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Abstract Most hypertension-related genome-wide association studies (GWASs) focus on non-African populations, despite hypertension (a major risk factor for cardiovascular disease) being highly prevalent in Africa. The AWI-Gen study GWAS meta-analysis for blood pressure (BP)-related traits (systolic and diastolic BP, pulse pressure, mean-arterial pressure and hypertension) from three sub-Saharan African geographic regions (N = 10,775), identifies two novel genome-wide significant signals (p

A genome-wide association study for five cognitive phenotypes in a rural South African community suggests several variants associated with general cognition and domain-specific cognitive pathways in this cohort.

Abstract Background Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.

Abstract Smoking is a leading risk factor for many of the top ten causes of death worldwide. Of the 1.3 billion smokers globally, 80% live in low- and middle-income countries, where the number of deaths due to tobacco use is expected to double in the next decade according to the World Health Organization. Genetic studies have helped to identify biological pathways for smoking behaviours, but have mostly focussed on individuals of European ancestry or living in either North America or Europe. We performed a genome-wide association study of two smoking behaviour traits in 10,558 men of African ancestry living in five African countries and the UK. Eight independent variants were associated with either smoking initiation or cessation at P-value

Genetic associations and polygenic scores for lipid traits have low transferability to African individuals. Here, the authors perform a large sub-Sarahan African lipid GWAS and find that larger datasets and better global representation in discovery GWAS help to bridge this gap.

We hypothesized that subjects with heterozygous loss-of-function (LoF) ACE mutations are at risk for Alzheimer’s disease because amyloid Aβ42, a primary component of the protein aggregates that accumulate in the brains of AD patients, is cleaved by ACE (angiotensin I-converting enzyme). Thus, decreased ACE activity in the brain, either due to genetic mutation or the effects of ACE inhibitors, could be a risk factor for AD. To explore this hypothesis in the current study, existing SNP databases were analyzed for LoF ACE mutations using four predicting tools, including PolyPhen-2, and compared with the topology of known ACE mutations already associated with AD. The combined frequency of >400 of these LoF-damaging ACE mutations in the general population is quite significant—up to 5%—comparable to the frequency of AD in the population > 70 y.o., which indicates that the contribution of low ACE in the development of AD could be under appreciated. Our analysis suggests several mechanisms by which ACE mutations may be associated with Alzheimer’s disease. Systematic analysis of blood ACE levels in patients with all ACE mutations is likely to have clinical significance because available sequencing data will help detect persons with increased risk of late-onset Alzheimer’s disease. Patients with transport-deficient ACE mutations (about 20% of damaging ACE mutations) may benefit from preventive or therapeutic treatment with a combination of chemical and pharmacological (e.g., centrally acting ACE inhibitors) chaperones and proteosome inhibitors to restore impaired surface ACE expression, as was shown previously by our group for another transport-deficient ACE mutation-Q1069R.

Genetic studies of disease-relevant traits have mostly been performed on European populations. Here, the authors perform a genome-wide association study for carotid intima-media thickness, in sub-Saharan African samples, finding population-specific and sex-specific loci.

Despite linguistic and geographic diversity in South Eastern Bantu-speaking (SEB) groups of South Africa, genetic variation in these groups has not been investigated in depth. Here, the authors analyse genome-wide data from 5056 individuals, providing insights into demographic history across SEB groups.

Research in European and Asian populations has reported associations between single nucleotide polymorphisms (SNPs) in CYP17A1 and SERPINA6/A1 and circulating glucocorticoid concentrations, and some key cardiometabolic risk factors. This study aimed to investigate these associations in black South African adults, who are disproportionally affected by the metabolic syndrome and its related cardiometabolic risk factors. The dataset included black South African adults (n = 4,431; 56.7% women) from the AWI-Gen study, genotyped on the H3A genotyping array and imputed using the African reference panel at the Sanger imputation service. From the imputed data, 31 CYP17A1 SNPs and 550 SERPINA6/A1 SNPs were extracted. The metabolic syndrome and its components were defined using the 2009 harmonized guidelines. Serum glucocorticoid concentrations were measured in a subset of 304 men and 573 women, using a liquid chromatography-mass spectrometry method. Genetic associations were detected using PLINK. Bonferroni correction was used to control for multiple testing. A SNP at SERPINA6/A1, rs17090691 (effect allele G), was associated with higher diastolic blood pressure (BP) in all adults combined (p = 9.47 × 10−6). Sex-stratified analyses demonstrated an association between rs1051052 (effect allele G), another SERPINA6/A1 SNP, and higher high-density lipoprotein (HDL) cholesterol concentrations in women (p = 1.23 × 10−5). No association was observed between these variants and glucocorticoids or between any of the CYP17A1 SNPs and metabolic outcomes after adjusting for multiple testing. Furthermore, there were no associations between any of the SNPs tested and the metabolic syndrome. This study reports novel genetic associations between two SNPs at SERPINA6/A1 and key cardiometabolic risk factors in black South Africans. Future replication and functional studies in larger populations are required to confirm the role of the identified SNPs in the metabolic syndrome and assess if these associations are mediated by circulating glucocorticoids.

