Carriers of Heterozygous Loss-of-Function ACE Mutations Are at Risk for Alzheimer's Disease.

We hypothesized that subjects with heterozygous loss-of-function (LoF) ACE mutations are at risk for Alzheimer's disease because amyloid Aß42, 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.

Genome-wide association study of esophageal squamous cell cancer identifies shared and distinct risk variants in African and Chinese populations.

Esophageal squamous cell carcinoma (ESCC) has a high disease burden in sub-Saharan Africa and has a very poor prognosis. Genome-wide association studies (GWASs) of ESCC in predominantly East Asian populations indicate a substantial genetic contribution to its etiology, but no genome-wide studies have been done in populations of African ancestry. Here, we report a GWAS in 1,686 African individuals with ESCC and 3,217 population-matched control individuals to investigate its genetic etiology. We identified a genome-wide-significant risk locus on chromosome 9 upstream of FAM120A (rs12379660, p = 4.58 × 10-8, odds ratio = 1.28, 95% confidence interval = 1.22-1.34), as well as a potential African-specific risk locus on chromosome 2 (rs142741123, p = 5.49 × 10-8) within MYO1B. FAM120A is a component of oxidative stress-induced survival signals, and the associated variants at the FAM120A locus co-localized with highly significant cis-eQTLs in FAM120AOS in both esophageal mucosa and esophageal muscularis tissue. A trans-ethnic meta-analysis was then performed with the African ESCC study and a Chinese ESCC study in a combined total of 3,699 ESCC-affected individuals and 5,918 control individuals, which identified three genome-wide-significant loci on chromosome 9 at FAM120A (rs12379660, pmeta = 9.36 × 10-10), chromosome 10 at PLCE1 (rs7099485, pmeta = 1.48 × 10-8), and chromosome 22 at CHEK2 (rs1033667, pmeta = 1.47 × 10-9). This indicates the existence of both shared and distinct genetic risk loci for ESCC in African and Asian populations. Our GWAS of ESCC conducted in a population of African ancestry indicates a substantial genetic contribution to ESCC risk in Africa.

Performance and accuracy evaluation of reference panels for genotype imputation in sub-Saharan African populations.

Based on evaluations of imputation performed on a genotype dataset consisting of about 11,000 sub-Saharan African (SSA) participants, we show Trans-Omics for Precision Medicine (TOPMed) and the African Genome Resource (AGR) to be currently the best panels for imputing SSA datasets. We report notable differences in the number of single-nucleotide polymorphisms (SNPs) that are imputed by different panels in datasets from East, West, and South Africa. Comparisons with a subset of 95 SSA high-coverage whole-genome sequences (WGSs) show that despite being about 20-fold smaller, the AGR imputed dataset has higher concordance with the WGSs. Moreover, the level of concordance between imputed and WGS datasets was strongly influenced by the extent of Khoe-San ancestry in a genome, highlighting the need for integration of not only geographically but also ancestrally diverse WGS data in reference panels for further improvement in imputation of SSA datasets. Approaches that integrate imputed data from different panels could also lead to better imputation.

A genome-wide association study for rheumatoid arthritis replicates previous HLA and non-HLA associations in a cohort from South Africa.

The complex pathogenesis of rheumatoid arthritis (RA) is not fully understood, with few studies exploring the genomic contribution to RA in patients from Africa. We report a genome-wide association study (GWAS) of South-Eastern Bantu-Speaking South Africans (SEBSSAs) with seropositive RA (n = 531) and population controls (n = 2653). Association testing was performed using PLINK (logistic regression assuming an additive model) with sex, age, smoking and the first three principal components as covariates. The strong association with the Human Leukocyte Antigen (HLA) region, indexed by rs602457 (near HLA-DRB1), was replicated. An additional independent signal in the HLA region represented by the lead SNP rs2523593 (near the HLA-B gene; Conditional P-value = 6.4 × 10-10) was detected. Although none of the non-HLA signals reached genome-wide significance (P < 5 × 10-8), 17 genomic regions showed suggestive association (P < 5 × 10-6). The GWAS replicated two known non-HLA associations with MMEL1 (rs2843401) and ANKRD55 (rs7731626) at a threshold of P < 5 × 10-3 providing, for the first time, evidence for replication of non-HLA signals for RA in sub-Saharan African populations. Meta-analysis with summary statistics from an African-American cohort (CLEAR study) replicated three additional non-HLA signals (rs11571302, rs2558210 and rs2422345 around KRT18P39-NPM1P33, CTLA4-ICOS and AL645568.1, respectively). Analysis based on genomic regions (200 kb windows) further replicated previously reported non-HLA signals around PADI4, CD28 and LIMK1. Although allele frequencies were overall strongly correlated between the SEBSSA and the CLEAR cohort, we observed some differences in effect size estimates for associated loci. The study highlights the need for conducting larger association studies across diverse African populations to inform precision medicine-based approaches for RA in Africa.

