CN111599476A - 一种高血压的预测模型及其建立方法以及用于预测高血压的生物标记物 - Google Patents
一种高血压的预测模型及其建立方法以及用于预测高血压的生物标记物 Download PDFInfo
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- CN111599476A CN111599476A CN202010415368.XA CN202010415368A CN111599476A CN 111599476 A CN111599476 A CN 111599476A CN 202010415368 A CN202010415368 A CN 202010415368A CN 111599476 A CN111599476 A CN 111599476A
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Abstract
本发明属于生物技术领域,提供了一种高血压的预测模型及其建立方法以及用于预测高血压的生物标记物。建模方法包括:筛选正常人群与高血压人群的差异性代谢产物,得到具有显著性差异的三组差异性代谢物,分别是腺嘌呤核苷酸、1‑甲基烟酰胺、次黄嘌呤核苷;对差异性代谢物分析;建立预测模型,发病风险=0.4035+6×10‑7*腺嘌呤核苷酸含量‑1.27×10‑4*1‑甲基烟酰胺含量+2.31×10‑5*次黄嘌呤核苷含量(1为发病,0为不发病),该模型预测准确率高达90.0%。进一步的,基于本发明的研究,可以得到用于预测高血压的生物标记物、试剂或者试剂盒。
Description
技术领域
本发明涉及生物技术领域,涉及高血压疾病预测方面,提供了一种高血压的预测模型及其建立方法以及用于预测高血压的生物标记物。
背景技术
当前,随着人民生活水平的日益提高,工作压力的逐渐增大,我国高血压患者人数也越来越多。据国际著名杂志JAMA Intern Med对我国10个地区(5个城市5个农村)的500,233例居民(年龄在35-75岁之间)的血压状况显示,我国高血压的患病率为32.5%,还有39.5%的居民为高血压前期(120/80~139/89mmHg),即我国七成以上的成年人都在高血压的威胁之下。即使在接受治疗的患者中,血压的控制率仅为29.6%,而且治疗率随着年龄的增加而降低。从整个研究人群来看,我国所有高血压患者的控制率仅为4.2%。其中,中青年人群若高血压不控制,心血管死亡风险最高。国家卫计委2016年发布的数据显示,中国18岁及以上成人高血压患病率为25.2%,患者人数2.7亿,每年有200万人的死亡与高血压有关。慢性病监测数据显示,在成人高血压患者中,3/4以上为中青年,且发病率的增长较老年人更加迅猛。
血压增高实际上是一个生命指标、一个生命体征数据。患了高血压,很多人会有症状,但有一些人偏偏没有感觉,这种人反而最危险。如果能感觉到血压高了、不舒服了,说明这是你的身体在自我保护。如果你感觉不到,很可能任由高血压损伤器官。综上所述,我国高血压管理形势严峻,血压诊断率、治疗率、治疗达标率均显著低于欧美国家水平。对高血压的早防早治、个体化药物治疗的疗效具有十分重要的科学意义。目前,针对高血压患病预测的模型尚不明确,已知的一些预测方法也尚不成熟,急需开发出一种快捷、有效、而又不依赖于单一血压值测量的高血压预测方法。
高血压本身的早期标志物主要集中于内皮细胞功能障碍与氧化应激方面,如一氧化氮与前列环素的下降,氧化的低密度脂蛋白与脂质过氧化物的增加。但是,目前为止,还没有出现能够利用这些标志物准确预测高血压的预测模型。因此,开发快速高效,且可以通过验血就能了解和预测高血压的方法和模型,具有重要的临床意义和市场前景。
