Functional Variant in the GCKR Gene Affects Lactate Levels Differentially in the Fasting State and During Hyperglycemia

Integrated transcriptomics and metabolomics analysis reveals the biomolecular mechanisms associated to the antitumoral potential of a novel silver-based core@shell nanosystem

A combination of omics techniques (transcriptomics and metabolomics) has been used to elucidate the mechanisms responsible for the antitumor action of a nanosystem based on a Ag core coated with mesoporous silica on which transferrin has been anchored as a targeting ligand against tumor cells (Ag@MSNs-Tf). Transcriptomics analysis has been carried out by gene microarrays and RT-qPCR, while high-resolution mass spectrometry has been used for metabolomics. This multi-omics strategy has enabled the discovery of the effect of this nanosystem on different key molecular pathways including the glycolysis, the pentose phosphate pathway, the oxidative phosphorylation and the synthesis of fatty acids, among others.

Genetic Pathways in Nonalcoholic Fatty Liver Disease: Insights From Systems Biology

Nonalcoholic fatty liver disease (NAFLD) represents a burgeoning worldwide epidemic whose etiology reflects multiple interactions between environmental and genetic factors. Here, we review the major pathways and dominant genetic modifiers known to be relevant players in human NAFLD and which may determine key components of the heritability of distinctive disease traits including steatosis and fibrosis. In addition, we have employed general assumptions which are based on known genetic factors in NAFLD to build a systems biology prediction model that includes functional enrichment. This prediction model highlights additional complementary pathways that represent plausible intersecting signaling networks that we define here as an NAFLD-Reactome. We review the evidence connecting variants in each of the major known genetic modifiers (variants in patatin-like phospholipase domain containing 3, transmembrane 6 superfamily member 2, membrane-bound O-acyltransferase domain containing 7, glucokinase regulator, and hydroxysteroid 17-beta dehydrogenase 13) to NAFLD and expand the associated underlying mechanisms using functional enrichment predictions, based on both preclinical and cell-based experimental findings. These major candidate gene variants function in distinct pathways, including substrate delivery for de novo lipogenesis; mitochondrial energy use; lipid droplet assembly, lipolytic catabolism, and fatty acid compartmentalization; and very low-density lipoprotein assembly and secretion. The NAFLD-Reactome model expands these pathways and allows for hypothesis testing, as well as serving as a discovery platform for druggable targets across multiple pathways that promote NAFLD development and influence several progressive outcomes. In conclusion, we summarize the strengths and weaknesses of studies implicating selected variants in the pathophysiology of NAFLD and highlight opportunities for future clinical research and pharmacologic intervention, as well as the implications for clinical practice.

Genetics of Non-Alcoholic Fatty Liver and Cardiovascular Disease: Implications for Therapy?

Non-alcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease worldwide. The most common cause of mortality in NAFLD is cardiovascular disease (CVD), and a key of focus in drug development is to discover therapies that target both liver injury and CVD risk. NAFLD and CVD are complex disease spectra with complex heritability patterns. Nevertheless, genome wide association studies and meta-analyses of these have identified genetic loci that are associated with increased risk of relevant pathological features of disease or clinical endpoints. This review focuses on the genetic risk loci identified in the NAFLD spectrum and asks whether any of these are also risk factors for CVD. Surprisingly, given the shared co-morbidities and risk factors, little robust evidence exists that NAFLD and CVD share genetic risk. Despite this, therapeutic intervention that targets both liver disease and CVD remains an important clinical need and a major focus for pharmaceutical development.

Association between lncRNA and GCKR gene in type 2 diabetes mellitus

OBJECTIVE

To screen long non-coding RNA (lncRNA) related to glucokinase regulatory protein gene (GCKR), its differential expression was analyzed in patients with Type 2 diabetes mellitus (T2DM) and control samples. The correlation of lncRNA with GCKR was verified and its potential value as a molecular marker of T2DM was assessed.

METHODS

Lymphocyte RNA was extracted from five patients with T2DM and five patients with non-T2DM. The expression profiles of circulating lncRNAs and mRNAs were obtained by microarray. Bioinformatics analysis was used to screen lncRNAs associated with the GCKR gene in 127 patients with T2DM and 130 patients with non-T2DM were selected. The expression levels of the GCKR gene and lncRNA (ENST00000588707.1 and TCONS_00004187) in the T2DM group and control group were verified by real-time PCR. Additionally, a correlation analysis was conducted. The value of circulating ENST00000588707.1 and TCONS_00004187 as biomarkers for the diagnosis of T2DM was performed by receiver operating characteristic curve analysis.

RESULTS

We identified 68 lncRNAs and 74 mRNAs differentially expressed from the expression profile. Compared with the control group, the expression levels of the GCKR gene and lncRNA ENST00000588707.1 and TCONS_00004187 in the T2DM group were significantly lower (P < 0.05). The correlation analysis revealed that ENST00000588707.1 and TCONS_00004187 were correlated with GCKR gene expression and glycolipid metabolism (P < 0.05). ROC analysis showed that the area under the curve value of ENST00000588707.1 between T2DM patients and non-T2DM patients was 0.816 (95% CI: 0.764-0.869, sensitivity 72.0%, specificity 80.3%) and the AUC value of TCONS_00004187 was 0.826 (95% CI: 0.774-0.879, sensitivity 81.6%, specificity 61.3%).

CONCLUSION

lncRNA ENST0000588707.1 and TCONS_00004187 could serve as potential biomarkers for T2DM, which could involve in glycolipid metabolism by regulating the GCKR gene.