Our finally selection of SNPs was made based on the Holm-Bonferroni results and the differences in metabolomics profile. This double criterion further restricts our results to meaningful genotypes associated to differential expression of UAE. The metabolomic profiles of patients with and without microalbuminuria were compared. Among all the metabolites measured, those with the highest contribution to the PLS-DA discrimination model were selected for further analysis. We explored the association between a metabolic profile and genetic variants using these selected metabolites. The PCA scores plot shows that most of the samples in the study are tightly clustered in a small area, indicating that the current protocol is reliable and thereby the variance derived from metabolomic analysis can be ignored at the following data analysis. Then, partial least squares discriminant analysis was applied. The PLS-DA model showed goodness of fit, adequate model predictability, and fairly good capability to explain the metabolic variation between normoalbuminurics and those with microalbuminuria. 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 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.