Summary statistics are available for download from the GWAS Catalog.
GWAS for urinary sodium and potassium excretion highlights pathways shared with cardiovascular traits.
Pazoki R, et al.
Nat Commun. 2019 Aug 13;10(1):3653. doi: 10.1038/s41467-019-11451-y.
PMID:31409800
Summary statistics are available for download at the deCODE Genetics website.
Eighty-eight variants highlight the role of T cell regulation and airway remodeling in asthma pathogenesis.
Olafsdottir TA, et al.
Nat Commun. 2020 Jan 20;11(1):393. doi: 10.1038/s41467-019-14144-8.
PMID:31959851
This dataset is a subset of the GIANT 2018 Body Fat Distribution exome chip analysis dataset.
This dataset is a subset of the GIANT 2018 Body Fat Distribution exome chip analysis dataset.
This dataset is a subset of the GIANT 2018 Body Fat Distribution exome chip analysis dataset.
This dataset is a subset of the GIANT 2018 Body Fat Distribution exome chip analysis dataset.
This dataset is a subset of the GIANT 2018 Body Fat Distribution exome chip analysis dataset.
This dataset is a subset of the ExTexT2D exome chip analysis dataset.
Note that the samples in the GoT2D exome chip analysis and FUSION exome chip analysis datasets are a subset of those included in the ExTexT2D exome chip analysis dataset. Cases in the EXTEND GWAS dataset are included in the ExTexT2D exome chip analysis dataset.
This dataset is a subset of the Hypertension exome chip analysis dataset.
Trans-ancestry Meta-Analyses Identify Rare and Common Variants Associated With Blood Pressure and Hypertension.
Surendran P, et al.
Nat Genet. 2016 Oct; 48(10): 1151–1161. doi: 10.1038/ng.3654
PMID:27618447
The ultimate goal of genetic association studies is to discover which genes and pathways have direct roles in risk of a disease or trait. Several methods now combine genetic association results with multiple kinds of evidence to generate lists of the genes that are most likely to mediate the genetic associations. The Knowledge Portals currently host results from three such methods that predict type 2 diabetes effector genes. The methods differ in the evidence types that they use as input and in the classifications or scores that they generate.