PuSH - Publikationsserver des Helmholtz Zentrums München

Export: TXT Text RIS Endnote (RIS) BIB BibTeX
Neumeyer; S. ; Hemani, G.* ; Zeggini, E.

Strengthening causal inference for complex disease using molecular quantitative trait loci.

Trends Mol. Med. 26, 232-241 (2020)
Verlagsversion Postprint DOI PMC
Open Access Hybrid
Creative Commons Lizenzvertrag
Large genome-wide association studies (GWAS) have identified loci that are associated with complex traits and diseases, but index variants are often not causal and reside in non-coding regions of the genome. To gain a better understanding of the relevant biological mechanisms, in termediate traits such as gene expression and protein levels are increasingly being investigated because these are likely mediators between genetic variants and disease outcome. Genetic variants associated with intermediate traits, termed molecular quantitative trait loci (molQTLs), car then be used as instrumental variables in a Mendelian randomization (MR) approach to identify the causal features and mechanisms of complex traits. Challenges such as pleiotropy and the non-specificity of molQTLs remain, and further approaches and methods need to be developed.
Impact Factor
Scopus SNIP
Web of Science
Times Cited
Scopus
Cited By
Altmetric
11.099
2.262
9
14
Tags
Anmerkungen
Besondere Publikation
Auf Hompepage verbergern

Zusatzinfos bearbeiten
Eigene Tags bearbeiten
Privat
Eigene Anmerkung bearbeiten
Privat
Auf Publikationslisten für
Homepage nicht anzeigen
Als besondere Publikation
markieren
Publikationstyp Artikel: Journalartikel
Dokumenttyp Review
Schlagwörter Complex Trait ; Gene Expression ; Genome-wide Association Study ; Gwas ; Mendelian Randomization ; Qtl; Mendelian Randomization; Gene-expression; Association; Identification; Epidemiology; Variants; Atlas; Gwas; Help; Bias
Sprache englisch
Veröffentlichungsjahr 2020
Prepublished im Jahr 2019
HGF-Berichtsjahr 2019
ISSN (print) / ISBN 1471-4914
e-ISSN 1471-499X
Zeitschrift Trends in Molecular Medicine
Quellenangaben Band: 26, Heft: 2, Seiten: 232-241 Artikelnummer: , Supplement: ,
Verlag Elsevier
Verlagsort The Boulevard, Langford Lane, Kidlington, Oxford Ox5 1gb, Oxon, England
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Translational Genomics (ITG)
POF Topic(s) 30205 - Bioengineering and Digital Health
Forschungsfeld(er) Genetics and Epidemiology
PSP-Element(e) G-506700-001
DOI 10.1016/j.molmed.2019.10.004
WOS ID WOS:000510616500009
Scopus ID 85075375834
PubMed ID 31718940
Erfassungsdatum 2019-11-26
[➜Korrektur melden]