Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR30918488.fastq.gz | Fastqsanger.gz | |||
| SRR30918489.fastq.gz | Fastqsanger.gz | |||
| SRR30918490.fastq.gz | Fastqsanger.gz |
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Project description:Objective. To identify gene expression differences in peripheral blood from patients with early and late onset juvenile idiopathic arthritis (JIA). Methods. Peripheral blood mononuclear cells (PBMC) were isolated from 56 healthy controls and 104 patients with recent onset JIA (39 persistent oligoarticular, 45 RF-polyarticular, and 20 systemic). Poly(A) RNA was amplified and labeled using NuGEN Ovation, and gene expression assessed with Affymetrix HG-U133 Plus 2.0 GeneChips®. Results. A total of 832 probe sets revealed gene expression differences (false-discovery rate 5%) in PBMC from children with oligoarticular JIA whose disease began before 6 years of age (age at onset [AaO] <6; early onset), compared to subjects whose disease began at 6 years of age or later (AaO ≥6; late onset). In early onset patients there was greater expression of genes related to B-cells, and lesser expression of genes related to cells of the myeloid lineage. Support Vector Machine algorithms identified samples from early or late onset oligoarticular (97% accuracy) or polyarticular (89% accuracy) JIA patients, but not systemic JIA patients or healthy controls. Principal component analysis showed that the major classifier of samples was AaO regardless of whether they had oligoarticular or polyarticular JIA. Conclusion. PBMC gene expression analysis reveals biologic differences between early and late onset JIA patients independent of classification based on the number of joints involved. These data suggest AaO may be an important parameter to consider in JIA classification. Furthermore, different pathologic mechanisms may influence AaO, and understanding these processes may lead to improved treatment of JIA.
2011-02-14 | GSE20307 | GEO
Project description:Objective. To identify gene expression differences in peripheral blood from patients with early and late onset juvenile idiopathic arthritis (JIA). Methods. Peripheral blood mononuclear cells (PBMC) were isolated from 56 healthy controls and 104 patients with recent onset JIA (39 persistent oligoarticular, 45 RF-polyarticular, and 20 systemic). Poly(A) RNA was amplified and labeled using NuGEN Ovation, and gene expression assessed with Affymetrix HG-U133 Plus 2.0 GeneChips®. Results. A total of 832 probe sets revealed gene expression differences (false-discovery rate 5%) in PBMC from children with oligoarticular JIA whose disease began before 6 years of age (age at onset [AaO] <6; early onset), compared to subjects whose disease began at 6 years of age or later (AaO ?6; late onset). In early onset patients there was greater expression of genes related to B-cells, and lesser expression of genes related to cells of the myeloid lineage. Support Vector Machine algorithms identified samples from early or late onset oligoarticular (97% accuracy) or polyarticular (89% accuracy) JIA patients, but not systemic JIA patients or healthy controls. Principal component analysis showed that the major classifier of samples was AaO regardless of whether they had oligoarticular or polyarticular JIA. Conclusion. PBMC gene expression analysis reveals biologic differences between early and late onset JIA patients independent of classification based on the number of joints involved. These data suggest AaO may be an important parameter to consider in JIA classification. Furthermore, different pathologic mechanisms may influence AaO, and understanding these processes may lead to improved treatment of JIA. Methods. Peripheral blood mononuclear cells (PBMC) were isolated from 56 healthy controls and 104 patients with recent onset JIA (39 persistent oligoarticular, 45 RF-polyarticular, and 20 systemic). Poly(A) RNA was amplified and labeled using NuGEN Ovation, and gene expression assessed with Affymetrix HG-U133 Plus 2.0 GeneChips®.
2011-02-14 | E-GEOD-20307 | biostudies-arrayexpress
Project description:We created a fetal lamb model of hypoplastic left heart syndrome (HLHS), by implanting coils in the left atrium in mid-gestation. We performed bulk RNA sequencing of left ventricles (LV), right ventricles (RV), ascending aortae (AAo) and pulmonary arteries (PA). Single nucleus RNA sequencing was performed on LV free wall tissue (n = 4 coiled samples, n = 3 controls).
2023-05-31 | E-MTAB-12327 | biostudies-arrayexpress
Project description:We created a fetal lamb model of hypoplastic left heart syndrome (HLHS), by implanting coils in the left atrium in mid-gestation. We performed bulk RNA sequencing of left ventricles (LV), right ventricles (RV), ascending aortae (AAo) and pulmonary arteries (PA). Single nucleus RNA sequencing was performed on LV free wall tissue (n = 4 coiled samples, n = 3 controls).
2023-05-31 | E-MTAB-12230 | biostudies-arrayexpress
Project description:Alzheimer’s disease (AD) manifested before age 65 is commonly referred to as early-onset AD (EOAD). While the majority (> 90%) of EOAD cases are not caused by autosomal-dominant mutations in PSEN1, PSEN2, and APP, they do have a higher heritability (92–100%) than sporadic late-onset AD (LOAD, 70%). Although the endpoint clinicopathological changes, i.e., Aβ plaques, tau tangles, and cognitive decline, are common across EOAD and LOAD, the disease progression is highly heterogeneous. This heterogeneity, leading to temporally distinct age at onset (AAO) and stages of cognitive decline, may be caused by myriad combinations of distinct disease-associated molecular mechanisms. We and others have used transcriptome profiling in AD patient-derived neuron models of autosomal-dominant EOAD and sporadic LOAD to identify disease endotypes. Further, analyses of large postmortem brain cohorts demonstrate that only one-third of AD patients show hallmark disease endotypes like increased inflammation and decreased synaptic signaling. Areas of the brain less affected by AD pathology at early disease stages—such as the primary visual cortex—exhibit similar transcriptomic dysregulation as those regions traditionally affected and, therefore, may offer a view into the molecular mechanisms of AD without the associated inflammatory changes and gliosis induced by pathology. To this end, we analyzed AD patient samples from the primary visual cortex (19 EOAD, 20 LOAD) using transcriptomic signatures to identify patient clusters and disease endotypes. Interestingly, although the clusters showed distinct combinations and severity of endotypes, each patient cluster contained both EOAD and LOAD cases, suggesting that AAO may not directly correlate with the identity and severity of AD endotypes.
2022-10-12 | GSE203206 | GEO