The Human Plasma Proteome

蛋白质组学 人血浆 蛋白质组 人类蛋白质组计划 血液蛋白质类 计算生物学 化学 白蛋白 生物信息学 生物 色谱法 生物化学 基因
作者
N. Leigh Anderson,Norman G. Anderson
出处
期刊:Molecular & Cellular Proteomics [Elsevier BV]
卷期号:1 (11): 845-867 被引量:4311
标识
DOI:10.1074/mcp.r200007-mcp200
摘要

The human plasma proteome holds the promise of a revolution in disease diagnosis and therapeutic monitoring provided that major challenges in proteomics and related disciplines can be addressed. Plasma is not only the primary clinical specimen but also represents the largest and deepest version of the human proteome present in any sample: in addition to the classical "plasma proteins," it contains all tissue proteins (as leakage markers) plus very numerous distinct immunoglobulin sequences, and it has an extraordinary dynamic range in that more than 10 orders of magnitude in concentration separate albumin and the rarest proteins now measured clinically. Although the restricted dynamic range of conventional proteomic technology (two-dimensional gels and mass spectrometry) has limited its contribution to the list of 289 proteins (tabulated here) that have been reported in plasma to date, very recent advances in multidimensional survey techniques promise at least double this number in the near future. Abundant scientific evidence, from proteomics and other disciplines, suggests that among these are proteins whose abundances and structures change in ways indicative of many, if not most, human diseases. Nevertheless, only a handful of proteins are currently used in routine clinical diagnosis, and the rate of introduction of new protein tests approved by the United States Food and Drug Administration (FDA) has paradoxically declined over the last decade to less than one new protein diagnostic marker per year. We speculate on the reasons behind this large discrepancy between the expectations arising from proteomics and the realities of clinical diagnostics and suggest approaches by which protein-disease associations may be more effectively translated into diagnostic tools in the future.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
subohr发布了新的文献求助10
1秒前
zz发布了新的文献求助10
2秒前
bbbbbhhhhh关注了科研通微信公众号
2秒前
云间宿完成签到 ,获得积分10
2秒前
2秒前
2秒前
3秒前
3秒前
南风完成签到,获得积分10
4秒前
老刘爱吃饭完成签到,获得积分10
4秒前
我是老大应助冷静的牛青采纳,获得10
5秒前
赘婿应助和谐楼房采纳,获得10
6秒前
roselau发布了新的文献求助10
6秒前
DDDDD完成签到,获得积分10
6秒前
7秒前
顾矜应助genius采纳,获得30
7秒前
现实的傲珊完成签到,获得积分10
8秒前
kazuma完成签到,获得积分10
8秒前
9秒前
9秒前
9秒前
9秒前
10秒前
10秒前
mzz完成签到,获得积分10
10秒前
11秒前
12秒前
乐超多发布了新的文献求助10
13秒前
和谐楼房完成签到,获得积分20
13秒前
sxw发布了新的文献求助10
13秒前
13秒前
14秒前
dxt发布了新的文献求助10
14秒前
rainyoun完成签到 ,获得积分10
14秒前
14秒前
不想学习应助THE采纳,获得10
15秒前
bbbbbhhhhh发布了新的文献求助10
15秒前
15秒前
16秒前
鲤鱼诗桃发布了新的文献求助30
16秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Principles of town planning: translating concepts to applications 1000
2016 Venous Blood Study (VBS) (Final V3.0) 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
核安全综合知识2024版 500
Photothermal Science and Techniques 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7704006
求助须知:如何正确求助?哪些是违规求助? 9262103
关于积分的说明 20035331
捐赠科研通 7279457
什么是DOI,文献DOI怎么找? 3294708
关于科研通互助平台的介绍 2449927
邀请新用户注册赠送积分活动 2301486