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Multi-Ancestry GWAS Leads to Loci Linked to Hundreds of Human Phenotypes

NEW YORK – A team from Osaka University, the RIKEN Center for Integrative Medical Sciences, Harvard Medical School, and elsewhere has uncovered thousands of new loci linked to human phenotypes in individuals from Japan and other populations, including associations that appear to track across populations.

For the study, published in Nature Genetics on Thursday, the researchers brought together genetic data for hundreds of thousands of individuals with Asian or European ancestry from the Biobank Japan project, UK Biobank, and FinnGenn for genome-wide association studies and GWAS meta-analyses focused on 220 deep human phenotypes.

The phenotypes selected "cover most of the common human diseases, medication usages among people, and various lab values," co-first and co-corresponding author Saori Sakaue, a post-doctoral researcher in genetics and rheumatology at the Brigham and Women's Hospital and Harvard Medical School, said in an email, noting that the work "substantially expanded the atlas of genetic associations."

Starting with array-based genotyping profiles and available phenotypic resources such as medical histories, electronic medical record text mining, and drug prescription records for around 179,000 BioBank Japan participants, the team searched for genetic ties to 159 disease endpoints, 38 biomarkers, and nearly two-dozen features related to medication usage, filling in genotyping gaps with insights imputed from population-specific 1000 Genomes Project whole-genome sequencing data.

In the process, the researchers saw 519 loci with genome-wide significant disease endpoint associations and some 2,249 biomarker-linked loci, and more than 200 loci that coincided with medication usage, including hundreds of loci not implicated in such phenotypes in the past.

When they delved into the associations further through GWAS meta-analyses involving around 628,000 more individuals enrolled in the UK Biobank or FinnGen projects, they found nearly 5,000 newly associated loci, including 571 disease-associated parts of the genome, almost 4,500 biomarker-related loci, and more than 300 loci associated with medication usage.

"We found that generally the genetic architecture is quite shared across populations, and similar diseases (e.g., cardiovascular diseases or allergic diseases) are clustered together based on genetic similarity in both populations," Sakaue noted, "which might make us think that the current clinical boundaries for human diseases broadly reflect the shared genetic etiology across populations, despite differences in populations and despite potential differences in diagnostic, environmental and prescription practices."

Moreover, Sakaue explained, the work offered a look at the genetic architecture behind numerous human traits across multiple human populations. Based on available summary statistics, for example, the investigators classified allergic conditions such as asthma and allergic rhinitis into a group that appeared to be distinct from atopic dermatitis, contact dermatitis, and metal allergies.

"These two axes recapitulated the classical pathways of hypersensitivity … and further deepened our biological and genetic understanding of those different axes," Sakaue noted. "We believe this result might be a proof-of-concept example which suggests potential application for genetics-driven categorization of human diseases."

She and her co-authors cautioned that "we did not conduct statistical fine-mapping for every locus we identified, which might cause a concern over potential effects due to [linkage disequilibrium] tagging for observed pleiotropy" and noted that "elucidation of pleiotropy in other populations is warranted to replicate our results."