IntroductionSLE is associated with a broad spectrum of autoantibodies, but currently there is no singleserologic test to diagnose SLE definitively. Diagnosis is thus based on multiple ACR or SLICCcriteria, including autoantibodies and clinical findings. Anti-nuclear antibody (ANA) testing is astandard procedure in evaluating suspected lupus patients. While the test is highly sensitive [97percent of patients with lupus will have a positive ANA test(1) (ANA+)], the test has poorspecificity; approximately 14 % of healthy individuals test positive at a 1:80 dilution(2). As a result,ANA+ results can be misinterpreted, causing patient concern, unnecessary testing and eveninappropriate therapy (3). A test to rule out the diagnosis of lupus in ANA+ patients withoutdisease would be a valuable adjunct to current serological testing and an important application ofthe SLE-key® Rule Out technology.

SLE-key® Rule-Out Test to Assess Lupus in Anti-Nuclear Antibody Positive Subjects Using

the ImmunArray iCHIP®

S. Batty 5, I.R. Cohen 1 , C. Putterman 2 , N. Jordan 3, K. Jakobi 4, R. Sorek 4, Y. Blumenstein 4, P. Safer 4, D. Pisetsky 6

1 Weizmann Institute of Science, Rehovot, Israel, 2 Division of Rheumatology, Albert Einstein School of Medicine, NY, United States, 3 Montefiore

Medical Center, NY, United States, 4 ImmunArray LTD, Rehovot, Israel, 5 ImmunArray Inc., Virginia, United States, 6 Duke University Medical Center

and Durham VAMC, Durham, NC, United States

MethodWe previously developed the SLE-key® Rule Out test to exclude the diagnosis of SLE based on theiCHIP®(4) (Figure 1) by profiling and identifying discriminating patterns of circulatingautoantibodies among 246 SLE patients compared to 252 self-declared healthy controls (clinicaldata is shown on Tables 1,2). We tested these samples using the ImmunArray iCHIP® - aproprietary microarray that displays multiple antigens representing a range of SLE-associatedbiochemical pathways (Figure 2). The informative LDA algorithm was developed using a subset of150 SLE patients and 150 healthy controls. Verification and validation were performed onadditional sets of 50 SLE patients and 50 healthy control samples each. Serum samples from 136self-declared healthy controls were available for comparative ANA testing and were sent to anexternal lab for fluorescence ANA (FANA) analysis.

ResultsFour different classification methods (Support vector machine, Logisticregression, Linear discriminant analysis (LDA) and Quadratic discriminantanalysis) were validated as part of the development of the SLE-key® rule outtest. The LDA classifier was selected for use because of the balance betweensensitivity (94%) and specificity (75%). Figure 3 and Table 3 show thevalidation of the LDA Classifier. Of the 136 healthy samples, 24 samples(17.6%) were found to be ANA+ by FANA testing at the standard dilution of1:80. The LDA classifier was used to analyze these ANA+ patients, and thetest excluded SLE in 67% of these subjects (Figure 4).

Figure 3: ROC curves for the four

classification models on validation data

set, indicating test performance at

selected threshold.

Table 3 : Validation of LDA algorithm

Validation Results LDA

Area under Curve (AUC) 0.94

Sensitivity 94%

Specificity 75%

Accuracy 84%

Positive Predictive Value (PPV) 78%

Negative Predictive Value (NPV) 93%

Figure 2: ImmunArray’s SLE iCHIP® antigen biochemical pathways representation

Table 1 : Sample demographics Table 2 : Sample clinical data

(n=246) SLE Patients

ACR Criteria

Range 4-11Mean (±SD) 5.24 (1.2)

SLEDAI score

Range 0-25

Mean (±SD) 4.11 (4.8)

Time post Diagnosis in years

Mean (±SD) 1.00 (1)

ConclusionThe SLE-key® Rule-Out test can be used as a decision-support tool for physicians in ruling out a diagnosis of SLE with a sensitivity of

94%, specificity of 75% and NPV of 93%. In the validation study, we were able to successfully rule out the diagnosis of SLE in 67% of

ANA+ subjects with the LDA classification model. A structured RUO study with community-based rheumatologists shows good

correlation between the referring rheumatologist’s clinical impression and SLE-key® Rule-Out results for both the ANA+ (95%

agreement) and ANA- populations (100% agreement). These initial findings suggest that the iCHIP® technology can be applied to develop

an even more refined classification to rule out SLE in the ANA+ population, presently an important unmet need.

Figure 5: SLE-key® test output. LDA

threshold is shown as dotted horizontal

purple line. The patient SLE-key® score

is represented as a red “X”.

References

(1) Kavenaugh A et al. 2000 (2) M. Satoh M et al., 2012 (3) Shmerling et al., 1986 (4) Fattal, I, et al; Immunology 2010.

Figure 1: iCHIP® - ImmunArray proprietary antigen micro-array platform

Figure 4: SLE-key® results for the 24

ANA+ healthy subjects for the LDA

classification model.

(n=498)SLE Patients

(n=246)Healthy Controls

(n=252)

Age in years Mean (±SD)

34.8 (11.4) 36.8 (12.0)

Ethnic category

Afro-American: Number (%) 130 (53.0) 113 (44.8)

White non Hispanic: Number (%) 53 (21.5) 74 (29.4)

Indian/Asian/Middle Eastern: Number (%) 5 (2.0) 20 (7.9)

White Hispanic: Number (%) 49 (20.0) 42 (16.7)

Other: Number (%) 9 (3.6) 3 (1.2)

Acknowledgements: The authors wish to acknowledge 1) the invaluable contributions of Ornit Cohen-Gindi, Miriam Lerner, Naama Shefer, Ilana Gilkaite, Angela Turner, Justin Pitts, Joseph Green and Nazanin Mirshahi. 2) Innovative Medicines Initiative Joint Undertaking under grant agreement n° 115308 BIOVACSAFE

Figure 6 : SLE-key® test results.

Early Clinical Experience We have recently completed a Research-use Only (RUO) program inwhich we evaluated 154 clinical samples with the SLE-key® Rule-Outtest over a period of 6 months. The test output is presented in Figure5. Data from the RUO patient samples can be seen in Figure 6 andTable 4. ANA test results were obtained from 58 patients. Of these 35were ANA+ (60%) and 23 patients were ANA- (40%). Results of post-hoc analysis showed that the SLE-key® Rule-Out test results werehighly correlated with the clinical impressions of the referringrheumatologists (Figure 7); these early findings suggest that the iCHIP®technology can be applied to develop a more refined classification torule out SLE in the ANA+ population.

(n=150)RUO

PatientsGender

Male number (%) 10 (6.7)Female number (%) 140 (93.3)

Ethnic categoryAfro-American number (%) 17 (11.4)White non Hispanic number (%) 86 (57.3)White Hispanic number (%) 11 (7.3)Not Specified number (%) 36 (24)

Age18 – 45 number (%) 69 (46)> 45 number (%) 81 (54)

Table 4 : RUO Patient samples clinical data

Figure 7 : Agreement between clinical

impression and ANA+ and ANA- patients

SLE-key® results for the LDA

classification model.

62%

38%

SLE Ruled Out SLE NOT Ruled Out

LDA

70

75

80

85

90

95

100

ANA+ ANA-

95

100

% A

gree

men

t w

ith

clin

ical

imp

ress

ion

Negative67%

Positive33%