【作者】 张伟；

【导师】 姜良铎； 刘清泉；

【作者基本信息】 北京中医药大学 ， 中医内科学， 2009， 博士

【摘要】 1背景脓毒症是具有感染依据的全身炎症反应综合征,是创伤、烧伤、休克、感染、大手术等临床急危重患者的严重并发症之一,也是诱发脓毒性休克、多器官功能障碍综合征的重要原因。国外流行病学调查显示,脓毒症的病死率已超过急性心肌梗塞,每年欧洲和美国有超过35万人死于此病,治疗费用高达250亿美元。每年全球有超过1,800万严重脓毒症病例,且患者数目每年以1.5%的速度递增。目前脓毒症发病率居高不下,缺乏行之有效的治疗方法,而且成本高昂,已成为严重影响生命健康的重要疾患,深入研究脓毒症的发病机制及遗传因素将对其早期诊断和治疗有重要价值。2理论依据脓毒症的发病机制非常复杂,与感染、炎症、免疫、凝血、组织损伤、遗传基因特性等有关。脓毒症患者的临床表现呈现多样性,实验室生化指标的差异也很大。在临床上经常可以见到,感染同一种病原微生物的不同脓毒症患者,其临床表现和预后截然不同。脓毒症临床表现的多样性与环境因素、疾病过程等固然有关,但遗传因素对脓毒症的发生、发展起了重要作用。已有资料表明,机体对致病微生物入侵人体后是否产生免疫应答、应答的强弱以及由此引起的炎症介质释放方式和病理生理变化,在一定程度上受到遗传因素的控制。基因多态性可能影响个体细胞因子产生水平、免疫应答反应强度、全身性炎症反应、脓毒症发生发展和预后。近年来关于基因多态性与脓毒症之间关系的研究日益增多,研究发现TNF、Toll样受体、IL-1、IL-10、CD14、MBL等均存在基因多态性,且某些基因多态性与脓毒症的易感性、死亡率等有相关性,这些研究有可能为脓毒症的早期识别、预后分析和基因治疗等提供理论依据。中医、中西医结合领域的学者们也进行了广泛深入的研究,对脓毒症的病因病机、诊断治疗也有了更为深刻的认识。本课题组在多年临床实践和研究的基础上发现,脓毒症的发病过程中存在瘀毒广泛伤络、阻络的病机,这不同于其他通常被认为有瘀毒病机的疾病,例如,不同于瘀毒损伤心络(如急性心肌梗塞)、脑络(如急性脑梗塞)等特定络脉的疾病,不同于存在瘀毒病机的各种非脓毒症的普通感染性疾病(如社区获得性肺炎、急性泌尿系感染等)。在普通感染性疾病中,瘀毒多表现为局限于特定脏腑器官,而没有向全身扩散的趋势;但脓毒症却不同,脓毒症表现为全身性炎性反应综合征,且病情随时可能迅速加重,出现严重脓毒症、多脏器功能障碍、脓毒性休克而预后不良,从中医证候角度则认为脓毒症表现出了瘀毒广泛损伤全身脉络的特点。因此,虽然多种疾病中都存在瘀毒病机,但却各有特点。脓毒症是一种发病率高、死亡率高、治疗费用高的疾病,若能从基因水平揭示出决定脓毒症瘀毒病机特点的遗传因素,则有可能为脓毒症的早期诊断、中医药防治等提供依据。然而我们并不知道脓毒症瘀毒病机可能与哪些基因有关,因此我们选用随机扩增多态性DNA(RAPD)技术对不同疾病群体间的基因多态性进行检测。3实验方法分别收集脓毒症(A群体)、急性心肌梗塞(B群体)、急性脑梗塞(C群体)、社区获得性肺炎(D群体)、急性泌尿系感染(E群体)病例,并将B群体与C群体混合(BC群体)作为瘀毒损伤特定脉络的代表疾病与脓毒症比较,将D群体与E群体混合(DE群体)作为普通感染、瘀毒局限于特定脏腑器官而未向全身扩散的代表疾病与脓毒症进行比较。用EDTA抗凝真空采血管采集患者外周血,以430ul每份分装于已灭菌的1.5ml EP管后,置于-86℃冻存备用,用Qiagen DNA Mini Kit提取外周血DNA,用紫外分光光度计测定OD260并计算DNA浓度,使用S01-S54共54条由10个核苷酸组成的随机引物分别与各DNA样本进行RAPD反应。RAPD反应体系如下:RAPD扩增产物经1.5%琼脂糖凝胶电泳(Gelred染色),在紫外成像仪下成像并保存。对图像进行分析,RAPD为显性标记,同一引物的扩增产物在电泳中迁移率相同的条带被认为是有同源性的,有带的记为1,无带记为0,形成二元数据矩阵。使用POPGENE软件对RAPD结果进行遗传分析,使用Fisher’精确检验对各分子标记在不同群体中的分布差异进行检验。4研究结果2008年5月至2008年12月共收集A群体脓毒症患者14例(年龄45-81岁,平均63.1±13.0岁,其中男性9例);B群体急性心肌梗塞患者7例(年龄51-80岁,平均66.9±12.0岁,其中男性5例),C群体急性脑梗塞患者7例(年龄58-77岁,平均69.4±6.6岁,其中男性5例),即BC混合群体共14例(年龄51-80岁,平均68.1±9.4岁,其中男性10例);D群体社区获得性肺炎患者7例(年龄18-79岁,平均51.1±26.2岁,其中男性3例),E群体急性泌尿系感染患者3例(年龄23-45岁,平均30.3±12.7岁,其中男性0例),即DE混合群体共10例(年龄18-79岁,平均44.9±24.3岁,其中男性3例)。病例来源于北京东直门医院、北京友谊医院、中日友好医院、北京军区总医院四所三级甲等医院急诊、ICU或CCU,均为汉族人群,群体内、群体间没有血缘关系。对RAPD结果进行分析,共有33条引物获得较为理想的扩增结果,共获得122条较为理想的分子标记。使用POPGENE32软件对RAPD分子标记结果进行遗传学分析:(1)多态位点百分率三种疾病群体的多态位点百分率差异不大,分别为A群体89.34%、BC群体81.97%、DE群体79.51%,平均为83.61%。在三种疾病群体共38个个体中共得到119个多态性位点,总的多态位点百分率为97.54%。(2)群体间遗传多样性A群体、BC群体、DE群体的Nei’s指数分别为0.3684±0.1626、0.3314±0.1874、0.3175±0.1911,平均为0.3881±0.1396;A群体、BC群体、DE群体的Shannon’s信息指数分别为0.5329±0.22023、0.4810±0.2582、0.4624±0.2647,平均为0.5634±0.1771。虽然Nei’s指数估计的基因多样性比Shannon’s信息指数估计的值低,但两者估计的不同疾病群体的遗传多样性的高低是一致的,这些数据显示不同群体间的变异不大。(3)群体间的遗传分化程度和基因流根据Nei’s指数估计的三个疾病群体总的遗传多样性是Ht=0.3863,其中群体内的遗传多样性为Hs=0.3391,群体的基因分化系数Gst=0.1222,即群体间的遗传变异占总群体遗传变异的12.22%,87.7 8%的遗传变异存在于各群体内部。根据群体间的遗传分化系数计算的基因流Nm=3.5908,说明群体间存在着基因交流,防止了由于遗传漂变导致的群体间的遗传分化。(4)群体间的遗传相似度和遗传距离根据Nei’s指数计算各疾病群体间的遗传相似度和遗传距离,结果表明A群体与BC群体的遗传相似度为0.8909,A群体与DE群体的遗传相似度为0.8588,BC群体与DE群体的遗传相似度为0.9288,其中BC与DE群体之间的遗传相似度最高,A群体与DE群体的遗传相似度最小。