Physical Activity Levels and Measures of High-Sensitivity C-reactive Protein in Apparently Healthy Male Firefighters

Heart attack or stroke is the number one cause of on-duty death in firefighters. High-sensitivity C-reactive protein (hs-CRP) is a nontraditional risk factor that has been linked to increased risk of future cardiac events. Purpose: The purpose of this study was to determine if physically active firefighters are less likely to have elevated levels of high-sensitivity C-reactive protein (hs-CRP) than sedentary firefighters. Methods: Self-Reported Physical Activity was determined using the International Physical Activity Questionnaire (IPAQ) in 62 male firefighters from Central Texas. Descriptive measures and blood lipid and metabolic measures were taken to determine cardiovascular risk. After participants were screened for exclusion criteria, a total number of 60 (N=60) firefighters completed the experiment process. The firefighters completed the IPAQ and where placed into two groups based on their score, physically active or sedentary. Participants’ anthropometric measurements (body mass index, body composition), blood pressure, hs-CRP and cholesterol levels were measured. Venous blood samples were collected, centrifuged, and sent to an off-site facility for lipid, glucose, and hs-CRP testing. In addition, each firefighter was asked the total number of years involved in the occupation, and approximate number of fires they have worked. A two-way ANOVA with age as a covariate, was used to detect differences in active and inactive firefighters. Pearson product-moment correlations coefficient were used to determine relationships between activity level, cardiac risk and hs-CRP. Significant markers from the ANOVA and correlation coefficients were used to develop a regression equation to predict hs-CRP. Results: There was a significant difference in the number of MET*minutes/wk between volunteer (VT) and career (CT) firefighters (VT: 1927 ± 1369, CT: 2727 ± 1284). This study also determined that hs-CRP risk scores were not correlated to traditional cardiovascular risk factors including total cholesterol (r= 0.014, p= 0.916), LDL-Cholesterol (r= 0.095, p= 0.480), HDL-Cholesterol (r= 0.140, p= 0.295), glucose (r= 0.082, p= 0.540), age (r= 0.021, p= 0.876), and Framingham risk score (FRS)-TC (r= 0.061, p= 0.295). For fire departments that do not have the financial means to pay for hs-CRP testing for all their firefighters, we have devised a regression formula, using significant correlations, to estimate hs-CRP levels. The formula below uses SBP, activity level, weight, body fat percent and waist circumference to estimate hs-CRP (hs-CRP = -2.907 + 0.015(SBP) – 0.487(Act) + 0.032(Wt kg) + 0.048(BF%) – 0.010 (Waist cm). Conclusion: Both FRS and hs-CRP risk levels should be used when evaluating risk of CVD in firefighters, and an exercise prescription should be recommended to those firefighters with increased CVD risk

e-GRASP: an integrated evolutionary and GRASP resource for exploring disease associations

Abstract Background Genome-wide association studies (GWAS) have become a mainstay of biological research concerned with discovering genetic variation linked to phenotypic traits and diseases. Both discrete and continuous traits can be analyzed in GWAS to discover associations between single nucleotide polymorphisms (SNPs) and traits of interest. Associations are typically determined by estimating the significance of the statistical relationship between genetic loci and the given trait. However, the prioritization of bona fide, reproducible genetic associations from GWAS results remains a central challenge in identifying genomic loci underlying common complex diseases. Evolutionary-aware meta-analysis of the growing GWAS literature is one way to address this challenge and to advance from association to causation in the discovery of genotype-phenotype relationships. Description We have created an evolutionary GWAS resource to enable in-depth query and exploration of published GWAS results. This resource uses the publically available GWAS results annotated in the GRASP2 database. The GRASP2 database includes results from 2082 studies, 177 broad phenotype categories, and ~8.87 million SNP-phenotype associations. For each SNP in e-GRASP, we present information from the GRASP2 database for convenience as well as evolutionary information (e.g., rate and timespan). Users can, therefore, identify not only SNPs with highly significant phenotype-association P-values, but also SNPs that are highly replicated and/or occur at evolutionarily conserved sites that are likely to be functionally important. Additionally, we provide an evolutionary-adjusted SNP association ranking (E-rank) that uses cross-species evolutionary conservation scores and population allele frequencies to transform P-values in an effort to enhance the discovery of SNPs with a greater probability of biologically meaningful disease associations. Conclusion By adding an evolutionary dimension to the GWAS results available in the GRASP2 database, our e-GRASP resource will enable a more effective exploration of SNPs not only by the statistical significance of trait associations, but also by the number of studies in which associations have been replicated, and the evolutionary context of the associated mutations. Therefore, e-GRASP will be a valuable resource for aiding researchers in the identification of bona fide, reproducible genetic associations from GWAS results. This resource is freely available at http://www.mypeg.info/egrasp