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CN-121978350-A - Marker, kit and prediction method for predicting treatment effect of autoimmune hepatitis

CN121978350ACN 121978350 ACN121978350 ACN 121978350ACN-121978350-A

Abstract

The invention discloses a marker for predicting the AIH treatment effect of autoimmune hepatitis, a kit and a prediction method, wherein the marker is JUNB protein, the identifier in a UniProt database is UniProtID:P17535, and the kit is used for detecting the JUNB protein. The invention efficiently and accurately distinguishes the complete biochemical response group and insufficient response group of the AIH standard treatment scheme by detecting the expression level of the JUNB in the PBMC under the determined cut-off value, and provides objective and accurate data support for clinicians to identify refractory patients early and adjust treatment strategies in time. The kit provided by the invention has the advantages that the accuracy of predicting the refractory patients of AIH is high, the missed diagnosis rate is zero, the sensitivity of the prediction method is high, the missed diagnosis risk of the refractory patients in clinic is eliminated, and the safety and reliability are high.

Inventors

  • WANG GUIQIANG
  • XU LONG

Assignees

  • 北京大学第一医院(北京大学第一临床医学院)

Dates

Publication Date
20260505
Application Date
20260210

Claims (10)

  1. 1. A marker for predicting the therapeutic effect of treating AIH by adopting a standard therapeutic scheme is characterized in that the marker is a JUNB protein in peripheral blood mononuclear cells before the treatment of an AIH patient, the identifier of the JUNB protein in a UniProt database is UniProtID:P17535, and the AIH is autoimmune hepatitis.
  2. 2. The marker of claim 1, wherein if the cutoff value of the relative expression level of the JUNB protein in peripheral blood mononuclear cells before treatment of the AIH patient is greater than or equal to 13.715, the AIH patient is judged to be treated with a standard treatment regimen to achieve a "complete biochemical response"; Wherein the standard treatment regimen is a standard glucocorticoid in combination with azathioprine treatment regimen.
  3. 3. A kit for predicting the therapeutic effect of treating AIH by adopting a standard therapeutic scheme is characterized by comprising a substance for detecting the expression level of a JUNB protein in peripheral blood mononuclear cells before the treatment of an AIH patient, wherein the identifier of the JUNB protein in a UniProt database is UniProtID:P17535, and the AIH is autoimmune hepatitis.
  4. 4. The kit according to claim 3, wherein the substance comprises lymphocyte separation solution, cell lysis solution, PBS buffer, trypsin, urea, dithiothreitol DTT, iodoacetamide IAA, ammonium bicarbonate buffer, formic acid, acetonitrile, and BCA protein concentration determination reagent.
  5. 5. The kit of claim 4, wherein detecting the amount of JUNB protein expression comprises: separating and washing peripheral blood of an AIH patient by using lymphocyte separating medium and PBS buffer solution to obtain peripheral blood mononuclear cell PBMC; performing lysis treatment on the PBMC by adopting cell lysate to obtain a total protein extract; Removing impurities in the total protein extract by adopting an acetone precipitation method, adding urea dissolving protein precipitate, and quantifying BCA protein by utilizing a BCA protein concentration measuring reagent; adding dithiothreitol to the protein sample subjected to BCA protein quantification to reduce disulfide bonds; Then, adding iodoacetamide for alkylation reaction after cooling; Adding ammonium bicarbonate buffer solution to dilute the urea concentration to below 1M; Then adding sequencing-grade trypsin, and carrying out enzymolysis according to the ratio of enzyme to protein=1:50 (w/w) to obtain a peptide fragment mixture; detecting the re-dissolved peptide mixture by using a liquid chromatography-tandem mass spectrometry system to obtain the original mass spectrometry data of the peptide mixture; And processing the too short mixed substance spectrum data by MaxQuant software to obtain the relative expression quantity of the JUNB protein of the patient.
  6. 6. The kit of claim 5, wherein if the relative expression level of the JUNB protein in the patient is greater than or equal to the cutoff value 13.715, the standard treatment regimen is predicted to be "complete biochemical response" for AIH, whereas the standard treatment regimen is predicted to be "inadequate response", wherein the standard treatment regimen is a standard glucocorticoid in combination with azathioprine treatment regimen.
  7. 7. The kit of claim 5, wherein the lymphocyte separation medium is a Ficoll separation medium.
  8. 8. The kit of claim 5, wherein the cell lysate is a RIPA lysate containing a protease inhibitor.
  9. 9. A method of predicting the therapeutic effect of treating AIH using a standard treatment regimen, comprising: Detecting the expression level of the JUNB protein in peripheral blood mononuclear cells before treatment of an AIH patient; If the relative expression quantity of the JUNB protein of the patient is more than or equal to a cutoff value 13.715, the AIH is predicted to be completely biochemically responded by adopting a standard treatment scheme; wherein the identifier of the JUNB protein in the UniProt database is UniProtID:P17535, and the standard treatment scheme is a standard glucocorticoid combined azathioprine treatment scheme.
  10. 10. The kit of claim 9, wherein detecting the amount of JUNB protein expression comprises: separating and washing peripheral blood of an AIH patient by using lymphocyte separating medium and PBS buffer solution to obtain peripheral blood mononuclear cell PBMC; performing lysis treatment on the PBMC by adopting cell lysate to obtain a total protein extract; Removing impurities in the total protein extract by adopting an acetone precipitation method, adding urea dissolving protein precipitate, and quantifying BCA protein by utilizing a BCA protein concentration measuring reagent; adding dithiothreitol to the protein sample subjected to BCA protein quantification to reduce disulfide bonds; Then, adding iodoacetamide for alkylation reaction after cooling; Adding ammonium bicarbonate buffer solution to dilute the urea concentration to below 1M; Then adding sequencing-grade trypsin, and carrying out enzymolysis according to the ratio of enzyme to protein=1:50 (w/w) to obtain a peptide fragment mixture; detecting the re-dissolved peptide mixture by using a liquid chromatography-tandem mass spectrometry system to obtain the original mass spectrometry data of the peptide mixture; And processing the too short mixed substance spectrum data by MaxQuant software to obtain the relative expression quantity of the JUNB protein of the patient.

