GUARDIAN: Mapping the Genes for Hypertension and Insulin Resistance (HTN-IR)
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PROVIDER: PRJNA392193 | ENA |
REPOSITORIES: ENA
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Project description:<p>The HTN-IR Study, funded by NHLBI, was designed to explore genetic contributions to hypertension and glucose homeostasis traits among Hispanics using a family-based design. The baseline examination of the cohort included the euglycemic hyperinsulinemic clamp test from which the two key phenotypes were obtained: insulin sensitivity (M) and metabolic clearance rate of insulin (MCRI). Genome-wide genotyping was obtained under separate funding by NIDDK as a part of the GUARDIAN (Genetics Underlying Diabetes in Hispanics) Consortium. </p>
| phs001394 | dbGaP
Project description:GUARDIAN: Insulin Resistance and Atherosclerosis Study (IRAS)
| PRJNA300462 | ENA
Project description:GUARDIAN: IRAS (Insulin Resistance Atherosclerosis Study) Family Study
| PRJNA299347 | ENA
Project description:We have performed gene expression microarray analysis to profile transcriptomic signatures between insulin resistance high risk subjects and insulin resistance low risk subjects Participants enrolled in this study were recruited in the overnight fasted state, then the collection and processing of glucose (fasting, 30, 60 and 120 minutes) and insulin from blood samples, hemoglobin A1c (HbA1c) , assessment of medical history, socio-demographic characteristics, lifestyle factors, blood pressure and anthropometric and body composition measurements were conducted. During baseline visit, participants were asked to refrain from eating, drinking and oral hygiene procedures for at least 1-hour prior to saliva collection.5 ml of unstimulated whole saliva samples were consistently collected, stabilized and preserved, the sample supernatants were reserved at -80°C prior to assay. Based on the homeostasis model assessment of insulin resistance (HOMA-IR), using the formula [HOMA-IR= (fasting glucose*fasting insulin)/405], participants were divided into 2 groups: IR high risk group (HOMA-IR value ?2.5) and IR low risk group (HOMA-IR value <2.5). Total RNA was extracted from saliva and subjected to gene expression microarray analysis using Affymetrix human genome 2.0 plus array
2015-04-10 | E-GEOD-67738 | biostudies-arrayexpress
Project description:Insulin resistance (IR) is likely to induce metabolic syndrome and type 2 diabetes mellitus (T2DM). Gluconeogenesis (GNG) is a complex metabolic process that may result in glucose generation from certain non-carbohydrate substrates. Chinese herbal medicine astragalus polysaccharides and berberine have been documented to ameliorate IR, and combined use of astragalus polysaccharide (AP) and berberine (BBR) are reported to synergistically produce an even better effect. However, what change may occur in the GNG signaling pathway of IR-HepG2 cells in this synergistic effect and whether AP-BBR attenuates IR by regulating the GNG signaling pathway remain unclear. For the first time, we discovered in this study that the optimal time of IR-HepG2 cell model formation was 48 hours after insulin intervention. AP-BBR attenuated IR in HepG2 cells and the optimal concentration was 10mg. AP-BBR reduced the intracellular H2O2 content with no significant effect on apoptosis of IR-HepG2 cells. In addition, a rapid change was observed in intracellular calcium current of the IR-HepG2 cell model, and AP-BBR intervention attenuated this change markedly. The gene sequencing results showed that the GNG signaling pathway was one of the signaling pathways of AP-BBR to attenuate IR in IR-Hepg2 cells. The expression of p-FoxO1Ser256 and PEPCK protein was increased and the expression of GLUT2 protein was decreased significantly in the IR-HepG2 cell model, and both of these effects could be reversed by AP-BBR intervention. AP-BBR attenuated IR in IR-HepG2 cells, probably by regulating the GNG signaling Pathway.
