Genomic and Metabolomic Profile Associated to Clustering of Cardio-Metabolic Risk Factors

Abstract

BackgroundTo identify metabolomic and genomic markers associated with the presence of clustering of cardiometabolic risk factors (CMRFs) from a general population.Methods and FindingsOne thousand five hundred and two subjects, Caucasian, > 18 years, representative of the general population, were included. Blood pressure measurement, anthropometric parameters and metabolic markers were measured. Subjects were grouped according the number of CMRFs (Group 1: <2; Group 2: 2; Group 3: 3 or more CMRFs). Using SNPlex, 1251 SNPs potentially associated to clustering of three or more CMRFs were analyzed. Serum metabolomic profile was assessed by 1H NMR spectra using a Brucker Advance DRX 600 spectrometer. From the total population, 1217 (mean age 54±19, 50.6% men) with high genotyping call rate were analysed. A differential metabolomic profile, which included products from mitochondrial metabolism, extra mitochondrial metabolism, branched amino acids and fatty acid signals were observed among the three groups. The comparison of metabolomic patterns between subjects of Groups 1 to 3 for each of the genotypes associated to those subjects with three or more CMRFs revealed two SNPs, the rs174577_AA of FADS2 gene and the rs3803_TT of GATA2 transcription factor gene, with minimal or no statistically significant differences. Subjects with and without three or more CMRFs who shared the same genotype and metabolomic profile differed in the pattern of CMRFS cluster. Subjects of Group 3 and the AA genotype of the rs174577 had a lower prevalence of hypertension compared to the CC and CT genotype. In contrast, subjects of Group 3 and the TT genotype of the rs3803 polymorphism had a lower prevalence of T2DM, although they were predominantly males and had higher values of plasma creatinine.ConclusionsThe results of the present study add information to the metabolomics profile and to the potential impact of genetic factors on the variants of clustering of cardiometabolic risk factors.

The Future of “Omics” in Hypertension

“…Other rodent studies used systems biology approaches to place proteomic data into larger disease pathways, identifying dysregulated networks and predicting further targets from such analyses 46, 47. In human hypertension, 2 recent studies by Marrachelli et al 48, 49. combined metabolomic and genomic data to study factors associated with microalbuminuria and a range of cardiometabolic risk factors.…”

“… 46 , 47 In human hypertension, 2 recent studies by Marrachelli et al. 48 , 49 combined metabolomic and genomic data to study factors associated with microalbuminuria and a range of cardiometabolic risk factors. The previously mentioned article by Shahin et al.…”

Clinical and lifestyle related factors influencing whole blood metabolite levels – A comparative analysis of three large cohorts

“…Second, previously applied covariates in metabolome association studies were included. The most frequently considered factors were age, sex, log-BMI, smoking status [6], [12], [13], [14], [15], [16], and, to a lesser extent, type-2-diabetes (T2D) and application of sex hormones [6], [7], [15], [17].…”

Cohort profile: the Hortega Study for the evaluation of non-traditional risk factors of cardiometabolic and other chronic diseases in a general population from Spain

“…The phase III Hortega Examination visit has generated numerous cross-sectional studies of traditional (including diabetes,15 hypertension16 and dyslipidaemia17) and non-traditional (genetic,15 17–20 metabolomics21 22 and environmental23–27) cardiovascular risk factors. The follow-up data from the Hortega Study will allow to conduct time to event survival analysis and other prospective studies which will provide novel evidence on the potential role of genetic, environmental and metabolomic factors in the pathogenesis of chronic disease, mainly cardiovascular, but also other such as cancer, and bone disease.…”