ArticleBMC medical genomics2015
Prediction of the gene expression in normal lung tissue by the gene expression in blood.
Article in BMC medical genomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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17 citing papers in PubMed, 28 citations in OpenAlex.
- Cross-tissue graph attention networks for semi-supervised gene expression prediction.Briefings in bioinformatics · 2026Article
- Gene expression in tumor and adjacent normal tissues in lung adenocarcinoma subtypes.BMC cancer · 2025Article
- A multi-modal framework improves prediction of tissue-specific gene expression from a surrogate tissue.EBioMedicine · 2024Article
- Inferring Characteristics of the Tumor Immune Microenvironment of Patients with HNSCC from Single-Cell Transcriptomics of Peripheral Blood.Cancer research communications · 2024Article
- Community cohesion looseness in gene networks reveals individualized drug targets and resistance.Briefings in bioinformatics · 2024Article
- Building an optimal predictive model for imputing tissue-specific gene expression by combining genotype and whole-blood transcriptome data.HGG advances · 2023Article
- MTM: a multi-task learning framework to predict individualized tissue gene expression profiles.Bioinformatics (Oxford, England) · 2023Article
- Cluster analysis of transcriptomic datasets to identify endotypes of idiopathic pulmonary fibrosis.Thorax · 2023Article
- Toward a Systematic Assessment of Sex Differences in Cystic Fibrosis.Journal of personalized medicine · 2023Article
- Article
- Predicting tissue-specific gene expression from whole blood transcriptome.Science advances · 2021Article
- Epigenome-wide association study identifies DNA methylation markers for asthma remission in whole blood and nasal epithelium.Clinical and translational allergy · 2020Article
- The Relationship between the Expression of Fatty Acyl Desaturase 2 (Life (Basel, Switzerland) · 2020Article
- SNP eQTL status and eQTL density in the adjacent region of the SNP are associated with its statistical significance in GWA studies.BMC genetics · 2019Article
- Symptom-based stratification of patients with primary Sjögren's syndrome: multi-dimensional characterisation of international observational cohorts and reanalyses of randomised clinical trials.The Lancet. Rheumatology · 2019Article
- Chemotherapy-induced fatigue is associated with changes in gene expression in the peripheral blood mononuclear cell fraction of patients with locoregional breast cancer.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2019Article
- RNA-sequencing across three matched tissues reveals shared and tissue-specific gene expression and pathway signatures of COPD.Respiratory research · 2019Article
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundComparative analysis of gene expression in human tissues is important for understanding the molecular mechanisms underlying tissue-specific control of gene expression. It can also open an avenue for using gene expression in blood (which is the most easily accessible human tissue) to predict gene expression in other (less accessible) tissues, which would facilitate the development of novel gene expression based models for assessing disease risk and progression. Until recently, direct comparative analysis across different tissues was not possible due to the scarcity of paired tissue samples from the same individuals.
methodsIn this study we used paired whole blood/lung gene expression data from the Genotype-Tissue Expression (GTEx) project. We built a generalized linear regression model for each gene using gene expression in lung as the outcome and gene expression in blood, age and gender as predictors.
resultsFor ~18 % of the genes, gene expression in blood was a significant predictor of gene expression in lung. We found that the number of single nucleotide polymorphisms (SNPs) influencing expression of a given gene in either blood or lung, also known as the number of quantitative trait loci (eQTLs), was positively associated with efficacy of blood-based prediction of that gene's expression in lung. This association was strongest for shared eQTLs: those influencing gene expression in both blood and lung.
conclusionsIn conclusion, for a considerable number of human genes, their expression levels in lung can be predicted using observable gene expression in blood. An abundance of shared eQTLs may explain the strong blood/lung correlations in the gene expression.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.