Ancient familial Mediterranean fever mutations in human pyrin and resistance to Yersinia pestis.

Familial Mediterranean fever (FMF) is an autoinflammatory disease caused by homozygous or compound heterozygous gain-of-function mutations in MEFV, which encodes pyrin, an inflammasome protein. Heterozygous carrier frequencies for multiple MEFV mutations are high in several Mediterranean populations, suggesting that they confer selective advantage. Among 2,313 Turkish people, we found extended haplotype homozygosity flanking FMF-associated mutations, indicating evolutionarily recent positive selection of FMF-associated mutations. Two pathogenic pyrin variants independently arose >1,800 years ago. Mutant pyrin interacts less avidly with Yersinia pestis virulence factor YopM than with wild-type human pyrin, thereby attenuating YopM-induced interleukin (IL)-1ß suppression. Relative to healthy controls, leukocytes from patients with FMF harboring homozygous or compound heterozygous mutations and from asymptomatic heterozygous carriers released heightened IL-1ß specifically in response to Y. pestis. Y. pestis-infected MefvM680I/M680I FMF knock-in mice exhibited IL-1-dependent increased survival relative to wild-type knock-in mice. Thus, FMF mutations that were positively selected in Mediterranean populations confer heightened resistance to Y. pestis.

2022 ASHG presidential address-One human race: Billions of genomes.

This article is based on the address given by the author at the 2022 meeting of The American Society of Human Genetics (ASHG) in Los Angeles, California. The video of the original address can be found at the ASHG website.

A brief history of human disease genetics.

A primary goal of human genetics is to identify DNA sequence variants that influence biomedical traits, particularly those related to the onset and progression of human disease. Over the past 25 years, progress in realizing this objective has been transformed by advances in technology, foundational genomic resources and analytical tools, and by access to vast amounts of genotype and phenotype data. Genetic discoveries have substantially improved our understanding of the mechanisms responsible for many rare and common diseases and driven development of novel preventative and therapeutic strategies. Medical innovation will increasingly focus on delivering care tailored to individual patterns of genetic predisposition.

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.

Sickle cell allele HBB-rs334(T) is associated with decreased risk of childhood Burkitt lymphoma in East Africa.

Burkitt lymphoma (BL) is an aggressive B-cell lymphoma that significantly contributes to childhood cancer burden in sub-Saharan Africa. Plasmodium falciparum, which causes malaria, is geographically associated with BL, but the evidence remains insufficient for causal inference. Inference could be strengthened by demonstrating that mendelian genes known to protect against malaria-such as the sickle cell trait variant, HBB-rs334(T)-also protect against BL. We investigated this hypothesis among 800 BL cases and 3845 controls in four East African countries using genome-scan data to detect polymorphisms in 22 genes known to affect malaria risk. We fit generalized linear mixed models to estimate odds ratios (OR) and 95% confidence intervals (95% CI), controlling for age, sex, country, and ancestry. The ORs of the loci with BL and P. falciparum infection among controls were correlated (Spearman's ρ = 0.37, p = .039). HBB-rs334(T) was associated with lower P. falciparum infection risk among controls (OR = 0.752, 95% CI 0.628-0.9; p = .00189) and BL risk (OR = 0.687, 95% CI 0.533-0.885; p = .0037). ABO-rs8176703(T) was associated with decreased risk of BL (OR = 0.591, 95% CI 0.379-0.992; p = .00271), but not of P. falciparum infection. Our results increase support for the etiological correlation between P. falciparum and BL risk.

Evolutionary forces in diabetes and hypertension pathogenesis in Africans.

