Gene expression in peripheral blood of patients with hypertension and patients with type 2 diabetes

Molecular mechanisms and potential therapeutic targets in the pathogenesis of hypertension in visceral adipose tissue induced by a high-fat diet

Background

Hypertension (HTN) presents a significant global public health challenge with diverse causative factors. The accumulation of visceral adipose tissue (VAT) due to a high-fat diet (HFD) is an independent risk factor for HTN. While various studies have explored pathogenic mechanisms, a comprehensive understanding of impact of VAT on blood pressure necessitates bioinformatics analysis.

Methods

Datasets GSE214618 and GSE188336 were acquired from the Gene Expression Omnibus and analyzed to identify shared differentially expressed genes between HFD-VAT and HTN-VAT. Gene Ontology enrichment and protein-protein interaction analyses were conducted, leading to the identification of hub genes. We performed molecular validation of hub genes using RT-qPCR, Western-blotting and immunofluorescence staining. Furthermore, immune infiltration analysis using CIBERSORTx was performed.

Results

This study indicated that the predominant characteristic of VAT in HTN was related to energy metabolism. The red functional module was enriched in pathways associated with mitochondrial oxidative respiration and ATP metabolism processes. Spp1, Postn, and Gpnmb in VAT were identified as hub genes on the pathogenic mechanism of HTN. Proteins encoded by these hub genes were closely associated with the target organs-specifically, the resistance artery, aorta, and heart tissue. After treatment with empagliflozin, there was a tendency for Spp1, Postn, and Gpnmb to decrease in VAT. Immune infiltration analysis confirmed that inflammation and immune response may not be the main mechanisms by which visceral adiposity contributes to HTN.

Conclusions

Our study pinpointed the crucial causative factor of HTN in VAT following HFD. Spp1, Postn, and Gpnmb in VAT acted as hub genes that promote elevated blood pressure and can be targets for HTN treatment. These findings contributed to therapeutic strategies and prognostic markers for HTN.

The CEBPA-FGF21 regulatory network may participate in the T2DM-induced skeletal muscle atrophy by regulating the autophagy-lysosomal pathway

AIMS

Recent years have witnessed an increasing research interest in the roles of transcription factor (TF)-gene regulatory network in type 2 diabetes mellitus (T2DM). Thus, we sought to characterize the mechanistic insights based on the TF-gene regulatory network in skeletal muscle atrophy in T2DM.

METHODS

Differentially expressed TFs (DETFs) and mRNAs (DEmRNAs) were obtained in T2DM-related gene expression profiles (GSE12643, GSE55650, GSE166502, and GSE29221), followed by WGCNA, and GO and KEGG enrichment analyses. Next, the iRegulon plug-in unit of Cytoscape software was used to construct a TF-mRNA regulatory network. Besides, RT-qPCR and ChIP-seq were utilized to measure the expression of CEBPA and FGF21 in the skeletal muscle tissues or cells of T2DM rat models. At last, the effect of overexpression of FGF21 on the autophagy-lysosomal pathway was examined in skeletal muscle cells of T2DM rats.

RESULTS

Totally, 12 DETFs and 102 DEmRNAs were found in the skeletal muscle tissues of T2DM samples. The DEmRNAs were mainly enriched in the autophagy-lysosomal pathway. CEBPA affected the skeletal muscle atrophy in T2DM by regulating 5 target genes via the autophagy-lysosomal pathway. CEBPA could target FGF21. In addition, the expression of CEBPA was elevated, while the expression of FGF21 was diminished in the skeletal muscle tissues or cells of T2DM rats. The CEBPA-FGF21 regulatory network promoted skeletal muscle atrophy in T2DM by activating the autophagy-lysosomal pathway.

CONCLUSION

The CEBPA-FGF21 regulatory network may participate in the T2DM-induced skeletal muscle atrophy by regulating the autophagy-lysosomal pathway. Thus, our study provides interesting targets for prevention of skeletal muscle atrophy in T2DM.

