JasMAP: A Joint Ancestry and SNP Association Method for a Multi-way Admixed Population

The large volume of research findings submitted to the GWAS catalog in the last decade is a clear indication of the exponential progress of these studies and association approaches. This success has, however, been dimmed by recurring concerns about disparity and the lack of population diversity. As a result, researchers are now responding, and GWAS extension to diverse populations is under way. Initial GWAS methods were calibrated using European populations with long-range regions of linkage disequilibrium (LD) and haplotypes. This implies that, as GWAS extends to diverse populations, the development of inclusive methods targeted at these populations is imperative. Particularly in multi-way admixed populations, methods that include both genotypes and ancestry associations have been shown to improve power while controlling for the additional LD structure introduced by admixture processes. However, these methods continue to be tailored to only 2-way admixed populations. Though this is a justifiable start, the breeding structures of today suggest that the world population is more likely to increase in the number of multi-admixed individuals, and tools targeted at 2-way admixed individuals will continue to exclude a larger part of diverse populations. In this study, we propose a joint ancestry and SNP association method, JasMAP, that is tailored to multi-way admixed populations. We explore the LMM approach that has become standard in GWAS of structured populations in a Bayesian context, model local ancestry variation as prior knowledge, and update the genotype association to obtain a joint posterior probability of association (PPA). The newly developed method has been assessed using various simulated datasets from our multi-scenario simulation framework, FractalSIM ([Mugo et al., 2017][1]), and we output not only the joint statistics but also the genotype-only and the ancestry-only association statistics for the user. JasMAP has also been applied to perform a GWAS analysis of a 5-way admixed South African Coloured (SAC) population with a tuberculosis (TB) phenotype. We obtained 1 significant risk SNP using the ancestry-only association but no SNPs were found to be significant using the standard genotype-only association. 13 risk SNPs, however, were detected as significant with a PPA > 0.5 using the joint association approach. 12 of these SNPs had a marginal significance threshold in genotype-only and ancestry-only association. By functional annotation and gene mapping, the 13 SNPs were found near 8 genes, 5 of which were either found in pathways, have functionality, or were linked to social behaviour associated with an increased risk of TB. Specifically, one of the significant SNPs, rs 17050321 on chromosome 4, was found close to the SLC7A11 gene that has previously been linked to TB in a GWAS study of a Chinese population. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This work was supported by the University of Cape Town-Africa Institute for Mathematical Sciences (UCT-AIMS) Scholarship, DAAD German Academic Exchange Service Fund No. A/91628092, the Integrative Biomedical Sciences Departmental Fund, and the NRF/RCUK Newton Grant. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Health Science ethics committees of Stellenbosch University and University of Cape Town gave ethical approval for this work. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes The reference data used in this study is publicly available in the 1000 Genomes resources, Human Genome Diversity Project (HGDP), and from Schlebusch et al. (2012). Simulated data is also available by request from the corresponding author. [1]: #ref-30