Rates of type 2 diabetes (T2D) and hypertension are increasing rapidly in urbanizing sub-Saharan Africa (SSA). While lifestyle factors drive the increases in T2D and hypertension prevalence, evidence across populations shows that genetic variation, which is driven by evolutionary forces including a natural selection that shaped the human genome, also plays a role. Here we report the evidence for the effect of selection in African genomes on mechanisms underlying T2D and hypertension, including energy metabolism, adipose tissue biology, insulin action and salt retention. Selection effects found for variants in genes PPARA and TCF7L2 may have enabled Africans to respond to nutritional challenges by altering carbohydrate and lipid metabolism. Likewise, African-ancestry-specific characteristics of adipose tissue biology (low visceral adipose tissue [VAT], high intermuscular adipose tissue and a strong association between VAT and adiponectin) may have been selected for in response to nutritional and infectious disease challenges in the African environment. Evidence for selection effects on insulin action, including insulin resistance and secretion, has been found for several genes including MPHOSPH9, TMEM127, ZRANB3 and MC3R. These effects may have been historically adaptive in critical conditions, such as famine and inflammation. A strong correlation between hypertension susceptibility variants and latitude supports the hypothesis of selection for salt retention mechanisms in warm, humid climates. Nevertheless, adaptive genomics studies in African populations are scarce. More work is needed, particularly genomics studies covering the wide diversity of African populations in SSA and Africans in diaspora, as well as further functional assessment of established risk loci.

GWAS in Africans identifies novel lipids loci and demonstrates heterogenous association within Africa.

Serum lipids are biomarkers of cardiometabolic disease risk, and understanding genomic factors contributing to their distribution is of interest. Studies of lipids in Africans are rare, though it is expected that such studies could identify novel loci. We conducted a GWAS of 4317 Africans enrolled from Nigeria, Ghana and Kenya. We evaluated linear mixed models of high-density lipoprotein cholesterol (HDLC), low-density lipoprotein cholesterol (LDLC), total cholesterol (CHOL), triglycerides (TG) and TG/HDLC. Replication was attempted in 9542 African Americans (AA). In our main analysis, we identified 28 novel associations in Africans. Of the 18 of these that could be tested in AA, three associations replicated (GPNMB-TG, ENPP1-TG and SMARCA4-LDLC). Five additional novel loci were discovered upon meta-analysis with AA (rs138282551-TG, PGBD5-HDLC, CD80-TG/HDLC, SLC44A1-CHOL and TLL2-CHOL). Analyses considering only those with predominantly West African ancestry (Nigeria, Ghana and AA) yielded new insights: ORC5-LDLC and chr20:60973327-CHOL. Among our novel findings are some loci with known connections to lipids pathways. For instance, rs147706369 (TLL2) alters a regulatory motif for sterol regulatory element-binding proteins, a family of transcription factors that control the expression of a range of enzymes involved in cholesterol, fatty acid and TG synthesis, and rs115749422 (SMARCA4), an independent association near the known LDLR locus that is rare or absent in populations without African ancestry. These findings demonstrate the utility of conducting genomic analyses in Africans for discovering novel loci and provide some preliminary evidence for caution against treating 'African ancestry' as a monolithic category.

HLA and autoantibodies define scleroderma subtypes and risk in African and European Americans and suggest a role for molecular mimicry.

Systemic sclerosis (SSc) is a clinically heterogeneous autoimmune disease characterized by mutually exclusive autoantibodies directed against distinct nuclear antigens. We examined HLA associations in SSc and its autoantibody subsets in a large, newly recruited African American (AA) cohort and among European Americans (EA). In the AA population, the African ancestry-predominant HLA-DRB1*08:04 and HLA-DRB1*11:02 alleles were associated with overall SSc risk, and the HLA-DRB1*08:04 allele was strongly associated with the severe antifibrillarin (AFA) antibody subset of SSc (odds ratio = 7.4). These African ancestry-predominant alleles may help explain the increased frequency and severity of SSc among the AA population. In the EA population, the HLA-DPB1*13:01 and HLA-DRB1*07:01 alleles were more strongly associated with antitopoisomerase (ATA) and anticentromere antibody-positive subsets of SSc, respectively, than with overall SSc risk, emphasizing the importance of HLA in defining autoantibody subtypes. The association of the HLA-DPB1*13:01 allele with the ATA+ subset of SSc in both AA and EA patients demonstrated a transancestry effect. A direct correlation between SSc prevalence and HLA-DPB1*13:01 allele frequency in multiple populations was observed (r = 0.98, P = 3 × 10-6). Conditional analysis in the autoantibody subsets of SSc revealed several associated amino acid residues, mostly in the peptide-binding groove of the class II HLA molecules. Using HLA α/ß allelic heterodimers, we bioinformatically predicted immunodominant peptides of topoisomerase 1, fibrillarin, and centromere protein A and discovered that they are homologous to viral protein sequences from the Mimiviridae and Phycodnaviridae families. Taken together, these data suggest a possible link between HLA alleles, autoantibodies, and environmental triggers in the pathogenesis of SSc.