Statistical Bioinformatics to Uncover the Underlying Biological Mechanisms That Linked Smoking with Type 2 Diabetes Patients Using Transcritpomic and GWAS Analysis

Type 2 diabetes (T2D) is a chronic metabolic disease defined by insulin insensitivity corresponding to impaired insulin sensitivity, decreased insulin production, and eventually failure of beta cells in the pancreas. There is a 30–40 percent higher risk of developing T2D in active smokers. Moreover, T2D patients with active smoking may gradually develop many complications. However, there is still no significant research conducted to solve the issue. Hence, we have proposed a highthroughput network-based quantitative pipeline employing statistical methods. Transcriptomic and GWAS data were analysed and obtained from type 2 diabetes patients and active smokers. Differentially Expressed Genes (DEGs) resulted by comparing T2D patients’ and smokers’ tissue samples to those of healthy controls of gene expression transcriptomic datasets. We have found 55 dysregulated genes shared in people with type 2 diabetes and those who smoked, 27 of which were upregulated and 28 of which were downregulated. These identified DEGs were functionally annotated to reveal the involvement of cell-associated molecular pathways and GO terms. Moreover, protein–protein interaction analysis was conducted to discover hub proteins in the pathways. We have also identified transcriptional and post-transcriptional regulators associated with T2D and smoking. Moreover, we have analysed GWAS data and found 57 common biomarker genes between T2D and smokers. Then, Transcriptomic and GWAS analyses are compared for more robust outcomes and identified 1 significant common gene, 19 shared significant pathways and 12 shared significant GOs. Finally, we have discovered protein–drug interactions for our identified biomarkers.

An Integrative Network Approach to Identify Common Genes for the Therapeutics in Tuberculosis and Its Overlapping Non-Communicable Diseases

Tuberculosis (TB) is the leading cause of death from a single infectious agent. The estimated total global TB deaths in 2019 were 1.4 million. The decline in TB incidence rate is very slow, while the burden of noncommunicable diseases (NCDs) is exponentially increasing in low- and middle-income countries, where the prevention and treatment of TB disease remains a great burden, and there is enough empirical evidence (scientific evidence) to justify a greater research emphasis on the syndemic interaction between TB and NCDs. The current study was proposed to build a disease-gene network based on overlapping TB with NCDs (overlapping means genes involved in TB and other/s NCDs), such as Parkinson’s disease, cardiovascular disease, diabetes mellitus, rheumatoid arthritis, and lung cancer. We compared the TB-associated genes with genes of its overlapping NCDs to determine the gene-disease relationship. Next, we constructed the gene interaction network of disease-genes by integrating curated and experimentally validated interactions in humans and find the 13 highly clustered modules in the network, which contains a total of 86 hub genes that are commonly associated with TB and its overlapping NCDs, which are largely involved in the Inflammatory response, cellular response to cytokine stimulus, response to cytokine, cytokine-mediated signaling pathway, defense response, response to stress and immune system process. Moreover, the identified hub genes and their respective drugs were exploited to build a bipartite network that assists in deciphering the drug-target interaction, highlighting the influential roles of these drugs on apparently unrelated targets and pathways. Targeting these hub proteins by using drugs combination or drug repurposing approaches will improve the clinical conditions in comorbidity, enhance the potency of a few drugs, and give a synergistic effect with better outcomes. Thus, understanding the Mycobacterium tuberculosis (Mtb) infection and associated NCDs is a high priority to contain its short and long-term effects on human health. Our network-based analysis opens a new horizon for more personalized treatment, drug-repurposing opportunities, investigates new targets, multidrug treatment, and can uncover several side effects of unrelated drugs for TB and its overlapping NCDs.

Bioinformatic gene analysis for possible biomarkers and therapeutic targets of hypertension-related renal cell carcinoma

BACKGROUND

Renal cell carcinoma (RCC) is one of the most prevalent malignant tumors of the urinary system. Hypertension can cause hypertensive nephropathy (HN). Meanwhile, Hypertension is considered to be related to kidney cancer. We analyzed co-expressed genes to find out the relationship between hypertension and RCC and show possible biomarkers and novel therapeutic targets of hypertension-related RCC.

METHODS

We identified the differentially expressed genes (DEGs) of HN and RCC through analyzing Gene Expression Omnibus (GEO) datasets GSE99339, GSE99325, GSE53757 and GSE15641 by means of bioinformatics analysis, respectively. Then we evaluated these genes with protein-protein interaction (PPI) networks, Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and CTD database. Subsequently, we verified co-expressed DEGs with Gene Expression Profiling Interactive Analysis (GEPIA) database. Finally, corresponding predicted miRNAs of co-expressed DEGs were identified and verified via mirDIP database and Starbase, respectively.

RESULTS

We identified 9 co-expressed DEGs, including BCAT1, CORO1A, CRIP1, ESRRG, FN1, LYZ, PYCARD, SAP30, and PTRF. CRIP1 and ESRRG and their corresponding predicted miRNAs, especially hsa-miR-221-5p, hsa-miR-205-5p, hsa-miR-152-3p and hsa-miR-137 may be notably related to hypertension-related RCC.

