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Peripheral blood gene expression as a biomarker for early detection of Alzheimer’s disease

ABSTRACT: To further development of our gene expression profile of Alzheimer's disease, we have employed whole genome microarray expression profiling as a discovery platform to identify genes with the potential biomarker for early disease detection

ORGANISM(S): Homo sapiens

PROVIDER: GSE85426 | GEO | 2016/08/11

SECONDARY ACCESSION(S): PRJNA338435

REPOSITORIES: GEO

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Peripheral blood gene expression as a biomarker for early detection of Alzheimerâ??s disease

Project description:To further development of our gene expression profile of Alzheimer's disease, we have employed whole genome microarray expression profiling as a discovery platform to identify genes with the potential biomarker for early disease detection Total RNA from peripheral blood cells was extracted, reverse-transcribed and labelled, then analysed for gene expression using GeneSpring GX12 (Agilent Technologies, USA). About 180 samples (AD=90, Non-demented control=90) was used for microarray analysis.

2016-08-11 | E-GEOD-85426 | biostudies-arrayexpress

Tracking the progression of Alzheimer’s disease with peripheral blood-based biomarkers

Project description:We investigate the gene expression signature of peripheral blood monocytes during the progression of Alzheimer's disease. We profiled gene expression in the mouse cortex using data obtained from RNA-seq of three individuals at 6-months old and three individuals at 24-months old.

2022-11-03 | GSE216918 | GEO

Expression profiling of peripheral blood mononuclear cell

Project description:This SuperSeries is composed of the following non-comparable subset Series which represent two different studies: GSE4226: Alzheimer's Disease peripheral blood mononuclear cell expression GSE4227: Alzheimer's disease and GSTM3 [Val255] single nucleotide polymorphism linkage with peripheral BMC expression Keywords: SuperSeries Refer to individual Series

2010-06-24 | E-GEOD-4229 | biostudies-arrayexpress

Detection of Alzheimer’s Disease at Mild Cognitive Impairment and Disease Progression Using Autoantibodies as Blood-based Biomarkers

Project description:Human serum samples from Alzheimer's disease driven mild cognitive impairment and non-diseased controls were probed onto human protein microarrays in order to identify differentially expressed autoantibody biomarkers that could be used as diagnostic indicators. Other neurodegenerative and non-neurodegenerative diseases were also used to help measure the specificity of the selected biomarkers.

2016-05-03 | GSE74763 | GEO

Deep undepleted human serum proteome profiling toward biomarker discovery for Alzheimer’s disease

Project description:Alzheimer's disease (AD) is a neurodegenerative disease, the most common cause of dementia in elderly persons. Accumulation of amyloid plaques in the brain is a characteristic of AD. The requirements for a biomarker include the ability to measure a pathologic process, predict outcome, distinguish disease or measure a pharmacological response to a drug treatment or therapeutic intervention. However, there are no reliable blood based biomarkers for AD. Serum-based protein measurement is a routine practice for biomarkers in human disease, but comprehensive profiling of serum proteome is often masked by the twenty most abundant proteins and impacted by large dynamic range. The commonly used depletion method can alleviate the challenge but introduce additional experimental variation. Here we present a deep analysis of un-depleted human serum proteome by combining 11-plex TMT labeling, exhaustive 2D liquid chromatography fractionation, and high resolution tandem mass spectrometry. This platform is capable of identifying 4,500 protein components, covering 6 orders of dynamic range, representing one of the deepest serum proteome datasets. Finally, a subset of proteins, show statistically significant difference between AD and control samples, which may serve as biomarker candidates.