Variations in lipid levels are attributed partly to genetic factors. Genome-wide association studies (GWASs) mainly performed in European, African American and Asian cohorts have identified variants associated with LDL-C, HDL-C, total cholesterol (TC) and triglycerides (TG), but few studies have been performed in sub-Saharan Africans. This study evaluated the effect of single nucleotide variants (SNVs) in eight candidate loci (ABCA1, LCAT, LPL, PON1, CETP, PCSK9, MVK, and MMAB) on lipid levels among 1855 Ghanaian adults. All lipid levels were measured directly using an automated analyser. DNA was extracted and genotyped using the H3Africa SNV array. Linear regression models were used to test the association between SNVs and log-transformed lipid levels, adjusting for sex, age and waist circumference. In addition Bonferroni correction was performed to account for multiple testing. Several variants of CETP, LCAT, PCSK9, and PON1 (MAF > 0.05) were associated with HDL-C, LDL-C and TC levels at p < 0.05. The lead variants for association with HDL-C were rs17231520 in CETP (β = 0.139, p < 0.0001) and rs1109166 in LCAT (β = −0.044, p = 0.028). Lower LDL-C levels were associated with an intronic variant in PCSK9 (rs11806638 [β = −0.055, p = 0.027]) and increased TC was associated with a variant in PON1 (rs854558 [β = 0.040, p = 0.020]). In silico functional analyses indicated that these variants likely influence gene function through their effect on gene transcription. We replicated a strong association between CETP variants and HDL-C and between PCSK9 variant and LDL-C in West Africans, with two potentially functional variants and identified three novel variants in linkage disequilibrium in PON1 which were associated with increasing TC levels in Ghanaians.

IntroductionAtherosclerosis is a key contributor to the burden of cardiovascular diseases (CVDs) and many epidemiological studies have reported on the effect of smoking on carotid intima-media thickness (cIMT) and its subsequent effect on CVD risk. Gene-environment interaction studies have contributed towards understanding some of the missing heritability of genome-wide association studies. Gene-smoking interactions on cIMT have been studied in non-African populations (European, Latino-American, and African American) but no comparable African research has been reported. Our aim was to investigate smoking-SNP interactions on cIMT in two West African populations by genome-wide analysis.Materials and methodsOnly male participants from Burkina Faso (Nanoro = 993) and Ghana (Navrongo = 783) were included, as smoking was extremely rare among women. Phenotype and genotype data underwent stringent QC and genotype imputation was performed using the Sanger African Imputation Panel. Smoking prevalence among men was 13.3% in Nanoro and 42.5% in Navrongo. We analyzed gene-smoking interactions with PLINK after adjusting for covariates: age and 6 PCs (Model 1); age, BMI, blood pressure, fasting glucose, cholesterol levels, MVPA, and 6 PCs (Model 2). All analyses were performed at site level and for the combined data set.ResultsIn Nanoro, we identified new gene-smoking interaction variants for cIMT within the previously described RCBTB1 region (rs112017404, rs144170770, and rs4941649) (Model 1: p = 1.35E-07; Model 2: p = 3.08E-08). In the combined sample, two novel intergenic interacting variants were identified, rs1192824 in the regulatory region of TBC1D8 (p = 5.90E-09) and rs77461169 (p = 4.48E-06) located in an upstream region of open chromatin. In silico functional analysis suggests the involvement of genes implicated in biological processes related to cell or biological adhesion and regulatory processes in gene-smoking interactions with cIMT (as evidenced by chromatin interactions and eQTLs).DiscussionThis is the first gene-smoking interaction study for cIMT, as a risk factor for atherosclerosis, in sub-Saharan African populations. In addition to replicating previously known signals for RCBTB1, we identified two novel genomic regions (TBC1D8, near BCHE) involved in this gene-environment interaction.

Abstract Background Cardiovascular diseases (CVDs) are the leading cause of non-communicable disease deaths globally, with hypertension being a major risk factor contributing to CVDs. Blood pressure is a heritable trait, with relatively few genetic studies having been performed in Africans. This study aimed to identify genetic variants associated with variance in systolic (SBP) and diastolic (DBP) blood pressure in black South Africans. Methods Genotyping was performed using the Metabochip in a subset of participants (mixed sex; median age 17.9) and their adult female caregivers (median age 41.0) from the Birth to Twenty cohort (n = 1947). Data were analysed as a merged dataset (all participants and caregivers together) in GEMMA (v0.94.1) using univariate linear mixed models, incorporating a centered relatedness matrix to account for the relatedness between individuals and with adjustments for age, sex, BMI and principal components of the genotype information. Results Association analysis identified regions of interest in the NOS1AP (DBP: rs112468105 - p = 7.18 × 10−5 and SBP: rs4657181 - p = 4.04 × 10−5), MYRF (SBP: rs11230796 - p = 2.16 × 10−7, rs400075 - p = 2.88 × 10−7) and POC1B (SBP: rs770373 - p = 7.05 × 10−5, rs770374 - p = 9.05 × 10−5) genes and some intergenic regions (DACH1|LOC440145 (DBP: rs17240498 - p = 4.91 × 10−6 and SBP: rs17240498 - p = 2.10 × 10−5) and INTS10|LPL (SBP: rs55830938 - p = 1.30 × 10−5, rs73599609 - p = 5.78 × 10−5, rs73667448 - p = 6.86 × 10−5)). Conclusions The study provided further insight into the contribution of genetic variants to blood pressure in black South Africans. Future functional and replication studies in larger samples are required to confirm the role of the identified loci in blood pressure regulation and whether or not these variants are African-specific.

