KR101946884B1 - Method for diagnosing Behcet's disease by using metabolomics - Google Patents

Method for diagnosing Behcet's disease by using metabolomics Download PDF

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KR101946884B1
KR101946884B1 KR1020170052665A KR20170052665A KR101946884B1 KR 101946884 B1 KR101946884 B1 KR 101946884B1 KR 1020170052665 A KR1020170052665 A KR 1020170052665A KR 20170052665 A KR20170052665 A KR 20170052665A KR 101946884 B1 KR101946884 B1 KR 101946884B1
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김경헌
차훈석
김정연
안중경
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Abstract

본 발명은 대사체 분석을 이용한 베체트병 진단방법에 관한 것으로, 대사체학을 이용하여 베체트병을 효과적으로 진단할 수 있는 바이오마커를 제공하며, 이는 베체트병 치료제 개발에도 적용할 수 있다.The present invention relates to a method for diagnosing Behcet's disease using metabolic analysis, and provides a biomarker capable of effectively diagnosing Behcet's disease using metabolomics, which can also be applied to the development of a therapeutic agent for Behcet's disease.

Description

대사체 분석을 이용한 베체트병의 진단방법{Method for diagnosing Behcet's disease by using metabolomics}Methods for Diagnosing Behcet's Disease Using Metabolism Analysis

본 발명은 대사체 분석을 통해 베체트병을 진단하는 방법에 관한 것이다.The present invention relates to a method for diagnosing Behcet's disease through metabolic analysis.

베체트병은 원인이 밝혀지지 않은 전신적인 혈관염으로, 구강, 성기 및 항문의 궤양, 포도막염, 관절염, 위장관, 혈관 및 중추 신경계 등의 중요 장기의 침범 등 다양한 증상을 특징으로 하는 질환이다). 베체트병은 지중해 연안부터 극동 아시아에 이르는 지역, 특히 한국, 중국, 일본 그리고 터키 지역에서 발병 빈도가 높은 것으로 보고되어 있다. Behcet's disease is an unexplained systemic vasculitis characterized by various symptoms such as oral, genital and anal ulcer, uveitis, arthritis, gastrointestinal tract, vascular and central nervous system involvement. Behcet's disease has been reported to occur frequently in areas ranging from the Mediterranean Sea to Far East Asia, particularly in Korea, China, Japan and Turkey.

베체트병의 임상 양상은 매우 다양하며, 반복적인 구강 궤양과 같은 경미한 증상부터 안구, 위장관, 혈관 및 중추 신경계 등을 침범하여 실명, 장궤양 및 천공, 동맥류로 인한 객혈, 심부 정맥 혈전증, 편측 마비와 같은 치명적인 후유증을 남길 수 있다. 베체트병의 다양한 증상은 20대에서 40대에서 가장 심한 질병의 활성도를 보여서 경제적, 사회적 손실이 매우 클 것으로 예상되는 질병이다.The clinical manifestations of Behcet's disease are very diverse, ranging from mild symptoms such as recurrent oral ulcers to ocular, gastrointestinal, vascular and central nervous system disorders, including blindness, intestinal ulceration and perforation, hemoptysis due to aneurysms, deep vein thrombosis, You can leave the same fatal aftereffects. Various symptoms of Behcet 's disease are the most severe disease activity in their 20s and 40s, so economic and social losses are expected to be very large.

베체트병은 다양한 기관의 침범에 따른 다양한 임상 양상과 예후를 보이기에, 이에 따른 진단 및 치료에 상당한 어려움을 겪고 있다. 그러므로 베체트병으로 합병증과 장애를 최소화하기 위해 베체트병을 조기에 정확히 진단하는 것은 매우 중요하다. Behcet 's disease has various clinical manifestations and prognoses due to invasion of various organs, and thus has a great difficulty in diagnosis and treatment. Therefore, it is very important to diagnose Behcet's disease early and accurately in order to minimize complications and disability with Behcet's disease.

이러한 베체트병의 진단은 베체트병 환자와 건강한 사람을 구분할 수 있는 객관적인 진단적 생체표지자가 없으므로, 주로 임상적인 증상에 의존하고 있다. 그러나 실제 베체트병은 유전적, 환경적, 면역학적 이상에 의해 여러 장기를 침범하여 다양한 임상 증상이 나타나게 되고, 이런 이유로 기존에 알려진 단일 생체표지자는 낮은 민감도 및 특이성을 보인다. 따라서 다양한 임상 증상과 기존의 생체표지자의 부정확성으로 인해 정확한 진단이 어려우므로, 발병 후 확진까지 오랜 시간이 걸리는 문제점이 있다. 이를 극복하기 위해서, 객관적인 진단적 생체표지자를 발명하는 것은 매우 중요하다. The diagnosis of Behcet's disease is based on clinical symptoms, since there is no objective diagnostic biomarker that can distinguish between patients with Behcet's disease and healthy individuals. However, the genetic, environmental, and immunological abnormalities of Behcet 's disease actually invade various organs and manifest various clinical symptoms. For this reason, a known single biomarker has low sensitivity and specificity. Therefore, accurate diagnosis is difficult due to various clinical signs and inaccuracies of existing biomarkers, and it takes a long time until diagnosis after the onset. To overcome this, it is very important to invent an objective diagnostic biomarker.

따라서 베체트병을 진단할 수 있는 객관적인 진단적 생체표지자를 발굴하는 것은, 베체트병을 조기 진단하여, 베체트병 확진에 걸리는 시간을 줄이고 발병에 적절한 치료를 할 수 있게 하여 환자의 증상 악화로 인한 합병증을 최소화시킬 수 있다. 또한 이는 고가의 불필요한 치료를 피하고 환자에게 맞춤형 치료, 그리고 질환과 관련한 예후에 관한 정확한 정보를 제공함으로써 더 좋은 치료 성적을 거둘 수 있을 것으로 생각된다. 최근 류마티스 관절염, 골관절염, 건선관절염, 전신홍반루푸스와 같은 류마티스 질환에서 생체표지자 발굴을 위해 메타볼로믹스 기술이 많은 각광을 받고 있다[비특허문헌 1~3] Therefore, the objective diagnostic diagnostic biomarker for diagnosing Behcet's disease is to diagnose Behcet's disease early, to reduce the time required for the diagnosis of Behcet's disease, and to treat the disease appropriately. Can be minimized. It may also provide better treatment results by avoiding expensive unnecessary treatments, tailoring treatment to patients, and providing accurate information about the prognosis associated with the disease. Recently, meta-bolromix techniques have been attracting much attention for the detection of biomarkers in rheumatic diseases such as rheumatoid arthritis, osteoarthritis, psoriatic arthritis, and systemic lupus erythematosus [Non-Patent Documents 1 to 3]

베체트병에서 생체표지자 발굴을 위해 현재까지 보고된 기술들은 주로 유전체학 또는 단백질체학적 접근이었지만, 그 결과가 뚜렷하지 못하거나 실제 베체트병 진단에 사용되기는 어려웠으며[비특허문헌 4~5], 베체트병에서 대사체학을 이용한 진단 및 예후 예측에 적절한 생체표지자 발굴을 위한 연구는 보고된 바 없다.Techniques reported to date for the detection of biomarkers in Behcet's disease were mainly genomic or proteomic approaches, but the results were not clear or were difficult to be used in the actual diagnosis of Behcet's disease [Non-Patent Documents 4-5] There have been no reports on the use of metabolomics for the detection of biomarkers suitable for diagnosis and prognosis prediction.

