Uganda Genome Resource Enables Insights into Population History and Genomic Discovery in Africa.

Genomic studies in African populations provide unique opportunities to understand disease etiology, human diversity, and population history. In the largest study of its kind, comprising genome-wide data from 6,400 individuals and whole-genome sequences from 1,978 individuals from rural Uganda, we find evidence of geographically correlated fine-scale population substructure. Historically, the ancestry of modern Ugandans was best represented by a mixture of ancient East African pastoralists. We demonstrate the value of the largest sequence panel from Africa to date as an imputation resource. Examining 34 cardiometabolic traits, we show systematic differences in trait heritability between European and African populations, probably reflecting the differential impact of genes and environment. In a multi-trait pan-African GWAS of up to 14,126 individuals, we identify novel loci associated with anthropometric, hematological, lipid, and glycemic traits. We find that several functionally important signals are driven by Africa-specific variants, highlighting the value of studying diverse populations across the region.

Africa-specific human genetic variation near CHD1L associates with HIV-1 load.

HIV-1 remains a global health crisis1, highlighting the need to identify new targets for therapies. Here, given the disproportionate HIV-1 burden and marked human genome diversity in Africa2, we assessed the genetic determinants of control of set-point viral load in 3,879 people of African ancestries living with HIV-1 participating in the international collaboration for the genomics of HIV3. We identify a previously undescribed association signal on chromosome 1 where the peak variant associates with an approximately 0.3 log10-transformed copies per ml lower set-point viral load per minor allele copy and is specific to populations of African descent. The top associated variant is intergenic and lies between a long intergenic non-coding RNA (LINC00624) and the coding gene CHD1L, which encodes a helicase that is involved in DNA repair4. Infection assays in iPS cell-derived macrophages and other immortalized cell lines showed increased HIV-1 replication in CHD1L-knockdown and CHD1L-knockout cells. We provide evidence from population genetic studies that Africa-specific genetic variation near CHD1L associates with HIV replication in vivo. Although experimental studies suggest that CHD1L is able to limit HIV infection in some cell types in vitro, further investigation is required to understand the mechanisms underlying our observations, including any potential indirect effects of CHD1L on HIV spread in vivo that our cell-based assays cannot recapitulate.

Addressing Ancestry and Sex Bias in Pharmacogenomics.

The association of an individual's genetic makeup with their response to drugs is referred to as pharmacogenomics. By understanding the relationship between genetic variants and drug efficacy or toxicity, we are able to optimize pharmacological therapy according to an individual's genotype. Pharmacogenomics research has historically suffered from bias and underrepresentation of people from certain ancestry groups and of the female sex. These biases can arise from factors such as drugs and indications studied, selection of study participants, and methods used to collect and analyze data. To examine the representation of biogeographical populations in pharmacogenomic data sets, we describe individuals involved in gene-drug response studies from PharmGKB, a leading repository of drug-gene annotations, and showcaseCYP2D6, a gene that metabolizes approximately 25% of all prescribed drugs. We also show how the historical underrepresentation of females in clinical trials has led to significantly more adverse drug reactions in females than in males.

The African Society of Human Genetics successfully launches global data science workshops.

To accelerate the impact of African genomics on human health, data science skills and awareness of Africa's rich genetic diversity must be strengthened globally. We describe the first African genomics data science workshop, implemented by the African Society of Human Genetics (AfSHG) and international partners, providing a framework for future workshops.

Prevalence and correlates of common mental disorders among participants of the Uganda Genome Resource: Opportunities for psychiatric genetics research.

Genetics research has potential to alleviate the burden of mental disorders in low- and middle-income-countries through identification of new mechanistic pathways which can lead to efficacious drugs or new drug targets. However, there is currently limited genetics data from Africa. The Uganda Genome Resource provides opportunity for psychiatric genetics research among underrepresented people from Africa. We aimed at determining the prevalence and correlates of major depressive disorder (MDD), suicidality, post-traumatic stress disorder (PTSD), alcohol abuse, generalised anxiety disorder (GAD) and probable attention-deficit hyperactivity disorder (ADHD) among participants of the Uganda Genome Resource. Standardised tools assessed for each mental disorder. Prevalence of each disorder was calculated with 95% confidence intervals. Multivariate logistic regression models evaluated the association between each mental disorder and associated demographic and clinical factors. Among 985 participants, prevalence of the disorders were: current MDD 19.3%, life-time MDD 23.3%, suicidality 10.6%, PTSD 3.1%, alcohol abuse 5.7%, GAD 12.9% and probable ADHD 9.2%. This is the first study to determine the prevalence of probable ADHD among adult Ugandans from a general population. We found significant association between sex and alcohol abuse (adjusted odds ratio [AOR] = 0.26 [0.14,0.45], p < 0.001) and GAD (AOR = 1.78 [1.09,2.49], p = 0.019) respectively. We also found significant association between body mass index and suicidality (AOR = 0.85 [0.73,0.99], p = 0.041), alcohol abuse (AOR = 0.86 [0.78,0.94], p = 0.003) and GAD (AOR = 0.93 [0.87,0.98], p = 0.008) respectively. We also found a significant association between high blood pressure and life-time MDD (AOR = 2.87 [1.08,7.66], p = 0.035) and probable ADHD (AOR = 1.99 [1.00,3.97], p = 0.050) respectively. We also found a statistically significant association between tobacco smoking and alcohol abuse (AOR = 3.2 [1.56,6.67], p = 0.002). We also found ever been married to be a risk factor for probable ADHD (AOR = 2.12 [0.88,5.14], p = 0.049). The Uganda Genome Resource presents opportunity for psychiatric genetics research among underrepresented people from Africa.

