Computation of Socio-Economic Status in the AWI-Gen Project.

Socio-economic status of participants in many public health, epidemiological, and genome-wide association studies is an important trait of interest. It is often used in these studies as a measure of direct interest or as a covariate. The Africa Wits INDEPTH Partnership for Genomic and Environmental Research (AWI-Gen) explores genomic and environmental factors in non-communicable diseases, particularly cardio-metabolic disease. In Phase I of AWI-Gen, approximately 12,000 participants were recruited at six sites in four African countries. Participants were asked questions about asset ownership. This technical note describes how AWI-Gen computed socio-economic status from the asset register.

A GWAS of ACE Inhibitor-Induced Angioedema in a South African Population.

Background: Angiotensin-converting enzyme inhibitor-induced angioedema (AE-ACEI) is a life-threatening adverse event and, globally, the commonest cause of emergency presentations with angioedema. Several large genome-wide association studies (GWAS) have found genomic associations with AE-ACEI. However, despite African Americans having a 5-fold increased risk of AE-ACEI, there are no published GWAS from Africa. The aim of this study was to conduct a case-control GWAS of AE-ACEI in a South African population and perform a meta-analysis with an African American and European American population. Methods: The GWAS included 202 South African adults with a history of AE-ACEI and 513 controls without angioedema following angiotensin-converting enzyme inhibitor (ACEI) treatment for at least 2 years. A meta-analysis was conducted with GWAS summary statistics from an African American and European American cohort (from Vanderbilt/Marshfield with 174 cases and 489 controls). Results: No SNPs attained genome-wide significance. However, 26 SNPs in the post-imputation standard GWAS of the South African cohort and 37 SNPs in the meta-analysis were associated to AE-ACEI with suggestive threshold(p-value<5.0×10 -06 ). Some of these SNPs were found to be located close to the genes PRKCQ and RIMS1, previously linked with drug-induced angioedema, and also close to the CSMD1 gene linked to ACEI cough, providing replication at the gene level, but with novel lead SNPs. Conclusions: Our results highlight the importance of African populations to detect novel variants in replication studies. Further increased sampling across the continent and matched functional work are needed to confirm the importance of genetic variation in understanding the biology of AE-ACEI.

Ancestry-aligned polygenic scores combined with conventional risk factors improve prediction of cardiometabolic outcomes in African populations.

BACKGROUND: Cardiovascular diseases (CVD) are a major health concern in Africa. Improved identification and treatment of high-risk individuals can reduce adverse health outcomes. Current CVD risk calculators are largely unvalidated in African populations and overlook genetic factors. Polygenic scores (PGS) can enhance risk prediction by measuring genetic susceptibility to CVD, but their effectiveness in genetically diverse populations is limited by a European-ancestry bias. To address this, we developed models integrating genetic data and conventional risk factors to assess the risk of developing cardiometabolic outcomes in African populations. METHODS: We used summary statistics from a genome-wide association meta-analysis (n = 14,126) in African populations to derive novel genome-wide PGS for 14 cardiometabolic traits in an independent African target sample (Africa Wits-INDEPTH Partnership for Genomic Research (AWI-Gen), n = 10,603). Regression analyses assessed relationships between each PGS and corresponding cardiometabolic trait, and seven CVD outcomes (CVD, heart attack, stroke, diabetes mellitus, dyslipidaemia, hypertension, and obesity). The predictive utility of the genetic data was evaluated using elastic net models containing multiple PGS (MultiPGS) and reference-projected principal components of ancestry (PPCs). An integrated risk prediction model incorporating genetic and conventional risk factors was developed. Nested cross-validation was used when deriving elastic net models to enhance generalisability. RESULTS: Our African-specific PGS displayed significant but variable within- and cross- trait prediction (max.R2 = 6.8%, p = 1.86 × 10-173). Significantly associated PGS with dyslipidaemia included the PGS for total cholesterol (logOR = 0.210, SE = 0.022, p = 2.18 × 10-21) and low-density lipoprotein (logOR = - 0.141, SE = 0.022, p = 1.30 × 10-20); with hypertension, the systolic blood pressure PGS (logOR = 0.150, SE = 0.045, p = 8.34 × 10-4); and multiple PGS associated with obesity: body mass index (max. logOR = 0.131, SE = 0.031, p = 2.22 × 10-5), hip circumference (logOR = 0.122, SE = 0.029, p = 2.28 × 10-5), waist circumference (logOR = 0.013, SE = 0.098, p = 8.13 × 10-4) and weight (logOR = 0.103, SE = 0.029, p = 4.89 × 10-5). Elastic net models incorporating MultiPGS and PPCs significantly improved prediction over MultiPGS alone. Models including genetic data and conventional risk factors were more predictive than conventional risk models alone (dyslipidaemia: R2 increase = 2.6%, p = 4.45 × 10-12; hypertension: R2 increase = 2.6%, p = 2.37 × 10-13; obesity: R2 increase = 5.5%, 1.33 × 10-34). CONCLUSIONS: In African populations, CVD and associated cardiometabolic trait prediction models can be improved by incorporating ancestry-aligned PGS and accounting for ancestry. Combining PGS with conventional risk factors further enhances prediction over traditional models based on conventional factors. Incorporating data from target populations can improve the generalisability of international predictive models for CVD and associated traits in African populations.