Madsen RK et al. Diagnostic properties of metabolic perturbations in rheumatoid arthritis (2011) Arthritis Res Ther. 13(1):R19, Madsen RK et al. Diagnostic properties of metabolic perturbations in rheumatoid arthritis (2011) Arthritis Res Ther. 13 (1): R19, Kapoor et al. Metabolic profiling predicts response to anti-tumor necrosis factor α therapy in patients with rheumatoid arthritis (2013) Arthritis Rheum 65:1448-65, Kapoor et al. Metabolic profiling predictors response to anti-tumor necrosis factor α therapy in patients with rheumatoid arthritis (2013) Arthritis Rheum 65: 1448-65, Kim s et al. Global metabolite profiling of synovial fluid for the specific diagnosis of rheumatoid arthritis from other inflammatory arthritis. (2014) PLos one 9:e97501Kim s et al. Global metabolite profiling of synovial fluid for the specific diagnosis of rheumatoid arthritis from other inflammatory arthritis. (2014) PLos one 9: e97501 Yuko et al. Proteomic surveillance of autoimmunity in Behcet's disease with uveitis: selenium binding protein is a novel autoantigen in Behcet's disease. (2007) Experimental Eye Research 84: 823-831, Yuko et al. Proteomic surveillance of autoimmunity in Behcet's disease with uveitis: Selenium binding protein is a novel autoantigen in Behcet's disease. (2007) Experimental Eye Research 84: 823-831, Seido et al. Proteomic surveillance of autoantigens in patients with Behcet's disease by a proteomic approach. (2010) Microbiol Immunol 54:354-361Seido et al. Proteomic surveillance of autoantigens in patients with Behcet's disease by a proteomic approach. (2010) Microbiol Immunol 54: 354-361

이에, 본 발명자들은 베체트병의 신속하고 편리한 진단을 위한 혈액 샘플 내에서 특이적인 생체표지자를 찾기 위해 GC/TOF MS(gas chromatography/time-of-flight mass spectrometry) 기법을 적용하여 검체 다양한 증상의 베체트병 환자들과 건강한 대조군들과 감별할 수 있는 혈액 내 대사물질들의 대사체 프로파일링 및 특이적 대사체들을 찾고자 연구 노력한 결과, 혈액에 대사체학적 기법을 적용하여 베체트병의 정확한 진단을 위한 새로운 생체표지자를 발굴함으로써 본 발명을 완성하게 되었다.Therefore, the present inventors applied GC / TOF MS (gas chromatography / time-of-flight mass spectrometry) technique to find a specific biomarker in a blood sample for quick and convenient diagnosis of Behcet's disease, The aim of this study was to investigate metabolic profiling and specific metabolites of blood metabolites which can be distinguished from patients and healthy control subjects. As a result, The present inventors have completed the present invention by discovering markers.

따라서, 본 발명은 대사체 분석을 통해 베체트병을 진단하기 위한 키트를 제공하는데 그 목적이 있다. Accordingly, it is an object of the present invention to provide a kit for diagnosing Behcet's disease through metabolic analysis.

또한, 본 발명은 베체트병을 진단하기 위한 대사체 차별성을 분석하는 방법을 제공하는데 목적이 있다. It is another object of the present invention to provide a method for analyzing metabolic differentiation for diagnosing Behcet's disease.

본 발명은 데칸산(decanoic acid), 프룩토오스(fructose), 타가토오스(tagatose), 올레산(oleic acid), 리놀레산(linoleic acid), L-시스테인(L-cysteine), 소르비톨(sorbitol), 우리딘(uridine), 이노신(inosine), 갈락토네이트(galactonate), 글라이콜레이트(glycolate), 팔미트산(palmitic acid) 및 히스티딘(histidine)으로 이루어진 군에서 선택된 하나 이상의 혈액 대사체에 대한 정량 장치를 포함하는 베체트병 진단 키트를 제공한다.The present invention relates to a process for the preparation of a pharmaceutical composition comprising decanoic acid, fructose, tagatose, oleic acid, linoleic acid, L-cysteine, sorbitol, A quantitative determination of one or more blood metabolites selected from the group consisting of uridine, inosine, galactonate, glycolate, palmitic acid, and histidine. The present invention provides a Behcet's disease diagnostic kit comprising the device.

또한, 본 발명은 정상 대조군과 베체트병에서 얻은 혈액 간의 대사체 차별성을 검출하는 방법으로,In addition, the present invention is a method for detecting metabolic differentiation between blood obtained from a normal control group and Behcet's disease,

(1) GC/TOF MS(gas chromatography/time-of-flight mass spectrometry)를 이용한 대사체 분석 단계; (1) metabolism analysis step using GC / TOF MS (gas chromatography / time-of-flight mass spectrometry);

(2) GC/TOF MS에서 동정된 대사체에 대해 부분최소자승판별분석(PLS-DA)를 이용하여 대사체 프로파일의 차이를 확인하는 단계;(2) identifying differences in metabolite profiles using partial least squares discriminant analysis (PLS-DA) for the metabolites identified in GC / TOF MS;

(3) PLS-DA에서 도출된 대사체의 VIP(Variable Importance for Projection) 값이 1.5 이상인 값을 대사체 바이오마커 후보물질로 선정하고, PLS-DA의 로딩 값을 통해 대사체 바이오마커 후보물질의 증감 확인하는 단계;(3) The value of Variable Importance for Projection (VIP) of the metabolite derived from PLS-DA was selected as the metabolite biomarker candidate, and the value of PLS-DA loading value was used as the metabolite biomarker candidate Ascertaining and decreasing;

(4) ROC 곡선(Receiver Operating Characteristic curve)을 이용하여 대사체 바이오마커를 검증하는 단계(4) Verifying the metabolite biomarker using the ROC curve (Receiver Operating Characteristic curve)

를 순차적으로 적용하여, 혈액으로부터 대사체 바이오마커를 분석하는 것을 포함하는 정상 대조군과 베체트병에서 얻은 혈액 간의 대사체 차별성 분석 방법을 제공한다.And analyzing the metabolite biomarker from the blood to provide a method of analyzing metabolism differentiation between blood obtained from a normal control group and Behcet's disease.