代谢组学(metabonomics)因其能够灵敏而全面地测定不同生理、病理状态下内源性代谢产物的改变,给出生物体对药物毒性和药效的整体信息,从而有利于全面认识和评价药物,现已广泛地应用到了药物研发领域。近年来研究发现,诸如代谢性疾病和恶性肿瘤等疾病发生发展过程中,机体基础生化代谢均发生了明显变化,代谢组学为复杂疾病的筛检和早期诊断提供崭新的技术方法。高效液相色谱-质谱联用(HPLC-MS/MQ技术具有灵敏度高、专属性强、动态范围宽、设备购置费用相对较低的特点,因此已越来越多地被应用于代谢组学,基于HPLC-MS/MS技术的代谢组学更有显著的优势。
发明内容
针对现有技术的不足,本发明基于代谢组学,提供了一种高血压的预测模型及其建立方法以及用于预测高血压的生物标记物。
本发明的技术方案是:
一种高血压的预测模型,风险系数=0.4035+6×10-7*R1-1.27×10-4*R2+2.31×10-5*R3,其中R1为腺嘌呤核苷酸,R2为1-甲基烟酰胺,R3为次黄嘌呤核苷,风险系数=1为发病,风险系数=0为不发病,参数为各代谢物质谱数据峰面积经过样本组织重量归一化后的数值,样本组织质量单位为g。
一种用于高血压的预测模型的建立方法,包括以下步骤:
(1)分析正常人群与高血压人群的多钟代谢产物;
(2)筛选正常人群与高血压人群的差异性代谢产物,得到具有显著性差异的三组差异性代谢物,分别是腺嘌呤核苷酸、1-甲基烟酰胺、次黄嘌呤核苷;筛选差异性代谢物的标准是:(1)OPLS-DA模型第一主成分的VIP值大于1;(2)S-PLOT图中covariance p的绝对值大于0.1且correlation p(cor)的绝对值大于0.5;
(3)多元线性回归分析建立预测模型为:风险系数=0.4035+6×10-7*R1-1.27×10-4*R2+2.31×10-5*R3,其中R1为腺嘌呤核苷酸,R2为1-甲基烟酰胺,R3为次黄嘌呤核苷,风险系数=1为发病,风险系数=0为不发病。
优选方案,通过经过HPLC/MS检测分析正常人群与高血压人群的多钟代谢产物,液相条件为:A相:4%-5%乙腈+20mM-25mM乙酸铵+20mM-25mM氨水,PH=8-9;B相:纯乙腈;流动梯度:0-0.1min 13%-15%A,0.1-3min 15%-70%A,3-5min 70%-86%A,5-7min 86%-90%A,7-10min 90%-15%A,10-10.1min13%-15%A;流速为0.3-0.5ml/min。此处百分比为A相占A+B相的比例;质谱条件如下:电喷雾电离源,正负离子两种模式进行扫描,多反应离子监测模式进行定量分析,负离子:柱温40℃-45℃,雾化温度为460℃-480℃,喷雾气(GS1)为50-60psi;正离子:柱温40℃-45℃,雾化温度为460℃-480℃,喷雾气(GS1)为50-60psi。
具体实施例中的最优方案是:色谱条件如下:UHPLC—QTRAP—MS(6500,ABSCIEX)仪器,色谱柱是Xbridge Amide 3.5μm 4.6×100mm;液相条件为:A相:5%乙腈+20mM乙酸铵+20mM氨水,PH=9;B相:纯乙腈;流动梯度:0-0.1min 15%A,0.1-3min15%-70%A,3-5min70%-86%A,5-7min 86%A,7-10min 86-15%A,10-10.1min 15%A;流速为0.4ml/min。此处百分比为A相占A+B相的比例。
质谱条件如下:电喷雾电离源(ESI),正负离子两种模式进行扫描,多反应离子监测模式进行定量分析。负离子:柱温40℃、雾化温度(TEM)为475℃、喷雾气(GS1)为50psi;正离子:柱温40℃,雾化温度(TEM)为475℃、喷雾气(GS1)为50psi。
本发明还提供了用于预测高血压的生物标记物,选自以下三种化合物中的一种或几种,所述三种化合物分别为腺嘌呤核苷酸、1-甲基烟酰胺、次黄嘌呤核苷。
