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Knauer-Arloth, J. ; Hryhorzhevska, A.* ; Binder, E.B.*

Multi-omics analysis of the molecular response to glucocorticoids - insights into shared genetic risk from psychiatric to medical disorders.

Biol. Psychiatry 97, 794-805 (2024)
Verlagsversion DOI PMC
Open Access Hybrid
Creative Commons Lizenzvertrag
BACKGROUND: Alterations in the effects of glucocorticoids have been implicated in mediating some of the negative health effects associated with chronic stress, including increased risk for psychiatric disorders as well as cardiovascular and metabolic diseases. This study investigates how genetic variants influence gene expression and DNA methylation (DNAm) in response to glucocorticoid receptor (GR)-activation, and their association with disease risk. METHODS: We measured DNAm (n=199) and gene expression (n=297) in peripheral blood before and after GR-activation with dexamethasone, with matched genotype data available for all samples. A comprehensive molecular quantitative trait locus (QTL) analysis was conducted, mapping GR-response methylation (me)QTLs, GR-response expression (e)QTLs, and GR-response expression quantitative trait methylation (eQTM). A multi-level network analysis was employed to map the complex relationships between the transcriptome, epigenome, and genetic variation. RESULTS: We identified 3,772 GR-response meCpGs corresponding to 104,828 local GR-response meQTLs that did not strongly overlap with baseline meQTLs. eQTM and eQTL analyses revealed distinct genetic influences on gene expression and DNAm. Multi-level network analysis uncovered GR-response network trio QTLs, characterized by SNP-CpG-transcript combinations where meQTLs act as both eQTLs and eQTMs. GR-response trio variants were enriched in GWAS for psychiatric, respiratory, autoimmune and cardiovascular diseases and conferred a higher relative heritability per SNP than GR-response meQTL and baseline QTL SNP. CONCLUSIONS: Genetic variants modulating the molecular effects of glucocorticoids are associated with psychiatric as well as medical diseases and not uncovered in baseline QTL analyses.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Cell Type-specificity ; Gene Expression ; Genetic Variation ; Immune Response ; Multi-omics Network Analysis ; Six Keywords: Dna Methylation ; Stress Response; Dna Methylation; Annotation; Disease
Sprache englisch
Veröffentlichungsjahr 2024
HGF-Berichtsjahr 2024
ISSN (print) / ISBN 0006-3223
e-ISSN 1873-2402
Zeitschrift Biological Psychiatry
Quellenangaben Band: 97, Heft: 8, Seiten: 794-805 Artikelnummer: , Supplement: ,
Verlag Elsevier
Verlagsort Ste 800, 230 Park Ave, New York, Ny 10169 Usa
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Computational Biology (ICB)
POF Topic(s) 30205 - Bioengineering and Digital Health
Forschungsfeld(er) Enabling and Novel Technologies
PSP-Element(e) G-503800-001
Förderungen Brain & Behavior Research Foundation through NARSAD Young Investigator grant
European Research Council
European Union, European Training Network grant, Translational SYStemics: Personalized Medicine at the Interface of Translational Research and Systems Medicine
DOI 10.1016/j.biopsych.2024.10.004
WOS ID 001459243700001
Scopus ID 85211197221
PubMed ID 39393618
Erfassungsdatum 2024-11-08
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