CONCLUSIONS

CRIP1 and ESRRG genes have great potential to become novel biomarkers and therapeutic targets concerning hypertension-related RCC.

Identification of Hub Genes in Type 2 Diabetes Mellitus Using Bioinformatics Analysis

BACKGROUND

Type 2 diabetes mellitus (T2DM) is one of the most common chronic diseases in the world with complicated pathogenesis. This study aimed to identify differentially expressed genes (DEGs) and molecular pathways in T2DM using bioinformatics analysis.

MATERIALS AND METHODS

To explore potential therapeutic targets for T2DM, we analyzed three microarray datasets (GSE50397, GSE38642, and GSE44035) acquired from the Gene Expression Omnibus (GEO) database. DEGs between T2DM islet and normal islet were picked out by the GEO2R tool and Venn diagram software. Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) to identify the pathways and functional annotation of DEGs. Then, protein-protein interaction (PPI) of these DEGs was visualized by Cytoscape with Search Tool for the Retrieval of Interacting Genes/Proteins (STRING).

RESULTS

In total, we identified 36 DEGs in the three datasets, including 32 up-regulated genes and four down-regulated genes. The improved functions and pathways of the DEGs enriched in cytokine-cytokine receptor interaction, pathways in cancer, PI3K-Akt signaling pathway, and Rheumatoid arthritis. Among them, ten hub genes with a high degree of connectivity were selected. Furthermore, via the re-analysis of DAVID, four genes (IL6, MMP3, MMP1, and IL11) were significantly enriched in the Rheumatoid arthritis pathway.

CONCLUSION

Our study, based on the GEO database, identified four significant up-regulated DEGs and provided novel targets for diagnosis and treatment of T2DM.

Bioinformatic analysis reveals novel hub genes and pathways associated with hypertensive nephropathy

AIM

Hypertensive nephropathy (HTN) is one of the leading causes of end-stage renal disease and is closely associated with inflammation and tubule-interstitial fibrosis. The molecular mechanism underlying HTN remains unclear. This study used bioinformatic analysis to identify the novel gene targets for HTN.

METHODS

We downloaded the microarray data of GSE99325 and GSE32591 from Gene Expression Omnibus. The dataset comprised 20 HTN and 15 normal samples. The differentially expressed genes (DEG) were identified, and then gene ontology (GO) enrichment was performed, and a GO tree was constructed by using clusterProfiler and ClueGO. In addition, a protein-protein interaction network was established using the Search Tool for the Retrieval of Interacting Genes database and visualized by Cytoscape. The novel hub genes were validated in in vitro experiments.

RESULTS

A total of 267 genes (117 up-regulated and 150 down-regulated genes) were identified as DEG. GO analysis and the GO tree indicated that the DEG were mainly associated with steroid hormone response and the extracellular matrix. Based on the protein-protein interaction network, we screened out several novel hub genes. Considering the findings and the literature review, we focused on and validated the dual specificity phosphatase 1, tissue inhibitor of matrix metalloproteinases 1, fos proto-oncogene and jun proto-oncogenes, which may play significant roles in the pathogenesis of HTN. These findings were consistent with the bioinformatic results for the in vitro validation.

CONCLUSION

This study identified for the first time novel hub genes with microarray data in HTN by using bioinformatic analysis and provided novel evidence and clues for future works.

Screening genes associated with elevated neutrophil‑to‑lymphocyte ratio in chronic heart failure

Neutrophil‑to‑lymphocyte ratio (NLR) is commonly considered a useful prognostic index for many cardiovascular diseases; however, it has limited sensitivity and specificity. Factors associated with elevated NLR may aid in the prediction of prognosis with heart failure (HF) in combination with NLR. The present study sought to identify decisive factors associated with NLR in HF patients and investigate their association with elevated NLR. The gene expression profile for blood samples from 197 individuals with chronic heart failure (CHF), with corresponding hematological parameters and clinical data were obtained from the public database, GSE77343. Differentially expressed genes (DEGs) were identified, and Gene Ontology and pathway enrichment analyses were performed. The protein‑protein interaction network was constructed with the Search Tool for the Retrieval of Interacting Genes along with Cytoscape. Receiver operating characteristic curves for predictive power, sensitivity and specificity were constructed. The present study identified specific associated DEGs by using Pearson linear correlation and logistic regression analysis. A mean NLR of 3.96 was determined as the cutoff value in the analysis. In total, 31 genes were initially identified as DEGs associated with elevated NLR. They were mainly enriched in neutrophil activation and neutrophil mediated immunity, in fluid shear stress and atherosclerosis, and transcriptional misregulation in cancer. Three focused DEGs, solute carrier family 22 member 4 (SLC22A4), interleukin‑1 receptor 2 (IL1R2) and vanin 3 (VNN3), were finally revealed to be independently associated with elevated NLR in CHF patients. The present study demonstrated that the three genes SLC22A4, IL1R2 and VNN3 may be independently associated with elevated NLR in CHF patients as potential decisive factors of NLR.

