趙娟,滕麗新,毛梅
冠狀動脈疾病的代謝組學(xué)特點及其診斷價值
趙娟1,滕麗新2,毛梅1
目的分析代謝產(chǎn)物變化對不同類型冠狀動脈疾?。–AD)的診斷價值。方法選自重慶市急救中心、重慶市腫瘤醫(yī)院、解放軍第三二四醫(yī)院及重慶市第三人民醫(yī)院等4所醫(yī)院老年病科于2003年1月~2016年1月住院患者1086例,男性712例,女性374例。依據(jù)癥狀和檢查結(jié)果分為:對照組(NCA組,116例,無冠狀動脈狹窄)、非阻塞性冠狀動脈粥樣硬化組(NOCA組,276例,冠狀動脈狹窄<50%)、急性心肌梗死組(AMI組,324例)、不穩(wěn)定型心絞痛組(UA組,307例)和穩(wěn)定型心絞痛組(SA組,63例)。液相色譜-質(zhì)譜聯(lián)用(LC-MS)檢測不同血樣中代謝產(chǎn)物的質(zhì)譜峰,從而確定其中所有的代謝產(chǎn)物。結(jié)果針對CAD代謝紊亂做了12個交叉比較,對89種不同的代謝產(chǎn)物進行鑒定。代謝途徑的改變包括磷脂代謝增加,氨基酸代謝降低,短鏈?;鈮A增多,三羧酸循環(huán)減少,原發(fā)性膽汁酸合成減少。受試者工作特征曲線(ROC)評估各組對比有差異的代謝產(chǎn)物診斷價值,有差異的代謝產(chǎn)物診斷NOCA與NCA(n=392)的曲線下面積(AUC)、敏感性和特異性分別為0.952、94.2%和80.7%;SA與NOCA(n=339)分別為0.993、96.4%和95.6%;UA與SA(n=370)分別為0.990、97.4%和91.1%;AMI與UA(n=631)分別為0.992、94.5%和95.3%。結(jié)論不同類型冠狀動脈疾病患者發(fā)生代謝紊亂,小分子代謝產(chǎn)物的變化對冠狀動脈疾病的鑒別診斷具有潛在價值。
冠狀動脈疾?。淮x組學(xué);代謝產(chǎn)物;診斷
冠狀動脈疾?。–AD)是世界范圍內(nèi)構(gòu)成死亡的主要原因,根據(jù)2013年全球疾病負擔研究,每年有814萬人因冠心病死亡(16.8%)[1]。根據(jù)臨床癥狀、動脈阻塞程度和心肌損傷,CAD分為不同的類別:非梗阻性冠狀動脈粥樣硬化(NOCA),穩(wěn)定型心絞痛(SA)、不穩(wěn)定型心絞痛(UA)、急性心肌梗死(AMI)[2]。UA和AMI也被稱為急性冠脈綜合征(ACS)。
動脈粥樣硬化是心絞痛和急性心肌梗死的常見原因,是一個緩慢而復(fù)雜的過程[3]。CAD的早期篩查和鑒別診斷,可使患者盡早獲得干預(yù)。目前臨床區(qū)分CAD主要基于臨床癥狀、心電圖(ECG)、心肌損傷標志物和冠狀動脈造影[4-7]。其中,冠狀動脈造影是診斷的“金標準”[8],但其存在專業(yè)技術(shù)和高成本的限制[9-12]。代謝組學(xué)是系統(tǒng)生物學(xué)中一個快速發(fā)展的領(lǐng)域,代謝改變在疾病的進展中具有重要意義[12]。心臟代謝改變也會導(dǎo)致體液代謝組學(xué)變化[13],多種小分子代謝產(chǎn)物的組合為疾病診斷提供參考[14,15]。本研究探討了冠狀動脈疾病中代謝的改變和意義。
1.1 研究對象選自重慶市急救中心、重慶市腫瘤醫(yī)院、解放軍第三二四醫(yī)院及重慶市第三人民醫(yī)院等4所醫(yī)院老年病科于2003年1月~2016年1月住院患者1086例,其中男性712例,女性374例。冠狀動脈疾病患者納入標準:胸痛癥狀;合并心血管危險因素;心電圖缺血性改變(ST段抬高或壓低、T波低平或倒置、出現(xiàn)U波等),或心肌酶升高(乳酸脫氫酶及其同工酶:>380 U/L、肌酸激酶及其同工酶>12 U/L);冠狀動脈造影檢查明確診斷。排除主動脈夾層、肺栓塞、惡性腫瘤、自身免疫性疾病、嚴重傳染病、外傷、近期手術(shù)史、重度心力衰竭伴左室射血分數(shù)<20%、肝功能異常(谷丙轉(zhuǎn)氨酶>135 U/L)、腎功能不全(肌酐>3 mg/dl);心肌炎、心包炎、Takotsubo心肌病。所有患者均知情同意。本研究經(jīng)我院倫理學(xué)委員會通過。