The Value Proposition of Coordinated Population Cohorts Across Africa.

Building longitudinal population cohorts in Africa for coordinated research and surveillance can influence the setting of national health priorities, lead to the introduction of appropriate interventions, and provide evidence for targeted treatment, leading to better health across the continent. However, compared to cohorts from the global north, longitudinal continental African population cohorts remain scarce, are relatively small in size, and lack data complexity. As infections and noncommunicable diseases disproportionately affect Africa's approximately 1.4 billion inhabitants, African cohorts present a unique opportunity for research and surveillance. High genetic diversity in African populations and multiomic research studies, together with detailed phenotyping and clinical profiling, will be a treasure trove for discovery. The outcomes, including novel drug targets, biological pathways for disease, and gene-environment interactions, will boost precision medicine approaches, not only in Africa but across the globe.

Mapping Epigenetic Gene Variant Dynamics: Comparative Analysis of Frequency, Functional Impact and Trait Associations in African and European Populations.

Epigenetic modifications influence gene expression levels, impact organismal traits, and play a role in the development of diseases. Therefore, variants in genes involved in epigenetic processes are likely to be important in disease susceptibility, and the frequency of variants may vary between populations with African and European ancestries. Here, we analyse an integrated dataset to define the frequencies, associated traits, and functional impact of epigenetic gene variants among individuals of African and European ancestry represented in the UK Biobank. We find that the frequencies of 88.4% of epigenetic gene variants significantly differ between these groups. Furthermore, we find that the variants are associated with many traits and diseases, and some of these associations may be population-specific owing to allele frequency differences. Additionally, we observe that variants associated with traits are significantly enriched for quantitative trait loci that affect DNA methylation, chromatin accessibility, and gene expression. We find that methylation quantitative trait loci account for 71.2% of the variants influencing gene expression. Moreover, variants linked to biomarker traits exhibit high correlation. We therefore conclude that epigenetic gene variants associated with traits tend to differ in their allele frequencies among African and European populations and are enriched for QTLs.

Reporting guidelines for precision medicine research of clinical relevance: the BePRECISE checklist.

