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两种不同技术所定义的遗传性异常脂蛋白模式的比较。

A comparison of heritable abnormal lipoprotein patterns as defined by two different techniques.

作者信息

Fredrickson D S, Levy R I, Lindgren F T

出版信息

J Clin Invest. 1969 Nov;47(11):2446-57. doi: 10.1172/JCI105927.

Abstract

Eight plasma lipoprotein patterns currently employed in attempts to identify different forms of familial dyslipoproteinemia have been compared by two methods. The first (NIH method) is based on paper electrophoretic patterns produced by the four lipoprotein classes obtained by paper electrophoresis in albuminated buffer, coupled with the measurement of the total cholesterol of three of these lipoprotein classes and ascertainment of abnormal flotation of beta-migrating lipoproteins. The second (Donner method) is based on lipoprotein patterns obtained in the analytical ultracentrifuge, adapted for computer analysis and complemented by chemical determination of the concentration of chylomicrons (lipoproteins of S(f) degrees > 400). Pooled samples representing patients with five types of familial hyperlipoproteinemia and three different forms of inherited lipoprotein dificiency were separately analyzed. For six of the eight pools, both methods provided a distinctive lipoprotein pattern in terms of changes in one or more variables. For the remaining two pools, type IV hyperlipoproteinemia and the heterozygote for Tangier disease, both methods provided identical but not unique patterns. The results indicate that lipoprotein analyses obtained by either method may be used interconvertibly in further genetic and other clinical studies.

摘要

目前用于识别不同类型家族性脂蛋白异常血症的八种血浆脂蛋白模式已通过两种方法进行了比较。第一种方法(美国国立卫生研究院方法)基于在白蛋白缓冲液中进行纸上电泳得到的四种脂蛋白类别的纸上电泳图谱,同时测量其中三种脂蛋白类别的总胆固醇,并确定β迁移脂蛋白的异常漂浮情况。第二种方法(唐纳方法)基于在分析超速离心机中获得的脂蛋白模式,该模式经过计算机分析调整,并通过化学测定乳糜微粒(沉降系数S(f)>400的脂蛋白)的浓度进行补充。分别对代表五种家族性高脂蛋白血症患者和三种不同形式遗传性脂蛋白缺乏症患者的混合样本进行了分析。在八个混合样本中的六个样本中,两种方法在一个或多个变量的变化方面都提供了独特的脂蛋白模式。对于其余两个样本,即IV型高脂蛋白血症和丹吉尔病杂合子样本,两种方法提供了相同但并非独特的模式。结果表明,通过这两种方法获得的脂蛋白分析结果在进一步的遗传学和其他临床研究中可以相互转换使用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aa65/297410/dbfba4eb90d6/jcinvest00246-0042-a.jpg

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