1.2 代謝組學(xué)檢測行冠狀動脈造影術(shù)前采集血漿標本,立刻放置于-80℃保存,以便進行代謝組學(xué)分析。與甲醇、乙醇、甲醇/乙醇(1:1),和甲醇/乙腈/丙酮(1:1:1)比較,選用乙腈為最佳提取溶劑。為確保代謝分析的數(shù)據(jù)質(zhì)量,納入正常冠狀動脈患者(82例)和冠心病患者(125例),通過混合等量的血漿(10 ml),制備質(zhì)量控制樣品。液相色譜-質(zhì)譜聯(lián)用(LC-MS)檢測不同血樣中代謝產(chǎn)物的質(zhì)譜峰,從而確定其中所有的代謝產(chǎn)物。
1.3 研究分組依據(jù)癥狀和檢查結(jié)果分為:對照組(NCA 組,116例,無冠狀動脈狹窄)、非阻塞性冠狀動脈粥樣硬化組(NOCA組,276例,冠狀動脈狹窄<50%)、急性心肌梗死組(AMI組,324例)、不穩(wěn)定型心絞痛組(UA組,307例)和穩(wěn)定型心絞痛組(SA組,63例)。
1.4 統(tǒng)計分析所有數(shù)據(jù)均采用SPSS 19.0統(tǒng)計學(xué)軟件分析。計量資料采用均數(shù)±標準差(±s)表示,兩組比較采用t檢驗,多組間均數(shù)的比較采用方差分析,計數(shù)資料采用例數(shù)(構(gòu)成比)表示,組間比較采用χ2檢驗。潛在的結(jié)構(gòu)判別分析(OPLS-DA)采用SIMCA 14.0.1的正交投影模型。每個代謝產(chǎn)物的交叉比較P值均采用Bonferroni校正。聚類分析使用MeV 4.6.0進行。用Cytoscape 3.2.0繪制相關(guān)網(wǎng)絡(luò)。受試者工作特征曲線(ROC)分析代謝產(chǎn)物差異的診斷價值。P<0.05為差異有統(tǒng)計學(xué)意義。
2.1 一般情況比較四組在年齡、左室射血分數(shù)、收縮壓、用藥情況、血脂和血糖等方面比較,差異有統(tǒng)計學(xué)意義(P均<0.01),表1。
2.2 與冠心病患者的比較及交叉比較在峰值校對和去除缺失值后,共檢測到2032個正模式特征,共有1130種離子發(fā)生了顯著變化。使用OPLS-DA模型描述代謝紊亂。VIP值>1的離子被認為是潛在差異代謝產(chǎn)物。比較不同組代謝產(chǎn)物和代謝途徑差異,在斑塊形成期(NOCA組 vs. NCA組),斑塊發(fā)展期(SA組 vs. NOCA組),斑塊穩(wěn)定到不穩(wěn)定期(UA組 vs. SA組),斑塊脫落期(AMI組vs. UA組)。結(jié)果如下:NOCA相對正常動脈,累計R2Y=0.655,Q2=0.503(圖1A);SA相對NOCA,R2Y=0.626,Q2=0.518(圖1B);UA相對SA,R2Y=0.645,Q2=0.548(圖1C);AMI和UA,R2Y=0.641,Q2=0.595(圖1D)。圖1E~1H表示代謝途徑變化。NOCA相對NCA,甘油、嘌呤和鞘脂代謝改變;SA相對NOCA,甘油、纈氨酸、亮氨酸、異亮氨酸、原發(fā)性膽汁酸、精氨酸和脯氨酸的生物合成改變;UA相對SA,甘油、天冬氨酸、谷氨酸、精氨酸、丙氨酸、脯氨酸的合成改變;AMI相對UA,甘油磷脂、鞘磷脂、精氨酸和脯氨酸的代謝均發(fā)生改變。甘油磷脂代謝在代謝中占有重要地位。
