Strong effects of genetic and lifestyle factors on biomarker variation and use of personalized cutoffs

被引：137

作者：

Enroth, Stefan ^{[1
]}

Johansson, Asa ^{[1
,2
]}

Enroth, Sofia Bosdotter ^{[3
]}

Gyllensten, Ulf ^{[1
]}

机构：

[1] Uppsala Univ, SciLifeLab Uppsala, Biomed Ctr, Dept Immunol Genet & Pathol, SE-75108 Uppsala, Sweden

[2] Uppsala Clin Res Ctr, SE-75237 Uppsala, Sweden

[3] Uppsala Univ, Dept Med Sci, SE-75185 Uppsala, Sweden

来源：

NATURE COMMUNICATIONS | 2014年 / 5卷

基金：

英国医学研究理事会;

关键词：

GENOME-WIDE ASSOCIATION; SOLUBLE E-SELECTIN; RISK LOCI; CANCER; VARIANTS; DISEASE; LYMPHANGIOGENESIS; INFORMATION; EXPRESSION; LINKAGE;

D O I：

10.1038/ncomms5684

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

070301 [无机化学]; 070403 [天体物理学]; 070507 [自然资源与国土空间规划学]; 090105 [作物生产系统与生态工程];

摘要：

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 x 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.

引用

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