{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Chew G"],"funding":["MOH | National Medical Research Council","MOH | National Medical Research Council (NMRC)"],"pagination":["99"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11078960"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["10(1)"],"pubmed_abstract":["Blood-based gene expression signatures could potentially be used as biomarkers for PD. However, it is unclear whether genetically-regulated transcriptomic signatures can provide novel gene candidates for use as PD biomarkers. We leveraged on the Genotype-Tissue Expression (GTEx) database to impute whole-blood transcriptomic expression using summary statistics of three large-scale PD GWAS. A random forest classifier was used with the consensus whole-blood imputed gene signature (IGS) to discriminate between cases and controls. Outcome measures included Area under the Curve (AUC) of Receiver Operating Characteristic (ROC) Curve. We demonstrated that the IGS (n = 37 genes) is conserved across PD GWAS studies and brain tissues. IGS discriminated between cases and controls in an independent who"],"journal":["NPJ Parkinson's disease"],"pubmed_title":["Transcriptomic imputation of genetic risk variants uncovers novel whole-blood biomarkers of Parkinson's disease."],"pmcid":["PMC11078960"],"funding_grant_id":["CSA","STaR and OF-LCG-000207 (SPARKS II Programme)"],"pubmed_authors":["Mai AS","Chew G","Wang Q","Tan EK","Petretto E","Qi Y","Chao Y","Ouyang JF"],"additional_accession":[]},"is_claimable":false,"name":"Transcriptomic imputation of genetic risk variants uncovers novel whole-blood biomarkers of Parkinson's disease.","description":"Blood-based gene expression signatures could potentially be used as biomarkers for PD. However, it is unclear whether genetically-regulated transcriptomic signatures can provide novel gene candidates for use as PD biomarkers. We leveraged on the Genotype-Tissue Expression (GTEx) database to impute whole-blood transcriptomic expression using summary statistics of three large-scale PD GWAS. A random forest classifier was used with the consensus whole-blood imputed gene signature (IGS) to discriminate between cases and controls. Outcome measures included Area under the Curve (AUC) of Receiver Operating Characteristic (ROC) Curve. We demonstrated that the IGS (n = 37 genes) is conserved across PD GWAS studies and brain tissues. IGS discriminated between cases and controls in an independent who","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 May","modification":"2026-06-03T06:54:03.401Z","creation":"2026-04-25T03:22:31.904Z"},"accession":"S-EPMC11078960","cross_references":{"pubmed":["38719867"],"doi":["10.1038/s41531-024-00698-y"]}}