본 발명은 베체트병 환자를 특이적으로 감별 진단하기 위해 대사체학적 접근을 통하여 신속하고 정확하게 베체트병을 진단할 수 있는 생체표지자를 발굴하였다. GC/TOF MS를 이용하여 베체트병 환자와 일반인의 혈액 내 대사체 분석을 통해 104개의 대사체를 검출하였다. 부분최소제곱회귀법(PLS-DA)과 VIP(variable importance for projection) 값, ROC (Receiver operating characteristic) 곡선의 AUC(area under the curve)의 값, fold change, p-value 등을 산출하여 통해 13개의 강력한 대사물질 생체표지자를 제시하였다. 또한, 최종적으로 5개(decanoic acid, fructose, tagatose, oleic acid, linoleic acid)의 생체표지자를 이용한 베체트병 진단 panel을 만들었으며, 이를 외부 검체(validation set)을 이용하여 임상적 타당성을 검증하였다. 본 발명을 통하여 대사체학을 혈액 분석에 이용해 베체트병을 특이적으로 진단할 수 있는 생체표지자를 최초로 규명하였다. 이는 아직까지도 완전히 밝혀져 있지 않은 베체트병의 발병 기전을 밝히는 연구의 기반이 될 수 있다. 또한, 다양한 임상 증상에 최적화된 치료제 개발에도 응용될 수 있다. 베체트병의 진단을 용이하게 하는 생체표지자의 발견은 베체트병 환자를 신속하고 정확하게 진단하고, 임상적 진단에 걸리는 긴 시간을 크게 줄여서 맞춤형 치료를 빠르게 제공하여 일상생활로 복귀를 빠르게 하는 등의 사회 경제적 파급 효과도 상당할 것으로 기대된다.The present invention uniquely identifies biologic markers that can diagnose Behcet's disease quickly and accurately through a metabolic approach to specifically differentiate patients with BD. Using GC / TOF MS, 104 metabolites were detected by metabolism analysis in the blood of patients with Behcet 's disease and the general population. We calculated the PLS-DA, the variable importance for projection (VIP), the area under the curve (AUC) of the receiver operating characteristic (ROC) curve, the fold change and the p- A strong metabolite biomarker was presented. Finally, we made a panel of 5 patients with Behçet's disease using biochemical markers such as decanoic acid, fructose, tagatose, oleic acid and linoleic acid. We validated the clinical feasibility using an external sample (validation set). Through the present invention, a biomarker capable of specifically diagnosing Behcet's disease by using metabolomics in blood analysis was first identified. This may be the basis for a study that reveals the pathogenesis of Behcet's disease, which has not yet been fully understood. It can also be applied to the development of therapeutic agents optimized for various clinical symptoms. The discovery of a biomarker that facilitates the diagnosis of Behcet's disease can be used to quickly and accurately diagnose Behcet's disease patients, greatly reduce the length of time required for clinical diagnosis, and thus provide customized treatment to speed up return to daily life, The ripple effect is also expected to be significant.

도 1은 PLS-DA를 이용하여 베체트병 환자와 건강한 대조군의 혈액 내 대사체 프로파일링 차이를 나타낸 결과이다[베체트병 환자와 건강한 대조군의 대사체가 확연한 차이를 보여 구분됨. BD, 베체트병; HC, 건강한 대조군].
도 2는 베체트병에서 유의미하게 증가한 상위 8개 대사물질(A)과 유의미하게 감소한 상위 5개 대사물질(B)의 수준 비교 그래프이다.
도 3은 베체트병 환자 내 steroid, colchicine, azathioprine 투여 그룹과 비투여 그룹 간의 대사체적 차이를 PLS-DA로 나타낸 결과이다[각각의 약물투여 그룹과 비투여 그룹 간의 차이가 Q2 값이 매우 낮아 재현성이 없고, 통계학적으로 그룹 간의 대사체적 차이가 없음을 보임].
도 4는 베체트병에서 유의미하게 증가한 상위 3개 대사물질(decanoic acid, fructose, tagatose)과 유의미하게 감소한 상위 2개 대사물질(oleic acid, linoleic acid)을 이용해 베체트병을 진단하는 대사체적 생체표지자 panel을 PCA를 통해 분석한 결과이다[PC1 하나의 축을 이용하였을 때, R2X 값이 0.721로 적절하게 구분됨을 보였으며, Q2값이 0.515로 모델이 재현성이 있음을 확인함].
도 5는 혈액 검체를 이용한 베체트병 진단을 위한 대사체적 진단 panel의 ROC(receiver operating characteristic curve) 결과이다[5개의 대사체 조합을 이용한 생체표지자 panel이 베체트병의 진단에 있어 민감도 100%, 특이도 97.1%, AUC 0.993의 결과를 보임].
도 6은 혈액 샘플을 이용한 베체트병 진단을 위한 대사체적 진단 panel의 외부 검체 검증 결과이다[주성분 분석에서 10개의 베체트병 환자 혈액 및 10개의 건강한 대조군 중 9개의 베체트병 환자 및 10개의 건강한 대조군을 정확하게 예측할 수 있음을 보임].
FIG. 1 shows the difference in the metabolism profile of metabolites in the blood between patients with BD and healthy controls using PLS-DA. The metabolites of patients with BD and healthy controls were distinctly different. BD, Behcet's disease; HC, healthy control].
FIG. 2 is a graph comparing the levels of the top eight metabolites (A) significantly increased and the five most significant metabolites (B) significantly increased in Behcet's disease.
FIG. 3 shows the results of PLS-DA as a metabolite difference between steroid, colchicine, and azathioprine administration group and non-administration group in Behcet's disease patients [the difference between each drug administration group and the non-administration group is very low No statistically significant difference between the groups.
Figure 4 is a graph showing the results of a metabolic biomarker panel (Fig. 4) for diagnosing Behcet's disease using the top three metabolites (decanoic acid, fructose, tagatose) and the two significantly higher oleic acid [PC1]. When using one axis, the R2X value was properly classified as 0.721, and the Q2 value was 0.515, confirming that the model was reproducible.
FIG. 5 is a receiver operating characteristic curve (ROC) result of a metabolic diagnostic panel for the diagnosis of Behcet's disease using a blood sample. The biomarker panel using 5 metabolism combinations showed sensitivity of 100% 97.1%, AUC 0.993).
Figure 6 shows the results of external sample verification of a metabolic panel for diagnosis of Behcet's disease using blood samples. [From the principal component analysis, ten patients with Behcet's disease blood, nine patients with Behcet's disease and ten healthy controls among ten healthy controls) It can be predicted].

이하, 본 발명의 구성을 구체적으로 설명한다.Hereinafter, the configuration of the present invention will be described in detail.

본 발명은 데칸산(decanoic acid), 프룩토오스(fructose), 타가토오스(tagatose), 올레산(oleic acid), 리놀레산(linoleic acid), L-시스테인(L-cysteine), 소르비톨(sorbitol), 우리딘(uridine), 이노신(inosine), 갈락토네이트(galactonate), 글라이콜레이트(glycolate), 팔미트산(palmitic acid) 및 히스티딘(histidine)으로 이루어진 군에서 선택된 하나 이상의 혈액 대사체에 대한 정량 장치를 포함하는 베체트병 진단 키트에 관한 것이다.The present invention relates to a process for the preparation of a pharmaceutical composition comprising decanoic acid, fructose, tagatose, oleic acid, linoleic acid, L-cysteine, sorbitol, A quantitative determination of one or more blood metabolites selected from the group consisting of uridine, inosine, galactonate, glycolate, palmitic acid, and histidine. And an apparatus for diagnosing a disease of the Behcet's disease.

