title: Strong effects of genetic and lifestyle factors on biomarker variation and use of personalized cutoffs.
abstract: 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.
authors.affiliation: Department of Immunology, Genetics, and Pathology, Biomedical Center, SciLifeLab Uppsala, Uppsala University, SE-75108 Uppsala, Sweden.
authors.forename: Stefan
authors.initials: S
authors.lastname: Enroth
authors.affiliation: 1] Department of Immunology, Genetics, and Pathology, Biomedical Center, SciLifeLab Uppsala, Uppsala University, SE-75108 Uppsala, Sweden [2] Uppsala Clinical Research Centre, Uppsala University, SE-75237 Uppsala, Sweden.
authors.forename: Asa
authors.initials: A
authors.lastname: Johansson
authors.affiliation: Department of Medical Sciences, Uppsala University, SE-75185 Uppsala, Sweden.
authors.forename: Sofia Bosdotter
authors.initials: SB
authors.lastname: Enroth
authors.affiliation: Department of Immunology, Genetics, and Pathology, Biomedical Center, SciLifeLab Uppsala, Uppsala University, SE-75108 Uppsala, Sweden.
authors.forename: Ulf
authors.initials: U
authors.lastname: Gyllensten
mesh_terms: D015415:Biomarkers / Q000032:analysis* / Q000097:blood; D014408:Biomarkers, Tumor / Q000032:analysis* / Q000235:genetics; D015331:Cohort Studies; D005260:Female; D055106:Genome-Wide Association Study; D006801:Humans; D007249:Inflammation / Q000378:metabolism; D008019:Life Style; D008297:Male; D020641:Polymorphism, Single Nucleotide; D012016:Reference Values; D013548:Sweden / Q000453:epidemiology
chemical_list: D015415:Biomarkers; D014408:Biomarkers, Tumor