Refining genome-wide associated loci for serum uric acid in individuals with African ancestry.

OBJECTIVE: Serum uric acid is the end-product of purine metabolism and at high levels is a risk factor for several human diseases including gout and cardiovascular disease. Heritability estimates range from 0.32 to 0.63. Genome-wide association studies (GWAS) provide an unbiased approach to identify loci influencing serum uric acid. Here, we performed the first GWAS for serum uric acid in continental Africans, with replication in African Americans. METHODS: Africans (n = 4126) and African Americans (n = 5007) were genotyped on high-density GWAS arrays. Efficient mixed model association, a variance component approach, was used to perform association testing for a total of ~ 18 million autosomal genotyped and imputed variants. CAVIARBF was used to fine map significant regions. RESULTS: We identified two genome-wide significant loci: 4p16.1 (SLC2A9) and 11q13.1 (SLC22A12). At SLC2A9, the most strongly associated SNP was rs7683856 (P = 1.60 × 10-44). Conditional analysis revealed a second signal indexed by rs6838021 (P = 5.75 × 10-17). Gene expression and regulatory motif data prioritized a single-candidate causal variant for each signal. At SLC22A12, the most strongly associated SNP was rs147647315 (P = 6.65 × 10-25). Conditional analysis and functional annotation prioritized the missense variant rs147647315 (R (Arg) > H (His)) as the sole causal variant. Functional annotation of these three signals implicated processes in skeletal muscle, subcutaneous adipose tissue and the kidneys, respectively. CONCLUSIONS: This first GWAS of serum uric acid in continental Africans identified three associations at two loci, SLC2A9 and SLC22A12. The combination of weak linkage disequilibrium in Africans and functional annotation led to the identification of candidate causal SNPs for all three signals. Each candidate causal variant implicated a different cell type. Collectively, the three associations accounted for 4.3% of the variance of serum uric acid.

Whole-Genome-Sequence-Based Haplotypes Reveal Single Origin of the Sickle Allele during the Holocene Wet Phase.

Five classical designations of sickle haplotypes are made on the basis of the presence or absence of restriction sites and are named after the ethno-linguistic groups or geographic regions from which the individuals with sickle cell anemia originated. Each haplotype is thought to represent an independent occurrence of the sickle mutation rs334 (c.20A>T [p.Glu7Val] in HBB). We investigated the origins of the sickle mutation by using whole-genome-sequence data. We identified 156 carriers from the 1000 Genomes Project, the African Genome Variation Project, and Qatar. We classified haplotypes by using 27 polymorphisms in linkage disequilibrium with rs334. Network analysis revealed a common haplotype that differed from the ancestral haplotype only by the derived sickle mutation at rs334 and correlated collectively with the Central African Republic (CAR), Cameroon, and Arabian/Indian haplotypes. Other haplotypes were derived from this haplotype and fell into two clusters, one composed of Senegal haplotypes and the other composed of Benin and Senegal haplotypes. The near-exclusive presence of the original sickle haplotype in the CAR, Kenya, Uganda, and South Africa is consistent with this haplotype predating the Bantu expansions. Modeling of balancing selection indicated that the heterozygote advantage was 15.2%, an equilibrium frequency of 12.0% was reached after 87 generations, and the selective environment predated the mutation. The posterior distribution of the ancestral recombination graph yielded a sickle mutation age of 259 generations, corresponding to 7,300 years ago during the Holocene Wet Phase. These results clarify the origin of the sickle allele and improve and simplify the classification of sickle haplotypes.

The African Genome Variation Project shapes medical genetics in Africa.

