Patients in cluster 3 had a highly active disease while those in cluster 1 had significant cytopenia. Mean age and mean right ventricular systolic pressure (RVSP) were both high in cluster 2, indicating later-onset PAH in this group. This was the first autoantibody-based cluster analysis study in SLE-PAH patients in India which confirmed that autoantibodies did exist as clusters and the presence of definite autoantibodies can predict future development of pulmonary hypertension in these patients.

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Autoantibody clustering of lupus-associated pulmonary hypertension

Cited by 10 publications

References 36 publications

Systemic Lupus Erythematosus and Pulmonary Hypertension

Systemic Lupus Erythematosus and Pulmonary Hypertension

Machine learning identifies clusters of longitudinal autoantibody profiles predictive of systemic lupus erythematosus disease outcomes

Autoantibody Clustering in Systemic Lupus Erythematosus–Associated Pulmonary Arterial Hypertension

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