본 발명자들은 베체트병의 바이오마커를 찾기 위해 환자들의 혈액으로부터 샘플을 채취하여 메탄올 추출하고 GC/TOF MS를 이용하여 베체트병 환자들과 정상인들의 대사체 프로파일 차이를 비교 분석하고, 이 차이를 이용하여 베체트병 환자들을 진단할 수 있는 바이오마커 발굴 연구를 수행하였다. The present inventors used a GC / TOF MS to compare the metabolite profiles of patients with Behcet's disease and normal subjects by collecting a sample from blood of patients to find a biomarker of BD, and using this difference We conducted biomarker research to diagnose patients with Behcet 's disease.

그 결과, 아민류, 아미노산류, 지방산류, 유기산류, 인산류, 당류 등으로 구분할 수 있는 104종의 대사체를 동정하였다. 이 중 아미노산류가 가장 많이 검출되었으며, 그 다음으로 유기산류, 지방산류, 당류, 아민류, 인산류 등의 순서로 검출되었다. As a result, 104 kinds of metabolites which can be classified into amines, amino acids, fatty acids, organic acids, phosphoric acids, sugars and the like were identified. Of these, amino acids were detected most frequently, followed by organic acids, fatty acids, sugars, amines, and phosphoric acids.

35명의 베체트병 환자와 35명의 건강한 대조군의 혈액을 비교하였을 때, 부분최소자승판별분석(PLS-DA)을 통해 베체트병 환자들과 건강한 대조군의 혈액 내 대사체 프로파일의 명확한 차이를 확인하였으며, 각각의 대사물질에 대해, VIP 값이 1.5, fold change 1.2, AUC 0.800 이상, p-values 0.01 미만을 기준으로 선정하고 13종의 대사체를 신규 바이오마커 후보 물질로 선정하였다. 각각의 대사물질은 베체트병과 건강한 대조군에서 통계적으로 확연한 차이를 보여, 적절한 후보 생체표지자임을 확인하였다. 또한 베체트병의 특이적 대사체 프로파일과 후보 생체표지자가 베체트병 치료를 위해 투여한 약물에 의한 영향이 아니라는 것을 확인하기 위해 베체트병에서 투여한 약물에 따라 그룹을 나누어 PLS-DA 분석을 시행하였다, 그 결과 베체트병에서 투여한 약물에 따른 대사체적 차이가 없음을 확인하였다. When comparing the blood of 35 patients with Behçet's disease and 35 healthy controls, the partial least squares discriminant analysis (PLS-DA) revealed a clear difference in the metabolite profiles in the blood between patients with Behçet's disease and healthy controls Were selected based on the VIP value of 1.5, fold change of 1.2, AUC of 0.800 or more, and p-values of less than 0.01, and 13 kinds of metabolites were selected as candidates for new biomarkers. Each metabolite showed a statistically significant difference in Behcet's disease and healthy controls, confirming it to be a suitable candidate biomarker. In addition, in order to confirm that the specific metabolite profile of BD and the effect of the candidate biomarker on the drug used for the BD treatment, the PLS-DA analysis was carried out by dividing the group according to the drug administered in BS. As a result, it was confirmed that there was no difference in metabolism according to drugs administered in the disease.

또한, 후보 생체표지자로 선정된 13개의 대사물질 중 베체트병 환자의 혈액에서 유의미하게 증가한 대사물질 3개(decanoic acid, fructose, tagatose)와, 베체트병 환자의 혈액에서 유의미하게 감소한 대사물질 2개(oleic acid, linoleic acid)를 선정하여, 5개의 대사물질로 구성된 베체트병을 감별하는 대사체적 생체표지자 panel을 생성하였다. 5개 대사체의 생체표지자 panel이 베체트병의 진단적 목적의 이용 가능성을 확인하기 위해 ROC curve를 이용하여 검증하였으며, sensitivity가 100%, specificity가 97.1%, AUC 값 0.993으로 베체트병을 진단하는데 매우 우수한 결과를 보였다. 또한 이 모델의 적정성을 확인하기 위해 다시 외부에서 받은 10개의 베체트병 환자와 10개의 건강한 대조군의 혈액을 이용하여 주성분 분석을 시행하였다. 그 결과 우리가 발견한 5개의 대사물질을 이용한 생체표지자 panel이 베체트병 진단에 적절함을 검증할 수 있었다.In addition, among the 13 metabolites selected as candidate biomarkers, three metabolites (decanoic acid, fructose, tagatose) significantly increased in the blood of patients with Behcet's disease and two metabolites significantly decreased in the blood of patients with Behcet's disease oleic acid, linoleic acid) were selected to produce a metabolic biomarker panel to discriminate between 5 metabolites of Behcet 's disease. A biomarker panel of 5 metabolites was tested by ROC curve to confirm the diagnostic utility of Behcet 's disease. The sensitivity, specificity and specificity of AUC were 100%, 97.1%, and 0.993, respectively. Showed excellent results. To confirm the adequacy of this model, we performed principal component analysis using blood from ten patients with Behcet 's disease and 10 healthy controls. As a result, we could confirm that the biomarker panel using the five metabolites we found is appropriate for the diagnosis of Behcet 's disease.

나아가, 본 발명자들에 의하여 새롭게 규명된 베체트병의 지표 대사체인 데칸산(decanoic acid), 프룩토오스(fructose), 타가토오스(tagatose), 올레산(oleic acid) 및 리놀레산(linoleic acid)으로 이루어진 군에서 선택된 하나 이상 외에도 L-시스테인(L-cysteine), 소르비톨(sorbitol), 우리딘(uridine), 이노신(inosine), 갈락토네이트(galactonate), 글라이콜레이트(glycolate), 팔미트산(palmitic acid) 및 히스티딘(histidine)로 이루어진 군에서 선택된 하나 이상에 대한 정량정보를 추가적으로 포함함으로써 보다 일관성 있고 신뢰도 높은 정확한 베체트병의 진단이 가능하다.Furthermore, it has been found that the surface metabolism of Behcet's disease newly discovered by the present inventors, consisting of decanoic acid, fructose, tagatose, oleic acid and linoleic acid, In addition to one or more selected from the group consisting of L-cysteine, sorbitol, uridine, inosine, galactonate, glycolate, palmitic acid, acid, and histidine, thereby making it possible to diagnose Behcet's disease more accurately and more reliably.

본 명세서에서 용어 "진단"은 특정 질병 또는 질환에 대한 한 객체의 감수성(susceptibility)을 판정하는 것, 한 객체가 특정 질병 또는 질환을 현재 가지고 있는 지 여부를 판정하는 것(예컨대, 베체트병 의 동정), 특정 질병 또는 질환에 걸린 한 객체의 예후(prognosis)를 판정하는 것, 또는 테라메트릭스(therametrics)(예컨대, 치료 효능에 대한 정보를 제공하기 위하여 객체의 상태를 모니터링 하는 것)을 포함한다.As used herein, the term "diagnosis" is intended to include determining the susceptibility of an object to a particular disease or disorder, determining whether an object currently has a particular disease or disorder (e.g., identifying a Behcet's disease Determining the prognosis of an object that has suffered a particular disease or disorder, or therametrics (e.g., monitoring the status of an object to provide information about the therapeutic efficacy).