Precision medicine should aspire to reduce error and improve accuracy in medical and health recommendations by comparison with contemporary practice, while maintaining safety and cost-effectiveness. The etiology, clinical manifestation and prognosis of diseases such as obesity, diabetes, cardiovascular disease, kidney disease and fatty liver disease are heterogeneous. Without standardized reporting, this heterogeneity, combined with the diversity of research tools used in precision medicine studies, makes comparisons across studies and implementation of the findings challenging. Specific recommendations for reporting precision medicine research do not currently exist. The BePRECISE (Better Precision-data Reporting of Evidence from Clinical Intervention Studies & Epidemiology) consortium, comprising 23 experts in precision medicine, cardiometabolic diseases, statistics, editorial and lived experience, conducted a scoping review and participated in a modified Delphi and nominal group technique process to develop guidelines for reporting precision medicine research. The BePRECISE checklist comprises 23 items organized into 5 sections that align with typical sections of a scientific publication. A specific section about health equity serves to encourage precision medicine research to be inclusive of individuals and communities that are traditionally under-represented in clinical research and/or underserved by health systems. Adoption of BePRECISE by investigators, reviewers and editors will facilitate and accelerate equitable clinical implementation of precision medicine.

The association of menopause with cardiometabolic disease risk factors in women living with and without HIV in sub-Saharan Africa: Results from the AWI-Gen 1 study.

BACKGROUND: Menopause and HIV are associated with cardiometabolic disease. In sub-Saharan Africa there is a growing population of midlife women living with HIV and a high prevalence of cardiometabolic disease. OBJECTIVES: The aim of this study was to determine whether menopause and HIV were associated with cardiometabolic disease risk factors in a population of midlife sub-Saharan African women. STUDY DESIGN: This was a cross-sectional comparison of cardiometabolic disease risk factors between 944 premenopausal women (733 living without HIV and 211 living with HIV) and 1135 postmenopausal women (932 living without HIV and 203 living with HIV) in sub-Saharan Africa. MAIN OUTCOME MEASURES: Anthropometric and cardiometabolic variables were compared between pre- and postmenopausal women living without HIV and between pre- and postmenopausal women living with HIV and between women living without HIV and women living with HIV. RESULTS: The prevalence of HIV was 19.9 %. Age at menopause was lower in women living with HIV than in women living without HIV (48.1 ± 5.1 vs 50.9 ± 4.7 years, p < 0.001). Women living with HIV and receiving efavirenz-based antiretroviral therapy had a lower body mass index (BMI), hip circumference, blood pressure and carotid intima media thickness but higher triglyceride levels and insulin resistance than women living without HIV. Antiretroviral therapy-naïve women living with HIV had lower HDL-cholesterol than women living without HIV. In this study, menopause was associated with higher LDL-C levels, regardless of HIV status. CONCLUSION: The high prevalence of obesity and related cardiometabolic disease risk factors in these midlife sub-Saharan African women is not related to the menopausal transition. The association of cardiometabolic disease risk factors with HIV and antiretroviral therapy is complex and requires further investigation in longitudinal studies, as does the negative association of age at final menstrual period with HIV.

An assessment of the genomic structural variation landscape in Sub-Saharan African populations.

Structural variants are responsible for a large part of genomic variation between individuals and play a role in both common and rare diseases. Databases cataloguing structural variants notably do not represent the full spectrum of global diversity, particularly missing information from most African populations. To address this representation gap, we analysed 1,091 high-coverage African genomes, 545 of which are public data sets, and 546 which have been analysed for structural variants for the first time. Variants were called using five different tools and datasets merged and jointly called using SURVIVOR. We identified 67,795 structural variants throughout the genome, with 10,421 genes having at least one variant. Using a conservative overlap in merged data, 6,414 of the structural variants (9.5%) are novel compared to the Database of Genomic Variants. This study contributes to knowledge of the landscape of structural variant diversity in Africa and presents a reliable dataset for potential applications in population genetics and health-related research.

Genetic association and transferability for urinary albumin-creatinine ratio as a marker of kidney disease in four Sub-Saharan African populations and non-continental individuals of African ancestry.

