Mapping genes underlying ethnic differences in tuberculosis risk by linkage disequilibrium in the South African coloured population of the Western Cape

Includes bibliographical references.The South Africa Coloured population of the Western Cape is the result of unions between Europeans, Africans (Bantu and Khoisan), and various other populations (Malaysian or Indonesian descent). The world-wide burden of tuberculosis remains an enormous problem, and is particularly severe in this population. In general, admixed populations that have arisen in historical times can make an important contribution to the discovery of disease susceptibility genes if the parental populations exhibit substantial variation in susceptibility. Despite numerous successful genome-wide association studies, detecting variants that have low disease risk still poses a challenge. Furthermore, admixture association studies for multi-way admixed populations pose constant challenges, including the choice of an accurate ancestral panel to infer ancestry and for imputing missing genotypes to identify possible genetic variants causing susceptibility to disease. This thesis addresses some of these challenges. We first developed PROXYANC, an approach to select the best proxy ancestral populations for admixed populations. From the simulation of a multi-way admixed population, we demonstrated the ability and accuracy of PROXYANC in selecting the best proxy ancestry and illustrated the importance of the choice of ancestries in both estimating admixture proportions and imputing missing genotypes. We applied this approach to the South African Coloured population, to refine both the choice of ancestral populations and their genetic contributions. We also demonstrated that the ancestral allele frequency differences correlated with increased linkage disequilibrium in the SAC, and that the increased LD originates from admixture events rather than population bottlenecks. Secondly, we conducted a study to determine whether ancestry-specific genetic contributions affect tuberculosis risk. We additionally conducted imputation genome-wide association studies and a meta-analysis incorporating previous genome-wide association studies of tuberculosis

Dissecting Meta-Analysis in GWAS Era: Bayesian Framework for Gene/Subnetwork-Specific Meta-Analysis

Over the past decades, advanced high-throughput technologies have continuously contributed to genome-wide association studies (GWASs). GWAS meta-analysis has been increasingly adopted, has cross-ancestry replicability, and has power to illuminate the genetic architecture of complex traits, informing about the reliability of estimation effects and their variability across human ancestries. However, detecting genetic variants that have low disease risk still poses a challenge. Designing a meta-analysis approach that combines the effect of various SNPs within genes or genes within pathways from multiple independent population GWASs may be helpful in identifying associations with small effect sizes and increasing the association power. Here, we proposed ancMETA, a Bayesian graph-based framework, to perform the gene/pathway-specific meta-analysis by combining the effect size of multiple SNPs within genes, and genes within subnetwork/pathways across multiple independent population GWASs to deconvolute the interactions between genes underlying the pathogenesis of complex diseases across human populations. We assessed the proposed framework on simulated datasets, and the results show that the proposed model holds promise for increasing statistical power for meta-analysis of genetic variants underlying the pathogenesis of complex diseases. To illustrate the proposed meta-analysis framework, we leverage seven different European bipolar disorder (BD) cohorts, and we identify variants in the angiotensinogen (AGT) gene to be significantly associated with BD across all 7 studies. We detect a commonly significant BD-specific subnetwork with the ESR1 gene as the main hub of a subnetwork, associated with neurotrophin signaling (p = 4e−14) and myometrial relaxation and contraction (p = 3e−08) pathways. ancMETA provides a new contribution to post-GWAS methodologies and holds promise for comprehensively examining interactions between genes underlying the pathogenesis of genetic diseases and also underlying ethnic differences

Whole exome sequencing reveals pathogenic variants in MYO3A, MYO15A and COL9A3 and differential frequencies in ancestral alleles in hearing impairment genes among individuals from Cameroon

There is scarcity of known gene variants of hearing impairment (HI) in African populations. This knowledge deficit is ultimately affecting the development of genetic diagnoses. We used whole exome sequencing to investigate gene variants, pathways of interactive genes and the fractions of ancestral overderived alleles for 159 HI genes among 18 Cameroonian patients with non-syndromic HI (NSHI) and 129 ethnically matched controls. Pathogenic and likely pathogenic (PLP) variants were found in MYO3A, MYO15A and COL9A3, with a resolution rate of 50% (9/18 patients). The study identified significant genetic differentiation in novel population-specific gene variants at FOXD4L2, DHRS2L6, RPL3L and VTN between HI patients and controls. These gene variants are found in functional/co-expressed interactive networks with other known HI-associated genes and in the same pathways with VTN being a hub protein, that is, focal adhesion pathway and regulation of the actin cytoskeleton (P-values <0.05). The results suggest that these novel population-specific gene variants are possible modifiers of the HI phenotypes. We found a high proportion of ancestral allele versus derived at low HI patients-specific minor allele frequency in the range of 0.0–0.1. The results showed a relatively low pickup rate of PLP variants in known genes in this group of Cameroonian patients with NSHI. In addition, findings may signal an evolutionary enrichment of some variants of HI genes in patients, as the result of polygenic adaptation, and suggest the possibility of multigenic influence on the phenotype of congenital HI, which deserves further investigations

