| Literature DB >> 21329504 |
Robert Biesen1, Cornelia Dähnrich, Anke Rosemann, Fidan Barkhudarova, Thomas Rose, Olga Jakob, Anne Bruns, Marina Backhaus, Winfried Stöcker, Gerd-Rüdiger Burmester, Wolfgang Schlumberger, Karl Egerer, Falk Hiepe.
Abstract
INTRODUCTION: The objective of this study was to compare the clinical usefulness of the new anti-double-stranded DNA nucleosome-complexed enzyme-linked immunosorbent assay (Anti-dsDNA-NcX ELISA), which is based on dsDNA-loaded nucleosomes as antigens, with established test systems based on dsDNA or nucleosomes alone for systemic lupus erythematosus (SLE) diagnostics and determination of disease activity.Entities:
Mesh:
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Year: 2011 PMID: 21329504 PMCID: PMC3241370 DOI: 10.1186/ar3250
Source DB: PubMed Journal: Arthritis Res Ther ISSN: 1478-6354 Impact factor: 5.156
Figure 1Right-positive and false-positive test results of anti-double-stranded DNA nucleosome-complexed enzyme-linked immunosorbent assay (Anti-dsDNA-NcX ELISA). (A) Scatterplot showing Anti-dsDNA-NcX ELISA immunoglobulin G results in 964 different sera. Dotted line represents the manufacturer's threshold (100 IU/ml). Values >800 IU/ml were set to 800 IU/ml for a clearer arrangement of the figure. SLE, systemic lupus erythematosus; SSc, systemic sclerosis; SS, Sjögren's syndrome; RA, rheumatoid arthritis; ND, normal donors; (B) Table showing all non-SLE patients who tested positive in the Anti-dsDNA-NcX ELISA listed with the test results of all measured assays and clinically relevant findings. Positive test results according to a comparable specificity of 98.9% are marked in bold. Nuc, anti-dsDNA-nucleosome ELISA; Farr, radioimmunoassay; CLIF, Crithidia luciliae immunofluorescence assay; ANA, antinuclear antibodies; C3, complement component 3.
Performance criteria in ROC analysisa
| Criteria | Anti-dsDNA-NcX | Anti-dsDNA | Antinucleosome | Farr |
|---|---|---|---|---|
| Area under the curve | 0.9133b | 0.8455 | 0.9118 | 0.8823 |
| 95% confidence interval | 0.89 to 0.94 | 0.81 to 0.88 | 0.89 to 0.94 | 0.85 to 0.91 |
| Sensitivity at specificity of 95% | 72.5%b | 55.6% | 67.2% | 65.7% |
| (cutoff) | (>49.7) | (>58.8) | (>6.8) | (>5.1) |
| Sensitivity at specificity of 98% | 66.7%b | 43.0% | 58.0% | 55.6% |
| (cutoff) | (>71.5) | (>99.7) | (>11.1) | (>6.0) |
| Sensitivity at specificity of 98.15%c | 66.7%b | 41.5% | 55.6% | 55.6 |
| (cutoff) | (>72.03) | (>105.8) | (>12.1) | (>6.0) |
| Sensitivity at specificity of 99% | 59.9%b | 35.8% | 53.6% | 54.1% |
| (cutoff) | (>103.4) | (>151.6) | (>14.8) | (>6.5) |
| Maximum sum of sensitivity + specificity | 170.9b | 159.1 | 168.7 | 162.1 |
adsDNA, double-stranded DNA. Test criteria for the Anti-dsDNA-NcX, anti-dsDNA and antinucleosome enzyme-linked immunosorbent assays (ELISAs), as well as for the anti-dsDNA radioimmunoassay (also known as a Farr assay), were calculated using receiver operating characteristic (ROC) curve analysis based on test readings of 964 samples from 207 systemic lupus erythematosus (SLE) patients, 357 disease controls and 400 healthy donors. Outcome parameters of ROC curve analysis were diagnosis versus no diagnosis of SLE. bHighest value over all four assays. cThis specificity was calculated for the Crithidia luciliae immunofluorescence (CLIF) assay.
Figure 2Comparison of patient sera that tested positive in the anti-double-stranded DNA nucleosome-complexed enzyme-linked immunosorbent assay (Anti-dsDNA-NcX ELISA) and other investigated test systems shown in Venn diagrams. (A) Absolute numbers of patient sera that tested positive in the Anti-dsDNA-NcX ELISA (dsDNA-NcX), the anti-dsDNA ELISA (dsDNA) and the anti-dsDNA nucleosome ELISA (Nuc) and their combined intersections are shown. (B) The same analysis as in Figure 2A is shown, including different detection techniques using Anti-dsDNA-NcX ELISA, Farr assay (radioimmunoassay) and Crithidia luciliae immunofluorescence (CLIF) assay is presented. Cutoffs for all positive test results were read out of receiver operating characteristic curve analysis at a specificity of 98.15% because this specificity was calculated for the CLIF assay.