A Large-Scale Multi-ancestry Genome-wide Study Accounting for Smoking Behavior Identifies Multiple Significant Loci for Blood Pressure

Genome-wide association analysis advanced understanding of blood pressure (BP), a major risk factor for vascular conditions such as coronary heart disease and stroke. Accounting for smoking behavior may help identify BP loci and extend our knowledge of its genetic architecture. We performed genome-wide association meta-analyses of systolic and diastolic BP incorporating gene-smoking interactions in 610,091 individuals. Stage 1 analysis examined ∼18.8 million SNPs and small insertion/deletion variants in 129,913 individuals from four ancestries (European, African, Asian, and Hispanic) with follow-up analysis of promising variants in 480,178 additional individuals from five ancestries. We identified 15 loci that were genome-wide significant (p < 5 × 10-8) in stage 1 and formally replicated in stage 2. A combined stage 1 and 2 meta-analysis identified 66 additional genome-wide significant loci (13, 35, and 18 loci in European, African, and trans-ancestry, respectively). A total of 56 known BP loci were also identified by our results (p < 5 × 10-8). Of the newly identified loci, ten showed significant interaction with smoking status, but none of them were replicated in stage 2. Several loci were identified in African ancestry, highlighting the importance of genetic studies in diverse populations. The identified loci show strong evidence for regulatory features and support shared pathophysiology with cardiometabolic and addiction traits. They also highlight a role in BP regulation for biological candidates such as modulators of vascular structure and function (CDKN1B, BCAR1-CFDP1, PXDN, EEA1), ciliopathies (SDCCAG8, RPGRIP1L), telomere maintenance (TNKS, PINX1, AKTIP), and central dopaminergic signaling (MSRA, EBF2).

Genetic variants of increased waist circumference in psychosis

We examined whether established metabolic risk genetic variants in the population confer a risk for increased waist circumference in patients with schizophrenia spectrum disorders and also an association with schizophrenia spectrum disorders irrespective of waist circumference.

Identification of novel alleles associated with insulin resistance in childhood obesity using pooled-DNA genome-wide association study approach

Background:

Recently, we witnessed great progress in the discovery of genetic variants associated with obesity and type 2 diabetes (T2D), especially in adults. Much less is known regarding genetic variants associated with insulin resistance (IR). We hypothesized that novel IR genes could be efficiently detected in a population of obese children and adolescents who may not exhibit comorbidities and other confounding factors.

Objectives:

This study aimed to determine whether a genome-wide association study (GWAS), using a DNA-pooling approach, could identify novel genes associated with IR.

Subjects:

The pooled-DNA GWAS analysis included Slovenian obese children and adolescents with and without IR matched for body mass index, gender and age. A replication study was conducted in another independent cohort with or without IR.

Methods:

For the pooled-DNA GWAS, we used HumanOmni5-Quad SNP array (Illumina). Allele frequency distributions were compared with modified t-tests and χ²-tests and ranked using PLINK. Top single nucleotide polymorphisms (SNPs) were validated using individual genotyping by high-resolution melting analysis and TaqMan assay.

Results:

We identified five top-ranking SNPs from the pooled-DNA GWAS analysis within the ECE1, IL1R2, GNPDA1, HLA-J and PYGB loci. All except SNP rs9261108 (HLA-J locus) were confirmed in the validation phase using individual genotyping. The SNP rs2258617 within PYGB remained statistically significant for both recessive and additive models in both cohorts and in a merged analysis of both cohorts and present the strongest novel candidate gene for IR.

Conclusion:

We report for the first time a pooled-DNA GWAS approach to identify five novel SNPs or genes for IR in a paediatric population. The four loci confirmed in the second validation phase study warrant further studies, especially the strongest SNP rs2258617 within PYGB, and provide targets for further basic research of IR mechanisms and for the development of potential new IR and T2D therapies.

