Expression mRNA and miRNA data from human postmortem putamen samples measured using the NanoString nCounter platform
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE77668 | GEO | 2016/06/30
SECONDARY ACCESSION(S): PRJNA311171
REPOSITORIES: GEO
Similar Datasets
Project description:Background: Molecular adaptations in the striatum mediated by dopamine (DA) denervation or Levodopa (L-dopa) treatment have been implicated with the motor deficits found in Parkinson’s disease (PD). Alterations in glutamatergic neurotransmission and anti-oxidant mechanisms are reported to play important roles in mediating these changes. However, the mechanisms mediating the molecular adaptations in the striatum are not well understood. In recent years, microRNAs (miRNAs) have been recognized as potent post-transcriptional regulators of gene expression with fundamental roles in numerous biological processes. miRNAs are known to influence the development and maintenance of striatal neurons. Therefore, we sought to determine the genome-wide expression levels of miRNAs in PD striatal tissues. Methods: Using a digital gene expression platform to quantify miRNA levels, we compared the expression of 800 miRNAs in human postmortem putamen tissues from PD patients and controls. Results: We detected the expression of approximately 250 miRNAs in postmortem human putamen samples collected from patients with PD and healthy controls. There was an abundance of a subset of 17 miRNAs (10 up- and 7 down-regulated) differing substantially between PD and the control tissues. Conclusions: We identified deregulated miRNAs most likely associated with altered striatal functions found in PD. This approach may provide insight into pathogenesis and additional therapeutic targets for the development novel treatment strategies for the disease.
2016-06-30 | GSE77667 | GEO
Project description:Background: Molecular adaptations in the striatum mediated by dopamine (DA) denervation or Levodopa (L-dopa) treatment have been implicated with the motor deficits found in Parkinson’s disease (PD). Alterations in glutamatergic neurotransmission and anti-oxidant mechanisms are reported to play important roles in mediating these changes. However, the mechanisms mediating the molecular adaptations in the striatum are not well understood. In recent years, microRNAs (miRNAs) have been recognized as potent post-transcriptional regulators of gene expression with fundamental roles in numerous biological processes. miRNAs are known to influence the development and maintenance of striatal neurons. To determine the contribution of miRNAs in molecular adaptations found in PD, we screened the expression of 800 miRNAs in postmortem striatum samples obtained from PD and neurologically normal controls. We detected the expression of approximately 250 miRNAs in postmortem human putamen samples collected from patients with PD and healthy controls. There was an abundance of a subset of 17 miRNAs (10 up- and 7 down-regulated) differing substantially between PD and the control, suggesting that miRNAs are altered in the striatum during the course of PD. Computational analysis show that many of these miRNAs targets pro-inflammatory factors in the striatum. Therefore, we sought to detrmine the expression of experimentally validated pro-inflammatory transcripts in PD striatum. Methods: Using a digital gene expression platform to quantify 134 gene transcripts, we compared human postmortem putamen tissues from patients with PD and neurologically normal controls. Results: We identified deregulated expression of 10 gene transcripts (4 up- and 6 down-regulated mRNAs) in postmortem human putamen samples collected fromPD patients compared to controls. The expression of these genes negative correlates with the expression of many of the differentially epxressed miRNAs. Moreover, many of these genes are predicted targets of the differentially expressed miRNAs. Conclusions: We identified deregulated mRNAs most likely associated with anti-oxidant mechanims in PD striatum. This approach may provide insights into pathogenesis of the disease.