本发明还提供了检测一个或多个代谢物的试剂在制备用于预测高血压和/或心血管疾病试剂或者试剂盒中的应用,所述一个或多个代谢物选自腺嘌呤核苷酸、1-甲基烟酰胺、次黄嘌呤核苷中的一种或几种。
与现有技术相比,本发明的优势是:
本发明首次发现与高血压相关的一组化合物,即与高血压相关的代谢物,并通过构建逻辑回归模型,得到根据这些代谢物预测高血压的模型,该预测模型快捷,方便,准确度高,设计合理可行。
以下结合附图和具体实施方式对本发明的详细结构作进一步描述。
附图说明
图1为OPLS-DA模型图,适合于发现正常大鼠(BLK)和高血压大鼠(HMP)两组之间的差异性物质。
图2为S-PLOT图,适合评估正常大鼠(BLK)和高血压大鼠(HMP)两组之间的差异性物质。
图3为200次置换检验结果图,适合评估正常大鼠(BLK)和高血压大鼠(HMP)两组之间的差异性物质。
图4中A为代谢物R1的质谱图,B为代谢物R3的质谱图。
具体实施方式
实施例1
本发明建模方法的详细步骤(实施例中所有百分含量均为体积百分含量):
步骤1,HPLC-MS检测技术获得数据,原始数据的提取、对齐与归一化;对两组组织样本,分为对照组5个样本和高血压组4个样本。样本经过HPLC/MS检测获得数据文件。色谱条件如下:UHPLC—QTRAP—MS(6500,AB SCIEX)仪器,色谱柱是Xbridge Amide 3.5μm 4.6×100mm;液相条件为:A相:5%乙腈+20mM乙酸铵+20mM氨水,PH=9;B相:纯乙腈;流动梯度:0-0.1min 15%A,0.1-3min 15%-70%A,3-5min70%-86%A,5-7min 86%A,7-10min 86-15%A,10-10.1min 15%A;流速为0.4ml/min。此处百分比为A相占A+B相的比例。
质谱条件如下:电喷雾电离源(ESI),正负离子两种模式进行扫描,多反应离子监测模式进行定量分析。负离子:柱温40℃,去簇电压(DP)为-93V、射入电压(EP)为-10V、碰撞室射出电压(CXP)为-0.3V、气帘气(CUR)为35psi、碰撞气(CAD)为10psi、喷雾电压(IS)为-4500V、雾化温度(TEM)为475℃、喷雾气(GS1)为50psi、辅助加热气(GS2)为50psi。正离子:柱温40℃,去簇电压(DP)为93V、射入电压(EP)为-10V、碰撞室射出电压(CXP)为10V、气帘气(CUR)为35psi、碰撞气(CAD)为10psi、喷雾电压(IS)为5500V、雾化温度(TEM)为475℃、喷雾气(GS1)为50psi、辅助加热气(GS2)为50psi。
纳入检测的化合物共计98种,它们是:
1-Methylhistamine;1-Methyladenosine;2-Pyrocatechuic acid;DL-2-Aminooctanoic acid;2-Isopropylmalic acid;3-Aminoisobutanoic acid;3-Hydroxyanthranilic acid;L-Acetylcarnitine;N-Alpha-acetyllysine;Adenine;Adenosine;L-Alanine;Allantoin;AICAR;Adenosine monophosphate;2-Aminobenzoicacid;L-Arginine;Ascorbic acid;L-Asparagine;L-Aspartic acid;Betaine;Betainealdehyde;L-Carnitine;Cholesterol sulfate;Choline;Citrulline;Creatine;Creatinine;Cyclic AMP;Cytidine;Deoxyuridine;D-Glucose;Dimethylglycine;Asymmetric