Chronic hypertension increases aortic endothelial hydraulic conductivity by upregulating endothelial aquaporin-1 expression

Numerous studies have examined the role of aquaporins in osmotic water transport in various systems, but virtually none have focused on the role of aquaporin in hydrostatically driven water transport involving mammalian cells save for our laboratory's recent study of aortic endothelial cells. Here, we investigated aquaporin-1 expression and function in the aortic endothelium in two high-renin rat models of hypertension, the spontaneously hypertensive genetically altered Wistar-Kyoto rat variant and Sprague-Dawley rats made hypertensive by two-kidney, one-clip Goldblatt surgery. We measured aquaporin-1 expression in aortic endothelial cells from whole rat aortas by quantitative immunohistochemistry and function by measuring the pressure-driven hydraulic conductivities of excised rat aortas with both intact and denuded endothelia on the same vessel. We used them to calculate the effective intimal hydraulic conductivity, which is a combination of endothelial and subendothelial components. We observed well-correlated enhancements in aquaporin-1 expression and function in both hypertensive rat models as well as in aortas from normotensive rats whose expression was upregulated by 2 h of forskolin treatment. Upregulated aquaporin-1 expression and function may be a response to hypertension that critically determines conduit artery vessel wall viability and long-term susceptibility to atherosclerosis.NEW & NOTEWORTHY The aortic endothelia of two high-renin hypertensive rat models express greater than two times the aquaporin-1 and, at low pressures, have greater than two times the endothelial hydraulic conductivity of normotensive rats. Data are consistent with theory predicting that higher endothelial aquaporin-1 expression raises the critical pressure for subendothelial intima compression and for artery wall hydraulic conductivity to drop.

Genomic correlates of glatiramer acetate adverse cardiovascular effects lead to a novel locus mediating coronary risk

Glatiramer acetate is used therapeutically in multiple sclerosis but also known for adverse effects including elevated coronary artery disease (CAD) risk. The mechanisms underlying the cardiovascular side effects of the medication are unclear. Here, we made use of the chromosomal variation in the genes that are known to be affected by glatiramer treatment. Focusing on genes and gene products reported by drug-gene interaction database to interact with glatiramer acetate we explored a large meta-analysis on CAD genome-wide association studies aiming firstly, to investigate whether variants in these genes also affect cardiovascular risk and secondly, to identify new CAD risk genes. We traced association signals in a 200-kb region around genomic positions of genes interacting with glatiramer in up to 60 801 CAD cases and 123 504 controls. We validated the identified association in additional 21 934 CAD cases and 76 087 controls. We identified three new CAD risk alleles within the TGFB1 region on chromosome 19 that independently affect CAD risk. The lead SNP rs12459996 was genome-wide significantly associated with CAD in the extended meta-analysis (odds ratio 1.09, p = 1.58×10⁻¹²). The other two SNPs at the locus were not in linkage disequilibrium with the lead SNP and by a conditional analysis showed p-values of 4.05 × 10⁻¹⁰ and 2.21 × 10⁻⁶. Thus, studying genes reported to interact with glatiramer acetate we identified genetic variants that concordantly with the drug increase the risk of CAD. Of these, TGFB1 displayed signal for association. Indeed, the gene has been associated with CAD previously in both in vivo and in vitro studies. Here we establish genome-wide significant association with CAD in large human samples.

Partial IGF-1 deficiency is sufficient to reduce heart contractibility, angiotensin II sensibility, and alter gene expression of structural and functional cardiac proteins

Circulating levels of IGF-1 may decrease under several circumstances like ageing, metabolic syndrome, and advanced cirrhosis. This reduction is associated with insulin resistance, dyslipidemia, progression to type 2 diabetes, and increased risk for cardiovascular diseases. However, underlying mechanisms between IGF-1 deficiency and cardiovascular disease remain elusive.

The specific aim of the present work was to study whether the partial IGF-1 deficiency influences heart and/or coronary circulation, comparing vasoactive factors before and after of ischemia-reperfusion (I/R). In addition, histology of the heart was performed together with cardiac gene expression for proteins involved in structure and function (extracellular matrix, contractile proteins, active peptides); carried out using microarrays, followed by RT-qPCR confirmation of the three experimental groups. IGF-1 partial deficiency is associated to a reduction in contractility and angiotensin II sensitivity, interstitial fibrosis as well as altered expression pattern of genes involved in extracellular matrix proteins, calcium dynamics, and cardiac structure and function.

Although this work is descriptive, it provides a clear insight of the impact that partial IGF-1 deficiency on the heart and establishes this experimental model as suitable for studying cardiac disease mechanisms and exploring therapeutic options for patients under IGF-1 deficiency conditions.