Causal effect of severe and non-severe malaria on dyslipidemia in African Ancestry individuals: A Mendelian randomization study.

BACKGROUND: Dyslipidemia is becoming prevalent in Africa, where malaria is endemic. Observational studies have documented the long-term protective effect of malaria on dyslipidemia; however, these study designs are prone to confounding. Therefore, we used Mendelian randomization (MR, a method robust to confounders and reverse causation) to determine the causal effect of severe malaria (SM) and the recurrence of non-severe malaria (RNM) on lipid traits. METHOD: We performed two-sample MR using genome wide association study (GWAS) summary statistics for recurrent non-severe malaria (RNM) from a Benin cohort (N = 775) and severe malaria from the MalariaGEN dataset (N = 17,000) and lipid traits from summary-level data of a meta-analyzed African lipid GWAS (MALG, N = 24,215) from the African Partnership for Chronic Disease Research (APCDR) (N = 13,612) and the Africa Wits-IN-DEPTH partnership for genomics studies (AWI-Gen) dataset (N = 10,603). RESULT: No evidence of significant causal association was obtained between RNM and high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholesterol and triglycerides. However, a notable association emerged between severe malarial anaemia (SMA) which is a subtype of severe malaria and reduced HDL-C levels, suggesting a potential subtype-specific effect. Nonetheless, we strongly believe that the small sample size likely affects our estimates, warranting cautious interpretation of these results. CONCLUSION: Our findings challenge the hypothesis of a broad causal relationship between malaria (both severe and recurrent non-severe forms) and dyslipidemia. The isolated association with SMA highlights an intriguing area for future research. However, we believe that conducting larger studies to investigate the connection between malaria and dyslipidemia in Africa will enhance our ability to better address the burden posed by both diseases.

Correction: Udosen et al. Meta-Analysis and Multivariate GWAS Analyses in 80,950 Individuals of African Ancestry Identify Novel Variants Associated with Blood Pressure Traits. Int. J. Mol. Sci. 2023, 24, 2164.

In the original publication [...].

Meta-analysis of African ancestry genome-wide association studies identified novel locus and validates multiple loci associated with kidney function.

Despite recent efforts to increase diversity in genome-wide association studies (GWASs), most loci currently associated with kidney function are still limited to European ancestry due to the underlying sample selection bias in available GWASs. We set out to identify susceptibility loci associated with estimated glomerular filtration rate (eGFRcrea) in 80027 individuals of African-ancestry from the UK Biobank (UKBB), Million Veteran Program (MVP), and Chronic Kidney Disease genetics (CKDGen) consortia.We identified 8 lead SNPs, 7 of which were previously associated with eGFR in other populations. We identified one novel variant, rs77408001 which is an intronic variant mapped to the ELN gene. We validated three previously reported loci at GATM-SPATA5L1, SLC15A5 and AGPAT3. Fine-mapping analysis identified variants rs77121243 and rs201602445 as having a 99.9% posterior probability of being causal. Our results warrant designing bigger studies within individuals of African ancestry to gain new insights into the pathogenesis of Chronic Kidney Disease (CKD), and identify genomic variants unique to this ancestry that may influence renal function and disease.

Discovery and fine-mapping of kidney function loci in first genome-wide association study in Africans.