Background: Genome-wide association studies (GWAS) have predominantly focused on populations of European and Asian ancestry, limiting our understanding of genetic factors influencing kidney disease in Sub-Saharan African (SSA) populations. This study presents the largest GWAS for urinary albumin-to-creatinine ratio (UACR) in SSA individuals, including 8,970 participants living in different African regions and an additional 9,705 non-resident individuals of African ancestry from the UK Biobank and African American cohorts. Methods: Urine biomarkers and genotype data were obtained from two SSA cohorts (AWI-Gen and ARK), and two non-resident African-ancestry studies (UK Biobank and CKD-Gen Consortium). Association testing and meta-analyses were conducted, with subsequent fine-mapping, conditional analyses, and replication studies. Polygenic scores (PGS) were assessed for transferability across populations. Results: Two genome-wide significant (P < 5 × 10-8) UACR-associated loci were identified, one in the BMP6 region on chromosome 6, in the meta-analysis of resident African individuals, and another in the HBB region on chromosome 11 in the meta-analysis of non-resident SSA individuals, as well as the combined meta-analysis of all studies. Replication of previous significant results confirmed associations in known UACR-associated regions, including THB53, GATM, and ARL15. PGS estimated using previous studies from European ancestry, African ancestry, and multi-ancestry cohorts exhibited limited transferability of PGS across populations, with less than 1% of observed variance explained. Conclusion: This study contributes novel insights into the genetic architecture of kidney disease in SSA populations, emphasizing the need for conducting genetic research in diverse cohorts. The identified loci provide a foundation for future investigations into the genetic susceptibility to chronic kidney disease in underrepresented African populations Additionally, there is a need to develop integrated scores using multi-omics data and risk factors specific to the African context to improve the accuracy of predicting disease outcomes.

Variability of polygenic prediction for body mass index in Africa.

BACKGROUND: Polygenic prediction studies in continental Africans are scarce. Africa's genetic and environmental diversity pose a challenge that limits the generalizability of polygenic risk scores (PRS) for body mass index (BMI) within the continent. Studies to understand the factors that affect PRS variability within Africa are required. METHODS: Using the first multi-ancestry genome-wide association study (GWAS) meta-analysis for BMI involving continental Africans, we derived a multi-ancestry PRS and compared its performance to a European ancestry-specific PRS in continental Africans (AWI-Gen study) and a European cohort (Estonian Biobank). We then evaluated the factors affecting the performance of the PRS in Africans which included fine-mapping resolution, allele frequencies, linkage disequilibrium patterns, and PRS-environment interactions. RESULTS: Polygenic prediction of BMI in continental Africans is poor compared to that in European ancestry individuals. However, we show that the multi-ancestry PRS is more predictive than the European ancestry-specific PRS due to its improved fine-mapping resolution. We noted regional variation in polygenic prediction across Africa's East, South, and West regions, which was driven by a complex interplay of the PRS with environmental factors, such as physical activity, smoking, alcohol intake, and socioeconomic status. CONCLUSIONS: Our findings highlight the role of gene-environment interactions in PRS prediction variability in Africa. PRS methods that correct for these interactions, coupled with the increased representation of Africans in GWAS, may improve PRS prediction in Africa.

Application of Genomic Medicine in Africa: 14th Conference of the African Society of Human Genetics and the 2nd International Congress of the Moroccan Society of Genomics and Human Genetics, Rabat, Morocco 2022.