Genome-wide association analysis identifies novel blood pressure loci and offers biological insights into cardiovascular risk

Elevated blood pressure is the leading heritable risk factor for cardiovascular disease worldwide. We report genetic association of blood pressure (systolic, diastolic, pulse pressure) among UK Biobank participants of European ancestry with independent replication in other cohorts, and robust validation of 107 independent loci. We also identify new independent variants at 11 previously reported blood pressure loci. In combination with results from a range of in silico functional analyses and wet bench experiments, our findings highlight new biological pathways for blood pressure regulation enriched for genes expressed in vascular tissues and identify potential therapeutic targets for hypertension. Results from genetic risk score models raise the possibility of a precision medicine approach through early lifestyle intervention to offset the impact of blood pressure-raising genetic variants on future cardiovascular disease risk.

Potential diagnostic biomarkers for chronic kidney disease of unknown etiology (CKDu) in Sri Lanka: a pilot study

Background

In Sri Lanka, there exists chronic kidney disease of both known (CKD) and unknown etiologies (CKDu). Identification of novel biomarkers that are customized to the specific causative factors would lead to early diagnosis and clearer prognosis of the diseases. This study aimed to find genetic biomarkers in blood to distinguish and identify CKDu from CKD as well as healthy populations from CKDu endemic and non-endemic areas of Sri Lanka.

Methods

The expression patterns of a selected panel of 12 potential genetic biomarkers were analyzed in blood using RT-qPCR. Fold changes of gene expressions in early and late stages of CKD and CKDu patients, and an apparently healthy population of a CKDu endemic area, Girandurukotte (GH) were calculated relative to apparently healthy volunteers from a CKDu non-endemic area, Kandy (KH) of Sri Lanka, using the comparative CT method.

Results

Significant differences were observed between KH and early stage CKDu for both the insulin-like growth factor binding protein 1 (IGFBP1; p = 0.012) and kidney injury molecule-1 (KIM1; p = 0.003) genes, and KH and late stage CKD and CKDu for the glutathione-S-transferase mu 1 (GSTM1; p < 0.05) gene. IGFBP1 and KIM1 genes showed significant difference between the early and late stage CKDu (p < 0.01). The glutamate cysteine ligase catalytic subunit (GCLC) gene had significantly different expression between KH and all the other study groups (p < 0.01). The GH group was significantly different from the KH group for the oxidative stress related genes, G6PD, GCLC and GSTM1 (p < 0.01), and also the KIM1 gene (p = 0.003). IGFBP1, insulin-like growth factor binding protein 3 (IGFBP3), fibronectin 1 (FN1) and KIM1 showed significant correlations with serum creatinine, and IGFBP1, KIM1 and kallikrein 1 (KLK1) with eGFR (p < 0.05).

Conclusion

A panel consisting of IGFBP1, KIM1, GCLC and GSTM1 genes could be used in combination for early screening of CKDu, whereas these genes in addition with FN1, IGFBP3 and KLK1 could be used to monitor progression of CKDu. The regulation of these genes has to be studied on larger populations to validate their efficiency for further clinical use.

Deciphering the molecular mechanisms involved in HIV-associated lipoatrophy by transcriptomics: a pilot study

HIV-associated lipoatrophy (LA) has considerable implications for risk of metabolic diseases, quality of life, and adherence to treatments. Although it has decreased in high-income countries, it is still very common in resource-limited countries. Understanding the pathophysiological mechanisms of LA can open the possibility to explore new ways to treat or prevent this condition. To identify new markers for an accurate and quick diagnosis will be also of interest. Thus, we aimed to examine functional classes of genes implicated in LA and to identify potential new markers for an accurate/quick diagnosis of LA and future complications. Eighteen participants were recruited: seven healthy volunteers, five non-LA-HIV patients, and six LA-HIV subjects. Clinical lipoatrophy was considered when changes in fat volume in the cheeks next to the nose, lateral aspect of the face, legs, arms, and buttocks were observed by the physicians. mRNA was isolated from peripheral blood mononuclear cells (PBMCs) to perform a transcriptomic and Gene Ontology analysis. To confirm RNA sequencing results, qPCRs were developed. A total of 55 genes were differentially expressed between LA and non-LA patients. Thirty-seven genes were overexpressed, whereas 18 genes were repressed. Functional analysis showed that overexpressed genes were involved in lymphocyte/neutrophil activation, inflammation, and atherogenesis. Several lymphoma markers and members of the lipocalin and aquaporin families were also found more expressed in LA patients. In contrast, most of the genes found less expressed in LA subjects were involved in angiogenesis and protection against myocardial infarction. Our results demonstrated a distinct transcriptomic signature in PBMCs of LA patients in comparison with non-LA-HIV subjects and, therefore, provided novel insights to the pathogenesis of HIV-associated lipoatrophy. Our study also highlights the potential usage of some of these genes as early markers of future complications.

