The number of genome-wide association studies (GWAS) with deep molecular phenotypes, especially metabolomics and proteomics, is rapidly increasing. On other places of this blog I maintain tables of published GWAS with metabolomics (mQTLs), proteomics (pQTLs), and DNA methylation (meQTLs).
Here I extend this collection by a table of all published epigenome-wide association studies (EWAS) with metabolomics, proteomics, and any other (still to be published) deep molecular phenotyps.
Should you know of any study missing here, please let me know.
|Reference||Study Population||#Samples||#CpGs||Omics phenotype|
|Petersen et al. (Hum. Mol. Genet. 2014)||German (KORA) population study||1814||20 (excluding CpGs with genetic confounders)||649 blood metabolic and lipid traits (Metabolon, Biocrates, and Numares/Lipofit platforms)|
|Sayols-Baixeras (Hum. Molec. Genet., 2016)||REGICOR study and Framingham Offspring Study (replication)||645+2542 (replication)||14 (9 genes + 2 intergenic loci)||Lipid traits (total, low-density and high-density lipoprotein cholesterol, and triglycerides)|
|Braun et al. (Clin. Epigenet., 2017)||Rotterdam Study||725+760 (replication)||5||blood levels of triglycerides, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and total cholesterol|
|Nano et al. (Gastroenterology, 2017)||Rotterdam Study||731+719 (replication)||8 (4 replicated)||blood for liver enzyme levels, including gamma-glutamyl transferase (GGT), alanine aminotransferase (ALT), and aspartate aminotransferase (AST)|
|Ahsan et al. (PLoS Genet., 2017)||Northern Sweden Population Health Study (NSPHS)||between 698 and 1033||124||121 protein biomarkers (Proseek immuno-assay technology)|
(updated September 22, 2017)