2016-06-30 | GSE77666 | GEO
Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series
2016-06-30 | E-GEOD-77668 | biostudies-arrayexpress
Project description:Background: Molecular adaptations in the striatum mediated by dopamine (DA) denervation or Levodopa (L-dopa) treatment have been implicated with the motor deficits found in Parkinsonâ??s disease (PD). Alterations in glutamatergic neurotransmission and anti-oxidant mechanisms are reported to play important roles in mediating these changes. However, the mechanisms mediating the molecular adaptations in the striatum are not well understood. In recent years, microRNAs (miRNAs) have been recognized as potent post-transcriptional regulators of gene expression with fundamental roles in numerous biological processes. miRNAs are known to influence the development and maintenance of striatal neurons. Therefore, we sought to determine the genome-wide expression levels of miRNAs in PD striatal tissues. Methods: Using a digital gene expression platform to quantify miRNA levels, we compared the expression of 800 miRNAs in human postmortem putamen tissues from PD patients and controls. Results: We detected the expression of approximately 250 miRNAs in postmortem human putamen samples collected from patients with PD and healthy controls. There was an abundance of a subset of 17 miRNAs (10 up- and 7 down-regulated) differing substantially between PD and the control tissues. Conclusions: We identified deregulated miRNAs most likely associated with altered striatal functions found in PD. This approach may provide insight into pathogenesis and additional therapeutic targets for the development novel treatment strategies for the disease. Human postmortem putamen tissues from 12 patients with PD symptoms and 12 neurologically normal controls. Samples were obtained from the Human Brain and Spinal Fluid Resource Center, Los Angeles, CA through NIH NeuroBioBank, and stored at -80°C until RNA isolation. Total RNA was extracted using the miRVana RNA isolation kit, following the manufacturerâ??s instructions (Ambion). Using 225ng total RNA, miRNA levels were assayed by direct digital detection using Nanostring miRNA assay kits (Nanostring Technologies).
2016-06-30 | E-GEOD-77667 | biostudies-arrayexpress
Project description:Background: Molecular adaptations in the striatum mediated by dopamine (DA) denervation or Levodopa (L-dopa) treatment have been implicated with the motor deficits found in Parkinsonâs disease (PD). Alterations in glutamatergic neurotransmission and anti-oxidant mechanisms are reported to play important roles in mediating these changes. However, the mechanisms mediating the molecular adaptations in the striatum are not well understood. In recent years, microRNAs (miRNAs) have been recognized as potent post-transcriptional regulators of gene expression with fundamental roles in numerous biological processes. miRNAs are known to influence the development and maintenance of striatal neurons. To determine the contribution of miRNAs in molecular adaptations found in PD, we screened the expression of 800 miRNAs in postmortem striatum samples obtained from PD and neurologically normal controls. We detected the expression of approximately 250 miRNAs in postmortem human putamen samples collected from patients with PD and healthy controls. There was an abundance of a subset of 17 miRNAs (10 up- and 7 down-regulated) differing substantially between PD and the control, suggesting that miRNAs are altered in the striatum during the course of PD. Computational analysis show that many of these miRNAs targets pro-inflammatory factors in the striatum. Therefore, we sought to detrmine the expression of experimentally validated pro-inflammatory transcripts in PD striatum. Methods: Using a digital gene expression platform to quantify 134 gene transcripts, we compared human postmortem putamen tissues from patients with PD and neurologically normal controls. Results: We identified deregulated expression of 10 gene transcripts (4 up- and 6 down-regulated mRNAs) in postmortem human putamen samples collected fromPD patients compared to controls. The expression of these genes negative correlates with the expression of many of the differentially epxressed miRNAs. Moreover, many of these genes are predicted targets of the differentially expressed miRNAs. Conclusions: We identified deregulated mRNAs most likely associated with anti-oxidant mechanims in PD striatum. This approach may provide insights into pathogenesis of the disease. Human postmortem putamen tissues from 12 patients with PD symptoms and 12 neurologically normal controls were used in the study. Samples were obtained from the Human Brain and Spinal Fluid Resource Center, Los Angeles, CA through NIH NeuroBioBank, and stored at -80°C until RNA isolation. Total RNA was extracted using the mirVana RNA isolation kit, following the manufacturerâs instructions (Ambion). Using 225ng total RNA, mRNA levels were assayed by direct digital detection using Nanostring nCounter assay kits (Nanostring Technologies).
