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1.
目的探究乳腺癌易感基因PALB2单核苷酸多态性与乳腺癌及其临床病理学参数的关系。方法收集280例乳腺癌患者作为病例组,288例健康人作为健康人对照组。以Mass ARRAY基因分型技术检测多态性位点rs447529、rs249954和rs120963在病例组和健康人对照组中的基因型分布,采用Logistic回归模型分析各基因型与乳腺癌易感性及其临床病理学参数的关系。结果 rs447529位点各基因型在病例组和健康人对照组中的分布差异无统计学意义(P0.05),rs120963位点的突变基因型TC(OR=2.46,95%CI=1.70~3.56,P0.01)、CC(OR=3.78,95%CI=1.58~9.01,P0.05)及TC/CC(OR=2.61,95%CI=1.82~3.72,P0.01)在病例组的分布频率均显著高于健康人对照组,rs249954位点的突变基因型CT(OR=1.99,95%CI=1.37~2.88,P0.01)、TT(OR=3.22,95%CI=1.75~5.92,P0.01)及CT/TT(OR=2.16,95%CI=1.51~3.09,P0.01)在病例组中的分布频率亦均显著高于健康人对照组。按照月经状态和初潮年龄进行分层分析,这2个多态性位点的各基因型在病例组中分布频率均显著高于健康人对照组(P0.05)。rs120963和rs249954与乳腺癌患者的肿瘤体积及淋巴结转移相关。结论 PALB2基因rs120963和rs249954位点基因多态性是乳腺癌发病的危险因素,并与乳腺癌的病理组织学参数相关。 相似文献
2.
在多囊肾病基因2(PKD2)中存在若干单核苷酸多态性(SNP)。PKD2突变可导致常染色体显性多囊肾病(ADPKD)。目前在PKD2中已检出数个SNP,但筛选的样本均来自高加索人。有学者认为,基因组平均每1001bp就有1个SNP,PKD2全长68000bp,理论上应有60多个SNP,这些遗传标记对于ADPKD发病机制的阐明具有重要意义。本研究检测PKD2中的SNP及其在上海市汉族人群中的频率分布。现报告如下。 相似文献
3.
单核苷酸多态性分析技术在2型糖尿病易感基因研究中的应用特点 总被引:1,自引:0,他引:1
目的:总结单核苷酸多态性分析技术在2型糖尿病易感基因研究中的应用成果。资料来源:应用计算机检索2000-01/2006-10Pubmed数据库与2型糖尿病易感基因相关的文献,检索词“type2diabetes,susceptibility gene”,并限定语种为“English”。同时检索2000-01/2006-10CNKI数据库相关文献,检索词“SNP,检测方法”,并限定语种为中文。同时手工检索相关书籍。资料选择:主要纳取实用性强和技术较新的单核苷酸多态性检测方法以及其在2型糖尿病易感基因研究中的具体应用。排除重复文献。资料提炼:对选择的文献进一步查找全文,共提炼出28篇文章进行综述,其中8篇中文文献,20篇英文文献。资料综合:2型糖尿病属于复杂遗传病,探索其基因基础,可为新的治疗方案提供资料。单核苷酸多态性分析技术可观察2型糖尿病与特殊的等位基因、基因型以及单倍体之间的关系,在研究易感基因方面有重要作用。而目前常用的单核苷酸多态性分析技术有:直接测序技术、限制性片段长度多态性分析技术、TaqMan探针技术、质谱分析法、基因芯片技术、分子信标技术、变性高效液相色谱技术、连接酶检测反应技术和多靶点液相芯片法技术等。结论:单核苷酸多态性分析技术作为易感基因研究的新技术,其应用日益广泛和深入。人们已发现一些基因的单核苷酸多态性位点的多态性可能与2型糖尿病的发生密切相关。所以,如何选择合适的单核苷酸多态性分析技术对糖尿病的易感基因进行深入研究是至关重要的。 相似文献
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目的建立高分辨率熔解(HRM)技术检测冠心病关联基因的标签单核苷酸多态性(SNPs)的方法;并探讨其与兰州地区汉族人群冠心病(CHD)易感性及血脂指标的相关性。方法建立CHD 5个关联基因CRP、ACE、NOS3、ENPP1、IQSEC1的7个SNPs位点(rs1205CT、rs4305AG、rs4353 GA、rs7830 CA、rs12528076CT、rs939899GA、rs1108640GC)的PCRHRM检测方法,并用260例CHD患者和238例体检健康者进行验证。结果标本经PCR扩增后均能进行基因分型,经直接测序验证,其分型正确率达100%。病例-对照分析显示rs4353 GA和rs12528076 CT等位基因频率在CHD组和对照组间差异有统计学意义(χ2=3.998,P=0.045;χ2=3.918,P=0.047),rs7830 CA基因型频率在两组间差异亦有统计学意义(χ2=6.369,P=0.041)。血脂水平分析显示,CHD患者与rs1205位点高密度脂蛋白胆固醇(HDL-C)水平存在相关性(F=14.067,P=0.001)。结论 PCR-HRM检测是一种快速、准确的基因分型方法。ACE、NOS3和ENPP1与兰州地区汉族人群CHD易感性相关,其中rs1205 CT联合HDL-C血清水平检测可预警CHD发生。 相似文献
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目的通过研究转化生长因子β2(TGFβ2)基因单核苷酸多态性与扩张型心肌病(DCM)的相关性,探讨DCM的免疫遗传学发病机制。方法从169例DCM患者(DCM组)和158例健康对照者(对照组)外周血中提取DNA,采用聚合酶链扩增反应-限制性片段长度多态性技术检测中国西南地区汉族人群DCM患者和健康对照者TGFβ2基因一个标签位点(rs6658835)单核苷酸多态性;用χ2检验比较DCM组与对照组之间基因型频率和等位基因频率的统计学差异。结果 DCM组与正常对照组基因型分布均符合Hardy-W e inberg平衡;与正常对照组相比,DCM患者组TGFβ2基因标签位点(rs6658835)GG+AG基因型和G等位基因频率明显增加,差异有统计学意义(分别为79.3%VS 62.7%和51.2%VS 39.6%,均P<0.01)。结论 TGFβ2基因rs6658835位点单核苷酸多态性与中国西南地区汉族人群DCM相关,TGFβ2基因多态性可能在DCM遗传易感性方面具有重要作用。 相似文献
