Renin-Angiotensin-Aldosterone System, Glucose Metabolism and Incident Type 2 Diabetes Mellitus: MESA.

Background Mechanistic studies suggest that aldosterone impairs glucose metabolism. We investigated the cross-sectional associations of aldosterone and plasma renin activity with fasting plasma glucose, insulin resistance ( IR ), β-cell function, and longitudinal association with incident diabetes mellitus among adults in MESA (the multiethnic study of atherosclerosis) prospective cohort study. Methods and Results Homeostatic model assessment of IR ( HOMA 2- IR ) and HOMA 2-β were used to estimate IR and β-cell function, respectively. Incident diabetes mellitus was defined as fasting plasma glucose ≥126 mg/dL or anti-diabetic medication use at follow-up. Linear regression was used to examine cross-sectional associations of aldosterone with fasting plasma glucose, HOMA 2- IR and HOMA 2-β; Cox regression was used to estimate hazard ratios ( HR ) for incident diabetes mellitus with multivariable adjustment. There were 116 cases of incident diabetes mellitus over 10.5 years among 1570 adults (44% non-Hispanic white, 13% Chinese American, 19% Black, 24% Hispanic American, mean age 64±10 years, 51% female). A 100% increase in log-aldosterone was associated with a 2.6 mg/dL higher fasting plasma glucose, 15% higher HOMA 2- IR and 6% higher HOMA 2-β ( P<0.01). A 1- SD increase in log-aldosterone was associated with a 44% higher risk of incident diabetes mellitus ( P<0.01) with the greatest increase of 142% ( P<0.01) observed in Chinese Americans ( P for interaction=0.09 versus other ethnicities). Similar cross-sectional findings for log-plasma renin activity existed, but log-plasma renin activity was not associated with incident diabetes mellitus after full adjustment. Conclusions Aldosterone is associated with glucose homeostasis and diabetes mellitus risk with graded associations among Chinese Americans and blacks, suggesting that pleiotropic effects of aldosterone may represent a modifiable mechanism in diabetes mellitus pathogenesis with potential racial/ethnic variation

Troglitazone inhibits angiotensin II-induced DNA synthesis and migration in vascular smooth muscle cells

AbstractAngiotensin II (AII) plays a crucial role in controlling the proliferation and migration of vascular smooth muscle cells (VSMCs). The present study was undertaken to determine if troglitazone (Tro) has an effect on the G-protein coupled signaling through AII type I (AT-1) receptors in cultured rat aortic VSMCs. AII-induced MAP kinase activation was inhibited 67.9% by Tro. AII-induced DNA synthesis and migration was completely inhibited by Tro or by the AT-1 receptor blocker irbesartan. The present study demonstrates that troglitazone inhibits AII-induced DNA synthesis, migration and MAP kinase activation in VSMCs which are important molecular events for the development of neointimal hyperplasia and atherosclerosis

A Dominant-Negative PPARγ Mutant Promotes Cell Cycle Progression and Cell Growth in Vascular Smooth Muscle Cells

PPARγ ligands have been shown to have antiproliferative effects on many cell types. We herein report that a synthetic dominant-negative (DN) PPARγ mutant functions like a growth factor to promote cell cycle progression and cell proliferation in human coronary artery smooth muscle cells (CASMCs). In quiescent CASMCs, adenovirus-expressed DN-PPARγ promoted G1→S cell cycle progression, enhanced BrdU incorporation, and increased cell proliferation. DN-PPARγ expression also markedly enhanced positive regulators of the cell cycle, increasing Rb and CDC2 phosphorylation and the expression of cyclin A, B1, D1, and MCM7. Conversely, overexpression of wild-type (WT) or constitutively-active (CA) PPARγ inhibited cell cycle progression and the activity and expression of positive regulators of the cell cycle. DN-PPARγ expression, however, did not up-regulate positive cell cycle regulators in PPARγ-deficient cells, strongly suggesting that DN-PPARγ effects on cell cycle result from blocking the function of endogenous wild-type PPARγ. DN-PPARγ expression enhanced phosphorylation of ERK MAPKs. Furthermore, the ERK specific-inhibitor PD98059 blocked DN-PPARγ-induced phosphorylation of Rb and expression of cyclin A and MCM7. Our data thus suggest that DN-PPARγ promotes cell cycle progression and cell growth in CASMCs by modulating fundamental cell cycle regulatory proteins and MAPK mitogenic signaling pathways in vascular smooth muscle cells (VSMCs)