Profiling of warfarin pharmacokinetics‐associated genetic variants: Black Africans portray unique genetic markers important for an African specific warfarin pharmacogenetics‐dosing algorithm

Background: Warfarin dose variability observed in patients is attributed to variation in genes involved in the warfarin metabolic pathway. Genetic variation in CYP2C9 and VKORC1 has been the traditional focus in evaluating warfarin dose variability, with little focus on other genes. Objective: We set out to evaluate 27 single nucleotide polymorphisms (SNPs) in the CYP2C cluster loci and 8 genes (VKORC1, ABCB1, CYP2C9, CYP2C19, CYP2C8, CYP1A2, CYP3A4, and CYP3A5) involved in pharmacokinetics of warfarin. Patients/methods: 503 participants were recruited among black Africans and Mixed Ancestry population groups, from South Africa and Zimbabwe, and a blood sample taken for DNA. Clinical parameters were obtained from patient medical records, and these were correlated with genetic variation. Results: Among black Africans, the SNPs CYP2C rs12777823G>A, CYP2C9 c.449G>A (*8), CYP2C9 c.1003C>T (*11) and CYP2C8 c.805A>T (*2) were significantly associated with warfarin maintenance dose. Conversely, CYP2C9 c.430C>T (*2), CYP2C8 c.792C>G (*4) and VKORC1 g.-1639G>A were significantly associated with maintenance dose among the Mixed Ancestry. The presence of CYP2C8*2 and CYP3A5*6 alleles was associated with increased mean warfarin maintenance dose, whereas CYP2C9*8 allele was associated with reduced warfarin maintenance dose. Conclusion: African populations present with a diversity of variants that are important in predicting pharmacogenetics-based warfarin dosing in addition to those reported in CYP2C9 and VKORC1. It is therefore important, to include African populations in pharmacogenomics studies to be able to identify all possible biomarkers that are potential predictors for drug response

A whole genome sequencing approach to anterior cruciate ligament rupture–a twin study in two unrelated families

Predisposition to anterior cruciate ligament (ACL) rupture is multi-factorial, with variation in the genome considered a key intrinsic risk factor. Most implicated loci have been identified from candidate gene-based approach using case-control association settings. Here, we leverage a hypothesis-free whole genome sequencing in two two unrelated families (Family A and B) each with twins with a history of recurrent ACL ruptures acquired playing rugby as their primary sport, aimed to elucidate biologically relevant function-altering variants and genetic modifiers in ACL rupture. Family A monozygotic twin males (Twin 1 and Twin 2) both sustained two unilateral non-contact ACL ruptures of the right limb while playing club level touch rugby. Their male sibling sustained a bilateral non-contact ACL rupture while playing rugby union was also recruited. The father had sustained a unilateral non-contact ACL rupture on the right limb while playing professional amateur level football and mother who had participated in dancing for over 10 years at a social level, with no previous ligament or tendon injuries were both recruited. Family B monozygotic twin males (Twin 3 and Twin 4) were recruited with Twin 3 who had sustained a unilateral non-contact ACL rupture of the right limb and Twin 4 sustained three non-contact ACL ruptures (two in right limb and one in left limb), both while playing provincial level rugby union. Their female sibling participated in karate and swimming activities; and mother in hockey (4 years) horse riding (15 years) and swimming, had both reported no previous history of ligament or tendon injury. Variants with potential deleterious, loss-of-function and pathogenic effects were prioritised. Identity by descent, molecular dynamic simulation and functional partner analyses were conducted. We identified, in all nine affected individuals, including twin sets, non-synonymous SNPs in three genes: COL12A1 and CATSPER2, and KCNJ12 that are commonly enriched for deleterious, loss-of-function mutations, and their dysfunctions are known to be involved in the development of chronic pain, and represent key therapeutic targets. Notably, using Identity By Decent (IBD) analyses a long shared identical sequence interval which included the LINC01250 gene, around the telomeric region of chromosome 2p25.3, was common between affected twins in both families, and an affected brother’. Overall gene sets were enriched in pathways relevant to ACL pathophysiology, including complement/coagulation cascades (p = 3.0e-7), purine metabolism (p = 6.0e-7) and mismatch repair (p = 6.9e-5) pathways. Highlighted, is that this study fills an important gap in knowledge by using a WGS approach, focusing on potential deleterious variants in two unrelated families with a historical record of ACL rupture; and providing new insights into the pathophysiology of ACL, by identifying gene sets that contribute to variability in ACL risk

