Project description:<p>INTRODUCTION: Type 2 Diabetes mellitus (T2DM) is a chronic metabolic disorder characterized by insulin resistance and hyperglycemia, often preceded by latent metabolic disruptions. Early detection of metabolic alterations can facilitate timely intervention to delay or prevent T2DM onset. Metabolic profiling offers a useful tool to identify novel disease biomarkers and metabolic alterations before clinical manifestations. OBJECTIVE: This study aimed to identify early metabolic alterations and potential biomarkers predictive of T2DM in a cohort of healthy normoglycemic participants over a six-year follow-up. METHODS: A cohort of 94 healthy participants, both men and women aged 18-40, was studied at six-year intervals. Clinical and biochemical parameters were measured, and LC/MS/MS-based untargeted metabolomics analysis of plasma was performed at baseline and follow-up. RESULTS: At follow-up, 9 participants developed T2DM, 51 had prediabetes and 34 remained normoglycemic. Increasing insulin resistance and elevated future T2DM risk were observed in both the Prediabetes and Normal groups. Metabolomics analysis identified Phosphatidylethanolamine (PE) (20:3_18:0), 3beta,7alpha-Dihydroxy-5-cholestenoate and Tridecanoic acid – as having good predictive capacity for future T2DM risk at baseline with alterations in Phosphatidylethanolamine (PE) (20:3_18:0), and Tridecanoic acid persisting at follow-up. CONCLUSION: The study highlights the potential of metabolomics in identifying early metabolic predictors of T2DM, emphasizing the need for early interventions in healthy normoglycemic young adults.</p>
Project description:This longitudinal study analyzed whole-blood DNA methylation profiles in adults classified as normoglycemic, prediabetic, or type 2 diabetes mellitus (T2DM). Oxford Nanopore PromethION long-read sequencing (PCR-free ligation preparation) was used to generate genome-wide CpG methylation data at baseline and at six-year follow-up. The dataset includes raw nanopore reads (available in SRA) and processed methylation outputs, including CpG-wise differential methylation, methylation summaries, promoter/CpG island annotation, HOMER functional annotation, and gene–pathway mapping
Project description:This dataset comprises RNA sequencing data generated from salivary samples as part of the study titled \\"Characterizing the Salivary RNA Landscape to Identify Potential Diagnostic, Prognostic, and Follow-Up Biomarkers for Breast Cancer.\\" The dataset includes single-end RNA-seq reads stored in FASTA format, derived from three sample groups: breast cancer patients (BC), healthy controls (CRL), and follow-up samples from treated breast cancer patients (FL). Each sample file is annotated with metadata containing information on sample type and anonymized patient IDs. The data captures both coding and long non-coding RNAs extracted from saliva, providing a comprehensive profile of the salivary RNA landscape. The primary goal of this dataset is to facilitate the identification of RNA biomarkers with potential diagnostic, prognostic, and treatment monitoring applications in breast cancer.
Project description:This SuperSeries is composed of the following subset Series: GSE21321: Blood microRNA profiles and upregulation of hsa-miR-144 in males with type 2 diabetes mellitus. GSE26167: MicroRNA 144 impairs insulin signaling by inhibiting the expression of insulin receptor substrate 1 in Type 2 Diabetes mellitus Refer to individual Series
Project description:Follow-up study of 9 year old IVF children who underwent embryo culture in G3 (Vitrolife) or K-SICM (Cook) medium. Genome-wide DNA methylation profiling of 9 year old IVF children (saliva samples) who had undergone embryo culture in G3 medium (Vitrolife) or K-SICM medium (Lonza). The EPIC array was used to profile the methylome at approximately 850,000 CpG sites across the human genome.
Project description:Diabetes mellitus (DM) after transplantation remains a crucial clinical problem in kidney transplantation. To obtain insights into molecular mechanisms underlying the development of post-transplant diabetes mellitus (PTDM) and its early impact on glomerular structures, here we comparatively analyze the proteome of histologically normal appearing glomeruli from patients with PTDM from normoglycemic (NG) transplant recipients, and from recipients with pre-existing type 2 DM (PTDM)
Project description:To evaluate whether serum micoRNAs can be biomarkers for diagnosis of type 1 diabetes mellitus, we analyzed the serum microRNA expression profiles in 6 patients with new-onset type 1 diabetes mellitus and 6 age- and gender-matched healthy controls. A difference was observed in 31 miRNAs between the patients and controls (fold change ≥ 2, P < 0.05)
Project description:Gestational diabetes mellitus (GDM), one of the most common pregnancy complications, affects approximately 6% of pregnancies. This study attempted to use the data-independent acquisition (DIA) mass spectrometry (MS) to identify the potential protein biomarkers from the placental tissues from the GDM patients and the normal pregnant women.