Frequency of sera being positive in one test system and negative in another test systema
| SLE patients ( | NcX+ | dsDNA+ | Nuc+ | Farr+ | CLIF+ |
|---|---|---|---|---|---|
| NcX- ( | - | 1% | 0% | 13% | 7% |
| dsDNA- ( | 44% | - | 33% | 35% | 14% |
| Nuc- ( | 25% | 12% | - | 21% | 8% |
| Farr- ( | 35% | 14% | 21% | - | 5% |
| CLIF- ( | 57% | 30% | 43% | 57% | - |
aSLE, systemic lupus erythematosus; NcX, anti-dsDNA-nucleosome-complexed enzyme-linked immunosorbent assay (ELISA); dsDNA, double-stranded DNA; Nuc, anti-dsDNA-nucleosome ELISA; Farr, radioimmunoassay; CLIF, Crithidia luciliae immunofluorescence assay. Cutoffs for all test systems were read out of receiver operating characteristic curve analysis at a specificity of 98.15% to include the CLIF assay in that analysis. Frequencies of sera being positive in one selected test (column headings) and negative in another test system (left column stub headings) were filled to demonstrate the extent of cross-reactivity between tests. The positive sera were compared with the negative sera to calculate percentages. For example, among all anti-dsDNA-NcX ELISA-negative sera (n = 69), 1% were positive on the basis of the anti-dsDNA ELISA.
Comparison of test assay titers in patients with versus those without a distinct present clinical findinga
| Disease feature | Number of patients | NcX | dsDNA | Nuc | Farr | CLIF |
|---|---|---|---|---|---|---|
| ACR criteria (ever), | ||||||
| Renal | 101 | 0.01 | 0.03 | 0.01 | ns | ns |
| Neurologic | 23 | 0.01 | 0.03 | 0.01 | 0.04 | ns |
| Hematological | 134 | ns | ns | ns | ns | 0.04 |
| mSLEDAI 2000 (current), | ||||||
| Casts | 3 | 0.03 | 0.04 | 0.04 | 0.02 | 0.04 |
| Hematuria | 13 | <0.001 | 0.001 | 0.003 | 0.002 | ns |
| Proteinuria | 16 | 0.04 | ns | ns | ns | ns |
| Leukocyturia | 3 | 0.04 | 0.02 | ns | ns | ns |
| Pleuritis | 5 | ns | ns | ns | 0.01 | ns |
| Pericarditis | 10 | ns | 0.02 | ns | ns | ns |
| Complement | 84 | 0.003 | 0.005 | 0.004 | 0.01 | 0.03 |
| Fever | 8 | 0.02 | 0.04 | ns | ns | ns |
| Thrombocytes | 5 | ns | 0.04 | ns | ns | 0.03 |
| Laboratory (current), | ||||||
| Decreased lymphocytes | 91 | 0.02 | 0.02 | ns | 0.03 | ns |
| Decreased monocytes | 27 | 0.02 | 0.02 | ns | ns | ns |
| Decreased C-reactive protein | 62 | 0.02 | 0.04 | 0.04 | ns | ns |
| Decreased C3 | 83 | 0.004 | 0.001 | 0.01 | 0.004 | ns |
| Decreased C4 | 63 | ns | 0.04 | ns | ns | ns |
| Proteinuria >150 mg/d | 39 | 0.01 | ns | 0.04 | ns | ns |
aComparison was performed using the Mann-Whitney U test. This table is reduced to statistically significant findings to increase readability. Significance with regard to any feature was always found for increased values of autoantibody assays. The number of patients with a positive finding (ACR and SLEDAI 2000) or an abnormal finding (local laboratory) of all patients is given. Current values refer to values on the date of blood withdrawal. NcX, anti-dsDNA-nucleosome-complexed enzyme-linked immunosorbent assay (ELISA); dsDNA, dsDNA, double-stranded DNA; Nuc, anti-dsDNA-nucleosome ELISA; Farr, radioimmunoassay; CLIF, Crithidia luciliae immunofluorescence assay; ACR, American College of Rheumatology; mSLEDAI 2000, modified Systemic Lupus Erythematosus Disease Activity Index 2000 [25]; C3, complement component C3; C4, complement component C4; ns, not significant.
Figure 3Changes in disease activity versus changes of six defined laboratory parameters over time. All results are based on a total of 69 patient visits of 20 different systemic lupus erythematosus patients. Delta values were calculated by subtracting values for a defined parameter from an actual visit from a defined parameter from the last visit (for example, ΔC3 = C3(visit + 1) - C3(visit ). Only changes in Anti-dsDNA-NcX and antinucleosome ELISA results correlated significantly with changes in modified Systemic Lupus Erythematosus Disease Activity Index 2000 (mSLEDAI 2000 [25]) score over time. The mSLEDAI items for double-stranded DNA (dsDNA) and complement components C3 and C4 were excluded to avoid bias. Linear regression analysis was used to calculate significance.