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

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 (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 among 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

Warfarin Pharmacogenomics for Precision Medicine in Real-Life Clinical Practice in Southern Africa: Harnessing 73 Variants in 29 Pharmacogenes

Pharmacogenomics is universally relevant for worldwide modern therapeutics and yet needs further development in resource-limited countries. While there is an abundance of genetic association studies in controlled medical settings, there is a paucity of studies with a naturalistic design in real-life clinical practice in patients with comorbidities and under multiple drug treatment regimens. African patients are often burdened with communicable and noncommunicable comorbidities, yet the application of pharmacogenomics in African clinical settings remains limited. Using warfarin as a model, this study aims at minimizing gaps in precision/personalized medicine research in African clinical practice. We present, therefore, pharmacogenomic profiles of a cohort of 503 black Africans (n = 252) and Mixed Ancestry (n = 251) patients from Southern Africa, on warfarin and co-prescribed drugs in a naturalized noncontrolled environment. Seventy-three (n = 73) single nucleotide polymorphisms (SNPs) in 29 pharmacogenes were characterized using a combination of allelic discrimination, Sanger sequencing, restriction fragment length polymorphism, and Sequenom Mass Array. The common comorbidities were hypertension (43-46%), heart failure (39-45%), diabetes mellitus (18%), arrhythmia (25%), and HIV infection (15%). Accordingly, the most common co-prescribed drugs were antihypertensives, antiarrhythmic drugs, antidiabetics, and antiretroviral therapy. We observed marked variation in major pharmacogenes both at interethnic levels and within African subpopulations. The Mixed Ancestry group presented a profile of genetic variants reflecting their European, Asian, and African admixture. Precision medicine requires that African populations begin to capture their own pharmacogenetic SNPs as they cannot always infer with absolute certainty from Asian and European populations. In the current historical moment of the COVID-19 pandemic, we also underscore that the spectrum of drugs interacting with warfarin will likely increase, given the systemic and cardiovascular effects of COVID-19, and the anticipated influx of COVID-19 medicines in the near future. This observational clinical pharmacogenomics study of warfarin, together with past precision medicine research, collectively, lends strong support for incorporation of pharmacogenetic profiling in clinical settings in African patients for effective and safe administration of therapeutics

Computational approaches for network-based integrative multi-omics analysis

Advances in omics technologies allow for holistic studies into biological systems. These studies rely on integrative data analysis techniques to obtain a comprehensive view of the dynamics of cellular processes, and molecular mechanisms. Network-based integrative approaches have revolutionized multi-omics analysis by providing the framework to represent interactions between multiple different omics-layers in a graph, which may faithfully reflect the molecular wiring in a cell. Here we review network-based multi-omics/multi-modal integrative analytical approaches. We classify these approaches according to the type of omics data supported, the methods and/or algorithms implemented, their node and/or edge weighting components, and their ability to identify key nodes and subnetworks. We show how these approaches can be used to identify biomarkers, disease subtypes, crosstalk, causality, and molecular drivers of physiological and pathological mechanisms. We provide insight into the most appropriate methods and tools for research questions as showcased around the aetiology and treatment of COVID-19 that can be informed by multi-omics data integration. We conclude with an overview of challenges associated with multi-omics network-based analysis, such as reproducibility, heterogeneity, (biological) interpretability of the results, and we highlight some future directions for network-based integration

High-depth African genomes inform human migration and health

The African continent is regarded as the cradle of modern humans and African genomes contain more genetic variation than those from any other continent, yet only a fraction of the genetic diversity among African individuals has been surveyed1. Here we performed whole-genome sequencing analyses of 426 individuals—comprising 50 ethnolinguistic groups, including previously unsampled populations—to explore the breadth of genomic diversity across Africa. We uncovered more than 3 million previously undescribed variants, most of which were found among individuals from newly sampled ethnolinguistic groups, as well as 62 previously unreported loci that are under strong selection, which were predominantly found in genes that are involved in viral immunity, DNA repair and metabolism. We observed complex patterns of ancestral admixture and putative-damaging and novel variation, both within and between populations, alongside evidence that Zambia was a likely intermediate site along the routes of expansion of Bantu-speaking populations. Pathogenic variants in genes that are currently characterized as medically relevant were uncommon—but in other genes, variants denoted as ‘likely pathogenic’ in the ClinVar database were commonly observed. Collectively, these findings refine our current understanding of continental migration, identify gene flow and the response to human disease as strong drivers of genome-level population variation, and underscore the scientific imperative for a broader characterization of the genomic diversity of African individuals to understand human ancestry and improve health