Back to Search
Start Over
A global atlas of genetic associations of 220 deep phenotypes
- Publication Year :
- 2020
- Publisher :
- Cold Spring Harbor Laboratory, 2020.
-
Abstract
- The current genome-wide association studies (GWASs) do not yet capture sufficient diversity in terms of populations and scope of phenotypes. To address an essential need to expand an atlas of genetic associations in non-European populations, we conducted 220 deep-phenotype GWASs (disease endpoints, biomarkers, and medication usage) in BioBank Japan (n = 179,000), by incorporating past medical history and text-mining results of electronic medical records. Meta-analyses with the harmonized phenotypes in the UK Biobank and FinnGen (ntotal = 628,000) identified over 4,000 novel loci, which substantially deepened the resolution of the genomic map of human traits, benefited from East Asian endemic diseases and East Asian specific variants. This atlas elucidated the globally shared landscape of pleiotropy as represented by the MHC locus, where we conducted fine-mapping by HLA imputation. Finally, to intensify the value of deep-phenotype GWASs, we performed statistical decomposition of matrices of phenome-wide summary statistics, and identified the latent genetic components, which pinpointed the responsible variants and shared biological mechanisms underlying current disease classifications across populations. The decomposed components enabled genetically informed subtyping of similar diseases (e.g., allergic diseases). Our study suggests a potential avenue for hypothesis-free re-investigation of human disease classifications through genetics.
- Subjects :
- 0303 health sciences
Locus (genetics)
Human leukocyte antigen
Disease
Biology
Biobank
Phenotype
Subtyping
3. Good health
03 medical and health sciences
0302 clinical medicine
Evolutionary biology
030217 neurology & neurosurgery
Imputation (genetics)
030304 developmental biology
Genetic association
Subjects
Details
- Database :
- OpenAIRE
- Accession number :
- edsair.doi...........fc338adde36b6d573d8c900a0599830b
- Full Text :
- https://doi.org/10.1101/2020.10.23.20213652