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Biomarkers for Systemic Sclerosis Diagnosis and PAH Prediction

A technology of systemic sclerosis and biological samples, applied in the field of systemic sclerosis diagnosis and PAH prediction biomarkers, can solve the problem of incomplete disease diagnosis and other problems

Active Publication Date: 2021-05-25
PEKING UNION MEDICAL COLLEGE HOSPITAL CHINESE ACAD OF MEDICAL SCI +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Studies have shown that currently relying on histopathological biopsy, biochemical examination and serum autoantibody examination can only detect and diagnose some SSc patients in time, and the diagnosis of this type of disease is still not perfect

Method used

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  • Biomarkers for Systemic Sclerosis Diagnosis and PAH Prediction
  • Biomarkers for Systemic Sclerosis Diagnosis and PAH Prediction
  • Biomarkers for Systemic Sclerosis Diagnosis and PAH Prediction

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Experimental program
Comparison scheme
Effect test

Embodiment 1

[0027]40 SSc patients, 30 autoimmune disease control patients and 20 normal controls were screened for SSc-related autoantibody target antigens using high-throughput protein chip technology containing 21,065 non-redundant recombinant human proteins. The analysis confirmed that 113 SSc-related autoantibody target antigens were screened out. In order to confirm the sensitivity, specificity and clinical application value of these SSc-related autoantibodies, 113 SSc-related autoantibodies corresponding to target antigens were used to construct and prepare SSc-related autoantibody target antigen protein chips for 400 cases of SSc patients and 160 cases of autoimmune diseases. Control patients (including 36 patients with rheumatoid arthritis, 37 patients with systemic lupus erythematosus, 37 patients with Sjogren's syndrome, 25 patients with dermatomyositis and 25 patients with polymyositis), 40 control patients with other chronic diseases (7 cases of endocrine system diseases, 8 ca...

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Abstract

The present invention discloses the use of disintegrin and metalloproteinase 4 with type 1 thrombospondin motif, ie ADAMTSL4, or its fragments in the preparation of reagents for predicting the possibility of pulmonary hypertension in systemic sclerosis. The present invention screens out 113 SSc-related autoantibody target antigens by using high-density protein chip technology. 113 SSc-related autoantibodies corresponding to target antigens were used to construct and prepare SSc-related autoantibody target antigen protein chip for clinical expansion sample verification. The results showed that the positive rate of anti-ADAMTSL4 antibody in SSc patients with PAH was 14.9%, which was significantly higher than the positive rate of 2.88% in SSc patients without PAH, which could be used to predict the possibility of PAH in SSc.

Description

technical field [0001] The invention belongs to the field of biological detection, and specifically relates to biomarkers for systemic sclerosis diagnosis and PAH prediction and uses thereof. Background technique [0002] Systemic sclerosis (SSc), also known as scleroderma, is a systemic autoimmune disease characterized by localized or diffuse skin thickening and fibrosis. The main features of the disease are innate and adaptive immune dysfunction and microvascular damage, which eventually lead to excessive production and accumulation of extracellular matrix and collagen. Although clinically, progressive skin thickening and hardening and fibrosis are usually the main features, but in addition to skin involvement, fibrotic lesions can also involve multiple internal organs (lungs, heart, kidneys, and digestive tract, etc.), and These changes are the decisive factors of clinical prognosis. Among them, interstitial lung disease (ILD) and pulmonary arterial hypertension (PAH) a...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01N33/53
CPCG01N33/53G01N2800/285
Inventor 李永哲胡朝军吴琳刘晨曦李柳冰张奉春
Owner PEKING UNION MEDICAL COLLEGE HOSPITAL CHINESE ACAD OF MEDICAL SCI