The 14th African Society of Human Genetics (AfSHG) Morocco Meeting and 2nd International Congress of the Moroccan Society of Genomics and Human Genetics (SM2GH), held in Rabat, Morocco, from December 12 through 17, 2022, brought together 298 attendees from 23 countries, organized by the AfSHG in collaboration with the SM2GH. The conference's overarching theme was "Applications of Genomics Medicine in Africa," covering a wide range of topics, including population genetics, genetics of infectious diseases, hereditary disorders, cancer genetics, and translational genetics. The conference aimed to address the lag in the field of genetics in Africa and highlight the potential for genetic research and personalized medicine on the continent. The goal was to improve the health of African populations and global communities while nurturing the careers of young African scientists in the field. Distinguished scientists from around the world shared their recent findings in genetics, immunogenetics, genomics, genome editing, immunotherapy, and ethics genomics. Precongress activities included a 2-day bioinformatics workshop, "NGS Analysis for Monogenic Disease in African Populations," and a Young Investigators Forum, providing opportunities for young African researchers to showcase their work. The vast genetic diversity of the African continent poses a significant challenge in investigating and characterizing public health issues at the genetic and functional levels. Training, research, and the development of expertise in genetics, immunology, genomics, and bioinformatics are vital for addressing these challenges and advancing genetics in Africa. The AfSHG is committed to leading efforts to enhance genetic research, coordinate training, and foster research collaborations on the continent.

Expanding the human gut microbiome atlas of Africa.

Population studies are crucial in understanding the complex interplay between the gut microbiome and geographical, lifestyle, genetic, and environmental factors. However, populations from low- and middle-income countries, which represent ~84% of the world population, have been excluded from large-scale gut microbiome research. Here, we present the AWI-Gen 2 Microbiome Project, a cross-sectional gut microbiome study sampling 1,803 women from Burkina Faso, Ghana, Kenya, and South Africa. By intensively engaging with communities that range from rural and horticultural to urban informal settlements and post-industrial, we capture population diversity that represents a far greater breadth of the world's population. Using shotgun metagenomic sequencing, we find that study site explains substantially more microbial variation than disease status. We identify taxa with strong geographic and lifestyle associations, including loss of Treponema and Cryptobacteroides species and gain of Bifidobacterium species in urban populations. We uncover a wealth of prokaryotic and viral novelty, including 1,005 new bacterial metagenome-assembled genomes, and identify phylogeography signatures in Treponema succinifaciens. Finally, we find a microbiome signature of HIV infection that is defined by several taxa not previously associated with HIV, including Dysosmobacter welbionis and Enterocloster sp. This study represents the largest population-representative survey of gut metagenomes of African individuals to date, and paired with extensive clinical biomarkers, demographic data, and lifestyle information, provides extensive opportunity for microbiome-related discovery and research.

Postprandial glucose variability and clusters of sex hormones, liver enzymes, and cardiometabolic factors in a South African cohort of African ancestry.

INTRODUCTION: This study aimed to, first, determine the clusters of sex hormones, liver enzymes, and cardiometabolic factors associated with postprandial glucose (PPG) and, second to evaluate the variation these clusters account for jointly and independently with polygenic risk scores (PRSs) in South Africans of African ancestry men and women. RESEARCH DESIGN AND METHODS: PPG was calculated as the integrated area under the curve for glucose during the oral glucose tolerance test (OGTT) using the trapezoidal rule in 794 participants from the Middle-aged Soweto Cohort. Principal component analysis was used to cluster sex hormones, liver enzymes, and cardiometabolic factors, stratified by sex. Multivariable linear regression was used to assess the proportion of variance in PPG accounted for by principal components (PCs) and type 2 diabetes (T2D) PRS while adjusting for selected covariates in men and women. RESULTS: The T2D PRS did not contribute to the PPG variability in both men and women. In men, the PCs' cluster of sex hormones, liver enzymes, and cardiometabolic explained 10.6% of the variance in PPG, with PC1 (peripheral fat), PC2 (liver enzymes and steroid hormones), and PC3 (lipids and peripheral fat) contributing significantly to PPG. In women, PC factors of sex hormones, cardiometabolic factors, and liver enzymes explained a similar amount of the variance in PPG (10.8%), with PC1 (central fat) and PC2 (lipids and liver enzymes) contributing significantly to PPG. CONCLUSIONS: We demonstrated that inter-individual differences in PPG responses to an OGTT may be differentially explained by body fat distribution, serum lipids, liver enzymes, and steroid hormones in men and women.

Proteomic insights into the pathophysiology of hypertension-associated albuminuria: Pilot study in a South African cohort.

