Patient adipose stem cell-derived adipocytes reveal genetic variation that predicts anti-diabetic drug response
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA474921 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR7271340.fastq.gz | Fastqsanger.gz | |||
| SRR7271350.fastq.gz | Fastqsanger.gz | |||
| SRR7271360.fastq.gz | Fastqsanger.gz | |||
| SRR7271341.fastq.gz | Fastqsanger.gz | |||
| SRR7271351.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 92 |
Similar Datasets
Project description:Thiazolidinedione drugs (TZDs) target the transcriptional activity of PPARg to reverse insulin resistance in type 2 diabetes, but side effects limit their clinical use. Here, using human adipose stem cell-derived adipocytes, we demonstrate that single-nucleotide polymorphisms (SNPs) were enriched at sites of patient-specific PPARg binding, which correlated with the individual-specific effects of TZD rosiglitazone (rosi) on gene expression. Rosi induction of ABCA1, which regulates cholesterol metabolism, was dependent upon SNP rs4743771, which modulated PPARg binding by influencing the genomic occupancy of its cooperating factor NFIA. Conversion of rs4743771 from the inactive SNP allele to the active one by CRISPR/Cas9-mediated editing rescued PPARg binding as well as rosi-induction of ABCA1 expression. Moreover, rs4743771 is a major determinant of undesired serum cholesterol increases in rosi-treated diabetics. These data highlight human genetic variation that impacts PPARg genomic occupancy and patient responses to antidiabetic drugs, with implications for developing personalized therapies for metabolic disorders
2019-01-11 | GSE115421 | GEO
Project description:Thiazolidinedione drugs (TZDs) target the transcriptional activity of peroxisome proliferator activated receptor γ (PPARγ) to reverse insulin resistance in type 2 diabetes, but side effects limit their clinical use. Here, using human adipose stem cell-derived adipocytes, we demonstrate that SNPs were enriched at sites of patient-specific PPARγ binding, which correlated with the individual-specific effects of the TZD rosiglitazone (rosi) on gene expression. Rosi induction of ABCA1, which regulates cholesterol metabolism, was dependent upon SNP rs4743771, which modulated PPARγ binding by influencing the genomic occupancy of its cooperating factor, NFIA. Conversion of rs4743771 from the inactive SNP allele to the active one by clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9-mediated editing rescued PPARγ binding and rosi induction of ABCA1 expression. Moreover, rs4743771 is a major determinant of undesired serum cholesterol increases in rosi-treated diabetics. These data highlight human genetic variation that impacts PPARγ genomic occupancy and patient responses to antidiabetic drugs, with implications for developing personalized therapies for metabolic disorders.
| S-EPMC6368460 | biostudies-literature
Project description:Brännmark2013 - Insulin signalling in human adipocytes (diabetic condition)
The paper describes insulin signalling in human adipocytes under normal and diabetic states using mathematical models based on experimental data. This model corresponds to insulin signalling under diabetic condtion
This model is described in the article:
Insulin Signaling in Type 2 Diabetes: EXPERIMENTAL AND MODELING ANALYSES REVEAL MECHANISMS OF INSULIN RESISTANCE IN HUMAN ADIPOCYTES.
Brännmark C, Nyman E, Fagerholm S, Bergenholm L, Ekstrand EM, Cedersund G, Strålfors P.
J Biol Chem. 2013 Apr 5;288(14):9867-80.
Abstract:
Type 2 diabetes originates in an expanding adipose tissue that for unknown reasons becomes insulin resistant. Insulin resistance reflects impairments in insulin signaling, but mechanisms involved are unclear because current research is fragmented. We report a systems level mechanistic understanding of insulin resistance, using systems wide and internally consistent data from human adipocytes. Based on quantitative steady-state and dynamic time course data on signaling intermediaries, normally and in diabetes, we developed a dynamic mathematical model of insulin signaling. The model structure and parameters are identical in the normal and diabetic states of the model, except for three parameters that change in diabetes: (i) reduced concentration of insulin receptor, (ii) reduced concentration of insulin-regulated glucose transporter GLUT4, and (iii) changed feedback from mammalian target of rapamycin in complex with raptor (mTORC1). Modeling reveals that at the core of insulin resistance in human adipocytes is attenuation of a positive feedback from mTORC1 to the insulin receptor substrate-1, which explains reduced sensitivity and signal strength throughout the signaling network. Model simulations with inhibition of mTORC1 are comparable with experimental data on inhibition of mTORC1 using rapamycin in human adipocytes. We demonstrate the potential of the model for identification of drug targets, e.g. increasing the feedback restores insulin signaling, both at the cellular level and, using a multilevel model, at the whole body level. Our findings suggest that insulin resistance in an expanded adipose tissue results from cell growth restriction to prevent cell necrosis.
This model is hosted on BioModels Database
and identified
by: MODEL1304160000
.
To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource
for published quantitative kinetic models
.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to the public
domain worldwide. Please refer to CC0 Public Domain
Dedication
for more information.
2024-09-02 | BIOMD0000000449 | BioModels
Project description:Transcriptomic clock predicts vascular changes of prodromal diabetic retinopathy
| PRJNA910951 | ENA
Project description:Microarray analysis comparing gene expression profiles of adipocytes from non-diabetic lean vs non-diabetic obese Pima Indian subjects to identify differentially expressed adipocyte genes with obesity. RNA samples of isolated abdominal subcutaneous adipocytes from 20 lean (10 Males / 10 Females, aged 31±6 year, Body Mass Index 25±3 kg/m2 ) and 19 obese (9M/10F, 29±5y, 55±8 kg/m2 ) subjects were hybridized individually to Affymetrix oligonucleotide arrays HG-U95A, B, C, D, and E.