2.3 CAD血漿中代謝產(chǎn)物的網(wǎng)絡(luò)分析除上述4組外,還進行了8個交叉比較的OPLS-DA圖,包括SA與NCA,UA與NCA,AMI與NCA,UA與NOCA;AMI與NOCA,AMI與SA,嚴重CAD(SA/UA/AMI)與相對不嚴重CAD(NCA/NOCA)以及ACS(UA/AMI)與SA。通過這12個不同的CAD組的綜合交叉比較,確定了89種不同的代謝產(chǎn)物,其中44個被證實可作為參考。圖2A是正常動脈和CAD組中89種不同代謝產(chǎn)物的平均歸一化量的熱圖,以正常動脈組為基準,共27種代謝產(chǎn)物升高,62種降低。CAD組在三羧酸循環(huán)和磷脂代謝產(chǎn)物下調(diào)有高度相關(guān)系數(shù),相關(guān)氨基酸水平上調(diào),短鏈?;鈮A在網(wǎng)絡(luò)中心,是橋梁的改變代謝物,膽汁酸代謝產(chǎn)物減少(圖2B)。
2.4 代謝生物標志物的鑒別診斷鑒別診斷的生物標志物VIP>1.5,具有參考價值。NOCA相對NCA有10種特定的代謝生物標志物被識別,SA相對NOCA有8種,UA相對SA有10種,AMI相對UA有9種(表2)。制作ROC曲線,NOCA與NCA(n=392)曲線下面積(AUC)、敏感性和特異性分別為0.952、94.2%和80.7%(圖3A);SA與NOCA組(n=339)分別為0.993、96.4%和95.6%(圖3B);UA與SA組(n=370)分別為0.990、97.4%和91.1%(圖3C);AMI與UA組(n=631)分別為0.992、94.5%和95.3%(圖3D)。在觀察階段,ROC最高預(yù)測的敏感性和特異性,最佳界值分別為NOCA對NCA為0.635,SA對NOCA為0.205,UA對SA為0.692,AMI對UA為0.475。臨界值用來預(yù)測CAD在測試階段和外部采集的不同階段。NOCA對NCA預(yù)測值在采集階段是95%,觀察階段是91.5%(圖3E);SA對NOCA是94.5%和89.7%(圖3F);UA對SA是91.8%和96.4%(圖3G);AMI對UA組是96%和85.3%(圖3H)。
表1 入組患者的基線資料比較
圖1 OPLS-DA評分圖和干擾代謝途徑
圖2 CAD類型和代謝相關(guān)網(wǎng)絡(luò)中的產(chǎn)物差異
圖3 診斷結(jié)果和預(yù)測準確度
2.5 各類型CAD的代謝特征和鑒別診斷對懷疑CAD患者進行冠狀動脈造影,通過液相色譜-質(zhì)譜法(LC-MS)測定代謝產(chǎn)物變化,將顯著改變的代謝物用于鑒別診斷。潛在結(jié)構(gòu)判別分析(OPLS-DA)評分圖的正交投影顯示了顯著與非顯著CAD之間的明顯差異。受試者工作特征曲線(ROC)分析提供曲線下面積(AUC)為0.938,靈敏度為83.3%,特異度為發(fā)現(xiàn)階段的91.6%,在試驗階段提供了93.0%的預(yù)測值,100%的以3為中心的外部驗證集。
本研究分析了冠心病進展各個階段患者代謝組學(xué)的變化,血漿樣品中89種代謝產(chǎn)物發(fā)生變化。在CAD的進展中存在磷脂代謝和三羧酸循環(huán)下降,氨基酸代謝和短鏈酰基肉堿增高與原發(fā)性膽汁酸合成下降。CAD患者卵磷脂膽固醇?;D(zhuǎn)移酶活性降低[16,17]。鞘脂水平升高是肥胖和心血管疾病的風險特征[18]。
動脈粥樣硬化斑塊的生長導(dǎo)致冠狀動脈狹窄。與NOCA組相比,SA組磷酸膽堿、磷脂酰乙醇胺、磷脂酰膽堿、溶血磷脂酰膽堿降低,植物鞘氨醇和磷脂酰肌醇升高。磷脂酰膽堿的減少對冠心病有一定的影響[19]。它和CAD之間的負相關(guān)關(guān)系已被報道[20]。SA組患者磷脂酰肌醇增加。磷脂酰肌醇的增加會導(dǎo)致患者嚴重的血管鈣化[21]。與SA相比,UA患者肌酸、2-羥基月桂酸、色氨酸和乙酰肉毒堿、天冬氨酸、卵磷脂、膽堿磷酸和膽堿水平下降。肌酸激酶系統(tǒng)可保護心血管系統(tǒng)免受缺血和收縮力增加帶來的影響[22]。2-羥基月桂酸與斑塊破裂、脂肪酸代謝紊亂相關(guān)[23]。色氨酸與免疫系統(tǒng)激活和炎癥密切相關(guān)[24]。短鏈?;鈮A水平升高提示激活脂肪酸代謝尿酸[25]。UA天冬氨酸降低提示心肌損害的高風險[26]。
