Genome-wide association study identifies novel candidate malaria resistance genes in Cameroon

Abstract

Recent data suggest that only a small fraction of severe malaria heritability is explained by the totality of genetic markers discovered so far. The extensive genetic diversity within African populations means that significant associations are likely to be found in Africa. In their series of multi-site genome-wide association studies (GWAS) across sub-Saharan Africa, the Malaria Genomic Epidemiology Network (MalariaGEN) observed specific limitations and encouraged country-specific analyses. Here, we present findings of a GWAS of Cameroonian participants that contributed to MalariaGEN projects (n = 1103). We identified protective associations at polymorphisms within the enhancer region of CHST15 [Benjamin-Hochberg false discovery rate (FDR) < 0.02] that are specific to populations of African ancestry, and that tag strong eQTLs of CHST15 in hepatic cells. In-silico functional analysis revealed a signature of epigenetic regulation of CHST15 that is preserved in populations in historically malaria endemic regions, with haplotype analysis revealing a haplotype that is specific to these populations. Association analysis by ethnolinguistic group identified protective associations within SOD2 (FDR < 0.04), a gene previously shown to be significantly induced in pre-asymptomatic malaria patients from Cameroon. Haplotype analysis revealed substantial heterogeneity within the beta-like globin (HBB) gene cluster amongst the major ethnic groups in Cameroon confirming differential malaria pressure and underscoring age-old fine-scale genetic structure within the country. Our findings revealed novel insights in the evolutionary genetics of populations living in Cameroon under malaria pressure with new significant protective loci (CHST15 and SOD2) and emphasized the significant attenuation of genetic association signals by fine-scale genetic structure.

Figure 1

Basic demographic characteristics, and recruitment sites of cases and controls.

Figure 2

Principal Component Analysis (PCA) and Imputation Performance. (A) PCA plot of Cameroonians and other African populations in the 1000 Genomes Project. Cameroonians cluster centrally between East (LWK = Luhya in Webuye, Kenya) and West African (YRI = Yoruba in Ibadan, Nigeria, ESN = Esan in Nigeria, GWD = Gambian in Western Division, Mandinka and MSL = Mende in Sierra Leone) populations as expected. (B) Per-chromosome imputation accuracy of our in-house, TOPMed, Michigan and Sanger imputation strategies.

Figure 3

Manhattan plot of significant association signals. (A) Significant associations around CHST15 in the merged set of BA, SB and FU individuals (top Manhattan plot) and in SOD2 in SB individuals. Red line = genome-wide significance (5e – 08); blue line = suggestive line (1e – 05). (B) Regional association plot showing LD between the lead signal and other variants around CHST15. Moderate LD (0.4–0.6) is observed between the lead SNPs and other suggestive associations. (C) Regional association plot showing LD between the lead signal and other variants in SOD2. Strong LD extends over a 100 Kb region covering SOD2 and other genes.

Figure 4

Genetic Diversity within and around CHST15. (A) Alignment of the rs113508623 significant variant with nine primate species from the ENSEMBL 10 EPO multiple sequence alignment. The bases highlighted in deep red represent regulatory region variants. The bases highlighted in light red represent positions with more than one allele across the different species. The underlined base shows the variant of interest, which is also a regulatory region variant. The variants occur in the enhancer region upstream of CHST15. (B) EHH plot showing haplotype decay around the rs113508623 significant variant. The ancestral allele (C) (blue line) shows an overall higher EHH score as compared with the derived allele (T) (red line). (C) Haplotype frequencies in the enhancer region upstream of CHST15 in global populations. The colours were generated using the rainbow colour function in R and numbered from bottom to top of the barplot, hence Hap1 is the bottom-most colour, whilst Hap8 is the top-most colour.

Figure 5

Haplotype frequencies in the HBB gene cluster in Cameroonians. CAM = merged set of all the ethnic groups. HbS = HbS-positive samples, HbA = HbS-negative samples. The colours were generated using the rainbow colour function in R and numbered from bottom to top of the barplot, hence AI is the bottom-most colour, whilst Hap7 is the top-most colour.