A群体与BC群体的遗传距离为0.1155,A群体与DE群体的遗传距离为0.1522,BC群体与DE群体的遗传距离为0.0738,A群体与DE群体的遗传距离最大。(5)群体间聚类分析使用POPGENE软件按Nei’s指数的遗传距离,对这三个疾病群体进行聚类,结果表明BC群体与DE群体聚为一个接近的群体1,群体1再与A群体聚为群体2,群体1与BC、DE的遗传距离为3.69216,群体2与群体1的遗传距离为3.00130,群体2与A群体的遗传距离为6.69345。使用Fisher’s精确检验分析各RAPD分子标记(条带)在不同群体间的分布差异:结果表明,在122个RAPD分子标记中共有26个在群体间分布有显著差异(P＜0.05),或极显著差异(P＜0.01)。这些分子标记分别为:S08-4、S10-2、S12-4、S13-2、S18-1、S20-4、S23-1、S23-2、S23-3、S25-1、S25-2、S25-3、S25-5、S28-1、S28-2、S28-3、S28-4、S28-5、S37-1、S38-2、S41-1、S43-2、S43-3、S49-1、S49-2、S49-3。共涉及到14条引物,分别为:S08(1个)、S10(1个)、S12(1个)、S13(1个)、S18(1个)、S20(1个)、S23(3个)、S25(4个)、S28(5个)、S37(1个)、S38(1个)、S41(1个)、S43(2个)、S49(3个)。这些有差异的RAPD分子标记中,有的表现为在A群体出现频率明显偏低,如S08-4、S10-2、S12-4、S41-1;或在A群体出现频率明显偏高,如S13-2、S18-1、S20-4、S37-1、S38-2。有4条引物的扩增结果中有2个及以上分子标记在不同群体间的分布情况存在差异,引物S43中的2个分子标记都表现为在A群体出现的频率明显偏高,而BC和DE的频率偏低且比较接近;引物S23中有3个分子标记在各群体中的分布有差异,且均为DE群体偏高,而A群体和BC群体偏低或没有出现;引物S25中有4个分子标记在各群体中的分布有差异,且都表现为在A群体的频率偏高,而BC群体的频率最低,且在此扩增结果中,C群体均没有扩增;引物S28中有5个分子标记在各群体中的分布有差异,且都表现为在A群体中的频率偏低;引物S49中有3个分子标记在各群体中的分布有差异,都表现为在BC群体中的频率偏高,A群体次之,而DE群体最低。5结论(1)使用RAPD技术发现不同个体、不同病证群体间存在丰富的基因多态性。(2)遗传分析表明各群体内遗传变异丰富,而群体间遗传变异较小,且群体间存在丰富的基因交流。(3)聚类分析能将脓毒症瘀毒广泛伤络阻络证候(A群体)与急性心肌梗塞和急性脑梗塞所代表的瘀毒损伤特定脉络的证候(BC群体)、社区获得性肺炎和急性泌尿系感染所代表的普通感染且非脓毒症的瘀毒损伤特定脏腑器官而无向全身扩散趋势的证候(DE群体)区分开,且后两者遗传距离较近。(4)Fisher’精确检验表明部分RAPD分子标记在不同群体间的分布存在显著差异,提示RAPD方法有可能找到脓毒症瘀毒伤络、阻络证候特异的分子标记。6创新点及存在问题与展望本研究的创新点在于使用RAPD DNA分子标记技术探讨与中医证候相关的微观物质基础,研究基因多态性与脓毒症中医瘀毒病机的关系,结果初步发现用RAPD方法研究证侯相关的基因多态性是可行的,并有可能通过RAPD方法寻找到脓毒症瘀毒伤络、阻络证候特异性的分子标记。然而这仅是一项使用RAPD技术进行的关于脓毒症瘀毒伤络、阻络证病证结合的物质基础的初步研究,由于本研究的样本量较小,使用的随机引物数量少,由部分推断整体仍有一定局限性,因此仍需要以本实验为基础,进一步开展大规模研究,增加样本量,并选用更多的随机引物进行筛选。或许可以尝试结合已知的基因组信息改进引物设计方法进行研究,但这种设想仍需进一步论证。同时对于已发现可能具有研究价值的分子标记仍需要进一步进行重复试验验证,既包括对于同一实验的反复重复验证,也包括从小样本到大样本的验证。此外,只有确切了解分子标记所携带的信息,才可能对临床有指导意义,因此必须对有意义的分子标记进行回收、测序、生物信息学分析,以鉴定其可能具有哪些功能特点,也可以针对序列信息设计有针对性的引物,将这种分子标记转化为序列特征化扩增区域(SCAR)标记,并通过经典的PCR反应进行验证,如果通过各种研究均能验证该分子标记是脓毒症瘀毒伤络、阻络证的特异性分子标记,则有可能为该疾病证候的早期诊断提供预警标记。更多还原

【Abstract】 1．BackgroundA systemic inflammatory response syndrome triggered by infection is known as sepsis. Sepsis is a serious complication of critical care diseases such as traum, burn, shock, infection, and big operation in clinic, and also the leading cause of sepsis shock and multiple organ dysfunction syndrome. The epidemiological study abrod shows that the fatality of sepsis is more than acute myocardial infarction already; more than 350 thousand people died from the disease every year in Europe and American, the cost reaches up to 250 hundred million U.S. dollars. There are more than 18 million sepsis patients every year , and the number is increasing at 1.5%. The incidence is high and effective therapies is absence, and the cost is expensive. So sepsis is an important disease influencing health, it is worth investigating the pathogenesis and genetic factors and it will be of help in diagnosis and treatment.2．