表2 各組患者的代謝生物標志物的統(tǒng)計分析
圖4 各類型CAD的代謝特征和鑒別診斷
與UA相比,AMI患者鞘氨醇、二十碳酸和色氨酸水平增加,磷酸膽酸、溶血卵磷脂、膽堿水平降低[27]。鞘氨醇是鞘氨醇堿的合成中間體[28],表明AMI患者神經(jīng)鞘脂類代謝受阻。二十碳三烯酸存在反映了AMI患者存在炎癥[29]。甘氨膽酸是合成膽汁酸和膽固醇的關(guān)鍵[30],AMI患者降低是因為膽固醇與磷脂代謝有明顯的抑制[31]。激活的氨基酸生物合成是急性心肌梗死的重要指標[32]。
在未來的研究中,建議使用雙分析平臺,如氣相色譜-質(zhì)譜聯(lián)用液相色譜-質(zhì)譜法,并進一步擴大人群。
[1] Naghavi M,Wang H,Lozano R,et al. Global, regional, and national agesex specific all-cause and cause-specific mortality for 240 causes of death, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013[J]. Lancet,2015,385:117-71.
[2] Epstein SE,Zhou YF,Zhu J,et al. Infection and atherosclerosis emerging mechanistic paradigms[J]. Circulation,1999,100(4):e20-8.
[3] De Backer GG. The global burden of coronary heart disease[J]. Medicogr aphia,2009,31:343-8.
[4] Libby P,Ridker PM,Hansson GK,et al. Progress and challenges in translating the biology of atherosclerosis[J]. Nature,2011,473:317-25.
[5] Bassand JP,Hamm CW,Ardissino D,et al. Guidelines for the diagnosis and treatment of nonST-segment elevation acute coronary syndromes[J].Eur Heart J,2007,2(8):1598-660.
[6] Lindahl B,Toss H,Siegbahn A,et al. Markers of myocardial damage and inflammation in relation to long-term mortality in unstable coronary artery disease[J]. N Engl J Med,2000,343(16):1139-47.
[7] Hambrecht R,Wolf A,Gielen S,et al. Effect of exercise on coronary endothelial function in patients with coronary artery disease[J]. N Engl J Med,2000,342(7):454-60.
[8] Achenbach S,Daniel WG. Noninvasive coronary angiography—an acceptable alternative[J]. N Engl J Med,2001,345(26):1909-10.