2007-08-25 | E-GEOD-2508 | biostudies-arrayexpress
Project description:Microarray analysis comparing gene expression profiles of adipocytes from non-diabetic lean vs non-diabetic obese Pima Indian subjects to identify differentially expressed adipocyte genes with obesity. RNA samples of isolated abdominal subcutaneous adipocytes from 20 lean (10 Males / 10 Females, aged 31±6 year, Body Mass Index 25±3 kg/m2 ) and 19 obese (9M/10F, 29±5y, 55±8 kg/m2 ) subjects were hybridized individually to Affymetrix oligonucleotide arrays HG-U95A, B, C, D, and E. Keywords = adipocyte Keywords = obesity Keywords = inflammation Keywords = gene expression Keywords: other
2006-01-01 | GSE2508 | GEO
Project description:A Gene Expression Signature that Predicts the Future Onset of Drug-Induced Renal Tubular Toxicity These data support the publication titled "A Gene Expression Signature that Predicts the Future Onset of Drug-Induced Renal Tubular Toxicity" Copyright (c) 2005 by Iconix Pharmaceuticals, Inc. Guidelines for commercial use: http://www.iconixbiosciences.com/guidelineCommUse.pdf replicated drug treatments with controls
2005-11-30 | E-GEOD-3210 | biostudies-arrayexpress
Project description:Diabetes is a known risk factor for various cardiovascular complications, mediated by endothelial dysfunction. Despite the high prevalence of this metabolic disorder, there is a lack of in vitro models that recapitulate the complexity of genetic and environmental factors associated with diabetic endothelial dysfunction. Here, we utilized human induced pluripotent stem cell (iPSC)-derived endothelial cells (ECs) to develop in vitro models of diabetic endothelial dysfunction. We found that the diabetic phenotype was recapitulated in diabetic patient-derived iPSC-ECs, even in the absence of a diabetogenic environment. Subsequent exposure with culture conditions that mimic the diabetic clinical chemistry induced a diabetic phenotype in healthy iPSC-ECs but did not affect the already dysfunctional diabetic iPSC-ECs. RNA-seq analysis revealed extensive transcriptome-wide differences between cells derived from healthy individuals and diabetic patients. The in vitro disease models were used as a screening platform which identified angiotensin receptor blockers (ARBs) that improved endothelial function in vitro for each patient. In summary, we present in vitro models of diabetic endothelial dysfunction using iPSC technology, taking into account the complexity of genetic and environmental factors in the metabolic disorder. Our study provides novel insights into the pathophysiology of diabetic endothelial dysfunction and highlights the potential of iPSC-based models for drug discovery and personalized medicine.
2023-07-05 | GSE236430 | GEO
Project description:Analysis of FACS sorted UCP1+ adipocytes shows that the mRNA signature of brite adipocytes is distinct from beige adipocytes, which arise through catecholamine signaling.
2016-12-13 | GSE87191 | GEO
Project description:Brännmark2013 - Insulin signalling in human adipocytes (normal condition)
The paper describes insulin signalling in human adipocytes under normal and diabetic states using mathematical models based on experimental data. This model corresponds to insulin signalling under normal condtion
This model is described in the article:
Insulin Signaling in Type 2 Diabetes: EXPERIMENTAL AND MODELING ANALYSES REVEAL MECHANISMS OF INSULIN RESISTANCE IN HUMAN ADIPOCYTES.
Brännmark C, Nyman E, Fagerholm S, Bergenholm L, Ekstrand EM, Cedersund G, Strålfors P.
J Biol Chem. 2013 Apr 5;288(14):9867-80.
Abstract:
Type 2 diabetes originates in an expanding adipose tissue that for unknown reasons becomes insulin resistant. Insulin resistance reflects impairments in insulin signaling, but mechanisms involved are unclear because current research is fragmented. We report a systems level mechanistic understanding of insulin resistance, using systems wide and internally consistent data from human adipocytes. Based on quantitative steady-state and dynamic time course data on signaling intermediaries, normally and in diabetes, we developed a dynamic mathematical model of insulin signaling. The model structure and parameters are identical in the normal and diabetic states of the model, except for three parameters that change in diabetes: (i) reduced concentration of insulin receptor, (ii) reduced concentration of insulin-regulated glucose transporter GLUT4, and (iii) changed feedback from mammalian target of rapamycin in complex with raptor (mTORC1). Modeling reveals that at the core of insulin resistance in human adipocytes is attenuation of a positive feedback from mTORC1 to the insulin receptor substrate-1, which explains reduced sensitivity and signal strength throughout the signaling network. Model simulations with inhibition of mTORC1 are comparable with experimental data on inhibition of mTORC1 using rapamycin in human adipocytes. We demonstrate the potential of the model for identification of drug targets, e.g. increasing the feedback restores insulin signaling, both at the cellular level and, using a multilevel model, at the whole body level. Our findings suggest that insulin resistance in an expanded adipose tissue results from cell growth restriction to prevent cell necrosis.
This model is hosted on BioModels Database
and identified
by: MODEL1304190000
.
To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource
for published quantitative kinetic models
.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to the public
domain worldwide. Please refer to CC0 Public Domain
Dedication
for more information.
2024-09-02 | BIOMD0000000448 | BioModels