dimethylarginine;Fructose 6-phosphate;FAD;Fumaric acid;Glucose 6-phosphate;L-Glutamic acid;L-Glutamine;Glutathione;Glycerophosphocholine;Guanine;Guanosine;Alpha-D-Glucose;4-Hydroxyproline;Hypoxanthine;Inosinicacid;Inosine;L-Kynurenine;L-Lactic acid;L-Alpha-aminobutyric acid;L-Cystathionine;L-Leucine;Lipoamide;Maleic acid;Melatonin;L-Methionine;1-Methylnicotinamide;Methylcysteine;Methylmalonic acid;Methylsuccinic acid;myo-Inositol;N-Acetylglutamicacid;N-Acetylglutamine;N-Acetyl-L-alanine;NAD;NADH;Ureidopropionic acid;Niacinamide;Oxalacetic acid;Oxoglutaric acid;p-Aminobenzoic acid;Pantothenic acid;L-Phenylalanine;Phenylpropiolic acid;Phosphoribosyl pyrophosphate;Pipecolic acid;L-Proline;Ribose 1-phosphate;D-Ribulose 5-phosphate;S-Adenosylhomocysteine;Sarcosine;L-Serine;5'-Methylthioadenosine;Glycerol 3-phosphate;Taurine;L-Threonine;L-Tryptophan;L-Tyrosine;Uridine 5'-diphosphate;Uridine 5'-monophosphate;Uracil;Urea;Uricacid;Uridine;L-Valine;Xanthosine。
在进行统计分析前,对所有样本进行重量归一化。将每个样品中所有代谢物的峰面积除以样本组织重量,得到重量归一化后的数值,样本组织质量单位为g。
步骤2,OPLS-DA模型建立;
正交偏最小二乘法判别分析(OPLS-DA)是PLS-DA的一种衍生运算分析方法,主要结合了正交矫正信号(OSC)和PLS两种方法,通过将X轴矩阵信息分解成与Y相关和不相关的两类信息,能够排除与分组不相关的一些变量,更准确的筛选出有价值的差异性变量从而使使判别能力更优。通过OPLS-DA分析过滤掉不相关的正交信号,结合差异性变量的重要性投影值(VIP)值,从而使获得的差异性代谢物更加可靠。我们建立了OPLS-DA模型,该模型质量参数为R2X=0.222,R2Y=0.89,Q2=0.693。其中,R2Y与Q2的值越接近,表示模型的预测能力越好(一般认为小于0.2为优)。我们建立的模型中R2Y-Q2小于0.2,说明模型质量好。且两组样本在分值图的第一主成分轴上(X轴)具有显著的分离,如图1所示,因此OPLS-DA模型完成了良好的分组,高血压大鼠组数据与对照组大鼠组数据区分明显,该模型适合于正常鼠(BLK)和高血压鼠(HMP)两组之间的差异性物质区分。
步骤3,差异性代谢物分析;