본 발명의 진단 키트에 포함된 정량 장치는 크로마토그래피/질량분석기일 수 있다. The quantification device included in the diagnostic kit of the present invention may be a chromatography / mass spectrometer.

본 발명에서 이용되는 크로마토그래피는 가스 크로마토그래피(Gas Chromatography), 액체-고체 크로마토그래피(Liquid-Solid Chromatography, LSC), 종이 크로마토그래피(Paper Chromatography, PC), 박층 크로마토그래피(Thin-Layer Chromatography, TLC), 기체-고체 크로마토그래피(Gas-Solid Chromatography, GSC), 액체-액체 크로마토그래피(Liquid-Liquid Chromatography, LLC), 포말 크로마토그래피(Foam Chromatography, FC), 유화 크로마토그래피(Emulsion Chromatography, EC), 기체-액체 크로마토그래피(Gas-Liquid Chromatography, GLC), 이온 크로마토그래피(Ion Chromatography, IC), 겔 여과 크로마토그래피(Gel Filtration Chromatograhy, GFC) 또는 겔 투과 크로마토그래피(Gel Permeation Chromatography, GPC)를 포함하나, 이에 제한되지 않고 당업계에서 통상적으로 사용되는 모든 정량용 크로마토그래피를 사용할 수 있다. 바람직하게는, 본 발명에서 이용되는 크로마토그래피는 가스 크로마토그래피이다. 더불어 본 발명에서 이용되는 질량분석기는 MALDI-TOF MS 또는 TOF MS이고, 보다 바람직하게는 TOF MS이다.Chromatography used in the present invention can be carried out by gas chromatography, liquid-solid chromatography (LSC), paper chromatography (PC), thin-layer chromatography (TLC) (GSC), Liquid-Liquid Chromatography (LLC), Foam Chromatography (FC), Emulsion Chromatography (EC), and the like. But not limited to, gas-liquid chromatography (GLC), ion chromatography (IC), gel filtration chromatography (GFC), or Gel Permeation Chromatography , But it is not limited thereto and any quantitative chromatography commonly used in the art can be used. Preferably, the chromatography used in the present invention is gas chromatography. In addition, the mass analyzer used in the present invention is MALDI-TOF MS or TOF MS, more preferably TOF MS.

본 발명의 혈액 대사체는 가스 크로마토그래피에서 각 성분들이 분리되며, Q-TOF MS를 거쳐 얻어진 정보를 이용하여 정확한 분자량 정보뿐만 아니라 구조 정보(elemental composition)를 통해 구성 성분을 확인한다.In the blood metabolism of the present invention, each component is separated by gas chromatography, and the components are identified through the elemental composition as well as accurate molecular weight information using the information obtained through Q-TOF MS.

본 발명의 바람직한 구현예에 따르면, 데칸산(decanoic acid), 프룩토오스(fructose), 타가토오스(tagatose), L-시스테인(L-cysteine), 소르비톨(sorbitol), 우리딘(uridine), 이노신(inosine), 갈락토네이트(galactonate) 및 글라이콜레이트(glycolate)로 이루어진 군에서 선택된 하나 이상의 농도가 증가되는 경우, 베체트병을 나타내고 올레산(oleic acid), 리놀레산(linoleic acid), 팔미트산(palmitic acid) 및 히스티딘(histidine)으로 이루어진 군에서 선택된 하나 이상의 농도가 감소되는 경우, 베체트병을 나타낸다. According to a preferred embodiment of the present invention there is provided a pharmaceutical composition comprising decanoic acid, fructose, tagatose, L-cysteine, sorbitol, uridine, When the concentration of one or more selected from the group consisting of inosine, galactonate and glycolate is increased, it is considered to be a disease of Behcet's disease and may be oleic acid, linoleic acid, palmitic acid, palmitic acid, and histidine is reduced, it exhibits a disease of Behcet's disease.

본 명세서에서, 용어 "혈액 대사체 농도의 증가"는 건강한 정상인에 비해 베체트병 환자의 혈액 대사체 농도가 측정 가능할 정도로 유의하게 증가된 것을 의미하며, 바람직하게는 70% 이상 증가된 것을 의미하고, 보다 바람직하게는 30% 이상 증가된 것을 의미한다. In the present specification, the term " increase in blood metabolite concentration "means that the blood metabolite concentration of a patient with Behcet's disease is significantly increased as compared with a healthy normal person, preferably 70% More preferably by 30% or more.

본 명세서에서, 용어 "혈액 대사체 농도의 감소"는 건강한 정상인에 비해 베체트병 환자의 혈액 대사체 농도가 측정 가능할 정도로 유의하게 감소된 것을 의미하며, 바람직하게는 40% 이상 감소된 것을 의미하고, 보다 바람직하게는 20% 이상 감소된 것을 의미한다. As used herein, the term "reduction in blood metabolite concentration" means that the blood metabolite concentration in a patient with Behcet's disease is significantly reduced to a measurable level, preferably 40% or more, More preferably by 20% or more.

본 발명에 따르면, 데칸산(decanoic acid), 프룩토오스(fructose), 타가토오스(tagatose), L-시스테인(L-cysteine), 소르비톨(sorbitol), 우리딘(uridine), 이노신(inosine), 갈락토네이트(galactonate) 및 글라이콜레이트(glycolate)로 이루어진 군에서 선택된 하나 이상은 건강한 정상인에 비해 베체트병 환자에서 유의하게 증가된 농도를 나타내고, 올레산(oleic acid), 리놀레산(linoleic acid), 팔미트산(palmitic acid) 및 히스티딘(histidine)으로 이루어진 군에서 선택된 하나 이상은 건강한 정상인에 비해 베체트병 환자에서 유의하게 감소된 농도를 나타낸다(표 1).According to the present invention there is provided a pharmaceutical composition comprising at least one of decanoic acid, fructose, tagatose, L-cysteine, sorbitol, uridine, inosine, , Galactonate and glycolate have significantly increased concentrations in patients with Behcet's disease compared to healthy normal subjects, and the concentrations of oleic acid, linoleic acid, Palmitic acid and histidine are significantly reduced in patients with Behcet's disease compared to healthy controls (Table 1).

본 발명은 또한 정상 대조군과 베체트병에서 얻은 혈액 간의 대사체 차별성을 검출하는 방법으로,The present invention also provides a method for detecting metabolic differentiation between blood obtained from a normal control group and a Behcet's disease,

(1) GC/TOF MS(gas chromatography/time-of-flight mass spectrometry)를 이용한 대사체 분석 단계; (1) metabolism analysis step using GC / TOF MS (gas chromatography / time-of-flight mass spectrometry);

(2) GC/TOF MS에서 동정된 대사체에 대해 부분최소자승판별분석(PLS-DA)를 이용하여 대사체 프로파일의 차이를 확인하는 단계;(2) identifying differences in metabolite profiles using partial least squares discriminant analysis (PLS-DA) for the metabolites identified in GC / TOF MS;

(3) PLS-DA에서 도출된 대사체의 VIP(Variable Importance for Projection) 값이 1.5 이상인 값을 대사체 바이오마커 후보물질로 선정하고, PLS-DA의 로딩 값을 통해 대사체 바이오마커 후보물질의 증감 확인하는 단계;(3) The value of Variable Importance for Projection (VIP) of the metabolite derived from PLS-DA was selected as the metabolite biomarker candidate, and the value of PLS-DA loading value was used as the metabolite biomarker candidate Ascertaining and decreasing;

(4) ROC 곡선(Receiver Operating Characteristic curve)을 이용하여 대사체 바이오마커를 검증하는 단계(4) Verifying the metabolite biomarker using the ROC curve (Receiver Operating Characteristic curve)

를 순차적으로 적용하여, 혈액으로부터 대사체 바이오마커를 분석하는 것을 포함하는 정상 대조군과 베체트병에서 얻은 혈액 간의 대사체 차별성 분석 방법에 관한 것이다.To a method for analyzing metabolism differentiation between blood obtained from a normal control group and a Behcet's disease, which comprises analyzing a metabolomic biomarker from blood.