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近年来,随着经济发展和生活方式的改变,2型糖尿病(T2DM)发病率在我国呈现逐渐升高的趋势。T2DM是一种遗传因素和环境因素共同作用而形成的多基因遗传的复杂性疾病,并以胰岛素分泌受损和(或)胰岛素抵抗为主要的临床特点,其遗传方式属于常染色体多基因隐性遗传,由于异常基因的遗传使后代具有糖尿病易感性。随着单核苷酸多态性(SNP)分析技术的发展以及全基因组关联研究结果的相继报道,至今已发现许多常见基 相似文献
7.
PPARG基因单核苷酸多态性与2型糖尿病血脂异常的相关性研究 总被引:2,自引:0,他引:2
目的研究PPARG基因单核苷酸多态性(SNPs)与中国汉族2型糖尿病(DM)及血脂异常的关系。方法测定593例2型DM患者及626名正常健康者SNPsrs1801282、rs12636454和rs11128597基因型,分析其与2型DM及血脂水平的关系。基因分型采用单碱基延伸法(SBE)。结果2型DM组SNPs rs1801282、rs12636454和rs11128597基因型及等位基因频率分布与对照组间差异均无统计学意义(P〉0.05)。2型DM组中rs1801282AB+BB基因型总胆固醇(TC)、血糖和低密度脂蛋白胆固醇(LDL—C)水平显著高于AA基因型(P均〈0.01)。rs1l2636454AA基因型三酰甘油(TG)水平高于AB+BB基因型(P〈0.05)。rs11128597AA基因型血糖水平高于AB+BB基因型(P〈0.01)。结论PPARG基因与中国汉族人2型DM无直接相关,但可能参与2型DM的血糖水平和脂质代谢的调节。 相似文献
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荧光偏振技术在单核苷酸多态性及基因型检测中的应用 总被引:1,自引:0,他引:1
单核苷酸多态性及基因型检测在多种疾病的诊断,病原体检测,组织配型,疾病预警及指导药物应用中具有重要的临床价值。荧光偏振检测技术因不需特制探针,简单,敏感,成本与芯片等DNA高通量检测技术相比较为低廉,有在临床推广应用的价值。 相似文献
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目的 最新研究显示华法林最佳用药剂量关联基因CYP2C9,CYP4F2和VKORC1可指导临床个体化用药,该成果的临床应用有赖于临床快速分子诊断方法的建立,为此该论文建立PCR-HRM(High-resolution melting)技术检测华法林最佳用药剂量关联基因单核苷酸多态性(SNP)并进行应用评价.方法 采用国际最前沿的基因突变筛查技术-HRM和新型荧光染料Eva Green对华法林最佳用药剂量关联基因CYP2C9*2,CYP2C9*3,CYP4F2 V433M和VKORC1 1173C/T四个SNP位点先进行染料法荧光PCR,接着进行PCR产物的高分辨熔解,依据熔解峰的特点进行SNP分型即PCR-HRM技术建立,最后通过检测临床181例标本进行临床应用评价.结果 在181例服用华法林的患者中检测到CYP2C9*2杂合子2例,CYP2C9*3杂合子15例,CYP4F2 V433M杂合子74例,纯合子14例,VKORC1 1173C/T杂合子33例.随机选择各类基因型PCR产物共24例进行测序,验证结果与检测结果一致.结论 PCR-HRM技术检测华法林最佳用药剂量关联基因SNP是一种灵敏、简便、快捷的低成本检测方法,可用于临床常规化分子诊断. 相似文献
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目的研究PPARG基因单核苷酸多态性(SNPs)与中国汉族2型糖尿病(DM)及血脂异常的关系。方法测定593例2型DM患者及626名正常健康者SNPs rs1801282、rs12636454和rs11128597基因型,分析其与2型DM及血脂水平的关系。基因分型采用单碱基延伸法(SBE)。结果2型DM组SNPs rs1801282、rs12636454和rs11128597基因型及等位基因频率分布与对照组间差异均无统计学意义(P>0.05)。2型DM组中rs1801282 AB+BB基因型总胆固醇(TC)、血糖和低密度脂蛋白胆固醇(LDL-C)水平显著高于AA基因型(P均<0.01)。rs12636454 AA基因型三酰甘油(TG)水平高于AB+BB基因型(P<0.05)。rs11128597 AA基因型血糖水平高于AB+BB基因型(P<0.01)。结论PPARG基因与中国汉族人2型DM无直接相关,但可能参与2型DM的血糖水平和脂质代谢的调节。 相似文献
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Warfarin exhibits significant interindividual variability in dosing requirements. Different drug responses are partly attributed to the single nucleotide polymorphisms (SNPs) that influence either drug action or drug metabolism. Rapid genotyping of these SNPs helps clinicians to choose appropriate initial doses to quickly achieve anticoagulation effects and to prevent complications. We report a novel application of surface-enhanced laser desorption and ionization time-of-flight mass spectrometry (SELDI-TOF MS) in the rapid genotyping of SNPs that impact warfarin efficacy. The SNPs were first amplified by PCR and then underwent single base extension to generate the specific SNP product. Next, genetic variants displaying different masses were bound to Q10 anionic proteinChips