Urinary sediment transcriptomic and longitudinal data to investigate renal function decline in type 1 diabetes
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PROVIDER: PRJNA590268 | ENA |
REPOSITORIES: ENA
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Project description:Using a discovery/validation approach we investigated associations between a panel of genes selected from a transcriptomic study and the renal function decline across time in a cohort of type 1 diabetes patients.
2019-11-19 | GSE140627 | GEO
Project description:Introduction: Using a discovery/validation approach we investigated associations between a panel of genes selected from a transcriptomic study and the estimated glomerular filtration rate (eGFR) decline across time in a cohort of type 1 diabetes (T1D) patients. Experimental: Urinary sediment transcriptomic was performed to select highly modulated genes in T1D patients with rapid eGFR decline (decliners) vs. patients with stable eGFR (non-decliners). The selected genes were validated in samples from a T1D cohort (n = 54, mean diabetes duration of 21 years, 61% women) followed longitudinally for a median of 12 years in a Diabetes Outpatient Clinic. Results: In the discovery phase, the transcriptomic study revealed 158 genes significantly different between decliners and non-decliners. Ten genes increasingly up or down-regulated according to renal function worsening were selected for validation by qRT-PCR; the genes CYP4F22, and PMP22 were confirmed as differentially expressed comparing decliners vs. non-decliners after adjustment for potential confounders. CYP4F22, LYPD3, PMP22, MAP1LC3C, HS3ST2, GPNMB, CDH6, and PKD2L1 significantly modified the slope of eGFR in T1D patients across time. Conclusions: Eight genes identified as differentially expressed in the urinary sediment of T1D patients presenting different eGFR decline rates significantly increased the accuracy of predicted renal function across time in the studied cohort. These genes may be a promising way of unveiling novel mechanisms associated with diabetic kidney disease progression.
| S-EPMC7204506 | biostudies-literature
Project description:Rationale: Molecular markers of disease progression in idiopathic pulmonary fibrosis are needed. Objective: Derive and validate a blood transcriptomic predictor of forced vital capacity (FVC) decline. Methods: A training cohort (n=74) of IPF patients was stratified according to the presence of progressive disease, defined as ≥10% relative decline in FVC over 12 months. Baseline to 4-month within-patient changes in gene expression were correlated with categorical FVC decline. Genes predictive of FVC decline were identified by two-group comparison with false discovery rate <5% followed by logistic LASSO regression and 10-Fold Cross-Validation for gene list prioritization. Independent validation cohorts with differing transcriptome assay platforms and blood transcriptome sampling times from UChicago (n=27), UPMC (n=35), and Imperial (n=24) underwent receiver operating characteristic with area under the curve (AUC) analyses for validation. Results: A longitudinally-derived FVC-gene predictor accurately discriminated most patients with stable and progressive IPF across four independent IPF cohorts with variable transcriptomic assay platforms and sampling times. The FVC-gene predictorand demonstrated sensitivity and specificity of 74.3% and 82.4% in the combined replication cohort. The likelihood ratio, LR+ and LR- were 4.11 and 0.32, respectively. TGF-beta was the highest-ranking canonical pathway by Gene Set Enrichment Analysis. An approach using longitudinal gene expression changes approach dramatically reduced within-group variation compared to cross-sectional expression for improved prediction modeling. Conclusions: This novel FVC-gene predictor developed from short-term longitudinal gene expression changes successfully discriminates most patients with high likelihood of one-year 10% FVC decline. This tool may better reflect disease activity and prove useful for predictive enrichment of clinical trial populations.
2019-09-30 | GSE133298 | GEO
Project description:Urinary extracellular vesicles (EVs) are an attractive source for the detection of disease biomarkers. Mass spectrometry (MS) based proteomics is increasingly used for urinary EV proteome profiling and protein biomarker discovery. However, little is known about the consistency and stability of urinary EV proteins within individuals over time and between different individuals. In this study we profiled the urinary EV proteome of 8 healthy individuals over 6 months at 9 timepoints (total 72 samples) using DIA-MS. We identified a total of 1802 proteins with high correlation amongst all samples. While a minor fraction (10%) of the total urinary EV proteome was shown to play a role in determining personal expression patterns, most of the urinary EV proteins was found to be stable with >90% of the proteins detected in more than 1 person at all timepoints. The variability of urinary EV proteome between different individuals was shown to be significantly higher than personal variation as a result of a small subset (<20%) of proteins. The core interaction network of proteins identified in all individuals revealed EV proteins involved in signaling and localization and sub-clusters enriched for glycolytic activity, protein synthesis, and immune function. Gender-specific expression patterns were detected in the urinary EV proteome, mostly related to hormonal and reproduction pathways. In summary, our findings indicate that the urinary EV proteome is stable in longitudinal samples of healthy subjects, underscoring its potential as a reliable source for protein biomarkers.