본 발명의 두 생체시료군 간의 대사체 차별성 분석 방법은 베체트병과 정상군에서 얻은 혈액 시료군 간의 대사체 차별성을 분석하는 방법을 예로 들어 구체적으로 설명한다.The metabolic differentiation analysis method between the two biological sample groups of the present invention will be described in detail as an example of a method of analyzing the metabolism differentiation between the diseased blood group and the diseased blood group obtained from Behcet's disease.

우선, 정산인과 베체트병 환자에서 채취한 혈액 샘플을 100% 메탄올로 추출한 후 GC/TOF MS 분석에 사용할 수 있도록 공지 기술을 이용하여 유도체화 과정을 거친다. First, blood samples taken from patients with measles and Behcet's disease are extracted with 100% methanol and subjected to derivatization using known techniques so that they can be used for GC / TOF MS analysis.

상기 GC/TOF MS를 이용한 혈액의 대사체 분석 방법은 혈액 추출물을 GC/TOF MS 기기로 분석하고, 분석 결과를 통계처리 가능한 수치로 변환한 다음, 변환된 수치를 이용하여 통계학적으로 두 생체시료군의 차별성을 검증하는 것을 포함한다.The method of analyzing blood metabolism using the GC / TOF MS was performed by analyzing the blood extract with a GC / TOF MS instrument, converting the analysis result into a statistically processable value, and then using the converted values, And verifying the differentiation of the group.

GC/TOF MS 분석 결과를 통계처리 가능한 수치로 변환하는 것은 총 분석시간을 단위시간 간격으로 나누어 단위시간 동안 나타난 크로마토그램 피크의 면적 또는 높이 중 가장 큰 수치를 단위시간 동안의 대표값으로 정하는 것일 수 있다.Converting the GC / TOF MS analysis results to a statistically processable value can be done by dividing the total analysis time by the unit time interval and setting the largest value of the area or height of the chromatogram peak during the unit time as the representative value for the unit time have.

본 발명의 일 구현예에 따르면, GC/TOF MS 분석 결과 아민류, 아미노산류, 지방산류, 유기산류, 인산류, 당류 등으로 구분할 수 있는 104종의 대사체를 동정하였고, 이 중 아미노산류가 가장 많이 검출 되었으며, 그 다음으로 유기산류, 지방산류, 당류, 아민류, 인산류 등의 순서로 검출되었다.According to one embodiment of the present invention, 104 kinds of metabolites classified into amines, amino acids, fatty acids, organic acids, phosphoric acids, and saccharides were identified by GC / TOF MS analysis, Followed by organic acids, fatty acids, sugars, amines, phosphoric acids, and so on.

상기 GC/TOF MS 분석 결과 나온 대사체의 강도를 총 동정된 대사체의 강도 합으로 나누어 각 대사체를 표준화하고, PLS-DA 분석을 실시한다. Each metabolite is standardized and the PLS-DA analysis is performed by dividing the intensity of the metabolite from the GC / TOF MS analysis by the sum of the intensities of the metabolites.

대사체의 PLS-DA 로딩 값과 VIP 값으로 구성된 V-plot를 작성하고, VIP 값이 1.5 이상인 값을 대사체 바이오마커 후보물질로 선정하고, PLS-DA의 로딩 값의 증감을 확인하며, 이때 로딩 값이 양수인 것은 대사체의 증가 경향을, 로딩 값이 음수인 것은 대사체의 감소 경향을 나타내는 것이다.A V-plot consisting of a PLS-DA loading value and a VIP value of a metabolite was prepared, and a value with a VIP value of 1.5 or more was selected as a candidate for biomarker for metabolism, and the increase or decrease of the loading value of PLS-DA was confirmed. When the loading value is positive, the increasing tendency of the metabolism and when the loading value is negative is the decreasing tendency of metabolism.

GC/TOF MS에서 분석된 혈액의 대사체의 강도를 이용하여 대사체의 증감을 확인할 수 있다.The increase / decrease of the metabolism can be confirmed by using the intensity of the metabolism of blood analyzed by GC / TOF MS.

ROC 곡선을 통해 상기 대사체 바이오마커를 검증한다.The metabolite biomarker is verified through the ROC curve.

본 발명의 일 구현예에 따르면, 베체트병을 진단하기 위한 바이오마커로, 데칸산(decanoic acid), 프룩토오스(fructose), 타가토오스(tagatose), 올레산(oleic acid), 리놀레산(linoleic acid), L-시스테인(L-cysteine), 소르비톨(sorbitol), 우리딘(uridine), 이노신(inosine), 갈락토네이트(galactonate), 글라이콜레이트(glycolate), 팔미트산(palmitic acid) 및 히스티딘(histidine)으로 이루어진 군에서 선택된 하나 이상을 사용할 수 있다. According to one embodiment of the present invention, biomarkers for diagnosing Behcet's disease include decanoic acid, fructose, tagatose, oleic acid, linoleic acid, ), L-cysteine, sorbitol, uridine, inosine, galactonate, glycolate, palmitic acid, and histidine (histidine) may be used.

본 발명의 정상군과 베체트병에서 얻은 혈액 시료군 간의 대사체 차별성 분석 방법을 통해 보다 일관성 있고 신뢰도 높은 정확한 베체트병을 진단할 수 있고, 이를 치료제 개발에 적용할 수 있다. The metabolism differentiation analysis method between the normal group of the present invention and the blood sample group obtained from the disease of Betezchez disease can diagnose a more accurate and reliable Betezche disease, and it can be applied to the development of a therapeutic agent.

이하, 본 발명에 따르는 실시예를 통하여 본 발명을 보다 상세히 설명하나, 본 발명의 범위가 하기 제시된 실시예에 의해 제한되는 것은 아니다. Hereinafter, the present invention will be described in more detail with reference to the following examples. However, the scope of the present invention is not limited by the following examples.

[실시예][Example]

실시예Example 1:  One: GCGC // TOFTOF MS를 이용한  Using MS 대사체Metabolism 동정  Sympathy

베체트병 환자 및 건강한 대조군의 혈액 20 ㎕에서 순수 메탄올 980 ㎕을 섞고 원심분리하여 대사체를 추출하였다. The metabolite was extracted by mixing 980 μl of pure methanol with 20 μl of blood from patients with Behcet's disease and a healthy control and centrifuging.