Given the importance of Africa to studies of human origins and disease susceptibility, detailed characterization of African genetic diversity is needed. The African Genome Variation Project provides a resource with which to design, implement and interpret genomic studies in sub-Saharan Africa and worldwide. The African Genome Variation Project represents dense genotypes from 1,481 individuals and whole-genome sequences from 320 individuals across sub-Saharan Africa. Using this resource, we find novel evidence of complex, regionally distinct hunter-gatherer and Eurasian admixture across sub-Saharan Africa. We identify new loci under selection, including loci related to malaria susceptibility and hypertension. We show that modern imputation panels (sets of reference genotypes from which unobserved or missing genotypes in study sets can be inferred) can identify association signals at highly differentiated loci across populations in sub-Saharan Africa. Using whole-genome sequencing, we demonstrate further improvements in imputation accuracy, strengthening the case for large-scale sequencing efforts of diverse African haplotypes. Finally, we present an efficient genotype array design capturing common genetic variation in Africa.

Genome-wide association study of prevalent and persistent cervical high-risk human papillomavirus (HPV) infection.

BACKGROUND: Genetic factors may influence the susceptibility to high-risk (hr) human papillomavirus (HPV) infection and persistence. We conducted the first genome-wide association study (GWAS) to identify variants associated with cervical hrHPV infection and persistence. METHODS: Participants were 517 Nigerian women evaluated at baseline and 6 months follow-up visits for HPV. HPV was characterized using SPF10/LiPA25. hrHPV infection was positive if at least one carcinogenic HPV genotype was detected in a sample provided at the baseline visit and persistent if at least one carcinogenic HPV genotype was detected in each of the samples provided at the baseline and follow-up visits. Genotyping was done using the Illumina Multi-Ethnic Genotyping Array (MEGA) and imputation was done using the African Genome Resources Haplotype Reference Panel. Association analysis was done for hrHPV infection (125 cases/392 controls) and for persistent hrHPV infection (51 cases/355 controls) under additive genetic models adjusted for age, HIV status and the first principal component (PC) of the genotypes. RESULTS: The mean (±SD) age of the study participants was 38 (±8) years, 48% were HIV negative, 24% were hrHPV positive and 10% had persistent hrHPV infections. No single variant reached genome-wide significance (p < 5 X 10- 8). The top three variants associated with hrHPV infections were intronic variants clustered in KLF12 (all OR: 7.06, p = 1.43 × 10- 6). The top variants associated with cervical hrHPV persistence were in DAP (OR: 6.86, p = 7.15 × 10- 8), NR5A2 (OR: 3.65, p = 2.03 × 10- 7) and MIR365-2 (OR: 7.71, p = 2.63 × 10- 7) gene regions. CONCLUSIONS: This exploratory GWAS yielded suggestive candidate risk loci for cervical hrHPV infection and persistence. The identified loci have biological annotation and functional data supporting their role in hrHPV infection and persistence. Given our limited sample size, larger discovery and replication studies are warranted to further characterize the reported associations.

Genome-wide association study of type 2 diabetes in Africa.

AIMS/HYPOTHESIS: Genome-wide association studies (GWAS) for type 2 diabetes have uncovered >400 risk loci, primarily in populations of European and Asian ancestry. Here, we aimed to discover additional type 2 diabetes risk loci (including African-specific variants) and fine-map association signals by performing genetic analysis in African populations. METHODS: We conducted two type 2 diabetes genome-wide association studies in 4347 Africans from South Africa, Nigeria, Ghana and Kenya and meta-analysed both studies together. Likely causal variants were identified using fine-mapping approaches. RESULTS: The most significantly associated variants mapped to the widely replicated type 2 diabetes risk locus near TCF7L2 (p = 5.3 × 10-13). Fine-mapping of the TCF7L2 locus suggested one type 2 diabetes association signal shared between Europeans and Africans (indexed by rs7903146) and a distinct African-specific signal (indexed by rs17746147). We also detected one novel signal, rs73284431, near AGMO (p = 5.2 × 10-9, minor allele frequency [MAF] = 0.095; monomorphic in most non-African populations), distinct from previously reported signals in the region. In analyses focused on 100 published type 2 diabetes risk loci, we identified 21 with shared causal variants in African and non-African populations. CONCLUSIONS/INTERPRETATION: These results demonstrate the value of performing GWAS in Africans, provide a resource to larger consortia for further discovery and fine-mapping and indicate that additional large-scale efforts in Africa are warranted to gain further insight in to the genetic architecture of type 2 diabetes.

