Strong effects of genetic and lifestyle factors on biomarker variation and use of personalized cutoffs.
Strong effects of genetic and lifestyle factors on biomarker variation and use of personalized cutoffs.
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DOI：
10.1038/ncomms5684
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发表时间：
2014-08-22
影响因子：
16.6
通讯作者：
Gyllensten, Ulf
中科院分区：
文献类型：
--
作者：
Enroth, Stefan;Johansson, Asa;Enroth, Sofia Bosdotter;Gyllensten, Ulf
用于疾病诊断的理想生物标志物应该仅显示受影响个体的偏离水平，并且对与疾病无关的因素具有稳稳性。在这里，我们展示了遗传、临床和生活方式因素对92种癌症和炎症蛋白生物标志物循环水平的影响，使用了1005个基于人群的队列。对于75%的生物标记物，其水平具有显著的遗传性，全基因组关联研究鉴定出16个新的位点，并复制了2个先前已知的位点，它们对一种或几种生物标记物有很强的影响，p值低至4.4 × 10−58。综合分析将56.3%的观察到的差异归因于非疾病因素。我们建议，应该利用主要遗传、临床和生活方式因素的生物标志物特异性信息来建立个性化的临床截止点，这将提高使用生物标志物预测临床终点的敏感性。蛋白质生物标志物可以在疾病的诊断和管理中发挥重要作用。在这里，作者研究了遗传、临床和生活方式因素对92种癌症和炎症蛋白质生物标志物的影响，并建议在癌症管理中应使用个性化的生物标志物阈值。
Ideal biomarkers used for disease diagnosis should display deviating levels in affected individuals only and be robust to factors unrelated to the disease. Here we show the impact of genetic, clinical and lifestyle factors on circulating levels of 92 protein biomarkers for cancer and inflammation, using a population-based cohort of 1,005 individuals. For 75% of the biomarkers, the levels are significantly heritable and genome-wide association studies identifies 16 novel loci and replicate 2 previously known loci with strong effects on one or several of the biomarkers with P-values down to 4.4 × 10−58. Integrative analysis attributes as much as 56.3% of the observed variance to non-disease factors. We propose that information on the biomarker-specific profile of major genetic, clinical and lifestyle factors should be used to establish personalized clinical cutoffs, and that this would increase the sensitivity of using biomarkers for prediction of clinical end points. Protein biomarkers could play an important role in the diagnosis and management of diseases. Here the authors investigate the impact of genetic, clinical and lifestyle factors on 92 protein biomarkers for cancer and inflammation and suggest that personalized biomarker thresholds should be used in cancer management.
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影响因子：
3.5
作者：
Besingi, Welisane;Johansson, Asa
通讯作者：
Johansson, Asa
DOI：
10.1002/ar.21096
发表时间：
2010-05-01
影响因子：
2
作者：
Feng, Yukuan;Wang, Wei;Zhang, Jianguo
通讯作者：
Zhang, Jianguo
影响因子：
9.8
作者：
Chen, Wei-Min;Abecasis, Goncalo R.
通讯作者：
Abecasis, Goncalo R.
DOI：
10.1080/00365510701297480
发表时间：
2007-01-01
影响因子：
2.1
作者：
Gao, Y. -C.;Yuan, Z. -B.;Lu, H. -K.
通讯作者：
Lu, H. -K.
影响因子：
--
作者：
Bolstad, Nils;Oijordsbakken, Miriam;Nustad, Kjell;Bjerner, Johan
通讯作者：
Bjerner, Johan