The Power of Local Ancestry Inference Algorithms in Mapping Candidate Denes: The Case Study of African Ancestry Protection against Hemorrhagic Dengue Fever
Luísa Pereira Institute of Molecular Pathology and Immunology of the University of Porto, Portugal
The continuous characterization of genome-wide diversity in population and case-cohort samples, allied to the development of new algorithms, are shedding light on the host ancestry impact in various complex diseases, namely infectious diseases. One of such powerful algorithms is known as local ancestry inference or admixture mapping, which reconstructs the jigsaw puzzle of ancestral blocks along all chromosomes of the admixed descendants. If one parental population acquired adaptation against a certain pathogen, the genomes of descendants will display an enrichment of that ancestry in the specific chromosomal region containing the protective gene, when comparing controls with cases.
We will illustrate this application with a case study conducted in an admixed Cuban cohort of dengue fever patients characterized for 2.5 million SNPs. We identified African-ancestry protection against the hemorrhagic phenotype in two genes intervening in lipid metabolism. Functional tests have confirmed the involvement of these genes in dengue disease, and open up new avenues for the development of therapies. Additional meta-analyses of other known dengue-associated candidate markers allowed to confirm that these markers have high discriminatory power between population groups, adding up to the evidence of ancestry heterogeneity in terms of susceptibility to dengue fever.
Dengue virus is not per se a significant selective motor (mortality rate is low), but other related viruses, such as yellow fever virus, could have been the drivers of the local African adaptation against several related infectious diseases. This African protection continued to favour African-descendants in the new world environment, when dengue virus was introduced there in the 19th/20th centuries.