Abstract
Protein biochips have a great potential in future parallel processing of complex samples as a research tool and in diagnostics. For the generation of protein biochips, highly automated technologies have been developed for cDNA expression library production, high throughput protein expression, large scale analysis of proteins, and protein microarray generation. Using this technology, we present here a strategy to identify potential autoantigens involved in the pathogenesis of alopecia areata, an often chronic disease leading to the rapid loss of scalp hair. Only little is known about the putative autoantigen(s) involved in this process. By combining protein microarray technology with the use of large cDNA expression libraries, we profiled the autoantibody repertoire of sera from alopecia areata patients against a human protein array consisting of 37,200 redundant, recombinant human proteins. The data sets obtained from incubations with patient sera were compared with control sera from clinically healthy persons and to background incubations with anti-human IgG antibodies. From these results, a smaller protein subset was generated and subjected to qualitative and quantitative validation on highly sensitive protein microarrays to identify novel alopecia areata-associated autoantigens. Eight autoantigens were identified by protein chip technology and were successfully confirmed by Western blot analysis. These autoantigens were arrayed on protein microarrays to generate a disease-associated protein chip. To confirm the specificity of the results obtained, sera from patients with psoriasis or hand and foot eczema as well as skin allergy were additionally examined on the disease-associated protein chip. By using alopecia areata as a model for an autoimmune disease, our investigations show that the protein microarray technology has potential for the identification and evaluation of autoantigens as well as in diagnosis such as to differentiate alopecia areata from other skin diseases.
Highlights
Protein biochips have a great potential in future parallel processing of complex samples as a research tool and in diagnostics
Alopecia areata is an autoimmune disease of the hair follicles that affects between 2 and 4% of patients seen in dermatological practice [7] resulting in rapid loss of hair, often featured by nail dystrophy
Profiling the Antibody Repertoire of Alopecia Areata Patients—In this study we screened a human high density protein array containing 37,200 redundant, recombinant proteins derived from a human fetal brain expression library with sera obtained from 20 alopecia areata patients
Summary
Patient Data—24 patients with alopecia areata (12 alopecia areata circumscripta, two alopecia areata of diffuse type, seven alopecia areata subtotalis or universalis, one alopecia areata ophiasis type, two alopecia areata data not available) in an active stage without any systemic or topical therapy were randomly chosen for participation in this investigation. Following three 30-min TBST washes and subsequent incubation with the secondary antibody (mouse antihuman IgG, Sigma, 1:5000 dilution) in 2% (w/v) BSA, TBST, the protein chips were washed three times for 20 min in TBST. The membrane was blocked in TST buffer (10 mM Tris/HCl, pH 7.5, 150 mM NaCl, 0.1% (v/v) Tween 20) for 1 h and incubated for 1 h with serum adjusted to 10 g/ml IgG in TST (alopecia areata patients serum and control patients serum) or diluted 1:1000 in TST (control human serum). The average value of the protein duplicates or quadruplicates was calculated (averageprotein of patient serumn or control serumn value) followed by the determination of the quality of the screen by calculating the coefficient of variation of the control antibodies, human IgG and mouse IgG, respectively These values were used for interchip normalization. We suggested F values above 2 for disease-significant autoantigens
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