Meta-analysis of sub-Saharan African studies provides insights into genetic architecture of lipid traits.

Genetic associations for lipid traits have identified hundreds of variants with clear differences across European, Asian and African studies. Based on a sub-Saharan-African GWAS for lipid traits in the population cross-sectional AWI-Gen cohort (N = 10,603) we report a novel LDL-C association in the GATB region (P-value=1.56 × 10-8). Meta-analysis with four other African cohorts (N = 23,718) provides supporting evidence for the LDL-C association with the GATB/FHIP1A region and identifies a novel triglyceride association signal close to the FHIT gene (P-value =2.66 × 10-8). Our data enable fine-mapping of several well-known lipid-trait loci including LDLR, PMFBP1 and LPA. The transferability of signals detected in two large global studies (GLGC and PAGE) consistently improves with an increase in the size of the African replication cohort. Polygenic risk score analysis shows increased predictive accuracy for LDL-C levels with the narrowing of genetic distance between the discovery dataset and our cohort. Novel discovery is enhanced with the inclusion of African data.

UGT1A1 regulatory variant with potential effect on efficacy of HIV and cancer drugs commonly prescribed in South Africa.

Aim: Despite the high disease burden of human immunodeficiency virus (HIV) infection and colorectal cancer (CRC) in South Africa (SA), treatment-relevant pharmacogenetic variants are understudied. Materials & methods: Using publicly available genotype and gene expression data, a bioinformatic pipeline was developed to identify liver expression quantitative trait loci (eQTLs). Results: A novel cis-eQTL, rs28967009, was identified for UGT1A1, which is predicted to upregulate UGT1A1 expression thereby potentially affecting the metabolism of dolutegravir and irinotecan, which are extensively prescribed in SA for HIV and colorectal cancer treatment, respectively. Conclusion: As increased UGT1A1 expression could affect the clinical outcome of dolutegravir and irinotecan treatment by increasing drug clearance, patients with the rs28967009A variant may require increased drug doses to reach therapeutic levels or should be prescribed alternative drugs.

Genetic substructure and complex demographic history of South African Bantu speakers.

South Eastern Bantu-speaking (SEB) groups constitute more than 80% of the population in South Africa. Despite clear linguistic and geographic diversity, the genetic differences between these groups have not been systematically investigated. Based on genome-wide data of over 5000 individuals, representing eight major SEB groups, we provide strong evidence for fine-scale population structure that broadly aligns with geographic distribution and is also congruent with linguistic phylogeny (separation of Nguni, Sotho-Tswana and Tsonga speakers). Although differential Khoe-San admixture plays a key role, the structure persists after Khoe-San ancestry-masking. The timing of admixture, levels of sex-biased gene flow and population size dynamics also highlight differences in the demographic histories of individual groups. The comparisons with five Iron Age farmer genomes further support genetic continuity over ~400 years in certain regions of the country. Simulated trait genome-wide association studies further show that the observed population structure could have major implications for biomedical genomics research in South Africa.

Interleukin-8 genetic diversity, haplotype structure and production differ in two ethnically distinct South African populations.