Theory basisThe pathogenesis of sepsis is definitly complicated, it is associated about infection, inflammation, immunization, blood coagulation, tissue damage, and genetic etc. The clinical manifestation and biochemical indicators of sepsis is various. Although the pathogenic microorganism is the same, the clinical manifestation and prognosis maybe completely different. It is associated with environmental agent and disease process, but genetic factor plays an important role in sepsis. It is manifested that whether there is immune response and the degree of respone to infection is inflenced by genetic factors. Study shows that the polymorphism of TNF, Toll like receptors, IL-1, IL-10, CD14, MBL and some other genes may be associate with the affectabilty and mortality of sepsis. These studies may provide theory basis for early recognition, prognosis analysis and gene therapy all others in sepsis.In the field of Chinese medicine and intergration of traditional Chinese and western medicine, there are more deepgoing recognition about sepsis pathogenesis and treatment.According to years of clinical experience, we find that substance stasis and toxin damage and mutually congealed in collaterals extensively in sepsis, and it is different from other diseases which usually considered with substance stasis and toxin mutually congealed in collateral, e.g. acute myocardial infarction and acute cerebral infarction. Also it is different from common infectious disease other than sepsis, e.g. community acquired pneumonia and acute urinary infection, the substance stasis and toxin are limited to definite organs other than extensively. Although there are factors of substance stasis together with toxin in any population, but they are different.The incidence rate, mortality, and treatment costs of sepsis are all very high, so if the genetic fator for syndrome of substance stasis together with toxin in sepsis can be discovered in gene level, it will provide basis for the early diagnosis prevention and cure in traditional Chinese medicine. However, we don’t know which gene is associate with substance stasis and toxin, so we choose randomly amplified polymorphic DNA (RAPD) to investigate the polymorphism among different populations.3．MethodCollect cases of sepsis (Population A), acute myocardial infarction (Population B), acute cerebral infarction (Population C), community acquired pneumonia (Population D), and acute urinary infection (Population E), and mix B and C (Population BC) as representative disease for substance stasis together with toxin damaging definite collaterals to compare with sepsis, and mix D and E (Population DE) as representative disease for common infection that substance stasis together with toxin damaging definite organs to compare with sepsis.Collect peripheral blood of patients by EDTA anticoagulation vacuum tube, and subpackag it in 1.5ml EP tubes with 430ul per tube, and freeze them in -86℃for use. Extract genome DNA by Qiagen DNA Mini Kit, measure OD260 by ultraviolet spectrophotometer and calculate