ArticleGenome medicine2017
Type 2 diabetes and obesity induce similar transcriptional reprogramming in human myocytes.
Article in Genome medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
25 citing papers in PubMed, 45 citations in OpenAlex.
- Fucoidan P Alleviates Sarcopenic Obesity by Regulating Muscle Protein and Energy Metabolism.International journal of biological sciences · 2026Article
- CD47-blocking antibody confers metabolic benefits against obesity.Cell reports. Medicine · 2025Article
- Specific muscle targeted delivery of miR-130a loaded lipid nanoparticles: a novel approach to inhibit lipid accumulation in skeletal muscle and obesity.Journal of nanobiotechnology · 2025Article
- Identification and study of mood-related biomarkers and potential molecular mechanisms in type 2 diabetes mellitus.Journal of molecular histology · 2025Article
- Skeletal muscle TET3 promotes insulin resistance through destabilisation of PGC-1α.Diabetologia · 2024Article
- Review
- Interactions among insulin resistance, epigenetics, and donor sex in gene expression regulation of iPSC-derived myoblasts.The Journal of clinical investigation · 2024Article
- Multidimensional conservation analysis decodes the expression of conserved long noncoding RNAs.Life science alliance · 2023Article
- Unraveling the Mechanism of Immunity and Inflammation Related to Molecular Signatures Crosstalk Among Obesity, T2D, and AD: Insights From Bioinformatics Approaches.Bioinformatics and biology insights · 2023Article
- A holistic view of muscle metabolic reprogramming through personalized metabolic modeling in newly diagnosed diabetic patients.PloS one · 2023Article
- Review
- Nampt activator P7C3 ameliorates diabetes and improves skeletal muscle function modulating cell metabolism and lipid mediators.Journal of cachexia, sarcopenia and muscle · 2022Article
- Comparing the long non-coding RNA expression profiles of skeletal muscle and kidney tissues from patients with diabetes.PloS one · 2022Article
- The Potential Role of Gut Microbiota in the Pathogenesis of Type 2 Diabetes MellitusEndocrine, metabolic & immune disorders drug targets · 2022Review
- Epigenetic interaction between UTX and DNMT1 regulates diet-induced myogenic remodeling in brown fat.Nature communications · 2021Article
- RNA sequencing reveals potential interacting networks between the altered transcriptome and ncRNome in the skeletal muscle of diabetic mice.Bioscience reports · 2021Article
- Genome-wide discovery of hidden genes mediating known drug-disease association using KDDANet.NPJ genomic medicine · 2021Article
- Molecular pathways behind acquired obesity: Adipose tissue and skeletal muscle multiomics in monozygotic twin pairs discordant for BMI.Cell reports. Medicine · 2021Article
- Knowledge-guided analysis of "omics" data using the KnowEnG cloud platform.PLoS biology · 2020Article
- Mitochondrial Function in Muscle Stem Cell Fates.Frontiers in cell and developmental biology · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSkeletal muscle is one of the primary tissues involved in the development of type 2 diabetes (T2D). The close association between obesity and T2D makes it difficult to isolate specific effects attributed to the disease alone. Therefore, here we set out to identify and characterize intrinsic properties of myocytes, associated independently with T2D or obesity.
methodsWe generated and analyzed RNA-seq data from primary differentiated myotubes from 24 human subjects, using a factorial design (healthy/T2D and non-obese/obese), to determine the influence of each specific factor on genome-wide transcription. This setup enabled us to identify intrinsic properties, originating from muscle precursor cells and retained in the corresponding myocytes. Bioinformatic and statistical methods, including differential expression analysis, gene-set analysis, and metabolic network analysis, were used to characterize the different myocytes.
resultsWe found that the transcriptional program associated with obesity alone was strikingly similar to that induced specifically by T2D. We identified a candidate epigenetic mechanism, H3K27me3 histone methylation, mediating these transcriptional signatures. T2D and obesity were independently associated with dysregulated myogenesis, down-regulated muscle function, and up-regulation of inflammation and extracellular matrix components. Metabolic network analysis identified that in T2D but not obesity a specific metabolite subnetwork involved in sphingolipid metabolism was transcriptionally regulated.
conclusionsOur findings identify inherent characteristics in myocytes, as a memory of the in vivo phenotype, without the influence from a diabetic or obese extracellular environment, highlighting their importance in the development of T2D.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.