The Future of "Omics" in Hypertension

Despite decades of research and clinical practice, the pathogenesis of hypertension remains incompletely understood, and blood pressure is often suboptimally controlled. “Omics” technologies allow the description of a large number of molecular features and have the potential to identify new factors that contribute to blood pressure regulation and how they interact. In this review, we focus on the potential of genomics, transcriptomics, proteomics, and metabolomics and explore their roles in unraveling the pathophysiology and diagnosis of hypertension, the prediction of organ damage and treatment response, and monitoring treatment effect. Substantial progress has been made in the area of genomics, in which genome-wide association studies have identified > 50 blood pressure–related, single-nucleotide polymorphisms, and sequencing studies (especially in secondary forms of hypertension) have discovered novel regulatory pathways. In contrast, other omics technologies, despite their ability to provide detailed insights into the physiological state of an organism, have only more recently demonstrated their impact on hypertension research and clinical practice. The majority of current proteomic studies focus on organ damage resulting from hypertension and may have the potential to help us understand the link between blood pressure and organ failure but also serve as biomarkers for early detection of cerebrovascular or coronary disease. Examples include signatures for early detection of left ventricular dysfunction or albuminuria. Metabolomic studies have the potential to integrate environmental and intrinsic factors and are particularly suited to monitor the response to treatment. We discuss examples of omics studies in hypertension and explore the challenges related to these novel technologies.

Pericytes in diabetes-associated vascular disease

Pericytes are mural cells that support and stabilise the microvasculature, and are present in all vascular beds. Pericyte-endothelial cell crosstalk is essential in both remodelling and quiescent vasculature, and this complex interaction is often disrupted in disease states. Pericyte loss is believed to be an early hallmark of diabetes-associated microvascular disease, including retinopathy and nephropathy. Here we review the current literature defining pericyte biology in the context of diabetes-associated vascular disease, with a particular focus on whether pericytes contribute actively to disease progression. We also speculate regarding the role of pericytes in the recovery from macrovascular complications, such as critical limb ischaemia. It becomes clear that dysfunctional pericytes are likely to actively induce disease progression by causing vasoconstriction and basement membrane thickening, resulting in tissue ischaemia. Moreover, their altered interactions with endothelial cells are likely to cause abnormal and inadequate neovascularisation in diverse vascular beds. Further research is needed to identify mechanisms by which pericyte function is altered by diabetes, with a view to developing therapeutic approaches that normalise vascular function and remodelling.

Expression Profiling of Genes Related to Endothelial Cells Biology in Patients with Type 2 Diabetes and Patients with Prediabetes

Endothelial dysfunction appears to be an early sign indicating vascular damage and predicts the progression of atherosclerosis and cardiovascular disorders. Extensive clinical and experimental evidence suggests that endothelial dysfunction occurs in Type 2 Diabetes Mellitus (T2DM) and prediabetes patients. This study was carried out with an aim to appraise the expression levels in the peripheral blood of 84 genes related to endothelial cells biology in patients with diagnosed T2DM or prediabetes, trying to identify new genes whose expression might be changed under these pathological conditions. The study covered a total of 45 participants. The participants were divided into three groups: group 1, patients with T2DM; group 2, patients with prediabetes; group 3, control group. The gene expression analysis was performed using the Endothelial Cell Biology RT² Profiler PCR Array. In the case of T2DM, 59 genes were found to be upregulated, and four genes were observed to be downregulated. In prediabetes patients, increased expression was observed for 49 genes, with two downregulated genes observed. Our results indicate that diabetic and prediabetic conditions change the expression levels of genes related to endothelial cells biology and, consequently, may increase the risk for occurrence of endothelial dysfunction.

Novel association of the obesity risk-allele near Fas Apoptotic Inhibitory Molecule 2 (FAIM2) gene with heart rate and study of its effects on myocardial infarction in diabetic participants of the PREDIMED trial

BACKGROUND

The Fas apoptotic pathway has been implicated in type 2 diabetes and cardiovascular disease. Although a polymorphism (rs7138803; G > A) near the Fas apoptotic inhibitory molecule 2 (FAIM2) locus has been related to obesity, its association with other cardiovascular risk factors and disease remains uncertain.

METHODS

We analyzed the association between the FAIM2-rs7138803 polymorphism and obesity, blood pressure and heart rate in 7,161 participants (48.3% with type 2 diabetes) in the PREDIMED study at baseline. We also explored gene-diet interactions with adherence to the Mediterranean diet (MedDiet) and examined the effects of the polymorphism on cardiovascular disease incidence per diabetes status after a median 4.8-year dietary intervention (MedDiet versus control group) follow-up.