MicroRNA-Integrated and Network-Embedded Gene Selection with Diffusion Distance

Gene network information has been used to improve gene selection in microarray-based studies by selecting marker genes based both on their expression and the coordinate expression of genes within their gene network under a given condition. Here we propose a new network-embedded gene selection model. In this model, we first address the limitations of microarray data. Microarray data, although widely used for gene selection, measures only mRNA abundance, which does not always reflect the ultimate gene phenotype, since it does not account for post-transcriptional effects. To overcome this important (critical in certain cases) but ignored-in-almost-all-existing-studies limitation, we design a new strategy to integrate together microarray data with the information of microRNA, the major post-transcriptional regulatory factor. We also handle the challenges led by gene collaboration mechanism. To incorporate the biological facts that genes without direct interactions may work closely due to signal transduction and that two genes may be functionally connected through multi paths, we adopt the concept of diffusion distance. This concept permits us to simulate biological signal propagation and therefore to estimate the collaboration probability for all gene pairs, directly or indirectly-connected, according to multi paths connecting them. We demonstrate, using type 2 diabetes (DM2) as an example, that the proposed strategies can enhance the identification of functional gene partners, which is the key issue in a network-embedded gene selection model. More importantly, we show that our gene selection model outperforms related ones. Genes selected by our model 1) have improved classification capability; 2) agree with biological evidence of DM2-association; and 3) are involved in many well-known DM2-associated pathways

Medium Chain Fatty Acids Are Selective Peroxisome Proliferator Activated Receptor (PPAR) γ Activators and Pan-PPAR Partial Agonists

Thiazolidinediones (TZDs) act through peroxisome proliferator activated receptor (PPAR) γ to increase insulin sensitivity in type 2 diabetes (T2DM), but deleterious effects of these ligands mean that selective modulators with improved clinical profiles are needed. We obtained a crystal structure of PPARγ ligand binding domain (LBD) and found that the ligand binding pocket (LBP) is occupied by bacterial medium chain fatty acids (MCFAs). We verified that MCFAs (C8–C10) bind the PPARγ LBD in vitro and showed that they are low-potency partial agonists that display assay-specific actions relative to TZDs; they act as very weak partial agonists in transfections with PPARγ LBD, stronger partial agonists with full length PPARγ and exhibit full blockade of PPARγ phosphorylation by cyclin-dependent kinase 5 (cdk5), linked to reversal of adipose tissue insulin resistance. MCFAs that bind PPARγ also antagonize TZD-dependent adipogenesis in vitro. X-ray structure B-factor analysis and molecular dynamics (MD) simulations suggest that MCFAs weakly stabilize C-terminal activation helix (H) 12 relative to TZDs and this effect is highly dependent on chain length. By contrast, MCFAs preferentially stabilize the H2-H3/β-sheet region and the helix (H) 11-H12 loop relative to TZDs and we propose that MCFA assay-specific actions are linked to their unique binding mode and suggest that it may be possible to identify selective PPARγ modulators with useful clinical profiles among natural products

The trans-ancestral genomic architecture of glycemic traits

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 x 10(-8)), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution. A trans-ancestry meta-analysis of GWAS of glycemic traits in up to 281,416 individuals identifies 99 novel loci, of which one quarter was found due to the multi-ancestry approach, which also improves fine-mapping of credible variant sets.Peer reviewe

Ancestral diversity improves discovery and fine-mapping of genetic loci for anthropometric traits - the Hispanic/Latino Anthropometry Consortium

Hispanic/Latinos have been underrepresented in genome-wide association studies (GWAS) for anthropometric traits despite their notable anthropometric variability, ancestry proportions, and high burden of growth stunting and overweight/obesity. To address this knowledge gap, we analyzed densely-imputed genetic data in a sample of Hispanic/Latino adults to identify and fine-map genetic variants associated with body mass index (BMI), height, and BMI-adjusted waist-to-hip ratio (WHRadjBMI). We conducted a GWAS of 18 studies/consortia as part of the Hispanic/Latino Anthropometry (HISLA) Consortium (Stage 1, n=59,771) and generalized our findings in 9 additional studies (HISLA Stage 2, n=10,538). We conducted a trans-ancestral GWAS with summary statistics from HISLA Stage 1 and existing consortia of European and African ancestries. In our HISLA Stage 1+2 analyses, we discovered one BMI locus, as well as two BMI signals and another height signal each within established anthropometric loci. In our trans-ancestral meta-analysis, we discovered three BMI loci, one height locus, and one WHRadjBMI locus. We also identified three secondary signals for BMI, 28 for height, and two for WHRadjBMI in established loci. We show that 336 known BMI, 1,177 known height, and 143 known WHRadjBMI (combined) SNPs demonstrated suggestive transferability (nominal significance and effect estimate directional consistency) in Hispanic/Latino adults. Of these, 36 BMI, 124 height, and 11 WHRadjBMI SNPs were significant after trait-specific Bonferroni correction. Trans-ancestral meta-analysis of the three ancestries showed a small-to-moderate impact of uncorrected population stratification on the resulting effect size estimates. Our findings demonstrate that future studies may also benefit from leveraging diverse ancestries and differences in linkage disequilibrium patterns to discover novel loci and additional signals with less residual population stratification