2019-11-14 | GSE139929 | GEO
Project description:GUARDIAN: Mapping the Genes for Hypertension and Insulin Resistance (HTN-IR)
| PRJNA392194 | ENA
Project description:Recent discovery reveals HFD insult can cause insulin resistance very rapidly, but the underlying mechanism is still not well understood. We performed a short term experiment in a Diet Induced Insulin resistance mouse model. Objective: Insulin resistance (IR) is one of the earliest predictors of type 2 diabetes. However, diagnosis of IR is limited. High fat fed mouse models provide key insights into IR. We hypothesized that early features of IR are associated with persistent changes in gene expression (GE) and endeavoured to (a) develop novel methods for improving signal:noise in analysis of human GE using mouse models; (b) identify a GE motif that accurately diagnoses IR in humans; and (c) identify novel biology associated with IR in humans. Methods: We integrated human muscle GE data with longitudinal mouse GE data and developed an unbiased three-level cross-species analysis platform (single-gene, gene-set and networks) to generate a gene expression motif (GEM) indicative of IR. A logistic regression classification model validated GEM in 3 independent human datasets (n =115). Results: This GEM of 93 genes substantially improved diagnosis of IR compared to routine clinical measures across multiple independent datasets. Individuals misclassified by GEM possessed other metabolic features raising the possibility that they represent a separate metabolic subclass. The GEM was enriched in pathways previously implicated in insulin action and revealed novel associations between β-catenin and Jak1 and IR. Functional analyses using small molecule inhibitors showed an important role for these proteins in insulin action. Conclusions: This study shows that systems approaches for identifying molecular signatures provides a powerful way to stratify individuals into discrete metabolic groups. Moreover, we speculate that the β-catenin pathway may represent a novel biomarker for IR in humans that warrant future investigation. Comparison of gene expression in muscle tissue during High Fat Diet (HFD) time course (day 5 and day 42). Chow diet will serve as control for HFD. 4 samples per group serve as experimental replicates.
2015-12-07 | E-GEOD-73036 | biostudies-arrayexpress
Project description:To explore genes that could be responsible to insulin in insulin resistance states (IR), we generated the IR mice models (mice after 6 weeks of high-fat feeding).
2023-07-19 | GSE205460 | GEO
Project description:5 arrays from obese insulin-resistant and lean insulin-sensitive females adipose tissue at fasting and after 3h hyperinsulinemia 5 arrays from obese insulin-resistant and lean insulin-sensitive females adipose tissue at fasting and after 3h hyperinsulinemia FIR x 5, FIS x 5, HIR x 5, HIS x 5 F=fasting, H=hyperinsulinemia, IR=Insulin-resistant, IS=Insulin-sensitive (FIR, FIS, HIR, HIS)
2012-02-21 | E-GEOD-26637 | biostudies-arrayexpress
Project description:Recent discovery reveals HFD insult can cause insulin resistance very rapidly, but the underlying mechanism is still not well understood. We performed a short term experiment in a Diet Induced Insulin resistance mouse model. Objective: Insulin resistance (IR) is one of the earliest predictors of type 2 diabetes. However, diagnosis of IR is limited. High fat fed mouse models provide key insights into IR. We hypothesized that early features of IR are associated with persistent changes in gene expression (GE) and endeavoured to (a) develop novel methods for improving signal:noise in analysis of human GE using mouse models; (b) identify a GE motif that accurately diagnoses IR in humans; and (c) identify novel biology associated with IR in humans. Methods: We integrated human muscle GE data with longitudinal mouse GE data and developed an unbiased three-level cross-species analysis platform (single-gene, gene-set and networks) to generate a gene expression motif (GEM) indicative of IR. A logistic regression classification model validated GEM in 3 independent human datasets (n =115). Results: This GEM of 93 genes substantially improved diagnosis of IR compared to routine clinical measures across multiple independent datasets. Individuals misclassified by GEM possessed other metabolic features raising the possibility that they represent a separate metabolic subclass. The GEM was enriched in pathways previously implicated in insulin action and revealed novel associations between β-catenin and Jak1 and IR. Functional analyses using small molecule inhibitors showed an important role for these proteins in insulin action. Conclusions: This study shows that systems approaches for identifying molecular signatures provides a powerful way to stratify individuals into discrete metabolic groups. Moreover, we speculate that the β-catenin pathway may represent a novel biomarker for IR in humans that warrant future investigation.
2015-12-07 | GSE73036 | GEO