Genome-wide association studies (GWAS) of kidney function have uncovered hundreds of loci, primarily in populations of European ancestry. We have undertaken the first continental African GWAS of estimated glomerular filtration rate (eGFR), a measure of kidney function used to define chronic kidney disease (CKD). We conducted GWAS of eGFR in 3288 East Africans from the Uganda General Population Cohort (GPC) and replicated in 8224 African Americans from the Women's Health Initiative. Loci attaining genome-wide significant evidence for association (P < 5 × 10-8) were followed up with Bayesian fine-mapping to localize potential causal variants. The predictive power of a genetic risk score (GRS) constructed from previously reported trans-ancestry eGFR lead single nucleotide polymorphism (SNPs) was evaluated in the Uganda GPC. We identified and validated two eGFR loci. At the glycine amidinotransferase (GATM) locus, the association signal (lead SNP rs2433603, P = 1.0 × 10-8) in the Uganda GPC GWAS was distinct from previously reported signals at this locus. At the haemoglobin beta (HBB) locus, the association signal (lead SNP rs141845179, P = 3.0 × 10-8) has been previously reported. The lead SNP at the HBB locus accounted for 88% of the posterior probability of causality after fine-mapping, but did not colocalise with kidney expression quantitative trait loci. The trans-ancestry GRS of eGFR was not significantly predictive into the Ugandan population. In the first GWAS of eGFR in continental Africa, we validated two previously reported loci at GATM and HBB. At the GATM locus, the association signal was distinct from that previously reported. These results demonstrate the value of performing GWAS in continental Africans, providing a rich genomic resource to larger consortia for further discovery and fine-mapping. The study emphasizes that additional large-scale efforts in Africa are warranted to gain further insight into the genetic architecture of CKD.

Reviewing and assessing existing meta-analysis models and tools.

Over the past few years, meta-analysis has become popular among biomedical researchers for detecting biomarkers across multiple cohort studies with increased predictive power. Combining datasets from different sources increases sample size, thus overcoming the issue related to limited sample size from each individual study and boosting the predictive power. This leads to an increased likelihood of more accurately predicting differentially expressed genes/proteins or significant biomarkers underlying the biological condition of interest. Currently, several meta-analysis methods and tools exist, each having its own strengths and limitations. In this paper, we survey existing meta-analysis methods, and assess the performance of different methods based on results from different datasets as well as assessment from prior knowledge of each method. This provides a reference summary of meta-analysis models and tools, which helps to guide end-users on the choice of appropriate models or tools for given types of datasets and enables developers to consider current advances when planning the development of new meta-analysis models and more practical integrative tools.

Benzimidazole compound abrogates SARS-COV-2 receptor-binding domain (RBD)/ACE2 interaction In vitro.

The development of clinically actionable pharmaceuticals against coronavirus disease (COVID-19); an infectious disease caused by the SARS-CoV-2 virus is very important for ending the pandemic. Coronavirus spike glycoprotein (GP)-Receptor Binding Domain (RBD) and its interaction with host receptor angiotensin converting enzyme 2 (ACE2) is one of the most structurally understood but therapeutically untapped aspect of COVID-19 pathogenesis. Binding interface based on previous x-ray structure of RBD/ACE2 were virtually screened to identify fragments with high-binding score from 12,000 chemical building blocks. The hit compound was subjected to fingerprint-based similarity search to identify compounds within the FDA-approved drug library containing the same core scaffold. Identified compounds were then re-docked into of RBD/ACE2. The best ranked compound was validated for RBD/ACE2 inhibition using commercial kit. Molecular dynamics simulation was conducted to provide further insight into the mechanism of inhibition. From the original 12000 chemical building blocks, benzimidazole (BAZ) scaffold was identified. Fingerprint-based similarity search of the FDA-approved drug library for BAZ-containing compounds identified 12 drugs with the benzimidazole-like substructure. When these compounds were re-docked into GP/ACE2 interface, the consensus docking identified bazedoxifene as the hit. In vitro RBD/ACE2 inhibition kinetics showed micromolar IC50 value (1.237 µM) in the presence of bazedoxifene. Molecular dynamics simulation of RBD/ACE2 in the presence BAZ resulted in loss of contact and specific hydrogen-bond interaction required for RBD/ACE2 stability. Taken together, these findings identified benzimidazole scaffold as a building block for developing novel RBD/ACE2 complex inhibitor and provided mechanistic basis for the use of bazedoxifene as a repurposable drug for the treatment of COVID-19 acting at RBD/ACE2 interface.

Meta-Analysis and Multivariate GWAS Analyses in 77,850 Individuals of African Ancestry Identify Novel Variants Associated with Blood Pressure Traits.

