ArticleScientific reports2016
Disease-specific classification using deconvoluted whole blood gene expression.
Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Integrated Analysis of Gene Co-Expression Network and Prediction Model Indicates Immune-Related Roles of the Identified Biomarkers in Sepsis and Sepsis-Induced Acute Respiratory Distress Syndrome.Frontiers in immunology · 2022Article
- Infiltrating T-cell abundance combined with EMT-related gene expression as a prognostic factor of colon cancer.Bioengineered · 2021Article
- The Human Blood Transcriptome in a Large Population Cohort and Its Relation to Aging and Health.Frontiers in big data · 2020Article
- Peripheral Blood RNA Levels ofCirculation. Genomic and precision medicine · 2019Article
- EpistasisRank and EpistasisKatz: interaction network centrality methods that integrate prior knowledge networks.Bioinformatics (Oxford, England) · 2019Article
- Computational deconvolution of synovial tissue cellular composition: presence of adipocytes in synovial tissue decreased during arthritis pathogenesis and progression.Physiological genomics · 2019Article
- Genome-Wide Patterns of Gene Expression in a Wild Primate Indicate Species-Specific Mechanisms Associated with Tolerance to Natural Simian Immunodeficiency Virus Infection.Genome biology and evolution · 2019Article
- RNA sequencing of identical twins discordant for autism reveals blood-based signatures implicating immune and transcriptional dysregulation.Molecular autism · 2019Article
- Novel eosinophilic gene expression networks associated with IgE in two distinct asthma populations.Clinical and experimental allergy : journal of the British Society for Allergy and Clinical Immunology · 2018Article
- Deep proteomic network analysis of Alzheimer's disease brain reveals alterations in RNA binding proteins and RNA splicing associated with disease.Molecular neurodegeneration · 2018Article
- EMT- and stroma-related gene expression and resistance to PD-1 blockade in urothelial cancer.Nature communications · 2018Article
- A miRNA Host Response Signature Accurately Discriminates Acute Respiratory Infection Etiologies.Frontiers in microbiology · 2018Article
- Systems immunology: just getting started.Nature immunology · 2017Review
- Robustification of Naïve Bayes Classifier and Its Application for Microarray Gene Expression Data Analysis.BioMed research international · 2017Article
- The frontline of immune response in peripheral blood.PloS one · 2017Article
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3 authors.
Funding
Abstract
Blood-based biomarker assays have an advantage in being minimally invasive. Diagnostic and prognostic models built on peripheral blood gene expression have been reported for various types of disease. However, most of these studies focused on only one disease type, and failed to address whether the identified gene expression signature is disease-specific or more widely applicable across diseases. We conducted a meta-analysis of 46 whole blood gene expression datasets covering a wide range of diseases and physiological conditions. Our analysis uncovered a striking overlap of signature genes shared by multiple diseases, driven by an underlying common pattern of cell component change, specifically an increase in myeloid cells and decrease in lymphocytes. These observations reveal the necessity of building disease-specific classifiers that can distinguish different disease types as well as normal controls, and highlight the importance of cell component change in deriving blood gene expression based models. We developed a new strategy to develop blood-based disease-specific models by leveraging both cell component changes and cell molecular state changes, and demonstrate its superiority using independent datasets.
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