African populations show a high level of genetic diversity and extensive regional admixture. Here, the authors sequence the whole genomes of 24 South African individuals of different ethnolinguistic origin and find substantive genomic divergence between two southeastern Bantu-speaking groups.

Single nucleotide polymorphism arrays have created new possibilities for performing genome-wide studies to detect genomic regions harboring sequence variants that affect complex traits. However, the majority of validated SNPs for which allele frequencies have been estimated are limited primarily to European breeds. The objective of this study was to perform SNP discovery in three South African indigenous breeds (Afrikaner, Drakensberger, and Nguni) using whole genome sequencing. DNA was extracted from blood and hair samples, quantified and prepared at 50 ng/μl concentration for sequencing at the Agricultural Research Council Biotechnology Platform using an Illumina HiSeq 2500. The fastq files were used to call the variants using the Genome Analysis Tool Kit. A total of 1,678,360 were identified as novel using Run 6 of 1000 Bull Genomes Project. Annotation of the identified variants classified them into functional categories. Within the coding regions, about 30% of the SNPs were non-synonymous substitutions that encode for alternate amino acids. The study of distribution of SNP across the genome identified regions showing notable differences in the densities of SNPs among the breeds and highlighted many regions of functional significance. Gene ontology terms identified genes such as MLANA, SYT10, and CDC42EP5 that have been associated with coat color in mouse, and ADAMS3, DNAJC3, and PAG5 genes have been associated with fertility in cattle. Further analysis of the variants detected 688 candidate selective sweeps (ZHp Z-scores ≤ -4) across all three breeds, of which 223 regions were assigned as being putative selective sweeps (ZHp scores ≤-5). We also identified 96 regions with extremely low ZHp Z-scores (≤-6) in Afrikaner and Nguni. Genes such as KIT and MITF that have been associated with skin pigmentation in cattle and CACNA1C, which has been associated with biopolar disorder in human, were identified in these regions. This study provides the first analysis of sequence data to discover SNPs in indigenous South African cattle breeds. The information will play an important role in our efforts to understand the genetic history of our cattle and in designing appropriate breed improvement programmes.

There is an alarming tide of cardiovascular and metabolic disease (CMD) sweeping across Africa. This may be a result of an increasingly urbanized lifestyle characterized by the growing consumption of processed and calorie-dense food, combined with physical inactivity and more sedentary behaviour. While the link between lifestyle and public health has been extensively studied in Caucasian and African American populations, few studies have been conducted in Africa. This paper describes the detailed methods for Phase 1 of the AWI-Gen study that were used to capture phenotype data and assess the associated risk factors and end points for CMD in persons over the age of 40 years in sub-Saharan Africa (SSA). We developed a population-based cross-sectional study of disease burden and phenotype in Africans, across six centres in SSA. These centres are in West Africa (Nanoro, Burkina Faso, and Navrongo, Ghana), in East Africa (Nairobi, Kenya) and in South Africa (Agincourt, Dikgale and Soweto). A total of 10,702 individuals between the ages of 40 and 60 years were recruited into the study across the six centres, plus an additional 1021 participants over the age of 60 years from the Agincourt centre. We collected socio-demographic, anthropometric, medical history, diet, physical activity, fat distribution and alcohol/tobacco consumption data from participants. Blood samples were collected for disease-related biomarker assays, and genomic DNA extraction for genome-wide association studies. Urine samples were collected to assess kidney function. The study provides base-line data for the development of a series of cohorts with a second wave of data collection in Phase 2 of the study. These data will provide valuable insights into the genetic and environmental influences on CMD on the African continent.

The H3ABioNet pan-African bioinformatics network, which is funded to support the Human Heredity and Health in Africa (H3Africa) program, has developed node-assessment exercises to gauge the ability of its participating research and service groups to analyze typical genome-wide datasets being generated by H3Africa research groups. We describe a framework for the assessment of computational genomics analysis skills, which includes standard operating procedures, training and test datasets, and a process for administering the exercise. We present the experiences of 3 research groups that have taken the exercise and the impact on their ability to manage complex projects. Finally, we discuss the reasons why many H3ABioNet nodes have declined so far to participate and potential strategies to encourage them to do so.