After spectral integration, differences were observed among subjects with and without microalbuminuria. As shown in Table 3, the differential endogenous compounds detected included mitochondrial metabolism, extra mitochondrial BMS-763534 metabolism and several amino acids and their derivative signals. Among these, branched amino acids exhibited a relatively high statistical significance. We also detected numerous fatty acid signals,, as well as signals from cholesterol, choline and phosphocholine, aminobutyrate, dimetylamine, trimethylamine, and albumin. In the present study, we identified a metabolomic profile associated to the presence of microalbuminuria, characterized by an increment in some mitochondrial and extra-mitochondrial metabolism derivate metabolites and fatty acid signals, as well as a decrease in branched amino acids. This microalbuminuric metabolomic profile was also present in normoalbuminuric subjects who share the genotype of two SNPs on the ACE-I and the RPH3A genes. We hypothesize that with the same metabolomic environment, individuals sharing the TT genotype of the rs10492025 polymorphism seems to have a higher risk, and those with the CC genotype of the rs4359 polymorphism partially protected from the development of microalbuminuria in the presence of hypertension and or diabetes. The study was performed in subjects representative of the general population from an area with a low rate of external admission. In this population, the prevalence of microalbuminuria was in agreement with other population-based studies. Microalbuminuria, was associated to the presence of diabetes and/or hypertension. In the present population and BIBP 3226 independent of these clinical conditions, the increment of UAE was weakly associated to genotypes of SNPs located in the chromosomes 11, 12 and 16, replicating previous studies. These SNPs were located in genes such as G protein beta polypeptide 3, ACEI and RPH3A, associated previously to UAE and to metabolic pathways not previously associated with UAE. However, the degree of association was not high enough to be considered as a positive association per se. Then we used the data from the metabolomic study to gain further insight into the potential relationship between genotypes and microalbuminuria. A characteristic metabolomic profile associated to microalbuminuria was identified by using a multivariate model, which allows for discrimination between normoalbuminuric and microalbuminuric individuals.