{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Xu X"],"funding":["Kidney Research UK","British Heart Foundation","NIAID NIH HHS","NIEHS NIH HHS","Medical Research Council","NHGRI NIH HHS","National Institute for Health Research (NIHR)","NLM NIH HHS","Wellcome Trust","NIGMS NIH HHS"],"pagination":["2359"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC10950894"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["15(1)"],"pubmed_abstract":["Genetic mechanisms of blood pressure (BP) regulation remain poorly defined. Using kidney-specific epigenomic annotations and 3D genome information we generated and validated gene expression prediction models for the purpose of transcriptome-wide association studies in 700 human kidneys. We identified 889 kidney genes associated with BP of which 399 were prioritised as contributors to BP regulation. Imputation of kidney proteome and microRNAome uncovered 97 renal proteins and 11 miRNAs associated with BP. Integration with plasma proteomics and metabolomics illuminated circulating levels of myo-inositol, 4-guanidinobutanoate and angiotensinogen as downstream effectors of several kidney BP genes (SLC5A11, AGMAT, AGT, respectively). We showed that genetically determined reduction in renal expr"],"journal":["Nature communications"],"pubmed_title":["Genetic imputation of kidney transcriptome, proteome and multi-omics illuminates new blood pressure and hypertension targets."],"pmcid":["PMC10950894"],"funding_grant_id":["AA/18/4/34221","R01 HG011035","NIHR203308","PG/22/10957","INT_002_20220705","PG/17/35/33001","R01 AI174108","T32 GM118294","PG/19/16/34270","MR/Y008340/1","R56 HG012358","R01 ES036042","T32 LM012415"],"pubmed_authors":["Lay AC","Antczak A","Liu DJ","Waldenberger M","Tomaszewski M","Szulinska M","Saluja S","Rubin S","Denniff M","Keavney B","Zukowska-Szczechowska E","Wang L","Rempega G","Walczak M","Diwadkar AR","Ryszawy J","Wystrychowski W","Guzik TJ","Morris AP","Matias-Garcia PR","Khunsriraksakul C","Krol R","Woolf AS","Talavera D","Charchar FJ","Markus H","Dormer JP","Maan A","Bogdanski P","Drzal M","Samani NJ","Scannali D","Prestes PR","Eales JM","Regan J","Zywiec J","Xu X","Human Kidney Tissue Resource Study Group","Danser AHJ"],"additional_accession":[]},"is_claimable":false,"name":"Genetic imputation of kidney transcriptome, proteome and multi-omics illuminates new blood pressure and hypertension targets.","description":"Genetic mechanisms of blood pressure (BP) regulation remain poorly defined. Using kidney-specific epigenomic annotations and 3D genome information we generated and validated gene expression prediction models for the purpose of transcriptome-wide association studies in 700 human kidneys. We identified 889 kidney genes associated with BP of which 399 were prioritised as contributors to BP regulation. Imputation of kidney proteome and microRNAome uncovered 97 renal proteins and 11 miRNAs associated with BP. Integration with plasma proteomics and metabolomics illuminated circulating levels of myo-inositol, 4-guanidinobutanoate and angiotensinogen as downstream effectors of several kidney BP genes (SLC5A11, AGMAT, AGT, respectively). We showed that genetically determined reduction in renal expr","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Mar","modification":"2026-07-15T04:22:47.329Z","creation":"2025-04-06T07:47:49.283Z"},"accession":"S-EPMC10950894","cross_references":{"pubmed":["38504097"],"doi":["10.1038/s41467-024-46132-y"]}}