RESULTS

We replicated the association between the FAIM2-rs7138803 polymorphism and greater obesity risk (OR: 1.08; 95% CI: 1.01-1.16; P = 0.011; per-A allele). Moreover, we detected novel associations of this polymorphism with higher diastolic blood pressure (DBP) and heart rate at baseline (B = 1.07; 95% CI: 0.97-1.28 bmp in AA vs G-carriers for the whole population), that remained statistically significant even after adjustment for body mass index (P = 0.012) and correction for multiple comparisons. This association was greater and statistically significant in type-2 diabetic subjects (B = 1.44: 95% CI: 0.23-2.56 bmp; P = 0.010 for AA versus G-carriers). Likewise, these findings were also observed longitudinally over 5-year follow-up. Nevertheless, we found no statistically significant gene-diet interactions with MedDiet for this trait. On analyzing myocardial infarction risk, we detected a nominally significant (P = 0.041) association in type-2 diabetic subjects (HR: 1.86; 95% CI:1.03-3.37 for AA versus G-carriers), although this association did not remain statistically significant following correction for multiple comparisons.

CONCLUSIONS

We confirmed the FAIM2-rs7138803 relationship with obesity and identified novel and consistent associations with heart rate in particular in type 2 diabetic subjects. Furthermore, our results suggest a possible association of this polymorphism with higher myocardial infarction risk in type-2 diabetic subjects, although this result needs to be replicated as it could represent a false positive.

Metformin rescues the MG63 osteoblasts against the effect of high glucose on proliferation

AIMS. To study the proliferation of osteoblasts and genes expression under normal glucose, high glucose, and metformin (Met). METHODS. MG63 osteoblast-like cells were cultured in osteogenic medium supplemented with normal glucose (glucose 5.5 mmol/L) or high glucose (glucose 16.7 mmol/L) and metformin + high glucose (Met 300  μmol/L + glucose 16.7 mmol/L). Proliferation was detected with CCK-8 assay at days 1, 3, and 7. Real-time PCR and Western blot were performed to compare the expression of collagen I (Col I), osteocalcin (OCN), osteoprotegerin (OPG), receptor activator for NF- κB ligand (RANKL), and metal matrix proteinases 1 and 2 (MMP1, MMP2). Alkaline phosphatase (ALP) activity was also detected at days 6, 12, and 18. RESULTS. Exposure to high glucose inhibited the proliferation of osteoblasts (P < 0.05), with suppressed OCN and OPG. Meanwhile, Col I, RANKL, MMP1, and MMP2 were unaffected. Metformin attenuated the suppression on proliferation with increased expression of Col I, OCN, and OPG, meanwhile suppressing MMP1 and MMP2. High glucose lowered the intracellular ALP, while metformin raised it. Metformin attenuated the downregulation of ALP completely at day 6, partly at day 12, but not at day 18. CONCLUSIONS. Metformin attenuated the suppression effect of high glucose to the osteoblast proliferation and gene expression, more prominently in earlier stage.

Analysis of the transcriptome in molecular epidemiology studies

The human transcriptome is complex, comprising multiple transcript types, mostly in the form of non-coding RNA (ncRNA). The majority of ncRNA is of the long form (lncRNA, ≥ 200 bp), which plays an important role in gene regulation through multiple mechanisms including epigenetics, chromatin modification, control of transcription factor binding, and regulation of alternative splicing. Both mRNA and ncRNA exhibit additional variability in the form of alternative splicing and RNA editing. All aspects of the human transcriptome can potentially be dysregulated by environmental exposures. Next-generation RNA sequencing (RNA-Seq) is the best available methodology to measure this although it has limitations, including experimental bias. The third phase of the MicroArray Quality Control Consortium project (MAQC-III), also called Sequencing Quality Control (SeQC), aims to address these limitations through standardization of experimental and bioinformatic methodologies. A limited number of toxicogenomic studies have been conducted to date using RNA-Seq. This review describes the complexity of the human transcriptome, the application of transcriptomics by RNA-Seq or microarray in molecular epidemiology studies, and limitations of these approaches including the type of cell or tissue analyzed, experimental variation, and confounding. By using good study designs with precise, individual exposure measurements, sufficient power and incorporation of phenotypic anchors, studies in human populations can identify biomarkers of exposure and/or early effect and elucidate mechanisms of action underlying associated diseases, even at low doses. Analysis of datasets at the pathway level can compensate for some of the limitations of RNA-Seq and, as more datasets become available, will increasingly elucidate the exposure-disease continuum.