差异性代谢物发现的原则:(1)OPLS-DA模型第一主成分的VIP值大于1;(2)S-PLOT图(图2)中covariance p的绝对值大于0.1且correlation p(cor)的绝对值大于0.5。VIP(Variable importance in the projection),为变量对模型的重要性,描述了每一个变量对模型的总体贡献,通常设定阈值为VIP>1。S-PLOT的X轴方向表示每一个变量对组别区分的影响,值越靠近X轴两端则对分组的贡献越大;Y轴方向即纵坐标轴方向表示组别区分变量的可靠性,其值介于-1到1之间,越靠近Y轴两端的变量其可靠性越好。因此,在S-PLOT中,右上角与左下角是需要重点关注的变量,也是代谢组学中有意义的生物标示物的识别区域,在本研究中则是高血压预测标志物的识别区域。本研究中,共筛选得到3个差异性代谢物:R1,R2,R3。R1为AMP(Adenosine monophosphate,即腺嘌呤核苷酸,腺苷酸),R2为MNA(1-Methylnicotinamide)R3为Inosine,(肌酐,也称为次黄苷、次黄嘌呤核苷等),具体见表1
表1 3个差异性代谢物
代谢物 | VIP值 | covariance p | correlation p(cor) |
R1 | 3.13 | 0.3963 | 0.905127 |
R2 | 1.18 | -0.104908 | -0.65309 |
R3.1 | 2.44 | -0.229271 | -0.60298 |
R3.2 | 2.2 | -0.214028 | -0.608395 |
本实验中,R3代谢物进行了两次进样检测,计算风险预测模型时,选取R3.1与R3.2的平均值作为代谢物R3的数值。
步骤4,模型评估;
为防止模型过拟合,采用200次置换检验(permutation Test)考察模型的拟合效果,评估模型的准确率。置换检验,是Fisher提出的一种基于大量计算(computationallyintensive),利用样本数据的随机排列(置换检验的核心思想,故名Permutation test),进行统计推断的方法。因其对总体分布自由,特别适合用于总体分布未知的小样本数据,以及一些常规方法难以使用的假设检验情况。依据已知测定数据变量X对预测变量Y进行多次迭代分析,并得出一个对这些变量的统计结果。通过考察所有样品对应R2、Q2计算值所组成的拟合直线在Y坐标轴的截距,表示模型的可靠性和过拟合程度。通常Q2截距值应明显小于模型变量预测度,并小于0.05。置换检验结果图的横坐标代表随机分组的Y与原始分组Y的相关性,纵坐标代表R2和Q2的得分。如图3所示,Y轴截距Q2Y-intercept=-0.793,小于0.05,认为模型具有较高准确率。
实施例2:
动物处理程序和样品制备:
为了证实此模型的有效性,从以下两个方面作了阐明:1.高血压模型的建立;2.高血压鼠差异化代谢物的筛选。
动物模型:选20周龄SHR大鼠(北京维通利华公司提供)制作高血压大鼠模型,对照组为WKY大鼠。SHR大鼠是1963年京都医学院(Kyoto school of Medicine)Okamoto利用有显著高血压症状的远交Wistar Kyoto(WKY)雄性鼠和带有轻微高血压症状的雌性鼠交配,自此开始兄妹交配并连续选择自发高血压性状。
分组实验:高血压组大鼠与正常对照组大鼠各6只,每天给与等量的生理盐水。
检测血压:各组大鼠在观察期间第2周、第3周、第4周,采用尾动脉测压法各测定1次大鼠尾动脉收缩压、动脉舒张压。血压仪为成都泰盟的BP-300A型号无创血压仪,采用尾动脉波动法进行测量。在干燥、通风、安静的环境中打开机器预热10分钟,将大鼠固定入测量所用鼠笼内,鼠尾穿过阻断器,待大鼠基本稳定且尾动脉充分扩张后,显示器上出现比较规则的脉搏波形时,开始对血压数据进行读取与记录。记录大鼠的收缩压和舒张压,每个时间点重复测量3至5次并取平均值作为每只大鼠的收缩压和舒张压。第4周时,高血压组大鼠收缩压为171.23±6.64mmHg,对照组大鼠收缩压为129.61±5.29mmHg(P=6.77×10-7);高血压组大鼠舒张压为138.04±5.25mmHg,对照组大鼠舒张压为93.89±9.14mmHg(P=2.90×10-6)。一般认为收缩压大于140mmHg即为高血压。由此可见,高血压组大鼠的高血压形状明显,其血压值与对照组大鼠具有显著差异(P<0.05),适合用于后续研究。