DNA concentration, use 54 random primers to proceed RAPD reaction with DNA samples respectively.RAPD reaction system: RAPD cycle:Make 1.5% agarose gel electrophoresis for RAPD production (staining by Gelred), and image with ultraviolet imagery system. Analyse the images, RAPD is dominance marker, and the productions with the same mobility of the same primer are considered as coisogenic, record "1" when exist and "0" when absence, form the bibasil data matrix. Make genetic analysis by POPGENE software, and make fisher’s exact test for the distributional difference of every RAPD marker among different populations.4．ResultFrom May 2008 to December 2008, we enrolled 14 patients with sepsis in population A (age from 45 to 81 yrs, average 63.1±13.0 yrs, including 9 male); 7 patients with acute myocardial infarction in population B (age from 51-80 yrs, average 66.9±12.0 yrs, including 5 male), 7 patients with acute cerebral infarction in population C (age from 58-77 yrs, average 69.4±6.6 yrs, including 5 male), i.e. there are 14 patients in population BC(age from 51-80 yrs, average 68.1±9.4 yrs, including 10 male); 7 patients with community acquired pneumonial in population D (age from 18-79 yrs, average 51.1±26.2 yrs, including 3 male) , 3 patients with acute urinary infection in population E (age from 23-45 yrs, average 30.3±12.7 yrs, including 0 male), i.e. there are 10 patient in population DE (age from 18-79 yrs, average 44.9±24.3 yrs, including 3 male). They were patients from emergency ICU or CCU of Dong Zhi Men hospital affiliated to Beijing University of Chinese Medicine, Beijing Friendship Hospital, China-Japan Friendship Hospital, and Beijing Command General Hospital. All of these patients are Han people, and there is no blood relation in and among populations.For the analysis of RAPD results, there are 33 random primers which has ideal amplification in all, and there are 122 ideal markers in all. The analysis of RAPD markers by POPGENE32 software:(1) The Percentage of Polymorphic Loci:There is no difference between the percentages of polymorphic loci in these populations, the percentages are 89.34% in population A, 81.97% in population BC, and 79.51% in population DE. The average percentage is 83.61%. There are 119 polymorphic loci in the whole 38 samples, the whole percentage of polymorphic loci is 97.54%.(2) Genic Variation Statistics:The Nei’s gene diversity is 0.3684±0.1626 in population A, 0.3314±0.1874 in population BC, 0.3175±0.1911 in population DE, and the average is 0.3881±0.1396; the Shannon’s Information index is 0.5329±0.22023 in population A, 0.4810±0.2582 in population BC, 0.4624±0.2647 in population DE, and the average is 0.5634±0.1771. Although Nei’s gene diversity is lower than Shannon’s Information index, but they have the same trend, and it shows that the diversity between populations is small.