and then genotyped by using SELDI-TOF MS in a multiplex fashion. SELDI-TOF MS offered unique properties of on-chip sample enrichment and clean-ups, which streamlined the testing procedures and eliminated many tedious experimental steps required by the conventional MS-based method. The turn-around time for genotyping three known warfarin-related SNPs, CYP2C9*2, CYP2C9*3, and VKORC1 3673G>A by SELDI-TOF MS was less than 5 hours. The analytical accuracy of this method was confirmed both by bidirectional DNA sequencing and by comparing the genotype results (n = 189) obtained by SELDI-TOF MS to reports from a clinical reference laboratory. This new multiplex genotyping method provides an excellent clinical laboratory platform to promote personalized medicine in warfarin therapy.Over the last 20 years, much knowledge has been gained toward advancing the understanding of human physiology and elucidating the molecular basis of common diseases. There are as many as 3 million single nucleotide polymorphisms (SNPs) in the human genome.1 An SNP is a single nucleotide variation at a specific location in the genome that, by definition, is found in more than 1% of the population. SNPs are important genetic markers that determine an individual''s susceptibility to various diseases. SNPs have been used as molecular markers to evaluate disease processes and to predict patients'' drug responses. Thus, a great deal of effort has been devoted to developing accurate, rapid, and cost-effective technologies for SNP analysis to advance clinical diagnosis and therapeutics.There are several technological platforms for the determination of SNPs.2 A typical genotyping approach is to first increase the number of SNPs that will be analyzed. In most instances, PCR amplification of a desired SNP-containing region is performed initially to introduce specificity and increase the number of allele-specific molecules. Afterward, amplified DNA fragments containing a specific SNP are measured by a device based on mass or another biochemical property. Mass spectrometry (MS) is a widely used method for the mass determination of various biomolecules such as peptides, proteins, oligosaccharides, and oligonucleotides. In this approach, the analyte is detected as a measurable peak with a specific mass/charge ratio. MS has been successfully used in SNP genotyping.2,3 For instance, Matrix-assisted laser desorption/ionization time of flight (MALDI-TOF) MS, a commonly used platform of MS, has been reported for detection of hereditary thrombotic risk factors.4,5The surface-enhanced laser desorption and ionization mass spectrometer (SELDI-TOF MS) is a unique type of MS that involves matrix array technology.6 The most important feature comes from the different matrices or chips that are available to isolate or enrich a specific