BACKGROUND: Systemic biomarkers provide insights into disease pathogenesis, diagnosis, and risk stratification. Many systemic biomarker concentrations are heritable phenotypes. Genome-wide association studies (GWAS) provide mechanisms to investigate the genetic contributions to biomarker variability unconstrained by current knowledge of physiological relations. METHODS: We examined the association of Affymetrix 100K GeneChip single nucleotide polymorphisms (SNPs) to 22 systemic biomarker concentrations in 4 biological domains: inflammation/oxidative stress; natriuretic peptides; liver function; and vitamins. Related members of the Framingham Offspring cohort (n = 1012; mean age 59 +/- 10 years, 51% women) had both phenotype and genotype data (minimum-maximum per phenotype n = 507-1008). We used Generalized Estimating Equations (GEE), Family Based Association Tests (FBAT) and variance components linkage to relate SNPs to multivariable-adjusted biomarker residuals. Autosomal SNPs (n = 70,987) meeting the following criteria were studied: minor allele frequency > or = 10%, call rate > or = 80% and Hardy-Weinberg equilibrium p > or = 0.001. RESULTS: With GEE, 58 SNPs had p < 10(-6): the top SNPs were rs2494250 (p = 1.0010(-14)) and rs4128725 (p = 3.6810(-12)) for monocyte chemoattractant protein-1 (MCP1), and rs2794520 (p = 2.8310(-8)) and rs2808629 (p = 3.1910(-8)) for C-reactive protein (CRP) averaged from 3 examinations (over about 20 years). With FBAT, 11 SNPs had p < 10(-6): the top SNPs were the same for MCP1 (rs4128725, p = 3.2810(-8), and rs2494250, p = 3.5510(-8)), and also included B-type natriuretic peptide (rs437021, p = 1.0110(-6)) and Vitamin K percent undercarboxylated osteocalcin (rs2052028, p = 1.0710(-6)). The peak LOD (logarithm of the odds) scores were for MCP1 (4.38, chromosome 1) and CRP (3.28, chromosome 1; previously described) concentrations; of note the 1.5 support interval included the MCP1 and CRP SNPs reported above (GEE model). Previous candidate SNP associations with circulating CRP concentrations were replicated at p < 0.05; the SNPs rs2794520 and rs2808629 are in linkage disequilibrium with previously reported SNPs. GEE, FBAT and linkage results are posted at http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007 webcite. CONCLUSION: The Framingham GWAS represents a resource to describe potentially novel genetic influences on systemic biomarker variability. The newly described associations will need to be replicated in other studies.