血清生化检测:经大鼠心尖采血,室温静置1h~2h后,4000rpm离心15min,取上清于离心管,-80℃保存备用。对血清生化样本进行总蛋白、白蛋白、球蛋白、总胆红素、直接胆红素、总胆汁酸、谷丙转氨酶、谷草转氨酶、尿素、尿酸、肌酐、甘油三酯、总胆固醇、高密度脂蛋白、低密度脂蛋白等指标的检测。样本血清生化检测由湘雅附属第一医院完成。通过血清生化检测,共发现以下8种血清生化指标在高血压组大鼠与对照组大鼠之间具有显著差异(P<0.05):
总蛋白(TP):对照组大鼠的总蛋白含量为61.05±1.04g/L,高血压组大鼠的总蛋白含量为66.83±3.80g/L,通过统计分析发现高血压组大鼠的总蛋白含量显著高于对照组大鼠的总蛋白含量(P=7.54×10-2)。据研究报道,总蛋白升高原因包括慢性肝炎、自身免疫性疾病、慢性感染等,提示这些因素可能在疾病发生起到关键作用。
白蛋白(ALB):对照组大鼠的总蛋白含量为32.22±1.03g/L,高血压组大鼠的总蛋白含量为37.00±1.58g/L,通过统计分析发现高血压组大鼠的总蛋白含量显著高于对照组大鼠的总蛋白含量(P=9.36×10-4)。
尿素(UREA):对照组大鼠的总蛋白含量为9.32±0.29mmol/L,高血压组大鼠的总蛋白含量为8.48±0.48mmol/L,通过统计分析发现高血压组大鼠的总蛋白含量显著低于对照组大鼠的总蛋白含量(P=1.61×10-2)。
尿酸(UA):对照组大鼠的总蛋白含量为60.95±9.77μmol/L,高血压组大鼠的总蛋白含量为165.80±17.35μmol/L,通过统计分析发现高血压组大鼠的总蛋白含量显著高于对照组大鼠的总蛋白含量(P=4.44×10-6)。据文献报道,尿酸升高是高血压的风险因素之一,结果提示该因素可能在高血压的发生过程中起到关键作用。
肌酐(CRE):对照组大鼠的总蛋白含量为51.72±4.98μmol/L,高血压组大鼠的总蛋白含量为60.78±5.09μmol/L,通过统计分析发现高血压组大鼠的总蛋白含量显著高于对照组大鼠的总蛋白含量(P=3.71×10-2)。肌酐含量可以作为肾损伤的指标,提示高血压组大鼠可能存在一定程度的肾损伤。
高密度脂蛋白(HDL-C):对照组大鼠的总蛋白含量为2.14±0.08mmol/L,高血压组大鼠的总蛋白含量为1.23±0.09mmol/L,通过统计分析发现高血压组大鼠的总蛋白含量显著低于对照组大鼠的总蛋白含量(P=2.68×10-7)。
低密度脂蛋白(LDL-C):对照组大鼠的总蛋白含量为0.69±0.05mmol/L,高血压组大鼠的总蛋白含量为0.38±0.05mmol/L,通过统计分析发现高血压组大鼠的总蛋白含量显著低于对照组大鼠的总蛋白含量(P=3.03×10-5)。
总胆固醇(TC):对照组大鼠的总蛋白含量为2.95±0.11mmol/L,高血压组大鼠的总蛋白含量为1.69±0.13mmol/L,通过统计分析发现高血压组大鼠的总蛋白含量显著低于对照组大鼠的总蛋白含量(P=4.37×10-7)。
代谢组学检测:取高血压组大鼠与对照组大鼠的心脏组织,储存于-80℃冷冻组织。每只实验鼠称取约50mg组织,放入预冷的研钵,不断加入液氮研磨,至研磨至粉状。加入预冷的甲水(甲醇:水为1:1)1.0ml,提取代谢物。取600μl混合液,涡旋45s,-20℃孵育1小时。4℃,13000rpm/min,离心15分钟。取上清,用氮气挥干。使用复溶液(氯仿:甲醇为1:1)50μl进行复溶。4℃,13000rpm/min,离心15分钟。取上清于进样瓶,进样测定。色谱条件同实施例1.
