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Abstract Number: 714

A Predictive Clinical-Immunological Index for Infections Unveils Novel Innate and Adaptive Immunity Abnormalities As Key Risk Factors for Infections in a Cohort of Patients with Systemic Lupus Erythematosus

Diana Gómez-Martín1,2, Jiram Torres-Ruíz3, Nancy R Mejía-Domínguez4, Guillermo Juárez-Vega5, Javier Merayo-Chalico3, Ana Barrera-Vargas3 and Jorge Alcocer-Varela1, 1Department of Immunology and Rheumatology, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico, 2Department of Immunology and Rheumatology, Instituto Nacional de Ciencias Médicas y Nutrición, Salvador Zubirán, Mexico city, Mexico, 3Department of Immunology and Rheumatology, Instituto Nacional de Ciencias Médicas y Nutrición, Salvador Zubirán, Mexico City, Mexico, 4Bioinformatics, Biostatistics and Computational Biology Unit, Red de Apoyo a la Investigación. Coordinación de la Investigación Científica, Universidad Nacional Autónoma de México, Mexico, Mexico, 5Flow Cytometry Unit, Red de Apoyo a la Investigación. Coordinación de la Investigación Científica, Universidad Nacional Autónoma de México, Mexico, Mexico

Meeting: 2018 ACR/ARHP Annual Meeting

Keywords: B cells, infection and monocytes, Lupus, T cells

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Session Information

Date: Sunday, October 21, 2018

Title: Systemic Lupus Erythematosus – Clinical Poster I: Clinical Manifestations and Comorbidity

Session Type: ACR Poster Session A

Session Time: 9:00AM-11:00AM

Background/Purpose:

Patients with systemic lupus erythematosus (SLE) have multiple innate and adaptive immune response abnormalities. It is unknown whether they play a key role in the development of infections, which was the aim of the present study. Until now, a tool to predict infections that encompasses the clinical and immunological features characteristic of SLE patients was lacking.

Methods:

A prospective cohort study of 55 SLE patients with less than 5 years since diagnosis was undertaken in a tertiary care center. Patients were prospectively followed up during a twelve-month period, looking for the primary outcome that was the development of infection, defined as the presence of characteristic clinical features with response to antibiotic treatment, with or without microbiological isolation. Severe infections were defined as those requiring hospital admission for at least 72 hrs, IV antibiotic treatment or causing death. We registered relevant clinical data and performed immunophenotyping by flow cytometry. We analyzed the number of neutrophil extracellular traps (NETs) and their LL-37 expression by confocal microscopy. Repeated measure analysis for the immunosuppressive therapy, mean adjusted SLEDAI score for disease activity. Relative risks (RR) for infection adjusted for clinical and immunological features. The study was approved by the institutional ethics and research committees.

Results:

During 12 months of follow-up, 18 patients (32%) presented 19 infectious events in a median time of 21.5 weeks (IQR 4-24), 12% were severe. The main causes of infection were community-acquired pneumonia (23%), superior respiratory tract (23%) and urinary tract infections (17%), herpes zoster virus (17%), gastroenteritis (11%) and cellulitis (5%). In comparison to their baseline immunological parameters, there was a higher expression of LL-37 in LPS induced NETs and a higher amount of LDGs during the infectious events. After univariate and multivariate analysis, we developed an index to predict infection in SLE patients assigning a score according to the RR absolute values. The index parameters were cyclophosphamide use, absolute numbers of B cells, total Th17 lymphocytes and expression of TLR2 in monocytes measured with multi-parametric flow cytometry. We validated the index retrospectively in a nested case-control study and at baseline. In the case-control analysis, a score ≥2 was able to predict infection in the following 3 months (AUC= 0.79; likelihood ratio = 2.22, P=0.015). The same cutoff point at baseline predicted infection in the following year (AUC= 0.84; likelihood ratio = 2.0, P=0.012).

Conclusion:

Our compound clinical-immunological index is able to predict the development of infection in SLE patients, taking into account the use of cyclophosphamide, absolute numbers of peripheral Th17 and B cells as well as TLR2 expression in monocytes. By alerting clinicians about patients who are more prone to develop infections, there could be a closer follow-up of these patients, with a targeted, multidisciplinary approach.


Disclosure: D. Gómez-Martín, None; J. Torres-Ruíz, None; N. R. Mejía-Domínguez, None; G. Juárez-Vega, None; J. Merayo-Chalico, None; A. Barrera-Vargas, None; J. Alcocer-Varela, None.

To cite this abstract in AMA style:

Gómez-Martín D, Torres-Ruíz J, Mejía-Domínguez NR, Juárez-Vega G, Merayo-Chalico J, Barrera-Vargas A, Alcocer-Varela J. A Predictive Clinical-Immunological Index for Infections Unveils Novel Innate and Adaptive Immunity Abnormalities As Key Risk Factors for Infections in a Cohort of Patients with Systemic Lupus Erythematosus [abstract]. Arthritis Rheumatol. 2018; 70 (suppl 9). https://acrabstracts.org/abstract/a-predictive-clinical-immunological-index-for-infections-unveils-novel-innate-and-adaptive-immunity-abnormalities-as-key-risk-factors-for-infections-in-a-cohort-of-patients-with-systemic-lupus-erythem/. Accessed .
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