A Genome-wide Association Study of Schizophrenia in the South African Xhosa and Generalizability of Polygenic Risk Score across African populations

African populations are vastly underrepresented in genetic studies despite having the most genetic variation globally and facing wide-ranging environmental exposures. Most of these studies have been conducted in populations of European (EUR) ancestry using GWAS arrays that represent the genetic variation in these populations. Thus, the prediction accuracy of polygenic risk scores (PRS) derived from EUR ancestry populations is less accurate in populations of non-European ancestry, and least accurate in African (AFR) ancestry populations. The extent to which PRS prediction accuracy varies within AFR ancestry populations has not, however, been previously investigated. This study had two aims: the first was to investigate the contribution of common variants to the risk of schizophrenia in the South African Xhosa (SAX) population through genome-wide association study (GWAS) analysis, and to determine if PRS derived from EUR and East Asian (EAS) ancestry populations from the Psychiatric Genomics Consortium (PGC) Schizophrenia Working Group were generalizable to SAX. The second aim was to assess the generalizability of PRS for non-psychiatric phenotypes that were derived from EUR ancestry individuals from the UK Biobank (UKB, n = ~350,000) in the Uganda General Population Cohort (GPC, n = 4,778) and the South African Drakenstein Child Health Study (DHCS, n = 638). To address the first aim, a GWAS was conducted in 2,086 Xhosa individuals from South Africa with and without schizophrenia (ncases = 1,038; ncontrols = 1,048) using a custom-designed Affymetrix GWAS array designed to capture variation in the Xhosa population. The schizophrenia GWAS in SAX yielded one SNP (rs35172303 ; P = 4.74e-08, OR = 0.6004, 95%CI:[0.499,0.721]) in ZFP3 that met genome-wide significance. The association of variants in ZFP3 from the schizophrenia GWAS is consistent with those from an earlier exomesequence study in SAX undertaken by colleagues, but this gene has not previously been associated with schizophrenia in large-scale schizophrenia GWAS of predominantly EUR ancestry. After characterizing the genetic architecture of schizophrenia in SAX, it was found that the heritability was enriched across functional categories involved in the regulation of gene expression. Then, the accuracy of PRS derived from PGC Schizophrenia Working Group from both EUR and EAS ancestries in predicting schizophrenia in SAX was quantified. There was low PRS prediction accuracy using PGC-derived summary statistics in SAX (PGC-EUR: max R2 = 0.0057, P = 0.008; PGC-EAS: max R2 = 0.0059, P = 0.007). These findings are consistent with previous findings that showed that PRS predication accuracy is low when discovery and target cohorts come from different ancestral backgrounds. For the second aim, PRS prediction accuracy was quantified in simulations using data from the African Genome Variation project (AGVP) to represent continental AFR diversity. Samples were categorised by geographical region into West, East and South Africa cohorts. Each cohort was divided into a discovery and target datasets. The West and East African discovery data was used to predict the simulated phenotype in the three target cohorts. Using UKB EUR ancestry individuals, PRS prediction accuracy was assessed for 34 anthropometric and blood panel traits in the Uganda GPC, and then meta-analysed UKB with PAGE (Population Architecture using Genomics and Epidemiology, comprising about 50,000 Latino/Hispanic and African-American individuals) and BBJ (Biobank Japan, n = ~162,000) to assess how the inclusion of diverse sample impacts PRS prediction accuracy. Simulations were limited by sample size but showed that PRS prediction accuracy was highest when the discovery and target cohorts were matched by African region, and for phenotypes with the sparsest genetic architecture. Using empirical data from UKB and the Uganda GPC, a low prediction accuracy was observed across all 34 quantitative traits in GPC when using GWAS data from UKB. There was differential prediction accuracy across AFR ancestry groups within UKB, i.e. the prediction accuracy was highest for the Ethiopian and admixed populations, and lowest for southern African populations. When comparing PRS prediction accuracy of East African individuals from the UKB to that of individuals from GPC, the prediction accuracy was lowest in the Ugandan GPC population, indicating that the difference in environments between the two groups may be contributing to the difference in PRS accuracy. Moreover, the cross-ancestry meta-analyses showed that the inclusion of diverse samples in large scale studies improves PRS prediction accuracy, most especially for phenotypes with population-enriched variants. It was demonstrated for the first time in this thesis that EUR ancestry-derived PRS prediction accuracy varied within continental AFR ancestry groups, and tracks with population history and the evolution of humans. The higher prediction accuracy observed in Ethiopians can be explained by their genetic proximity to Europeans as a result of the back to Africa migration, whereas the southern African populations (including SAX) are more proximal to the ancestral populations that never left the continent. It is therefore imperative to not only include more African samples in future large-scale studies, but to have samples that adequately represent the genetic and environmental diversity on the African continent

HIV-1 strain-specific neutralizing antibody responses and the dynamics of viral evolution