BACKGROUND: Hypertension is an important public health priority with a high prevalence in Africa. It is also an independent risk factor for kidney outcomes. We aimed to identify potential proteins and pathways involved in hypertension-associated albuminuria by assessing urinary proteomic profiles in black South African participants with combined hypertension and albuminuria compared to those who have neither condition. METHODS: The study included 24 South African cases with both hypertension and albuminuria and 49 control participants who had neither condition. Protein was extracted from urine samples and analysed using ultra-high-performance liquid chromatography coupled with mass spectrometry. Data were generated using data-independent acquisition (DIA) and processed using Spectronaut™ 15. Statistical and functional data annotation were performed on Perseus and Cytoscape to identify and annotate differentially abundant proteins. Machine learning was applied to the dataset using the OmicLearn platform. RESULTS: Overall, a mean of 1,225 and 915 proteins were quantified in the control and case groups, respectively. Three hundred and thirty-two differentially abundant proteins were constructed into a network. Pathways associated with these differentially abundant proteins included the immune system (q-value [false discovery rate] = 1.4 × 10- 45), innate immune system (q = 1.1 × 10- 32), extracellular matrix (ECM) organisation (q = 0.03) and activation of matrix metalloproteinases (q = 0.04). Proteins with high disease scores (76-100% confidence) for both hypertension and chronic kidney disease included angiotensinogen (AGT), albumin (ALB), apolipoprotein L1 (APOL1), and uromodulin (UMOD). A machine learning approach was able to identify a set of 20 proteins, differentiating between cases and controls. CONCLUSIONS: The urinary proteomic data combined with the machine learning approach was able to classify disease status and identify proteins and pathways associated with hypertension-associated albuminuria.

Factors associated with frequency of fruit and vegetable consumption among selected sub-Saharan African populations: evidence from the Cardiovascular H3Africa Innovation Resource Project.

BACKGROUND: Frequent fruit and vegetable consumption is considered a promising dietary behaviour that protects health. However, most existing studies about the factors associated with this phenomenon among Africans are based on single-country reports, apart from one meta-regression combining smaller studies. This study harmonized large datasets and assessed factors associated with the frequency of fruit and vegetable consumption in this population. METHODS: Individual-level data on sociodemographics, lifestyle and diet from 20 443 participants across five African countries (Burkina Faso, Ghana, Kenya, South Africa and Nigeria), from the Stroke Investigative Research and Educational Network (SIREN) and Africa Wits-INDEPTH partnership for Genomic Research (AWI-Gen) studies, were harmonized. Total frequency of fruit and vegetable consumption (in portions/week) was classified as 'low' (≤6), 'moderate' (7-14) and 'high' (≥15). Adjusted odds ratios (aORs) and 95% confidence intervals (CIs) of factors associated with the total frequency of fruit and vegetable consumption (using 'low' consumption as the reference) were estimated using multinomial regression models. RESULTS: Mean age of participants was 54.3 ± 11.8 years, 10 641 (52.1%) were female, and the median (interquartile range) frequency of total fruit and vegetable consumption was 10.0 (4.0, 21.0) portions/week. Participants with a family history of cardiovascular disease [moderate (aOR, 0.92; 95% CI, 0.85, 1.00) and high (aOR, 0.85; 95% CI, 0.78, 0.92)], current smokers [moderate (aOR, 0.83; 95% CI, 0.74, 0.94) and high (aOR, 0.78; 95% CI, 0.69, 0.88)], current alcohol users [moderate (aOR, 0.92; 95% CI, 0.85, 1.00) and high (aOR, 0.82; 95% CI, 0.76, 0.89)] and physically inactive participants [moderate (aOR, 0.85; 95% CI, 0.75, 0.96) and high (aOR, 0.80; 95% CI, 0.70, 0.90)] were less likely to consume fruits and vegetables frequently. CONCLUSION: Africans with lifestyle risk factors for cardiovascular disease were less likely to consume fruit and vegetables frequently.