(3) Nei’s Analysis of Gene Diversity in Subdivided PopulationsThe general genetic diversity estimated by Nei’s gene diversity is Ht＝0.3863, the genetic diversity in populations is Hs＝0.3391, the coefficient of gene differentiation is Gst＝0.1222, i.e. the percentage of genetic diversity between populations is 12.22%, and there are 87.78% in populations. The gene flow calculate by coefficient of gene differentiation is Nm＝3.5908, it shows that there is gene exchange between populations, and prevent genetic differentiation caused by genetic drift.(4) Genetic Identity and Genetic distanceCalculate genetic identity and genetic distance by Nei’s gene diversity, the genetic identity is 0.8909 between A and BC, 0.8588 between A and DE, and 0.9288 between BC and DE. The identity between BC and DE is the highest, and the identity between A and DE is the lowest. The genetic distance between A and BC is 0.1155, between A and DE is 0.1522, between BC and DE is 0.0738, the distance between A and DE is the biggest.(5) Dendrogram Based Nei’s Genetic DistanceThe dendrogram based on Nei’s genetic distance shows that population BC and population DE gather to pop1, then pop1 and population A gather to pop2. The distance between pop1 and BC/DE is 3.69216, the distance between pop1 and pop2 is 3.00130, the distance between pop2 and population A is 6.69345.Analysis of RAPD marker distributional difference among populations by fisher’s exact test:In the whole 122 markers, there are 26 RAPD markers which has significant difference between populations (P＜0.05 or P＜0.01). These markers are S08-4, S10-2, S12-4, S13-2, S18-1, S20-4, S23-1, S23-2, S23-3, S25-1, S25-2, S25-3, S25-5, S28-1, S28-2, S28-3, S28-4, S28-5, S37-1, S38-2, S41-1, S43-2, S43-3, S49-1, S49-2, S49-3. And 14 random primers are involved, they are S08(1), S10(1), S12(1), S13(1), S18(1), S20(1), S23(3), S25(4), S28(5), S37(1), S38(1), S41(1), S43(2), S49(3).Among these discrepant RAPD markers, some behaves low occurrence frequency in population A, such as S08-4, S10-2, S12-4, S41-1; some behaves high occurrence frequency in population A, such as S13-2, S18-1, S20-4, S37-1, S38-2. For four random primers, they have more than 2 markers which has significant difference between populations. 2 markers of primer S43 behave high occurrence frequency in population A, and low occurrence frequency in population BC and DE. 3 markers of primer S23 behave high occurrence frequency in population DE, and low or absent in population A and BC. 4 markers of primer S25 behave high occurrence frequency in population A, low occurrence frequency in population BC, especially there is no amplification in population C. 5 markers of primer S28 behave low occurrence frequency in population A. 3 markers of primer S49 behave high occurrence in population BC, then population A, and the lowest in population DE.5．Conclusions (1)It is detected that there is abundant gene polymorphism between individuals and among different disease combined syndrome populations.