It is widely held that for an HIV-1 vaccine to provide sterilizing immunity, it would need to elicit broadly neutralizing antibodies (bnAbs). However, factors underlying the development of these antibodies are not clear. There is evidence to suggest that in some individuals who develop bnAbs, the development of breadth is influenced by the co-evolution of the transmitted/founder (t/f) virus and earlier strain-specific neutralizing antibody (ssnAb) responses. Here we characterized the viral evolution, ssnAb and bnAbs responses in CAP292, an HIV-1 infected woman who developed bnAb responses from one year post infection. We used single genome amplification (SGA) to characterize viral evolution at four time points: at acute infection; after the development of strain-specific neutralizing responses; at the first detection of the broadly neutralizing antibody response; and lastly, at the peak of the broad response. We identified the t/f virus, and generated chimeric viruses from this to determine the targets of the ssnAb responses. A panel of site-directed mutant viruses were used to map the specificity of the bnAb responses. Our data indicated that infection was most likely founded by a single virus and that the first wave of ssnAbs emerged at 14 weeks post infection (w.p.i), targeting the V1V2 loop of Envelope (Env). A second wave of ssnAbs, possibly targeting the C3V4 region, emerged by 30 w.p.i. Two distinct viral clusters were detected by the time the bnAb response peaked, suggesting the presence of distinct escape pathways. Mapping of the bnAb specificities indicated that CAP292 produced PGT128-like bnAb responses targeted toward the 332 glycan

Multi-ancestry meta-analysis of asthma identifies novel associations and highlights the value of increased power and diversity

Publisher Copyright: © 2022 The Author(s)Asthma is a complex disease that varies widely in prevalence across populations. The extent to which genetic variation contributes to these disparities is unclear, as the genetics underlying asthma have been investigated primarily in populations of European descent. As part of the Global Biobank Meta-analysis Initiative, we conducted a large-scale genome-wide association study of asthma (153,763 cases and 1,647,022 controls) via meta-analysis across 22 biobanks spanning multiple ancestries. We discovered 179 asthma-associated loci, 49 of which were not previously reported. Despite the wide range in asthma prevalence among biobanks, we found largely consistent genetic effects across biobanks and ancestries. The meta-analysis also improved polygenic risk prediction in non-European populations compared with previous studies. Additionally, we found considerable genetic overlap between age-of-onset subtypes and between asthma and comorbid diseases. Our work underscores the multi-factorial nature of asthma development and offers insight into its shared genetic architecture.Peer reviewe

Genome-wide association studies in ancestrally diverse populations: opportunities, methods, pitfalls, and recommendations

Genome-wide association studies (GWASs) have focused primarily on populations of European descent, but it is essential that diverse populations become better represented. Increasing diversity among study participants will advance our understanding of genetic architecture in all populations and ensure that genetic research is broadly applicable. To facilitate and promote research in multi-ancestry and admixed cohorts, we outline key methodological considerations and highlight opportunities, challenges, solutions, and areas in need of development. Despite the perception that analyzing genetic data from diverse populations is difficult, it is scientifically and ethically imperative, and there is an expanding analytical toolbox to do it well

Genetic structure correlates with ethnolinguistic diversity in eastern and southern Africa

African populations are the most diverse in the world yet are sorely underrepresented in medical genetics research. Here, we examine the structure of African populations using genetic and comprehensive multi-generational ethnolinguistic data from the Neuropsychiatric Genetics of African Populations-Psychosis study (NeuroGAP-Psychosis) consisting of 900 individuals from Ethiopia, Kenya, South Africa, and Uganda. We find that self-reported language classifications meaningfully tag underlying genetic variation that would be missed with consideration of geography alone, highlighting the importance of culture in shaping genetic diversity. Leveraging our uniquely rich multi-generational ethnolinguistic metadata, we track language transmission through the pedigree, observing the disappearance of several languages in our cohort as well as notable shifts in frequency over three generations. We find suggestive evidence for the rate of language transmission in matrilineal groups having been higher than that for patrilineal ones. We highlight both the diversity of variation within Africa as well as how within-Africa variation can be informative for broader variant interpretation; many variants that are rare elsewhere are common in parts of Africa. The work presented here improves the understanding of the spectrum of genetic variation in African populations and highlights the enormous and complex genetic and ethnolinguistic diversity across Africa

Genome-wide association studies in ancestrally diverse populations: opportunities, methods, pitfalls, and recommendations

Genome-wide association studies (GWASs) have focused primarily on populations of European descent, but it is essential that diverse populations become better represented. Increasing diversity among study participants will advance our understanding of genetic architecture in all populations and ensure that genetic research is broadly applicable. To facilitate and promote research in multi-ancestry and admixed cohorts, we outline key methodological considerations and highlight opportunities, challenges, solutions, and areas in need of development. Despite the perception that analyzing genetic data from diverse populations is difficult, it is scientifically and ethically imperative, and there is an expanding analytical toolbox to do it well

Genetic structure correlates with ethnolinguistic diversity in eastern and southern Africa

African populations are the most diverse in the world yet are sorely underrepresented in medical genetics research. Here, we examine the structure of African populations using genetic and comprehensive multi-generational ethnolinguistic data from the Neuropsychiatric Genetics of African Populations-Psychosis study (NeuroGAP-Psychosis) consisting of 900 individuals from Ethiopia, Kenya, South Africa, and Uganda. We find that self-reported language classifications meaningfully tag underlying genetic variation that would be missed with consideration of geography alone, highlighting the importance of culture in shaping genetic diversity. Leveraging our uniquely rich multi-generational ethnolinguistic metadata, we track language transmission through the pedigree, observing the disappearance of several languages in our cohort as well as notable shifts in frequency over three generations. We find suggestive evidence for the rate of language transmission in matrilineal groups having been higher than that for patrilineal ones. We highlight both the diversity of variation within Africa as well as how within-Africa variation can be informative for broader variant interpretation; many variants that are rare elsewhere are common in parts of Africa. The work presented here improves the understanding of the spectrum of genetic variation in African populations and highlights the enormous and complex genetic and ethnolinguistic diversity across Africa