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Autoantigen microarrays reveal autoantibodies associated with proliferative nephritis and active disease in pediatric systemic lupus erythematosus.

Haddon DJ, Diep VK, Price JV, Limb C, Utz PJ, Balboni I - Arthritis Res. Ther. (2015)

Bottom Line: We also compared pSLE patients with biopsy-confirmed class III or IV proliferative nephritis (n = 23) and without significant renal involvement (n = 18).High levels of anti-BAFF were associated with active disease.Our model, based on ELISA measurements and clinical variables, correctly identified patients with proliferative nephritis with 91 % accuracy.

View Article: PubMed Central - PubMed

Affiliation: Department of Medicine, Division of Immunology and Rheumatology, Stanford University School of Medicine, 291 Campus Drive, Stanford, CA, 94305, USA. djhaddon@stanford.edu.

ABSTRACT

Introduction: Pediatric systemic lupus erythematosus (pSLE) patients often initially present with more active and severe disease than adults, including a higher frequency of lupus nephritis. Specific autoantibodies, including anti-C1q, anti-DNA and anti-alpha-actinin, have been associated with kidney involvement in SLE, and DNA antibodies are capable of initiating early-stage lupus nephritis in severe combined immunodeficiency (SCID) mice. Over 100 different autoantibodies have been described in SLE patients, highlighting the need for comprehensive autoantibody profiling. Knowledge of the antibodies associated with pSLE and proliferative nephritis will increase the understanding of SLE pathogenesis, and may aid in monitoring patients for renal flare.

Methods: We used autoantigen microarrays composed of 140 recombinant or purified antigens to compare the serum autoantibody profiles of new-onset pSLE patients (n = 45) to healthy controls (n = 17). We also compared pSLE patients with biopsy-confirmed class III or IV proliferative nephritis (n = 23) and without significant renal involvement (n = 18). We performed ELISA with selected autoantigens to validate the microarray findings. We created a multiple logistic regression model, based on the ELISA and clinical information, to predict whether a patient had proliferative nephritis, and used a validation cohort (n = 23) and longitudinal samples (88 patient visits) to test its accuracy.

Results: Fifty autoantibodies were at significantly higher levels in the sera of pSLE patients compared to healthy controls, including anti-B cell-activating factor (BAFF). High levels of anti-BAFF were associated with active disease. Thirteen serum autoantibodies were present at significantly higher levels in pSLE patients with proliferative nephritis than those without, and we confirmed five autoantigens (dsDNA, C1q, collagens IV and X and aggrecan) by ELISA. Our model, based on ELISA measurements and clinical variables, correctly identified patients with proliferative nephritis with 91 % accuracy.

Conclusions: Autoantigen microarrays are an ideal platform for identifying autoantibodies associated with both pSLE and specific clinical manifestations of pSLE. Using multiple regression analysis to integrate autoantibody and clinical data permits accurate prediction of clinical manifestations with complex etiologies in pSLE.

No MeSH data available.


Related in: MedlinePlus

Identification of a pediatric SLE proliferative nephritis predictive signature. a Least absolute shrinkage and selection operator (LASSO) was used on a training set of ELISA and clinical measurements from 41 new-onset pSLE patient samples as a variable selection and linear regression method to construct a predictive model of proliferative nephritis. A separate test set of 23 new-onset pSLE patient samples was used to evaluate the performance of the model, and the nephritis scores obtained for each patient with the model are shown. Unfilled black circles indicate patients who were biopsied and found to be class II, and unfilled black triangles indicate class V nephritis patients. The model was also used to calculate nephritis scores for samples from new-onset pSLE patients who were suspected to have nephritis, but were not confirmed by biopsy (unknown). b Five pSLE patients from the test set were selected for longitudinal analysis. ELISA was used to determine each serum sample’s anti-dsDNA and anti-C1q IgG levels, and a chart review was performed to collect all applicable clinical data. The LASSO model based on the training set was used to calculate nephritis scores for each patient at each time point. Vertical dashed lines indicate when biopsies were performed, and the horizontal dashed line indicates the nephritis score cutoff. ELISA enzyme-linked immunosorbent assay, IgG immunoglobulin G, pSLE pediatric systemic lupus erythematosus, SLE systemic lupus erythematosus
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Fig5: Identification of a pediatric SLE proliferative nephritis predictive signature. a Least absolute shrinkage and selection operator (LASSO) was used on a training set of ELISA and clinical measurements from 41 new-onset pSLE patient samples as a variable selection and linear regression method to construct a predictive model of proliferative nephritis. A separate test set of 23 new-onset pSLE patient samples was used to evaluate the performance of the model, and the nephritis scores obtained for each patient with the model are shown. Unfilled black circles indicate patients who were biopsied and found to be class II, and unfilled black triangles indicate class V nephritis patients. The model was also used to calculate nephritis scores for samples from new-onset pSLE patients who were suspected to have nephritis, but were not confirmed by biopsy (unknown). b Five pSLE patients from the test set were selected for longitudinal analysis. ELISA was used to determine each serum sample’s anti-dsDNA and anti-C1q IgG levels, and a chart review was performed to collect all applicable clinical data. The LASSO model based on the training set was used to calculate nephritis scores for each patient at each time point. Vertical dashed lines indicate when biopsies were performed, and the horizontal dashed line indicates the nephritis score cutoff. ELISA enzyme-linked immunosorbent assay, IgG immunoglobulin G, pSLE pediatric systemic lupus erythematosus, SLE systemic lupus erythematosus