差异性代谢物分析;
差异性代谢物发现的原则:(1)OPLS-DA模型第一主成分的VIP值大于1;(2)S-PLOT图(图2)中covariance p的绝对值大于0.1且correlation p(cor)的绝对值大于0.5。共筛选得到3个差异性代谢物:R1,R2,R3。本部分计算通过软件SIMCA-P V14.1完成。使用SIMCA14.1中的OPLS模块,建立正交偏最小二乘回归分析模型。通过建立数学模型,实现由X数据组中的各变量与回归目标Y建立误差最小的拟合方程式。基于正交算法的过滤,在模型拟合时可排除与Y无关的变量,从而可对目标生物现象或过程进行更深刻的解读,发现与回归目标Y最重要的变量X;同时,可通过新样本的X数据预测出其Y值。
模型评估;
利用200次置换检验(permutation Test)评估模型的准确率。如图3所示,Y轴截距Q2Y-intercept=-0.793,小于0.05,认为模型具有较高准确率。本部分计算由软件SIMCA-PV14.1完成。
以上所述为本发明的具体实施方式,但本发明的保护范围不局限于此,任何熟悉技术领域的技术人员在本发明揭露的技术范围内,根据本发明的技术方案及其构思加以等同替换或改变,都应涵盖在本发明权利要求的保护范围之内。
Claims (5)
1.一种高血压的预测模型,其特征是,风险系数=0.4035+6×10-7*R1-1.27×10-4*R2+2.31×10-5*R3,其中R1为腺嘌呤核苷酸,R2为1-甲基烟酰胺,R3为次黄嘌呤核苷,风险系数=1为发病,风险系数=0为不发病,参数为各代谢物质谱数据峰面积经过样本组织重量归一化后的数值,样本组织质量单位为g。
2.一种用于高血压的预测模型的建立方法,其特征是,包括以下步骤:
(1)分析正常人群与高血压人群的多钟代谢产物;
(2)筛选正常人群与高血压人群的差异性代谢产物,得到具有显著性差异的三组差异性代谢物,分别是腺嘌呤核苷酸、1-甲基烟酰胺、次黄嘌呤核苷;筛选差异性代谢物的标准是:(1)OPLS-DA模型第一主成分的VIP值大于1;(2)S-PLOT图中covariance p的绝对值大于0.1且correlation p(cor)的绝对值大于0.5;
(3)多元线性回归分析建立预测模型为:风险系数=0.4035+6×10-7*R1-1.27×10-4*R2+2.31×10-5*R3,其中R1为腺嘌呤核苷酸,R2为1-甲基烟酰胺,R3为次黄嘌呤核苷,风险系数=1为发病,风险系数=0为不发病,参数为各代谢物质谱数据峰面积经过样本组织重量归一化后的数值,样本组织质量单位为g。
3.根据权利要求2所述用于高血压的预测模型的建立方法,其特征是,通过经过HPLC/MS检测分析正常人群与高血压人群的多钟代谢产物,液相条件为:A相:4%-5%乙腈+20mM-25mM乙酸铵+20mM-25mM氨水,PH=8-9;B相:纯乙腈;流动梯度:0-0.1min 13%-15%A,0.1-3min 15%-70%A,3-5min 70%-86%A,5-7min 86%-90%A,7-10min 90%-15%A,10-10.1min 13%-15%A;流速为0.3-0.5ml/min。此处百分比为A相占A+B相的比例;质谱条件如下:电喷雾电离源,正负离子两种模式进行扫描,多反应离子监测模式进行定量分析,负离子:柱温40℃-45℃,雾化温度为460℃-480℃,喷雾气为50-60psi;正离子:柱温40℃-45℃,雾化温度为460℃-480℃,喷雾气为50-60psi。
4.用于预测高血压的生物标记物,其特征是,选自以下三种化合物中的一种或几种,所述三种化合物分别为腺嘌呤核苷酸、1-甲基烟酰胺、次黄嘌呤核苷。
5.检测一个或多个代谢物的试剂在制备用于预测高血压和/或心血管疾病试剂或者试剂盒中的应用,所述一个或多个代谢物选自腺嘌呤核苷酸、1-甲基烟酰胺、次黄嘌呤核苷中的一种或几种。
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