Genetic Association and Transferability for Urinary Albumin-Creatinine Ratio as a Marker of Kidney Disease in four Sub-Saharan African Populations and non-continental Individuals of African Ancestry.

BACKGROUND: Genome-wide association studies (GWAS) have predominantly focused on populations of European and Asian ancestry, limiting our understanding of genetic factors influencing kidney disease in Sub-Saharan African (SSA) populations. This study presents the largest GWAS for urinary albumin-to-creatinine ratio (UACR) in SSA individuals, including 8,970 participants living in different African regions and an additional 9,705 non-resident individuals of African ancestry from the UK Biobank and African American cohorts. METHODS: Urine biomarkers and genotype data were obtained from two SSA cohorts (AWI-Gen and ARK), and two non-resident African-ancestry studies (UK Biobank and CKD-Gen Consortium). Association testing and meta-analyses were conducted, with subsequent fine-mapping, conditional analyses, and replication studies. Polygenic scores (PGS) were assessed for transferability across populations. RESULTS: Two genome-wide significant (P<5x10-8) UACR-associated loci were identified, one in the BMP6 region on chromosome 6, in the meta-analysis of resident African individuals, and another in the HBB region on chromosome 11 in the meta-analysis of non-resident SSA individuals, as well as the combined meta-analysis of all studies. Replication of previous significant results confirmed associations in known UACR-associated regions, including THB53, GATM, and ARL15. PGS estimated using previous studies from European ancestry, African ancestry, and multi-ancestry cohorts exhibited limited transferability of PGS across populations, with less than 1% of observed variance explained. CONCLUSION: This study contributes novel insights into the genetic architecture of kidney disease in SSA populations, emphasizing the need for conducting genetic research in diverse cohorts. The identified loci provide a foundation for future investigations into the genetic susceptibility to chronic kidney disease in underrepresented African populations Additionally, there is a need to develop integrated scores using multi-omics data and risk factors specific to the African context to improve the accuracy of predicting disease outcomes. METHODS: Urine biomarkers and genotype data were obtained from two SSA cohorts (AWI-Gen and ARK), and two non-resident African-ancestry studies (UK Biobank and CKD-Gen Consortium). Association testing and meta-analyses were conducted, with subsequent fine-mapping, conditional analyses, and replication studies. Polygenic scores (PGS) were assessed for transferability across populations. RESULTS: Two genome-wide significant (P<5x10-8) UACR-associated loci were identified, one in the BMP6 region on chromosome 6, in the meta-analysis of resident African individuals, and another in the HBB region on chromosome 11 in the meta-analysis of non-resident SSA individuals, as well as the combined meta-analysis of all studies. Replication of previous significant results confirmed associations in known UACR-associated regions, including THB53, GATM, and ARL15. PGS estimated using previous studies from European ancestry, African ancestry, and multi-ancestry cohorts exhibited limited transferability of PGS across populations, with less than 1% of observed variance explained. CONCLUSION: This study contributes novel insights into the genetic architecture of kidney function in SSA populations, emphasizing the need for conducting genetic research in diverse cohorts. The identified loci provide a foundation for future investigations into the genetic susceptibility to chronic kidney disease in underrepresented African populations.

A multi-cohort genome-wide association study in African ancestry individuals reveals risk loci for primary open-angle glaucoma.

Primary open-angle glaucoma (POAG), the leading cause of irreversible blindness worldwide, disproportionately affects individuals of African ancestry. We conducted a genome-wide association study (GWAS) for POAG in 11,275 individuals of African ancestry (6,003 cases; 5,272 controls). We detected 46 risk loci associated with POAG at genome-wide significance. Replication and post-GWAS analyses, including functionally informed fine-mapping, multiple trait co-localization, and in silico validation, implicated two previously undescribed variants (rs1666698 mapping to DBF4P2; rs34957764 mapping to ROCK1P1) and one previously associated variant (rs11824032 mapping to ARHGEF12) as likely causal. For individuals of African ancestry, a polygenic risk score (PRS) for POAG from our mega-analysis (African ancestry individuals) outperformed a PRS from summary statistics of a much larger GWAS derived from European ancestry individuals. This study quantifies the genetic architecture similarities and differences between African and non-African ancestry populations for this blinding disease.