The genomic landscape of African populations in health and disease.

A deeper appreciation of the complex architecture of African genomes is critical to the global effort to understand human history, biology and differential distribution of disease by geography and ancestry. Here, we report on how the growing engagement of African populations in genome science is providing new insights into the forces that shaped human genomes before and after the Out-of-Africa migrations. As a result of this human evolutionary history, African ancestry populations have the greatest genomic diversity in the world, and this diversity has important ramifications for genomic research. In the case of pharmacogenomics, for instance, variants of consequence are not limited to those identified in other populations, and diversity within African ancestry populations precludes summarizing risk across different African ethnic groups. Exposure of Africans to fatal pathogens, such as Plasmodium falciparum, Lassa Virus and Trypanosoma brucei rhodesiense, has resulted in elevated frequencies of alleles conferring survival advantages for infectious diseases, but that are maladaptive in modern-day environments. Illustrating with cardiometabolic traits, we show that while genomic research in African ancestry populations is still in early stages, there are already many examples of novel and African ancestry-specific disease loci that have been discovered. Furthermore, the shorter haplotypes in African genomes have facilitated fine-mapping of loci discovered in other human ancestry populations. Given the insights already gained from the interrogation of African genomes, it is imperative to continue and increase our efforts to describe genomic risk in and across African ancestry populations.

Measuring gene-gene interaction using Kullback-Leibler divergence.

Genome-wide association studies (GWAS) are used to investigate genetic variants contributing to complex traits. Despite discovering many loci, a large proportion of "missing" heritability remains unexplained. Gene-gene interactions may help explain some of this gap. Traditionally, gene-gene interactions have been evaluated using parametric statistical methods such as linear and logistic regression, with multifactor dimensionality reduction (MDR) used to address sparseness of data in high dimensions. We propose a method for the analysis of gene-gene interactions across independent single-nucleotide polymorphisms (SNPs) in two genes. Typical methods for this problem use statistics based on an asymptotic chi-squared mixture distribution, which is not easy to use. Here, we propose a Kullback-Leibler-type statistic, which follows an asymptotic, positive, normal distribution under the null hypothesis of no relationship between SNPs in the two genes, and normally distributed under the alternative hypothesis. The performance of the proposed method is evaluated by simulation studies, which show promising results. The method is also used to analyze real data and identifies gene-gene interactions among RAB3A, MADD, and PTPRN on type 2 diabetes (T2D) status.

Genetic Basis of Obesity and Type 2 Diabetes in Africans: Impact on Precision Medicine.

PURPOSE OF REVIEW: Recent advances in genomics provide opportunities for novel understanding of the biology of human traits with the goal of improving human health. Here, we review recent obesity and type 2 diabetes (T2D)-related genomic studies in African populations and discuss the implications of limited genomics studies on health disparity and precision medicine. RECENT FINDINGS: Genome-wide association studies in Africans have yielded genetic discovery that would otherwise not be possible; these include identification of novel loci associated with obesity (SEMA-4D, PRKCA, WARS2), metabolic syndrome (CA-10, CTNNA3), and T2D (AGMO, ZRANB3). ZRANB3 was recently demonstrated to influence beta cell mass and insulin response. Despite these promising results, genomic studies in African populations are still limited and thus genomics tools and approaches such as polygenic risk scores and precision medicine are likely to have limited utility in Africans with the unacceptable possibility of exacerbating prevailing health disparities. African populations provide unique opportunities for increasing our understanding of the genetic basis of cardiometabolic disorders. We highlight the need for more coordinated and sustained efforts to increase the representation of Africans in genomic studies both as participants and scientists.

The H3Africa policy framework: negotiating fairness in genomics.

Human Heredity and Health in Africa (H3Africa) research seeks to promote fair collaboration between scientists in Africa and those from elsewhere. Here, we outline how concerns over inequality and exploitation led to a policy framework that places a firm focus on African leadership and capacity building as guiding principles for African genomics research.