High blood pressure (HBP) has been implicated as a major risk factor for cardiovascular diseases in several populations, including individuals of African ancestry. Despite the elevated burden of HBP-induced cardiovascular diseases in Africa and other populations of African descent, limited genetic studies have been carried out to explore the genetic mechanism driving this phenomenon. We performed genome-wide association univariate and multivariate analyses of both systolic (SBP) and diastolic blood pressure (DBP) traits in 77, 850 individuals of African ancestry. We used summary statistics data from six independent cohorts, including the African Partnership for Chronic Disease Research (APCDR), the UK Biobank, and the Million Veteran Program (MVP). FUMA was used to annotate, prioritize, visualize, and interpret our findings to gain a better understanding of the molecular mechanism(s) underlying the genetics of BP traits. Finally, we undertook a Bayesian fine-mapping analysis to identify potential causal variants. Our meta-analysis identified 10 independent variants associated with SBP and 9 with DBP traits. Whilst our multivariate GWAS method identified 21 independent signals, 18 of these SNPs have been previously identified. SBP was linked to gene sets involved in biological processes such as synapse assembly and cell-cell adhesion via plasma membrane adhesion. Of the 19 independent SNPs identified in the BP meta-analysis, only 11 variants had posterior probability (PP) of > 50%, including one novel variant: rs562545 (MOBP, PP = 77%). To facilitate further research and fine-mapping of high-risk loci/variants in highly susceptible groups for cardiovascular disease and other related traits, large-scale genomic datasets are needed. Our findings highlight the importance of including ancestrally diverse populations in large GWASs and the need for diversity in genetic research.

Genetic loci implicated in meta-analysis of body shape in Africans.

BACKGROUND AND AIMS: Obesity is one of the leading causes of non-communicable diseases (NCD). Thus, NCD risk varies in obese individuals based on the location of their fat depots; while subcutaneous adiposity is protective, visceral adiposity increases NCD risk. Although, previously anthropometric traits have been used to quantify body shape in low-income settings, there is no consensus on how it should be assessed. Hence, there is a growing interest to evaluate body shape derived from the principal component analysis (PCA) of anthropometric traits; however, this is yet to be explored in individuals of African ancestry whose body shape is different from those of Europeans. We set out to capture body shape in its multidimensional structure and examine the association between genetic variants and body shape in individuals of African ancestry. METHOD AND RESULTS: We performed a genome-wide association study (GWAS) for body shape derived from PCA analysis of anthropometric traits in the Ugandan General Population Cohort (GPC, n = 6407) and the South African Zulu Cohort (SZC, n = 2595), followed by a GWAS meta-analysis to assess the genetic variants associated with body shape. We identified variants in FGF12, GRM8, TLX1NB and TRAP1 to be associated with body shape. These genes were different from the genes been associated with BMI, height, weight, WC and waist-hip ration in continental Africans. Notably, we also observed that a standard deviation change in body shape was associated with an increase in blood pressure and blood lipids. CONCLUSION: Variants associated with body shape, as a composite variable might be different for those of individual anthropometric traits. Larger studies are required to further explore these phenomena.

Metabolic Traits and Stroke Risk in Individuals of African Ancestry: Mendelian Randomization Analysis.

BACKGROUND AND PURPOSE: Metabolic traits affect ischemic stroke (IS) risk, but the degree to which this varies across different ethnic ancestries is not known. Our aim was to apply Mendelian randomization to investigate the causal effects of type 2 diabetes (T2D) liability and lipid traits on IS risk in African ancestry individuals, and to compare them to estimates obtained in European ancestry individuals. METHODS: For African ancestry individuals, genetic proxies for T2D liability and circulating lipids were obtained from a meta-analysis of the African Partnership for Chronic Disease Research study, the UK Biobank, and the Million Veteran Program (total N=77 061). Genetic association estimates for IS risk were obtained from the Consortium of Minority Population Genome-Wide Association Studies of Stroke (3734 cases and 18 317 controls). For European ancestry individuals, genetic proxies for the same metabolic traits were obtained from Million Veteran Program (lipids N=297 626, T2D N=148 726 cases, and 965 732 controls), and genetic association estimates for IS risk were obtained from the MEGASTROKE study (34 217 cases and 406 111 controls). Random-effects inverse-variance weighted Mendelian randomization was used as the main method, complemented with sensitivity analyses more robust to pleiotropy. RESULTS: Higher genetically proxied T2D liability, LDL-C (low-density lipoprotein cholesterol), total cholesterol and lower genetically proxied HDL-C (high-density lipoprotein cholesterol) were associated with increased risk of IS in African ancestry individuals (odds ratio per doubling the odds of T2D liability [95% CI], 1.09 [1.07-1.11]; per standard-deviation increase in LDL-C, 1.12 [1.04-1.21]; total cholesterol: 1.23 [1.06-1.43]; HDL-C, 0.93 [0.89-0.99]). There was no evidence for differences in these estimates when performing analyses in European ancestry individuals. CONCLUSIONS: Our analyses support a causal effect of T2D liability and lipid traits on IS risk in African ancestry individuals, with Mendelian randomization estimates similar to those obtained in European ancestry individuals.