Mentions: To construct a predictive model of proliferative nephritis for pSLE patients, we created a training set of ELISA and clinical measurements from the new-onset pSLE patient samples (n = 41) used in the microarray analysis and ELISA validation. We decided to utilize our ELISA results instead of microarray values in order to create a model that could be determined at centers without the requirement of highly specialized microarray equipment. Clinical measurements in the training set included: urinalysis, basic clinical information, SLE diagnostic criteria, and typical SLE laboratory tests (Table S1 in Additional file 1). We used the least absolute shrinkage and selection operator (LASSO) on the training set as a variable selection and linear regression method [35]. LASSO selected the following variables in the model: ELISA measurements of anti-C1q and anti-dsDNA serum IgG, and clinical measurements of absolute lymphocyte count (ALC), white blood cell (WBC) count, blood hemoglobin (Hgb), erythrocyte sedimentation rate (ESR), complement C4 levels, and abnormal urine RBC. We used the predictive model to calculate nephritis scores for each patient sample, which are shown in Fig. 5a. The model successfully partitioned the patients according to whether they did or did not have proliferative nephritis.Fig. 5


Autoantigen microarrays reveal autoantibodies associated with proliferative nephritis and active disease in pediatric systemic lupus erythematosus.

Haddon DJ, Diep VK, Price JV, Limb C, Utz PJ, Balboni I - Arthritis Res. Ther. (2015)

Identification of a pediatric SLE proliferative nephritis predictive signature. a Least absolute shrinkage and selection operator (LASSO) was used on a training set of ELISA and clinical measurements from 41 new-onset pSLE patient samples as a variable selection and linear regression method to construct a predictive model of proliferative nephritis. A separate test set of 23 new-onset pSLE patient samples was used to evaluate the performance of the model, and the nephritis scores obtained for each patient with the model are shown. Unfilled black circles indicate patients who were biopsied and found to be class II, and unfilled black triangles indicate class V nephritis patients. The model was also used to calculate nephritis scores for samples from new-onset pSLE patients who were suspected to have nephritis, but were not confirmed by biopsy (unknown). b Five pSLE patients from the test set were selected for longitudinal analysis. ELISA was used to determine each serum sample’s anti-dsDNA and anti-C1q IgG levels, and a chart review was performed to collect all applicable clinical data. The LASSO model based on the training set was used to calculate nephritis scores for each patient at each time point. Vertical dashed lines indicate when biopsies were performed, and the horizontal dashed line indicates the nephritis score cutoff. ELISA enzyme-linked immunosorbent assay, IgG immunoglobulin G, pSLE pediatric systemic lupus erythematosus, SLE systemic lupus erythematosus
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Fig5: Identification of a pediatric SLE proliferative nephritis predictive signature. a Least absolute shrinkage and selection operator (LASSO) was used on a training set of ELISA and clinical measurements from 41 new-onset pSLE patient samples as a variable selection and linear regression method to construct a predictive model of proliferative nephritis. A separate test set of 23 new-onset pSLE patient samples was used to evaluate the performance of the model, and the nephritis scores obtained for each patient with the model are shown. Unfilled black circles indicate patients who were biopsied and found to be class II, and unfilled black triangles indicate class V nephritis patients. The model was also used to calculate nephritis scores for samples from new-onset pSLE patients who were suspected to have nephritis, but were not confirmed by biopsy (unknown). b Five pSLE patients from the test set were selected for longitudinal analysis. ELISA was used to determine each serum sample’s anti-dsDNA and anti-C1q IgG levels, and a chart review was performed to collect all applicable clinical data. The LASSO model based on the training set was used to calculate nephritis scores for each patient at each time point. Vertical dashed lines indicate when biopsies were performed, and the horizontal dashed line indicates the nephritis score cutoff. ELISA enzyme-linked immunosorbent assay, IgG immunoglobulin G, pSLE pediatric systemic lupus erythematosus, SLE systemic lupus erythematosus
Mentions: To construct a predictive model of proliferative nephritis for pSLE patients, we created a training set of ELISA and clinical measurements from the new-onset pSLE patient samples (n = 41) used in the microarray analysis and ELISA validation. We decided to utilize our ELISA results instead of microarray values in order to create a model that could be determined at centers without the requirement of highly specialized microarray equipment. Clinical measurements in the training set included: urinalysis, basic clinical information, SLE diagnostic criteria, and typical SLE laboratory tests (Table S1 in Additional file 1). We used the least absolute shrinkage and selection operator (LASSO) on the training set as a variable selection and linear regression method [35]. LASSO selected the following variables in the model: ELISA measurements of anti-C1q and anti-dsDNA serum IgG, and clinical measurements of absolute lymphocyte count (ALC), white blood cell (WBC) count, blood hemoglobin (Hgb), erythrocyte sedimentation rate (ESR), complement C4 levels, and abnormal urine RBC. We used the predictive model to calculate nephritis scores for each patient sample, which are shown in Fig. 5a. The model successfully partitioned the patients according to whether they did or did not have proliferative nephritis.Fig. 5