analyte before mass analysis. Several kinds of chips are available, each coated with a specific chemical matrix. Examples include immobilized metal affinity capture chips, cation or anion exchange chips, or chips with hydrophobic properties. Therefore, it is possible to preselect a chip (based on the properties of target analytes), enrich a target molecule, remove unwanted elements such as salt, and then detect it by using an MS. Conceivably, the unique features of SELDI-TOF MS make it the most plausible device for genotype testing because it can rapidly and efficiently isolate the targeted oligonucleotides (analytes) from other reaction reagents and therefore greatly improve the detection process.Warfarin (Coumadin) is an anticoagulant that disrupts the process of vitamin K recycling. Vitamin K is an essential cofactor for the posttranslational modification of several clotting factors including Factors II, VII, IX, and X, and the anticoagulant proteins C and S. Patients on therapeutic warfarin exhibit low clotting potential and therefore show less propensity for thrombotic disorders.7 There are two major pathways that determine warfarin drug efficacy. First, warfarin inhibits the function of vitamin K epoxide reductase (VKORC1) that is responsible for regeneration and recycling of vitamin K.8 Suppression of VKORC1 results in a reduction of endogenous vitamin K and a subsequent reduction of vitamin K-dependent clotting factors. It has been shown that VKORC1 variants exhibit different sensitivities to the drug. Patients who are found to have the genotype AA for the SNP VKORC1 3673G>A in the promoter region have a lower amount of VKORC1 and, therefore, typically require a lower warfarin dose than average. In contrast, those patients who have the GG genotype are resistant to warfarin, typically requiring a greater dose of the drug to achieve the desired therapeutic effect. Other patients carry an AG genotype. Secondly, the elimination of warfarin is almost entirely controlled through drug metabolism. Warfarin drug effect is primarily removed when it is converted to a hydroxylated metabolite by hepatic microsomal enzymes (cytochrome P-450). The cytochrome P-450 2C9 (CYP2C9) isozyme appears to be the principal form of human liver P-450, which controls the drug activity of warfarin. The variant alleles, particularly variant CYP2C9*2 and CYP2C9*3, result in decreased hydroxylation of warfarin, therefore reducing the rate of warfarin clearance.9,10,11 The role of genotype-based warfarin therapy to improve both drug efficacy and safety has been implicated in several recently published studies.12,13,14,15In this study, we used SELDI-TOF MS and developed a novel approach for rapid genotyping of SNPs that are known to influence warfarin sensitivity or warfarin metabolism. 相似文献
12.