A single nucleotide polymorphism (SNP), 251 bases upstream from the IL-8 transcription start (-251A>T, rs4073), has been extensively investigated in cancers and inflammatory and infectious diseases in predominantly European and Asian populations. We sequenced the IL-8 gene of 109 black and 32 white South African (SA) individuals and conducted detailed characterization of gene variation and haplotype structure. IL-8 production in phytohaemagglutinin (PHA)-stimulated peripheral blood mononuclear cells (PBMCs) of a subset (black: N = 22; white: N = 32) of these individuals was measured using ELISA. Select variants were genotyped for additional black individuals (N = 141), and data from the 1000 Genomes Project were used for haplotype analysis and comparative purposes. In white individuals, the -251A>T SNP formed part of a prevalent six-variant haplotype [haplotype frequency (HF): 61%], Hap-1C, involving the following variants: -251A>T; +394T>G (rs2227307); +780C>T (rs2227306); +1240->A (rs2227541); +1635C>T (rs2227543) and +2770A>T (rs2227543). Hap-1C (-251T+394T+780C+1240+A+1635C+2770A) was composed of two three-variant sub-haplotypes [Hap-1Ca: -251T+394T+1240+A; Hap-1Cb: +780C+1635C+2770A) sharing similarities with haplotypes identified in the black population. Hap-1C was found to be present in European, East and South Asian populations. Four haplotypes were identified in the black population with the two prevalent haplotypes each comprised of two variants: Hap-1B [-251A>T and +1240->A; -251T+1240+A; HF: 14%] and Hap-2B [-743T>C (rs2227532) and +2452A>C (rs2227545); -743C+2452C; HF: 13%]. Populations did not differ in unstimulated PBMC IL-8 production. Upon PHA stimulation, PBMCs from white individuals produced more IL-8 (P = 0.04), suggesting the -251T allele is responsible for higher production, however further analysis revealed that Hap-1C (and constituent sub-haplotypes), did not associate with IL-8 production. Populations did however differ in monocyte number with the white population having significantly more monocytes compared to the black population (P = 0.025), and furthermore monocyte number strongly correlated with IL-8 production in both population groups (black: p = 0.0002, r = 0.71; white: P = 0.0005, r = 0.59). Hap-1B, Hap-2B, and a SNP located one base pair upstream of the IL-8 ATG start codon, +100C>T SNP (rs2227538), all associated with higher IL-8 production in the black population - individuals harbouring at least one of these haplotypes/variant associated with higher IL-8 production (P = 0.003) compared to individuals without. The black population was enriched for individuals harbouring Hap-1B and/or Hap-2B compared to the 1000 Genomes project sub-Saharan African population (P = 0.006), suggesting that SA black individuals may be high IL-8 producers. Given the paucity of IL-8-related studies that have been conducted in populations from sub-Saharan Africa, this study has significantly increased our understanding of this important chemokine in the South African population.

Bantu-speaker migration and admixture in southern Africa.

The presence of Early and Middle Stone Age human remains and associated archeological artifacts from various sites scattered across southern Africa, suggests this geographic region to be one of the first abodes of anatomically modern humans. Although the presence of hunter-gatherer cultures in this region dates back to deep times, the peopling of southern Africa has largely been reshaped by three major sets of migrations over the last 2000 years. These migrations have led to a confluence of four distinct ancestries (San hunter-gatherer, East-African pastoralist, Bantu-speaker farmer and Eurasian) in populations from this region. In this review, we have summarized the recent insights into the refinement of timelines and routes of the migration of Bantu-speaking populations to southern Africa and their admixture with resident southern African Khoe-San populations. We highlight two recent studies providing evidence for the emergence of fine-scale population structure within some South-Eastern Bantu-speaker groups. We also accentuate whole genome sequencing studies (current and ancient) that have both enhanced our understanding of the peopling of southern Africa and demonstrated a huge potential for novel variant discovery in populations from this region. Finally, we identify some of the major gaps and inconsistencies in our understanding and emphasize the importance of more systematic studies of southern African populations from diverse ethnolinguistic groups and geographic locations.

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.

Identification of a novel recombinant allele, HLA-DPB1*835:01:01:02, in Black South African individuals.

Genetic characterisation of a novel intra-locus recombinant allele, HLA-DPB1*835:01:01:02, in Black South African individuals.

Identification of a novel allele, HLA-DPB1*34:01:01:03, in Black South African individuals.

Genetic characterisation of a non-coding region allelic variant, HLA-DPB1*34:01:01:03, in Black South African individuals.

Novel and Known Gene-Smoking Interactions With cIMT Identified as Potential Drivers for Atherosclerosis Risk in West-African Populations of the AWI-Gen Study.

INTRODUCTION: Atherosclerosis 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 METHODS: Only 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. RESULTS: In 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). DISCUSSION: This 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.

African genetic diversity provides novel insights into evolutionary history and local adaptations.

Genetic variation and susceptibility to disease are shaped by human demographic history and adaptation. We can now study the genomes of extant Africans and uncover traces of population migration, admixture, assimilation and selection by applying sophisticated computational algorithms. There are four major ethnolinguistic divisions among present day Africans: Hunter-gatherer populations in southern and central Africa; Nilo-Saharan speakers from north and northeast Africa; Afro-Asiatic speakers from north and east Africa; and Niger-Congo speakers who are the predominant ethnolinguistic group spread across most of sub-Saharan Africa. The enormous ethnolinguistic diversity in sub-Saharan African populations is largely paralleled by extensive genetic diversity and until a decade ago, little was known about detailed origins and divergence of these groups. Results from large-scale population genetic studies, and more recently whole genome sequence data, are unravelling the critical role of events like migration and admixture and environmental factors including diet, infectious diseases and climatic conditions in shaping current population diversity. It is now possible to start providing quantitative estimates of divergence times, population size and dynamic processes that have affected populations and their genetic risk for disease. Finally, the availability of ancient genomes from Africa provides historical insights of unprecedented depth. In this review, we highlight some key interpretations that have emerged from recent African genome studies.

