title: Leveraging Functional-Annotation Data in Trans-ethnic Fine-Mapping Studies.
abstract: Localization of causal variants underlying known risk loci is one of the main research challenges following genome-wide association studies. Risk loci are typically dissected through fine-mapping experiments in trans-ethnic cohorts for leveraging the variability in the local genetic structure across populations. More recent works have shown that genomic functional annotations (i.e., localization of tissue-specific regulatory marks) can be integrated for increasing fine-mapping performance within single-population studies. Here, we introduce methods that integrate the strength of association between genotype and phenotype, the variability in the genetic backgrounds across populations, and the genomic map of tissue-specific functional elements to increase trans-ethnic fine-mapping accuracy. Through extensive simulations and empirical data, we have demonstrated that our approach increases fine-mapping resolution over existing methods. We analyzed empirical data from a large-scale trans-ethnic rheumatoid arthritis (RA) study and showed that the functional genetic architecture of RA is consistent across European and Asian ancestries. In these data, we used our proposed methods to reduce the average size of the 90% credible set from 29 variants per locus for standard non-integrative approaches to 22 variants.
authors.affiliation: Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA 90095, USA.
authors.forename: Gleb
authors.initials: G
authors.lastname: Kichaev
authors.affiliation: Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA. Electronic address: pasaniuc@ucla.edu.
authors.forename: Bogdan
authors.initials: B
authors.lastname: Pasaniuc
mesh_terms: D001172:Arthritis, Rheumatoid / Q000235:genetics*; D001499:Bayes Theorem; D002874:Chromosome Mapping / Q000379:methods*; D005006:Ethnicity / Q000235:genetics; D014644:Genetic Variation; D005828:Genetics, Population / Q000379:methods*; D006801:Humans; D008957:Models, Genetic; D058977:Molecular Sequence Annotation / Q000379:methods*; D018570:Risk Assessment / Q000379:methods*