本研究对白血病患者及健康对照者的血清样本进行检测分析,筛选新的生物标记物并建立白血病的蛋白质指纹图谱诊断模型.应用SELDI-TOF-MS技术检测40例白血病标本及37例健康对照标本,用Biomarker Wizard软件分析筛选新的生物标记物,使用Biomarker Patterns 5.0软件进行标记物的比较判别,建立白血病决策树诊断模型.结果表明,蛋白质指纹图谱分析发现有22个差异显著的蛋白峰(P<0.05);由m/z为4650,8609及11660建立的决策树诊断模型对白血病的诊断灵敏度为97.5% (39/40),特异性为91.9% (34/37).结论:由3个蛋白标记物构成的白血病蛋白质指纹图谱诊断模型为白血病的诊断提供了新的借鉴和参考. 相似文献
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Wanna Thongnoppakhun Surasak Jiemsup Suganya Yongkiettrakul Chompunut Kanjanakorn Chanin Limwongse Prapon Wilairat Anusorn Vanasant Nanyawan Rungroj Pa-thai Yenchitsomanus 《The Journal of molecular diagnostics : JMD》2009,11(4):334-346
A number of common mutations in the hemoglobin β (HBB) gene cause β-thalassemia, a monogenic disease with high prevalence in certain ethnic groups. As there are 30 HBB variants that cover more than 99.5% of HBB mutant alleles in the Thai population, an efficient and cost-effective screening method is required. Three panels of multiplex primer extensions, followed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry were developed. The first panel simultaneously detected 21 of the most common HBB mutations, while the second panel screened nine additional mutations, plus seven of the first panel for confirmation; the third panel was used to confirm three HBB mutations, yielding a 9-Da mass difference that could not be clearly distinguished by the previous two panels. The protocol was both standardized using 40 samples of known genotypes and subsequently validated in 162 blind samples with 27 different genotypes (including a normal control), comprising heterozygous, compound heterozygous, and homozygous β-thalassemia. Results were in complete agreement with those from the genotyping results, conducted using three different methods overall. The method developed here permitted the detection of mutations missed using a single genotyping procedure. The procedure should serve as the method of choice for HBB genotyping due to its accuracy, sensitivity, and cost-effectiveness, and can be applied to studies of other gene variants that are potential disease biomarkers.To date, 739 point mutations in the hemoglobin, β (HBB) gene causing β-thalassemia (MIM# 141900) have been reported in HbVar: A Database of Human Hemoglobin Variants and Thalassemias (http://globin.cse.psu.edu/globin/hbvar/menu.html, accessed March 2009), but each ethnic group has a limited number of common mutations and a considerable number of rarer mutations.1 The c.79G>A (also known as CD26G>A or Hb E) is the most frequent HBB variant in Southeast Asia including Thailand.2 “Thai” generally refers to speakers of Thai (Tai) languages. The ethnic groups of Thailand comprise Thais (constituting 85% of the population) and Hill Peoples living primarily in the north, as well as other groups including the Chinese and minorities in the south.3 In the Thai population, approximately 40 HBB mutations have been identified,4 of which 30 variants account for more than 99.5% of all mutant HBB alleles Common HBB mutations (13)
HBB mutations causing abnormal Hb (10)
Rare HBB mutations (7)
Common name HGVS nomenclature Common name HGVS nomenclature Common name HGVS nomenclature CD26G>A (Hb E) c.79G>A* CD147+AC (Hb Tak) c.441_442insAC*†‡ CD43G>T c.130G>T* CD41/42-TTCT c.124_127delTTCT*† CD126T>G (Hb Dhonburi) c.380T>G* CD123/125 (−8 bp) c.370_377delACC CCACC† CD17A>T c.52A>T*†‡ CD136G>A (Hb Hope) c.410G>A* −87C>A c.−137C>A† −28A>G c.−78A>G* CD6G>A (Hb C) c.19G>A*† CD15-T c.46delT† IVS2#654C>T c.316−197C>T* CD56G>A (Hb J-Bangkok) c.170G>A* CD8/9+G c.27_28insG† IVS1#5G>C c.92 + 5G>C* CD83G>A (Hb Pyrgos) c.251G>A* CD27/28+C c.84_85insC† CD19A>G (Hb Malay) c.59A>G* CD6A>C (Hb G Makassar) c.20A>C*† CD41-C c.126delC*† CD71/72 + A c.216_217insA* CD6A>T (Hb S) c.20A>T*†‡ IVS1#1G>T c.92 + 1G>T† CD121G>C (Hb D Punjab) c.364G>C* −31A>G c.−81A>G† CD1T>C (Hb Raleigh) c.5T>C† −30T>C c.−80T>C* CD35C>A c.108C>A† CD0T>G c.2T>G*