2021-09-09 | PXD022983 | Pride
Project description:Longitudinal Blood Transcriptomic Changes Predict Lung Function Decline in Idiopathic Pulmonary Fibrosis
| PRJNA548528 | ENA
Project description:The Rationale: Molecular markers of disease activity that are predictive of forced vital capacity (FVC) progression in idiopathic pulmonary fibrosis are needed. Objectives: Develop a predictor using longitudinal within-patient gene expression differences (ΔGE) in peripheral blood mononuclear cells (PBMC) to predict of FVC progression. Methods: Patients in the training cohort (n=74) experiencing ≥10% relative reduction in FVC% of predicted over 12 months were categorized as progressors in contrast to the remaining stable patients. Baseline to 4-month within-patient ΔGE were correlated with FVC status. FVC-predictor genes were prioritized by two-group comparison with FDR<5%, logistic LASSO regression with p<0.05, and 10-Fold Cross-Validation with ≥50% support. Receiver operating characteristic with area under the curve (AUC) analyses were conducted in training subsets and independent validation cohorts from UChicago (n=27), UPMC (n=35), and Imperial (n=24) where different transcriptome assay platforms and varying transcriptome sampling times were used to derive ΔGE. Results: Intra-subject Compared to cross-sectional analysis of baseline GE, our longitudinal ΔGE variation approach demonstratedlargely reduced within-group sample variation and increased statistic power fin progressor and stable groups for prediction model development. A 25-gene FVC-predictor separated “progressors” from “stable” by Principal Component Analysis in the training and subsets of the training cohort. The resulting FVC-predictor consistently demonstrated high discriminatory performance independent of transcriptome assay platforms and varying sampling times in validation cohorts (AUC= 0.77-0.80). TGF beta was the highest-ranking canonical pathway by Gene Set Enrichment Analysis. Conclusions: Our novel short-term longitudinal within-patient ΔGE approach identified a FVC-predictor which may reflect disease activity and prove to be a reliable biomarker predictive of future FVC decline.
2019-09-30 | GSE132607 | GEO
Project description:Background: Renal cell carcinoma (RCC) accounts for about 2% of all cancers. Renal biopsy is the gold standard among the diagnostic tools, but it is invasive and not suitable for all patients. Therefore, new reliable and non-invasive biomarkers for ccRCC detection are required. Secretion of extracellular vesicles (EVs), containing RNA molecules that can be transferred between cells, seems to be a general characteristic of malignant transformation. Consistently, cancer-derived EVs are enriched in the blood, urine and various malignant effusions of cancer patients. Therefore, urinary samples can be a non-invasive approach for discovering diagnostic biomarkers. Methods: We enrolled 33 clear-cell RCC (ccRCC) patients and 22 healthy subjects (HS), age and sex-matched, for urine collection and extracellular vesicles isolation by differential centrifugation. Transcriptional profiles of urinary EVs from 12 patients with ccRCC and 11 HS were generated using the Illumina HumanHT-12 v4 BeadChip oligonucleotide arrays. Microarray analysis led to the identification of RNA that were then validated using RT-qPCR. Results: We showed for the first time that urinary exosomal shuttle RNA (esRNA) was significantly different in ccRCC patients compared to HS and we identified three EVs esRNA involved in the tumor biology that are potentially suitable as non-invasive biomarkers. GSTA1, CEBPA and PCBD1 RNA levels decreased in urinary EVs of patients compared to HS. After 1 month post-operation, the levels of RNA increased to reach the normal level. Conclusions: This study suggests, for the first time, the potential use of the RNA content of urinary EVs to provide a non-invasive first step to diagnose the ccRCC. Total RNA obtained from urinary extracellular vesicles isolated from ccRCC patients and healthy subjects.
2016-09-01 | E-GEOD-72922 | biostudies-arrayexpress
Project description:Diabetes mellitus (DM) is a leading cause of chronic kidney disease and the pathobiology of diabetic nephropathy is widely studied. Less, however, is known about urinary bladder disease in DM despite dysfunctional voiding being a common clinical problem. We hypothesised that diabetic cystopathy would have a characteristic molecular signature, due to the adaptive response to increased urine load combined with the metabolic impacts of DM. To distinguish the consequences of DM from polyuria we compared bladders of untreated control, diabetic (streptozotocin-induced) and sucrose-treated male Wistar rats after 16 weeks using gene array
2021-07-17 | E-MTAB-9255 | biostudies-arrayexpress
Project description:Longitudinal Blood Transcriptomic Changes Predict Lung Function Decline in patients with Idiopathic Pulmonary Fibrosis
| PRJNA551014 | ENA
Project description:Phthalates are ubiquitous pollutants in the environment; however, the mechanisms of phthalate-associated reproductive disorders in men are not fully understood. The aim of this study is to investigate associations between urinary phthalate metabolite concentrations and sperm DNA methylation. The study was conducted on 697 men from three prospective pregnancy cohorts: Longitudinal Investigation of Fertility and the Environment (LIFE) Study, Sperm Environmental Epigenetics and Development Study (SEEDS), and Environment and Reproductive Health (EARTH) Study.
2024-10-14 | GSE267620 | GEO