Bottom Line: We also compared pSLE patients with biopsy-confirmed class III or IV proliferative nephritis (n = 23) and without significant renal involvement (n = 18).High levels of anti-BAFF were associated with active disease.Our model, based on ELISA measurements and clinical variables, correctly identified patients with proliferative nephritis with 91 % accuracy.

View Article: PubMed Central - PubMed

Affiliation: Department of Medicine, Division of Immunology and Rheumatology, Stanford University School of Medicine, 291 Campus Drive, Stanford, CA, 94305, USA. djhaddon@stanford.edu.

ABSTRACT

Introduction: Pediatric systemic lupus erythematosus (pSLE) patients often initially present with more active and severe disease than adults, including a higher frequency of lupus nephritis. Specific autoantibodies, including anti-C1q, anti-DNA and anti-alpha-actinin, have been associated with kidney involvement in SLE, and DNA antibodies are capable of initiating early-stage lupus nephritis in severe combined immunodeficiency (SCID) mice. Over 100 different autoantibodies have been described in SLE patients, highlighting the need for comprehensive autoantibody profiling. Knowledge of the antibodies associated with pSLE and proliferative nephritis will increase the understanding of SLE pathogenesis, and may aid in monitoring patients for renal flare.

Methods: We used autoantigen microarrays composed of 140 recombinant or purified antigens to compare the serum autoantibody profiles of new-onset pSLE patients (n = 45) to healthy controls (n = 17). We also compared pSLE patients with biopsy-confirmed class III or IV proliferative nephritis (n = 23) and without significant renal involvement (n = 18). We performed ELISA with selected autoantigens to validate the microarray findings. We created a multiple logistic regression model, based on the ELISA and clinical information, to predict whether a patient had proliferative nephritis, and used a validation cohort (n = 23) and longitudinal samples (88 patient visits) to test its accuracy.

Results: Fifty autoantibodies were at significantly higher levels in the sera of pSLE patients compared to healthy controls, including anti-B cell-activating factor (BAFF). High levels of anti-BAFF were associated with active disease. Thirteen serum autoantibodies were present at significantly higher levels in pSLE patients with proliferative nephritis than those without, and we confirmed five autoantigens (dsDNA, C1q, collagens IV and X and aggrecan) by ELISA. Our model, based on ELISA measurements and clinical variables, correctly identified patients with proliferative nephritis with 91 % accuracy.

Conclusions: Autoantigen microarrays are an ideal platform for identifying autoantibodies associated with both pSLE and specific clinical manifestations of pSLE. Using multiple regression analysis to integrate autoantibody and clinical data permits accurate prediction of clinical manifestations with complex etiologies in pSLE.

No MeSH data available.


Related in: MedlinePlus