Whole-genome sequencing for an enhanced understanding of genetic variation among South Africans.

The Southern African Human Genome Programme is a national initiative that aspires to unlock the unique genetic character of southern African populations for a better understanding of human genetic diversity. In this pilot study the Southern African Human Genome Programme characterizes the genomes of 24 individuals (8 Coloured and 16 black southeastern Bantu-speakers) using deep whole-genome sequencing. A total of ~16 million unique variants are identified. Despite the shallow time depth since divergence between the two main southeastern Bantu-speaking groups (Nguni and Sotho-Tswana), principal component analysis and structure analysis reveal significant (p < 10-6) differentiation, and FST analysis identifies regions with high divergence. The Coloured individuals show evidence of varying proportions of admixture with Khoesan, Bantu-speakers, Europeans, and populations from the Indian sub-continent. Whole-genome sequencing data reveal extensive genomic diversity, increasing our understanding of the complex and region-specific history of African populations and highlighting its potential impact on biomedical research and genetic susceptibility to disease.

Assessing computational genomics skills: Our experience in the H3ABioNet African bioinformatics network.

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.

Population Stratification and Underrepresentation of Indian Subcontinent Genetic Diversity in the 1000 Genomes Project Dataset.

Genomic variation in Indian populations is of great interest due to the diversity of ancestral components, social stratification, endogamy and complex admixture patterns. With an expanding population of 1.2 billion, India is also a treasure trove to catalogue innocuous as well as clinically relevant rare mutations. Recent studies have revealed four dominant ancestries in populations from mainland India: Ancestral North-Indian (ANI), Ancestral South-Indian (ASI), Ancestral Tibeto-Burman (ATB) and Ancestral Austro-Asiatic (AAA). The 1000 Genomes Project (KGP) Phase-3 data include about 500 genomes from five linguistically defined Indian-Subcontinent (IS) populations (Punjabi, Gujrati, Bengali, Telugu and Tamil) some of whom are recent migrants to USA or UK. Comparative analyses show that despite the distinct geographic origins of the KGP-IS populations, the ANI component is predominantly represented in this dataset. Previous studies demonstrated population substructure in the HapMap Gujrati population, and we found evidence for additional substructure in the Punjabi and Telugu populations. These substructured populations have characteristic/significant differences in heterozygosity and inbreeding coefficients. Moreover, we demonstrate that the substructure is better explained by factors like differences in proportion of ancestral components, and endogamy driven social structure rather than invoking a novel ancestral component to explain it. Therefore, using language and/or geography as a proxy for an ethnic unit is inadequate for many of the IS populations. This highlights the necessity for more nuanced sampling strategies or corrective statistical approaches, particularly for biomedical and population genetics research in India.

Genome wide expression profiling during spinal cord regeneration identifies comprehensive cellular responses in zebrafish.

BACKGROUND: Among the vertebrates, teleost and urodele amphibians are capable of regenerating their central nervous system. We have used zebrafish as a model to study spinal cord injury and regeneration. Relatively little is known about the molecular mechanisms underlying spinal cord regeneration and information based on high density oligonucleotide microarray was not available. We have used a high density microarray to profile the temporal transcriptome dynamics during the entire phenomenon. RESULTS: A total of 3842 genes expressed differentially with significant fold changes during spinal cord regeneration. Cluster analysis revealed event specific dynamic expression of genes related to inflammation, cell death, cell migration, cell proliferation, neurogenesis, neural patterning and axonal regrowth. Spatio-temporal analysis of stat3 expression suggested its possible function in controlling inflammation and cell proliferation. Genes involved in neurogenesis and their dorso-ventral patterning (sox2 and dbx2) are differentially expressed. Injury induced cell proliferation is controlled by many cell cycle regulators and some are commonly expressed in regenerating fin, heart and retina. Expression pattern of certain pathway genes are identified for the first time during regeneration of spinal cord. Several genes involved in PNS regeneration in mammals like stat3, socs3, atf3, mmp9 and sox11 are upregulated in zebrafish SCI thus creating PNS like environment after injury. CONCLUSION: Our study provides a comprehensive genetic blue print of diverse cellular response(s) during regeneration of zebrafish spinal cord. The data highlights the importance of different event specific gene expression that could be better understood and manipulated further to induce successful regeneration in mammals.