(2)Genetic analysis shows abundant gene variation in populations, but gene variation between population is low, and there are affluent gene exchanges between populations.(3)Cluster analysis shows that sepsis with substance stasis together with toxin extensively damage and mutually congealed in collaterals syndrome (population A) is different from population BC and population DE, population BC is acute myocardial infarction and acute cerebral infarction which represent syndrome of substance stasis together with toxin damage definite collaterals, population DE is community acquired pneumonial and acute urinary infection which represent common infection also the syndrome of substance stasis together with toxin damage definite organs other than extensively.(4)Fisher’s exact test shows that some RAPD markers has significant distributional difference among populations, it prompts that it is possible to find specific molecule markers for the syndrome of substance stasis together with toxin extensively damage and mutually congealed in collaterals in sepsis by method of RAPD.6．Innovation, problem and prospectThe innovation of this study is the use of RAPD DNA molecular markers in studying traditional Chinese medicine syndromes related micro-material base, and in studying the relationship between gene polymorphism and sepsis TCM blood poisoning pathogenesis, and the preliminary study found that RAPD is feasible in studying syndrome related gene polymorphism. And it is possible to find specific molecular markers related to syndrome of substance stasis together with toxin extensively damage and mutually congealed in collaterals in sepsis by method of RAPD.However, it is just a pilot study of material basis related to syndrome of substance stasis together with toxin extensively damage and mutually congealed in collaterals in sepsis by RAPD, the results shows RAPD maybe possible method to find specific molecular markers. The sample in this study is small, and the radom primers is still less, so it is limited to infer the whole by the study and further study is needed. We can make large scale, choose more random primers, or try to improve primer design method by connecting foregone geneome information. Make duplicate test for the molecular markers that worthy further study, both duplicate and test in large samples. In addition, only a firm understanding of molecular marker information may have clinical meaning, so we must retrieve molecular markers, sequencing, and do bioinformatics analysis for interested markers and identify its features. And design specific primer according to sequence information, and transfer it into sequence characterized amplified region (SCAR) marker, and make verification by classical PCR reaction. If it is related to syndrome of substance stasis together with toxin extensively damage and mutually congealed in collaterals in sepsis by various tests, then it maybe worthy in early diagnosis of the syndrome in sepsis.更多还原