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Nature Communications|March 7, 2015
Whole-genome sequence-based analysis of thyroid functionPeter N Taylor, Eleonora Porcu, Shelby Chew, et al.
Nature Communications|June 13, 2015
Genome-wide association study identifies novel genetic variants contributing to variation in blood metabolite levelsHarmen H M Draisma, René Pool, Michael Kobl, et al.
The American Journal of Clinical Nutrition|June 6, 2019
Association of dietary folate and vitamin B-12 intake with genome-wide DNA methylation in blood: a large-scale epigenome-wide association analysis in 5841 individualsPooja R Mandaviya, Roby Joehanes, Jennifer Brody, et al.
Nature Neuroscience|June 7, 2019
Author Correction: GWAS of lifetime cannabis use reveals new risk loci, genetic overlap with psychiatric traits, and a causal effect of schizophrenia liabilityJoëlle A Pasman, Karin J H Verweij, Zachary Gerring, et al.
Nature Neuroscience|August 29, 2018
GWAS of lifetime cannabis use reveals new risk loci, genetic overlap with psychiatric traits, and a causal influence of schizophreniaJoëlle A Pasman, Karin J H Verweij, Zachary Gerring, et al.
Nature Communications|June 29, 2021
A multi-ethnic epigenome-wide association study of leukocyte DNA methylation and blood lipidsMin-A Jhun, Michael Mendelson, Rory Wilson, et al.
American Journal of Human Genetics|December 5, 2017
DNA Methylation Analysis Identifies Loci for Blood Pressure RegulationMelissa A Richard, Tianxiao Huan, Symen Ligthart, et al.
Journal of Thrombosis and Haemostasis : JTH|January 30, 2023
DNA methylation analysis is used to identify novel genetic loci associated with circulating fibrinogen levels in bloodJulie Hahn, Jan Bressler, Arce Domingo-Relloso, et al.
Nature Communications|June 15, 2019
An integrative cross-omics analysis of DNA methylation sites of glucose and insulin homeostasisJun Liu, Elena Carnero-Montoro, Jenny van Dongen, et al.
American Journal of Respiratory and Critical Care Medicine|May 10, 2022
Pulmonary Function and Blood DNA Methylation: A Multiancestry Epigenome-Wide Association Meta-analysisMikyeong Lee, Tianxiao Huan, Daniel L McCartney, et al.
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