GC/TOF MS 분석을 위한 유도체화 과정은 다음과 같다. The derivatization process for GC / TOF MS analysis is as follows.

추출한 샘플을 스피드 백으로 건조시킨 후에 5 ㎕의 40%(w/v) 농도의 O-methylhydroxylamine hydrochloride in pyridine을 넣고 30도 200 rpm에서 90분간 반응을 시켰다. 그리고 45 ㎕의 N-methyl-N-(trimethylsilyl)trifluoroacetamide를 넣고 37도 200 rpm에서 30분간 반응을 실시하였다. After the extracted sample was dried with a speed bag, 5 μl of 40% (w / v) O-methylhydroxylamine hydrochloride in pyridine was added and reacted at 30 ° C. and 200 rpm for 90 minutes. Then, 45 μl of N-methyl-N- (trimethylsilyl) trifluoroacetamide was added, and reaction was carried out at 37 ° C and 200 rpm for 30 minutes.

GC/TOF MS 분석을 위한 기기 조건은 다음과 같다. The equipment conditions for GC / TOF MS analysis are as follows.

분석할 때 사용한 컬럼은 RTX-5Sil MS capillary column (30 m length, 0.25 mm film thickness, and 25 mm inner diameter)이며, GC 컬럼 온도 조건은 먼저 50도에서 5분간 유지시킨 후 330도까지 승온시킨 다음 1분간 유지하였다. 1 ㎕의 샘플을 비분할법(splitless)으로 주입(injection)하였다. Transfer line 온도와 Ion source 온도는 각각 280도, 250도로 유지시켰다. GC/TOF MS 결과를 보유하고 있는 라이브러리에서 찾아 동정하여, 104개의 대사체를 동정하였다(표 1).The column used was RTX-5Sil MS capillary column (30 m length, 0.25 mm film thickness, and 25 mm inner diameter). The GC column temperature was maintained at 50 ° C for 5 minutes, then increased to 330 ° C And maintained for 1 minute. 1 [mu] l of the sample was injected in a splitless manner. Transfer line temperature and Ion source temperature were maintained at 280 and 250 degrees, respectively. The GC / TOF MS results were identified and identified in a library holding 104 metabolites (Table 1).

표 1에서와 같이, 각각의 대사체군별로 분류하였을 때. 아미노산 26%, 유기산 19%, 지방산 17%, 당 15%, 아민 11%, 인 5%, 기타 7%로 나타났다.As shown in Table 1, when classified by each metabolic group, Amino acid 26%, organic acid 19%, fatty acid 17%, sugar 15%, amine 11%, phosphorus 5% and other 7%.

Figure 112017040238379-pat00001
Figure 112017040238379-pat00001

Figure 112017040238379-pat00002
Figure 112017040238379-pat00002

실시예Example 2:  2: PLSPLS -DA를 이용한 베체트병 환자와 건강한 대조군의 혈액 내 -DA in patients with Behcet's disease and healthy controls 대사체Metabolism 프로파일 차이 Profile difference

실시예 1로부터 나온 대사체의 강도(intensity)를 총 동정된 대사체의 강도 합으로 나누어 각 대사체를 표준화하였다. 그 후 SIMCA-P+ (ver. 12.0)를 이용하여 PLS-DA 분석을 실시하였다.Each metabolite was standardized by dividing the intensity of the metabolite from Example 1 by the sum of the intensities of the metabolites. PLS-DA analysis was then performed using SIMCA-P + (ver. 12.0).

도 1에 나타낸 바와 같이, 베체트병 환자와 건강한 대조군의 혈액 내 대사체 프로파일링이 명확하게 차이가 나는 것을 확인하였다. As shown in Fig. 1, it was confirmed that profiling of metabolites in the blood of patients with Behcet's disease and healthy control clearly differed.

실시예Example 3: 베체트병 환자에 특이적인 생체표지자 대사물질들의 선별 3: Selection of biomarker metabolites specific for patients with Behcet's disease

베체트병 환자에서 특이적으로 증감한 생체표지자를 찾기 위해서, 각각의 대사물질로부터 실시예 2로부터 도출된 대사체 프로파일링의 차이에 영향을 미치는 VIP 값과 fold channge, AUC, p-value를 구하였다. VIP 값이 1.5 이상, fold change 1.2, AUC 0.800 이상, p-value 0.01 미만의 기준을 각각의 대사물질에 대해 구하였고, 13개의 대사물질이 베체트병 진단에 적절함을 보였다(표 2). 또한 이 대사물질들의 절대적 intensity를 그룹별로 비교하였다 (도 2).The VIP value, fold channel, AUC, and p-value, which affect the difference in metabolism profiling derived from Example 2, were determined from each metabolite in order to find specifically biotransformed biomarkers in patients with Behcet's disease . A VIP value of 1.5 or more, a fold change of 1.2, a AUC of 0.800 or more, and a p-value of less than 0.01 were obtained for each metabolite, and 13 metabolites were appropriate for the diagnosis of Behcet's disease (Table 2). The absolute intensities of these metabolites were also compared in groups (Figure 2).

Figure 112017040238379-pat00003
Figure 112017040238379-pat00003

실시예Example 4:  4: PLSPLS -DA를 이용한 베체트병 환자에서 증감한 대사물질에 약물 효과 존재 유무 검증-D, the presence or absence of drug effects on metabolites in patients with Behcet's disease

베체트병 환자에서 특이적으로 증감한 생체표지자가 약물에 의해 증감한 물질이 아님을 보이기 위해서, 각각의 약물투여 그룹 vs. 약물비투여 그룹을 PLS-DA를 이용해 비교한 결과, 분리 수준이 적절하지 않고 재현성이 없는 것으로 나타났다. 3개의 투여된 약물 그룹 steroid, colchicine, azathioprine에서 각각 재현성이 없는 결과를 보였으며, 약물에 따른 차이가 통계적으로 유의미하지 않았다. In order to show that the biomarker specifically increased or decreased in patients with Behcet's disease was not a substance changed by the drug, Comparisons of non-drug-treated groups with PLS-DA showed that the level of separation was not adequate and not reproducible. There was no reproducibility in the three drug groups steroid, colchicine, and azathioprine, respectively, and differences between the drugs were not statistically significant.

따라서, 실시예 3에서 보인 베체트병에서 증감한 대사물질이 질병 자체에 의한 변화이므로 생체표지자로 적절함을 확인하였다(도 3).Therefore, it was confirmed that the metabolite changed in Behcet's disease shown in Example 3 is a change due to the disease itself and thus is suitable as a biomarker (FIG. 3).