Characterization of CYP2B6 and CYP2A6 Pharmacogenetic Variation in Sub-Saharan African Populations.

Genetic variation in CYP2B6 and CYP2A6 is known to impact interindividual response to antiretrovirals, nicotine, and bupropion, among other drugs. However, the full catalogue of clinically relevant pharmacogenetic variants in these genes is yet to be established, especially across African populations. This study therefore aimed to characterize the star allele (haplotype) distribution in CYP2B6 and CYP2A6 across diverse and understudied sub-Saharan African (SSA) populations. We called star alleles from 961 high-depth full genomes using StellarPGx, Aldy, and PyPGx. In addition, we performed CYP2B6 and CYP2A6 star allele frequency comparisons between SSA and other global biogeographical groups represented in the new 1000 Genomes Project high-coverage dataset (n = 2,000). This study presents frequency information for star alleles in CYP2B6 (e.g., *6 and *18; frequency of 21-47% and 2-19%, respectively) and CYP2A6 (e.g., *4, *9, and *17; frequency of 0-6%, 3-10%, and 6-20%, respectively), and predicted phenotypes (for CYP2B6), across various African populations. In addition, 50 potentially novel African-ancestry star alleles were computationally predicted by StellarPGx in CYP2B6 and CYP2A6 combined. For each of these genes, over 4% of the study participants had predicted novel star alleles. Three novel star alleles in CYP2A6 (*54, *55, and *56) and CYP2B6 apiece, and several suballeles were further validated via targeted Single-Molecule Real-Time resequencing. Our findings are important for informing the design of comprehensive pharmacogenetic testing platforms, and are highly relevant for personalized medicine strategies, especially relating to antiretroviral medication and smoking cessation treatment in Africa and the African diaspora. More broadly, this study highlights the importance of sampling diverse African ethnolinguistic groups for accurate characterization of the pharmacogene variation landscape across the continent.

Multimorbidity in African ancestry populations: a scoping review.

OBJECTIVES: Multimorbidity (MM) is a growing concern linked to poor outcomes and higher healthcare costs. While most MM research targets European ancestry populations, the prevalence and patterns in African ancestry groups remain underexplored. This study aimed to identify and summarise the available literature on MM in populations with African ancestry, on the continent, and in the diaspora. DESIGN: A scoping review was conducted in five databases (PubMed, Web of Science, Scopus, Science Direct and JSTOR) in July 2022. Studies were selected based on predefined criteria, with data extraction focusing on methodology and findings. Descriptive statistics summarised the data, and a narrative synthesis highlighted key themes. RESULTS: Of the 232 publications on MM in African-ancestry groups from 2010 to June 2022-113 examined continental African populations, 100 the diaspora and 19 both. Findings revealed diverse MM patterns within and beyond continental Africa. Cardiovascular and metabolic diseases are predominant in both groups (80% continental and 70% diaspora). Infectious diseases featured more in continental studies (58% continental and 16% diaspora). Although many papers did not specifically address these features, as in previous studies, older age, being women and having a lower socioeconomic status were associated with a higher prevalence of MM, with important exceptions. Research gaps identified included limited data on African-ancestry individuals, inadequate representation, under-represented disease groups, non-standardised methodologies, the need for innovative data strategies, and insufficient translational research. CONCLUSION: The growing global MM prevalence is mirrored in African-ancestry populations. Recognising the unique contexts of African-ancestry populations is essential when addressing the burden of MM. This review emphasises the need for additional research to guide and enhance healthcare approaches for African-ancestry populations, regardless of their geographic location.