[9] Patel MR,Peterson ED,Dai D,et al. Low diagnostic yield of elective coronary angiography[J]. N Engl J Med,2010,362(10):886-95.
[10] Amsterdam EA,Wenger NK,Brindis RG,et al. 2014 AHA/ACC guideline for the management of patients with non-ST-elevation acute coronary syndromes: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines[J]. J Am Coll Cardiol, 2014,64:e139-228.
[11] Sabatine MS,Liu E,Morrow DA,et al. Metabolomic identification of novel biomarkers of myocardial ischemia[J]. Circulation,2005,112(25):3868-75.
[12] Cheng ML,Wang CH,Shiao MS,et al. Metabolic disturbances identified in plasma are associated with outcomes in patients with heart failure:diagnostic and prognostic value of metabolomics[J]. J Am Coll Cardiol,2015,65(15):1509-20.
[13] Sreekumar A,Poisson LM,Rajendiran TM,et al. Metabolomic profiles delineate potential role for sarcosine in prostate cancer progression[J].Nature,2009,457(7231):910-4.
[14] Huang Q,Tan Y,Yin P,et al. Metabolic characterization of hepatocellular carcinoma using nontargeted tissue metabolomics[J]. Cancer Res,2013,73(16):4992-5002.
[15] Gika HG,Theodoridis GA,Wingate JE,et al. Within-day reproducibility of an HPLCMS-based method for metabonomic analysis: application to human urine[J]. J Proteome Res,2007, 6(8):3291-303.
[16] Ganna A,Salihovic S,Sundstr?m J,et al. Large-scale metabolomic profiling identifies novel biomarkers for incident coronary heart disease[J]. PLoS Genet,2014,10(12):e1004801.
[17] Stegemann C,Pechlaner R,Willeit P,et al. Lipidomics profiling and risk of cardiovascular disease in the prospective population-based Bruneck study[J]. Circulation,2014,129(18):1821-31.
[18] Wymann MP,Schneiter R. Lipid signalling in disease[J]. Nat Rev Mol Cell Bio,2008, 9(2):162-76.
[19] Tang WHW,Wang Z,Levison BS,et al. Intestinal microbial metabolism of phosphatidylcholine and cardiovascular risk[J]. N Engl J Med,2013,368(17):1575-84.
[20] Lin Z,Pan X,Wu F,et al. Fibroblast growth factor 21 prevents atherosclerosis by suppression of hepatic sterol regulatory elementbinding protein-2 and induction of adiponectin in mice[J]. Circulation,2015,131(21):1861-71.
[21] Masuda M,Miyazaki-Anzai S,Keenan AL,et al. Saturated phosphatidic acids mediate saturated fatty acid-induced vascular calcification and lipotoxicity[J]. J Clin Invest,2015,125(12):4544-58.
[22] Bottomley PA,Panjrath GS,Lai S,et al. Metabolic rates of ATP transfer through creatine kinase (CK Flux) predict clinical heart failure events and death[J]. Sci Transl Med,2013,5(215):215re3.
[23] Rizos EC,Ntzani EE,Bika E,et al. Association between omega-3 fatty acid supplementation and risk of major cardiovascular disease events: a systematic review and meta-analysis[J]. J Am Med Assoc,2012,308(10):1024-33.
[24] Mellor AL,Sivakumar J,Chandler P,et al. Prevention of T cell-driven complement activation and inflammation by tryptophan catabolism during pregnancy[J]. Nat Immunol,2001,2(1):64-8.
[25] Koves TR,Ussher JR,Noland RC,et al. Mitochondrial overload and incomplete fatty acid oxidation contribute to skeletal muscle insulin resistance[J]. Cell Metab,2008,7(1):45-56.
[26] Lazo M,Rubin J,Clark JM,et al. The association of liver enzymes with biomarkers of subclinical myocardial damage and structural heart disease[J]. J Hepatol,2015,(62):841-7.
[27] Shah SH,Sun JL,Stevens RD,et al. Baseline metabolomic profiles predict cardiovascular events in patients at risk for coronary artery disease[J].Am Heart J,2012,163(5):844-50.
