Graphical abstract

No abstract

The need to facilitate the complex management of cardiometabolic diseases (CMD) has led to the detection of many biomarkers, however, there are no clear explanations of their role in the prevention, diagnosis or prognosis of these diseases. Molecules associated with disease pathways represent valid disease surrogates and well-fitted CMD biomarkers. To address this challenge, data from multi-omics types (genomics, epigenomics, transcriptomics, proteomics, metabolomics, microbiomics, and nutrigenomics), from human and animal models, have become available. However, individual omics types only provide data on a small part of molecules involved in the complex CMD mechanisms, whereas, here, we propose that their integration leads to multidimensional data. Such data provide a better understanding of molecules related to CMD mechanisms and, consequently, increase the possibility of identifying well-fitted biomarkers. In addition, the application of gender medicine also helps to identify accurate biomarkers according to gender, facilitating a differential CMD management. Accordingly, the impact of gender differences in CMD pathophysiology has been widely demonstrated, where gender is referred to the complex interrelation and integration of sex (as a biological and functional marker of the human body) and psychological and cultural behavior (due to ethnical, social, and religious background). In this review, all these aspects are described and discussed, as well as potential limitations and future directions in this incipient field.

Background: Congenital heart defects (CHDs) are present in about 40–60% of newborns with Down syndrome (DS). Patients with DS can also develop acquired cardiac disorders. Mouse models suggest that a critical 3.7 Mb region located on human chromosome 21 (HSA21) could explain the association with CHDs. This region includes a cluster of genes (IFNAR1, IFNAR2, IFNGR2, IL10RB) encoding for interferon receptors (IFN-Rs). Other genes located on different chromosomes, such as the vascular endothelial growth factor A (VEGFA), have been shown to be involved in cardiac defects. So, we investigated the association between single nucleotide polymorphisms (SNPs) in IFNAR2, IFNGR2, IL10RB and VEGFA genes, and the presence of CHDs or acquired cardiac defects in patients with DS. Methods: Individuals (n = 102) with DS, and age- and gender-matched controls (n = 96), were genotyped for four SNPs (rs2229207, rs2834213, rs2834167 and rs3025039) using KASPar assays. Results: We found that the IFNGR2 rs2834213 G homozygous genotype and IL10RB rs2834167G-positive genotypes were more common in patients with DSand significantly associated with heart disorders, while VEGFA rs3025039T-positive genotypes (T/*) were less prevalent in patients with CHDs. Conclusions: We identified some candidate risk SNPs for CHDs and acquired heart defects in DS. Our data suggest that a complex architecture of risk alleles with interplay effects may contribute to the high variability of DS phenotypes.

Background: Previous studies have demonstrated that polymorphisms involved in immune genes can affect the risk, pathogenesis, and outcome of thoracic ascending aortic aneurysms (TAAA). Here, we explored the potential associations of five functional promoter polymorphisms in interleukin-6 (IL-6), IL-1B, IL-1A, IL-18, and Tumor necrosis factor (TNF)A genes with TAAA. Methods: 144 TAAA patients and 150 age/gender matched controls were typed using KASPar assays. Effects on telomere length and levels of TAAA related histopathological and serological markers were analyzed. Results: Significant associations with TAAA risk were obtained for IL-6 rs1800795G>C and IL-1B rs16944C>T SNPs. In addition, the combined rs1800795C/rs16944T genotype showed a synergic effect on TAAA pathogenesis and outcome. The combined rs1800795C/rs16944T genotype was significantly associated with: (a) higher serum levels of both cytokines and MMP-9 and -2; (b) a significant CD3+CD4+CD8+ CD68+CD20+ cell infiltration in aorta aneurysm tissues; (c) a significant shorter telomere length and alterations in telomerase activity. Finally, it significantly correlated with TAAA aorta tissue alterations, including elastic fragmentation, medial cell apoptosis, cystic medial changes, and MMP-9 levels. Conclusions: the combined rs1800795C/rs16944T genotype appears to modulate TAAA risk, pathogenesis, and outcome, and consequently can represent a potential predictive and prognostic TAAA biomarker for individual management, implementation of innovative treatments, and selection of the more proper surgical timing and approaches.