실시예Example 5: 혈액 검체를 통한 베체트병의 진단을 위해 5개의 대사물질을 이용한  5: Five metabolites were used for the diagnosis of Behcet's disease through blood specimens 대사체적Metabolite volume 진단 panel의 생성 Create Diagnostic Panel

실시예 3으로부터 선정된 베체트병 진단을 위한 생체표지자 13개 중 베체트병에서 특이적으로 증가한 물질 상위 3개(decanoic acid, fructose, tagatose), 베체트병에서 특이적으로 감소한 물질 상위 2개(oleic acid, linoleic acid)를 선정하여 베체트병을 진단할 수 있는 대사체적 진단 panel을 주성분 분석을 이용하여 생성시켰다. PC1의 하나의 축을 이용했을 때, R2X 값이 0.721, Q2 값이 0.515로 베체트병 환자와 건강한 대조군을 적절하고 재현성 있게 구분하였다(도 4).Among the 13 biomarkers for diagnosis of Behcet's disease selected from Example 3, the top three substances specifically increased in Behcet's disease (decanoic acid, fructose, tagatose) and the two substances specifically reduced in Behcet's disease (oleic acid , linoleic acid) were used to generate a metabolic panel for the diagnosis of Behcet 's disease using principal component analysis. When one axis of PC1 was used, the value of R2X was 0.721 and the value of Q2 was 0.515, so that patients with Behçet's disease and healthy controls were appropriately and reproducibly distinguished (FIG. 4).

실시예Example 6: 혈액 검체를 이용한 베체트병의 진단을 위한  6: Diagnosis of Behcet's disease using blood specimens 대사체적Metabolite volume 진단 panel의 ROC 및 외부 검체 검증을 통한 모델 검증 Model verification through ROC and external sample verification of diagnostic panel

실시예 5를 통해 생성된 혈액 검체를 통한 베체트병 진단용 대사체적 생체표지자 panel이 진단에 적절한지 살펴보기 위하여 모델 내 각 검체의 PC1 score를 이용해서 ROC(receiver operating characteristic) 곡선을 그렸다. 그 결과 sensitivity가 100%, specificity가 97.1%, AUC값이 0.993으로 모델이 베체트병 진단에 매우 적합함을 보였다(도 5). 또한 이 panel이 외부 검체를 이용하여 베체트 질환의 진단을 예측할 수 있는지 살펴보기 위하여, 베체트병 환자 및 건강한 대조군의 혈액 검체를 각 10개씩, 총 20개의 검체를 이용하였다. 그 결과 총 검체 중 19개의 검체를 정확하게 베체트병 환자 혹은 건강한 대조군으로 예측할 수 있음을 나타내어, 5개의 대사체 생체표지자 panel이 외부 검체의 베체트병 진단에도 적절함을 나타내었다(도 6). The receiver operating characteristic (ROC) curve was drawn using the PC1 score of each sample in the model to see if the metabolic biomarker panel for the diagnosis of Behcet's disease via the blood sample generated in Example 5 was appropriate for diagnosis. As a result, the sensitivity was 100%, the specificity was 97.1%, and the AUC value was 0.993, indicating that the model is well suited for diagnosis of Behcet's disease (Fig. 5). In order to examine whether this panel can predict the diagnosis of Behcet 's disease using external samples, 20 specimens were used, each of 10 blood samples from Behcet' s disease patients and healthy controls. As a result, 19 specimens of the total specimens could be accurately predicted as Behcet's disease patients or healthy controls, indicating that five metabolite biomarker panels are suitable for the diagnosis of Behcet's disease of external specimens (FIG. 6).

Claims (10)

데칸산(decanoic acid), 프룩토오스(fructose), 타가토오스(tagatose), 올레산(oleic acid), 리놀레산(linoleic acid), L-시스테인(L-cysteine), 소르비톨(sorbitol), 우리딘(uridine), 이노신(inosine), 갈락토네이트(galactonate), 글라이콜레이트(glycolate), 팔미트산(palmitic acid) 및 히스티딘(histidine)으로 이루어진 군에서 선택된 하나 이상의 혈액 대사체에 대한 정량 장치를 포함하되,
데칸산(decanoic acid), 프룩토오스(fructose), 타가토오스(tagatose), L-시스테인(L-cysteine), 소르비톨(sorbitol), 우리딘(uridine), 이노신(inosine), 갈락토네이트(galactonate) 및 글라이콜레이트(glycolate)로 이루어진 군에서 선택된 하나 이상의 농도가 증가하는 경우; 또는 올레산(oleic acid), 리놀레산(linoleic acid), 팔미트산(palmitic acid) 및 히스티딘(histidine)으로 이루어진 군에서 선택된 하나 이상의 농도가 감소하는 경우; 베체트병을 나타내는 것인, 베체트병 진단 키트.
L-cysteine, sorbitol, uridine (linoleic acid), linoleic acid, L-cysteine, and a quantitative device for one or more blood metabolites selected from the group consisting of uridine, inosine, galactonate, glycolate, palmitic acid, and histidine. However,
(S), decanoic acid, fructose, tagatose, L-cysteine, sorbitol, uridine, inosine, galactonate wherein the concentration of at least one selected from the group consisting of galactonate and glycolate is increased; Or when the concentration of at least one selected from the group consisting of oleic acid, linoleic acid, palmitic acid, and histidine is decreased; RTI ID = 0.0 > of Behcet's disease. ≪ / RTI >
제 1 항에 있어서,
상기 혈액 대사체 중 데칸산(decanoic acid), 프룩토오스(fructose), 타가토오스(tagatose), 올레산(oleic acid) 및 리놀레산(linoleic acid)으로 구성되는 군으로부터 선택된 하나 이상을 포함하는 베체트병 진단 키트.
The method according to claim 1,
Wherein the blood metabolism is at least one selected from the group consisting of decanoic acid, fructose, tagatose, oleic acid and linoleic acid, Diagnostic Kit.
제 1 항에 있어서,
정량 장치는 크로마토그래피/질량분석기인 베체트병 진단 키트.
The method according to claim 1,
The quantification device is a chromatographic / mass spectrometer, the Behcet's disease diagnostic kit.
삭제delete 삭제delete 삭제delete 삭제delete 삭제delete 삭제delete 삭제delete
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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
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Family Cites Families (10)

* Cited by examiner, † Cited by third party
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KR100448488B1 (en) 2001-09-03 2004-09-13 (주)프로테옴텍 A Diagnostic System Employing Apolipoprotein A-1 as a Marker of Behcet's Disease
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JP2016070798A (en) 2014-09-30 2016-05-09 学校法人 埼玉医科大学 Method for assisting determination of behcet's disease and method for assisting evaluation of activity of behcet's disease
KR101568632B1 (en) * 2015-03-02 2015-11-11 연세대학교 산학협력단 A kit for diagnosing Behcet’s disease comprising antibodies against HSC71 protein
KR101806136B1 (en) * 2015-05-28 2017-12-08 고려대학교 산학협력단 Method for diagnosing Behcet's disease with arthritis by using metabolomics
KR101724130B1 (en) * 2015-06-16 2017-04-10 연세대학교 산학협력단 Biomarkers for Diagnosing Intestinal Behcet's Disease and Uses Thereof
WO2017040464A1 (en) 2015-08-31 2017-03-09 Merck Patent Gmbh Methods for the modulation of lgals3bp to treat systemic lupus erythematosus

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR101516086B1 (en) 2013-10-25 2015-05-07 고려대학교 산학협력단 Method for diagnosing rheumatoid arthritis by using metabolomics

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
J.K Ahn et al., PLOS ONE, 2015, pp. 1-13.*

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