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Journal of Gastroenterology and Hepatology 2018-Jun

Investigation of novel biomarkers for predicting the clinical course in patients with ulcerative colitis.

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Shinsaku Hamanaka
Tomoo Nakagawa
Takaki Hiwasa
Yuki Ohta
Shingo Kasamatsu
Hideaki Ishigami
Takashi Taida
Kenichiro Okimoto
Keiko Saito
Daisuke Maruoka

کلید واژه ها

خلاصه

BACKGROUND

The clinical course of ulcerative colitis (UC) is characterized by repeated episodes of relapse and remission. We hypothesized that biomarkers that help distinguish refractory UC patients who are in remission using strong anti-immunotherapy could contribute in preventing the overuse of corticosteroids for treatment. Here, we clarified novel autoantibodies for UC patients in remission as clinical indicators to distinguish between refractory and non-refractory UC.

METHODS

Antigen proteins recognized by serum antibodies of patients with UC in remission were screened using the protein array method. To validate the results, AlphaLISA was used to analyze the serum antibody titers with candidate protein antigens. Serum samples from 101 healthy controls, 121 patients with UC, and 39 patients with Crohn's disease were analyzed.

RESULTS

Of 66 candidate protein antigens screened by ProtoArray™, six were selected for this study. The serum titers of anti-poly ADP-ribose glycohydrolase (PARG), anti-transcription elongation factor A protein-like 1, and anti-proline-rich 13 (PRR13) antibodies were significantly higher in patients with UC than in healthy controls. Anti-PARG and anti-PRR13 antibody titers were significantly higher in patients with refractory UC than in patients with non-refractory UC. There were no significant differences in any antibody titer between the active and remission phases.

CONCLUSIONS

The serum titers of anti-PARG, anti-transcription elongation factor A protein-like 1, and anti-PRR13 antibodies were elevated in patients with UC. Anti-PARG and anti-PRR13 antibody titers may be novel clinical indicators for detecting refractory UC in patients in remission.

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کاملترین پایگاه داده گیاهان دارویی با پشتیبانی علمی

  • به 55 زبان کار می کند
  • درمان های گیاهی با پشتوانه علم
  • شناسایی گیاهان توسط تصویر
  • نقشه GPS تعاملی - گیاهان را در مکان نشان دهید (به زودی)
  • انتشارات علمی مربوط به جستجوی خود را بخوانید
  • گیاهان دارویی را با توجه به اثرات آنها جستجو کنید
  • علایق خود را سازماندهی کنید و با تحقیقات اخبار ، آزمایشات بالینی و حق ثبت اختراع در جریان باشید

علامت یا بیماری را تایپ کنید و در مورد گیاهانی که ممکن است به شما کمک کنند ، بخوانید ، یک گیاه تایپ کنید و بیماری ها و علائمی را که در برابر آن استفاده می شود ، ببینید.
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