Description

Marker, kit and prediction method for predicting treatment effect of autoimmune hepatitis Technical Field The invention relates to a marker for predicting an AIH treatment effect of autoimmune hepatitis, a kit and a prediction method. Background Autoimmune hepatitis (AutoimmuneHepatitis, AIH) is a chronic progressive liver inflammatory disease mediated by immunity and is characterized clinically by elevated serum transaminases, hyperimmune globulin G (IgG) blood disease, and the appearance of autoantibodies. Currently, standard first-line treatment regimens for AIH rely primarily on corticosteroids (such as prednisone or prednisolone) alone or in combination with azathioprine for immunosuppressive therapy. The main goal of clinical treatment is to obtain a "complete biochemical response", i.e. a return of serum aminotransferase (ALT/AST) and IgG levels to within the normal range. Numerous studies have shown that patients who obtain a complete biochemical response have significantly better liver inflammation resolution, reversal of fibrosis, and long-term survival than patients who have "inadequate responses". Therefore, in early treatment or diagnosis stage, the immune state of the patient is deeply analyzed through samples such as Peripheral Blood Mononuclear Cells (PBMC) and the like, so that the potential responsiveness of the patient to treatment is accurately distinguished, and the method has extremely important clinical significance for developing an individual treatment scheme and improving the prognosis of the patient. Current AIH diagnosis relies primarily on ‌ autoantibody detection ‌, including ‌ anti-nuclear antibodies (ANA) ‌ and ‌ anti-smooth muscle antibodies (ASMA) ‌ for type I AIH diagnosis. ‌ anti-liver and kidney microsomal antibody (LKM) ‌ core marker of AIH type II. ‌ high specificity markers against soluble liver antigen/hepatopancreatic antigen antibodies (SLA/LP) ‌:type III AIH. These antibodies have been clinically validated and are the primary basis for diagnosis of AIH. While the current standardized treatment regimen is effective for most AIH patients, in clinical practice, some patients still appear to be "poorly responsive" (IncompleteResponse) or unresponsive to treatment. In the prior art, the evaluation of AIH therapy response has mainly the following problems: ① The hysteresis of the evaluation index is that the clinic is mainly dependent on the treatment for a period of time (usually 3-6 months or even longer) at present, and the curative effect is retrospectively judged by monitoring the descending trend of serum biochemical indexes (such as ALT, AST, igG). The trial-and-error method has obvious hysteresis, and can not predict whether patients belong to the group of refractory (i.e. insufficient response) patients at the initial stage of treatment or during diagnosis. ② Lack of accurate molecular markers existing evaluation systems lack specific molecular markers based on pathogenesis (e.g. specific protein expression levels). Although some studies have focused on cytokine levels, it is difficult to use as a stable predictor due to its short half-life and large fluctuations. ③ The limitation of invasive examination is that liver biopsy, while a gold standard for assessing liver inflammation and fibrosis, is invasive, presents a risk of complications such as bleeding, and makes it difficult to dynamically monitor treatment response by repeated sampling. To overcome the above technical drawbacks, the effectiveness of treatment regimens on AIH patients is currently evaluated mainly using a combined scoring system based on clinical biochemical indicators (e.g. based on models of pre-treatment bilirubin, transaminase levels) or on the detection of single immune cell subsets (e.g. Treg cell ratios), but these techniques also have the following drawbacks: ① The sensitivity and the specificity are insufficient, namely, the two groups of people with complete response and insufficient response are difficult to accurately distinguish by simply relying on the baseline level of the conventional biochemical indexes, because the biochemical manifestations of the two groups of patients when suffering from diseases are overlapped greatly (Overlap), so that the area under the ROC curve (AUC) of a prediction model is usually lower, and the misjudgment rate is higher. ② The AIH essence is broken, and the existing rough index cannot reflect the key difference of specific transcription factors (such as AP-1 family members) in an immune regulation network, so that the deep biological mechanism of response difference is difficult to reveal. Disclosure of Invention The invention aims to provide a marker for predicting the AIH treatment effect of autoimmune hepatitis (AIH), a detection kit and a prediction method, aiming at the problems that in the prior art, patients with complete biochemical response and insufficient response cannot be accurately distinguished in early stage of the AIH treatment