2019-04-23 | PXD011482 | Pride

Plasma microRNA biomarker detection for mild cognitive impairment using differential correlation analysis

Project description:Background: Mild cognitive impairment (MCI) is an intermediate state between normal aging, and Alzheimer’s disease, and other dementias. Early detection of dementia, and MCI, is a crucial issue in terms of secondary prevention. Blood biomarker detection is a possible way for early detection of MCI. Although disease biomarkers are detected by, in general, using single molecular analysis such as t-test, another possible approach is based on interaction between molecules. Results: Differential correlation analysis, which detects difference on correlation of two variables in case/control study, was carried out to the dataset with 745 microRNAs (miRNAs) from plasma samples of 30 age-matched controls and 23 MCI patients in Japan. The 20 pairs of miRNAs, which consist of 20 miRNAs, were selected as MCI markers. Two pairs of miRNAs (hsa-miR-191 and hsa-miR-101, and hsa-miR-103 and hsa-miR-222) out of 20 attained the highest area under the curve (AUC) value of 0.962 for MCI detection. Other two miRNA pairs that include hsa-miR-191 and hsa-miR-125b also attained high AUC value of ≥ 0.95. Pathway analysis was performed to the MCI markers for further understanding of biological implications. As a result, collapsed correlation on hsa-miR-191 and emerged correlation on hsa-miR-125b may have key role in MCI, and dementia progression. Conclusion: Differential correlation analysis, a bioinformatics tool to elucidate complicated and interdependent biological systems behind diseases, detects effective MCI markers that cannot be found by single molecule analysis such as t-test.

2016-12-10 | GSE90828 | GEO

Detection of Chemotherapy-Resistant Pancreatic Cancer Using a Glycan Biomarker

Project description:Detection of Chemotherapy-Resistant Pancreatic Cancer Using a Glycan Biomarker

| PRJNA611767 | ENA

Inflammatory gene expression profiling in peripheral blood from patients with Alzheimer’s disease reveals key pathways and hub genes with potential diagnostic utility

Project description:Late-onset Alzheimer disease (LOAD) is the most common neurodegenerative disorder worldwide. Recent studies have shown that differential expression in genes (DEG) related to inflammatory response may result associated with disease onset and progression. This study aimed to explore the molecular pathogenesis of LOAD-related inflammation through next-generation sequencing, to assess RNA expression profiles in Alzheimer's disease patients and healthy controls.

2021-03-13 | GSE168813 | GEO

Circulating Cell-Free RNA in Blood as a Host Response Biomarker for the Detection of Tuberculosis [validation_data]

Project description:Tuberculosis (TB) remains a leading cause of death from an infectious disease worldwide. This is partly due to a lack of tools to effectively screen and triage individuals with potential TB. Whole blood RNA signatures have been extensively studied as potential biomarkers for TB, but they have failed to meet the World Health Organization's (WHOs) optimal target product profiles (TPPs) for a non-sputum triage or diagnostic test. In this study, we investigated the utility of plasma cell-free RNA (cfRNA) as a host response biomarker for TB. We used RNA profiling by sequencing to analyze plasma samples from individuals with a cough lasting at least two weeks, who were seen at outpatient TB clinics in Uganda, Vietnam, and the Philippines. We split the samples into a discovery set for model training and testing, and reserved a validation set from a separate cohort to validate the model performance. We trained 15 machine learning classification models and developed a 6-gene signature that has a high performance in differentiating TB positive and negative individuals (Area Under the Curve, AUC = 0.95, 0.92, 0.95 for the test, training and validation sets respectively). This 6-gene signature exceeds the optimal WHO TPPs for a TB triage test (sensitivity: 97.1% [95% CI: 80.9-100%], specificity: 85.2% [95% CI: 72.4-100%]) and was robust to differences in geographic location, sample collection, and HIV status. Analysis of matched whole blood samples from the validation cohort highlighted the differences in origin of plasma and whole blood RNA. Overall, our results demonstrate the utility of plasma cfRNA for the detection of TB and suggest the potential for a point-of-care, gene expression-based assay to aid in early detection of TB.

2024-02-06 | GSE255074 | GEO

Circulating Cell-Free RNA in Blood as a Host Response Biomarker for the Detection of Tuberculosis [test_data]

2024-02-06 | GSE255073 | GEO

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