[28] Knapp M,Baranowski M,Lisowska A,et al. Decreased free sphingoid base concentration in the plasma of patients with chronic systolic heart failure[J]. Adv Med Sci,2012,57(1):100-5.
[29] Akasaka H,Ruan KH. IDENTIFICATION OF THE TWO-PHASE MECHANISM OF ENDOGENOUS OMEGA-6 FATTY ACID,ARACHIDONIC ACID, REGULATING VASCULAR INFLAMMATION BY TARGETING CYCLOOXYGENASE-2 AND MICROSOMAL PROSTAGLANDIN E2 SYNTHASE-1[J]. J Am College Cardiol,2016,67(13):2318.
[30] Sayin SI,Wahlstr?m A,Felin J,et al. Gut microbiota regulates bile acid metabolism by reducing the levels of tauro-beta-muricholic acid, a naturally occurring FXR antagonist[J]. Cell Metab,2013,17(2):225-35.
[31] Chapman MJ,Ginsberg HN,Amarenco P,et al. Triglyceride-rich lipoproteins and highdensity lipoprotein cholesterol in patients at high risk of cardiovascular disease: evidence and guidance for management[J].Eur Heart J,2011,32(11):1345-61.
[32] Lewis GD,Wei RU,Liu E,et al. Metabolite profiling of blood from individuals undergoing planned myocardial infarction reveals early markers of myocardial injury[J]. J Clin Invest, 2008,118(10):3503-12.
本文編輯:姚雪莉
Metabolomic characteristics and their value in diagnosis of coronary artery disease
Zhao Juan*, Teng Lixin, Mao Mei.
*Ward of Geriatrics, Chinese PLA 324 Hospital, Chongqing 400020, China.
ObjectiveTo analyze the diagnostic value of metabolomic changes to different types of coronary artery disease (CAD).MethodsThe hospitalized patients (n=1086, male 712 and female 374) were chosen from the departments of geriatrics in the Emergency Center of Chongqing City, Tumor Hospital of Chongqing City,Chinese PLA 324 Hospital and the Third People’s Hospital of Chongqing City from Jan. 2003 to Jan. 2016. All patients were divided, according to symptoms and examination results, into normal coronary artery group (NCA group, n=116, without coronary stenosis), non-occlusion coronary atherosclerosis group (NOCA group, n=276,coronary stenosis<50%), acute myocardial infarction group (AMI group, n=324), unstable angina group (UA group,n=307) and stable angina group (SA group, n=63). The mass spectra peaks of metabolites in different blood samples were detected by using liquid chromatography-tandem mass spectrometry (LC-MS) for determining all metabolites.ResultsThere were 12 cross comparisons conducted aiming at metabolic disorders of CAD, and 89 different metabolites identified. The changes of metabolic pathways included increase of phospholipid metabolism, decrease of amino acid metabolism, increase of short chain acyl carnitine, decrease of three-carboxylic acid cycle, and decrease of primary bile acid synthesis. The results of receiver operating characteristic curve (ROC) in reviewing diagnostic value of varying metabolites in all groups showed that area under curve (AUC) was 0.952, sensitivity was 94.2% and specificity was 80.7% in NOCA group and NCA group (n=392), 0.993, 96.4% and 95.6% in SA group and NOCA group (n=339), 0.990, 97.4% and 91.1% in UA group and SA group (n=370), and 0.992, 94.5% and 95.3% in AMI group and UA group (n=631).ConclusionThe patients with different types of CAD will suffer from metabolic disorders. The changes of small molecular metabolites have potential value in the antidiastole of CAD.
Coronary artery disease; Metabolomics; Metabolites; Diagnosis
Zhao Juan, E-mail: zhaojuanqc78@163.com
R543.3 【文獻標志碼】 A 【文獻標志碼】1674-4055(2017)09-1112-06
1400020 重慶,解放軍第三二四醫(yī)院干部病房;2518000 深圳,香港大學(xué)深圳醫(yī)院心血管內(nèi)科
趙娟,E-mail:zhaojuanqc78@163.com
10.3969/j.issn.1674-4055.2017.09.26