2016-06-30 | E-GEOD-77666 | biostudies-arrayexpress
Project description:Expression mRNA and miRNA data from human postmortem putamen samples measured using the NanoString nCounter platform
| PRJNA311171 | ENA
Project description:Background: The diagnosis of Parkinson’s disease (PD) is usually not established until advanced neurodegeneration leads to clinically detectable symptoms. Previous blood PD transcriptome studies show low concordance, possibly due to the use of microarray technology, which has high measurement variation. The Leucine-rich repeat kinase 2 (LRRK2) G2019S mutation predisposes to PD. Using preclinical and clinical studies, we sought to develop a novel statistically motivated transcriptomic-based approach to identify a molecular signature in the blood of Ashkenazi Jewish PD patients including LRRK2 mutation carriers. Methods: Using a digital gene expression platform to quantify 175 mRNA markers with low coefficients of variation (CV), we first compared whole blood transcript levels in mouse models 1) over-expressing wild-type (WT) LRRK2, 2) overexpressing G2019S LRRK2, 3) lacking LRRK2 (knockout), 4) and in WT controls. We then studied an Ashkenazi Jewish cohort of 34 symptomatic PD patients (both WT LRRK2 and G2019S LRRK2) and 32 asymptomatic controls. Results: The expression profiles distinguished the 4 mouse groups with different genetic background. In patients, we detected significant differences in blood transcript levels both between individuals differing in LRRK2 genotype and between PD patients and controls. Discriminatory PD markers included genes associated with innate and adaptive immunity and inflammatory disease. Notably, gene expression patterns in L-DOPA-treated PD patients were significantly closer to those of healthy controls in a dose-dependent manner. Conclusions: We identify whole blood low CV mRNA signatures correlating with LRRK2 genotype and with PD disease state. This approach may provide insight into pathogenesis and a route to early disease detection.
2015-10-17 | GSE62470 | GEO
Project description:Background: The diagnosis of Parkinson’s disease (PD) is usually not established until advanced neurodegeneration leads to clinically detectable symptoms. Previous blood PD transcriptome studies show low concordance, possibly due to the use of microarray technology, which has high measurement variation. The Leucine-rich repeat kinase 2 (LRRK2) G2019S mutation predisposes to PD. Using preclinical and clinical studies, we sought to develop a novel statistically motivated transcriptomic-based approach to identify a molecular signature in the blood of Ashkenazi Jewish PD patients including LRRK2 mutation carriers. Methods: Using a digital gene expression platform to quantify 175 mRNA markers with low coefficients of variation (CV), we first compared whole blood transcript levels in mouse models 1) over-expressing wild-type (WT) LRRK2, 2) overexpressing G2019S LRRK2, 3) lacking LRRK2 (knockout), 4) and in WT controls. We then studied an Ashkenazi Jewish cohort of 34 symptomatic PD patients (both WT LRRK2 and G2019S LRRK2) and 32 asymptomatic controls. Results: The expression profiles distinguished the 4 mouse groups with different genetic background. In patients, we detected significant differences in blood transcript levels both between individuals differing in LRRK2 genotype and between PD patients and controls. Discriminatory PD markers included genes associated with innate and adaptive immunity and inflammatory disease. Notably, gene expression patterns in L-DOPA-treated PD patients were significantly closer to those of healthy controls in a dose-dependent manner. Conclusions: We identify whole blood low CV mRNA signatures correlating with LRRK2 genotype and with PD disease state. This approach may provide insight into pathogenesis and a route to early disease detection.
2015-10-17 | GSE62469 | GEO
Project description:This SuperSeries is composed of the SubSeries listed below.
2015-10-17 | GSE62471 | GEO
Project description:BackgroundDespite genomic simplicity, recent studies have reported at least 3 major atypical teratoid rhabdoid tumor (ATRT) subgroups with distinct molecular and clinical features. Reliable ATRT subgrouping in clinical settings remains challenging due to a lack of suitable biological markers, sample rarity, and the relatively high cost of conventional subgrouping methods. This study aimed to develop a reliable ATRT molecular stratification method to implement in clinical settings.MethodsWe have developed an ATRT subgroup predictor assay using a custom genes panel for the NanoString nCounter System and a flexible machine learning classifier package. Seventy-one ATRT primary tumors with matching gene expression array and NanoString data were used to construct a multi-algorithms ensemble classifier. Additional validation was performed using an independent gene expression array against the independently generated dataset. We also analyzed 11 extra-cranial rhabdoid tumors with our classifier and compared our approach against DNA methylation classification to evaluate the result consistency with existing methods.ResultsWe have demonstrated that our novel ensemble classifier has an overall average of 93.6% accuracy in the validation dataset, and a striking 98.9% accuracy was achieved with the high-prediction score samples. Using our classifier, all analyzed extra-cranial rhabdoid tumors are classified as MYC subgroups. Compared with the DNA methylation classification, the results show high agreement, with 84.5% concordance and up to 95.8% concordance for high-confidence predictions.ConclusionsHere we present a rapid, cost-effective, and accurate ATRT subgrouping assay applicable for clinical use.
| S-EPMC10825849 | biostudies-literature