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51 result(s) for "Band, Gavin"
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A Genetic Atlas of Human Admixture History
Modern genetic data combined with appropriate statistical methods have the potential to contribute substantially to our understanding of human history. We have developed an approach that exploits the genomic structure of admixed populations to date and characterize historical mixture events at fine scales. We used this to produce an atlas of worldwide human admixture history, constructed by using genetic data alone and encompassing over 100 events occurring over the past 4000 years. We identified events whose dates and participants suggest they describe genetic impacts of the Mongol empire, Arab slave trade, Bantu expansion, first millennium CE migrations in Eastern Europe, and European colonialism, as well as unrecorded events, revealing admixture to be an almost universal force shaping human populations.
Resistance to malaria through structural variation of red blood cell invasion receptors
Structural variants are mapped that are correlated with a reduced risk of severe malaria. Large-scale deletions and duplications of genes, referred to as structural variants (SVs), are common within the human genome and have been linked to disease. Examining a genomic region that appears to confer a selective benefit, Leffler et al. used fine mapping to identify a specific SV that reduces the risk of severe malaria by an estimated 40% (see the Perspective by Winzeler). Data from African individuals revealed that populations harbor different SVs in this region. Furthermore, by dissecting a highly complex genomic region, the authors identified the likely causal element. This element encodes hybrid genes that affect glycophorin proteins, which are used by the malarial parasite in infection and are associated with resistance to severe disease. Science , this issue p. eaam6393 ; see also p. 1122 The malaria parasite Plasmodium falciparum invades human red blood cells by a series of interactions between host and parasite surface proteins. By analyzing genome sequence data from human populations, including 1269 individuals from sub-Saharan Africa, we identify a diverse array of large copy-number variants affecting the host invasion receptor genes GYPA and GYPB . We find that a nearby association with severe malaria is explained by a complex structural rearrangement involving the loss of GYPB and gain of two GYPB-A hybrid genes, which encode a serologically distinct blood group antigen known as Dantu. This variant reduces the risk of severe malaria by 40% and has recently increased in frequency in parts of Kenya, yet it appears to be absent from west Africa. These findings link structural variation of red blood cell invasion receptors with natural resistance to severe malaria.
Evidence of the interplay of genetics and culture in Ethiopia
The rich linguistic, ethnic and cultural diversity of Ethiopia provides an unprecedented opportunity to understand the level to which cultural factors correlate with–and shape–genetic structure in human populations. Using primarily new genetic variation data covering 1,214 Ethiopians representing 68 different ethnic groups, together with information on individuals’ birthplaces, linguistic/religious practices and 31 cultural practices, we disentangle the effects of geographic distance, elevation, and social factors on the genetic structure of Ethiopians today. We provide evidence of associations between social behaviours and genetic differences among present-day peoples. We show that genetic similarity is broadly associated with linguistic affiliation, but also identify pronounced genetic similarity among groups from disparate language classifications that may in part be attributable to recent intermixing. We also illustrate how groups reporting the same culture traits are more genetically similar on average and show evidence of recent intermixing, suggesting that shared cultural traits may promote admixture. In addition to providing insights into the genetic structure and history of Ethiopia, we identify the most important cultural and geographic predictors of genetic differentiation and provide a resource for designing sampling protocols for future genetic studies involving Ethiopians. Ethiopia is one of the most ethnically and culturally diverse countries. Here, the authors look at genetic and cultural variation in 1,214 Ethiopians to unravel the relationship between genetic admixture and cultural factors.
Using de novo assembly to identify structural variation of eight complex immune system gene regions
Driven by the necessity to survive environmental pathogens, the human immune system has evolved exceptional diversity and plasticity, to which several factors contribute including inheritable structural polymorphism of the underlying genes. Characterizing this variation is challenging due to the complexity of these loci, which contain extensive regions of paralogy, segmental duplication and high copy-number repeats, but recent progress in long-read sequencing and optical mapping techniques suggests this problem may now be tractable. Here we assess this by using long-read sequencing platforms from PacBio and Oxford Nanopore, supplemented with short-read sequencing and Bionano optical mapping, to sequence DNA extracted from CD14 + monocytes and peripheral blood mononuclear cells from a single European individual identified as HV31. We use this data to build a de novo assembly of eight genomic regions encoding four key components of the immune system, namely the human leukocyte antigen, immunoglobulins, T cell receptors, and killer-cell immunoglobulin-like receptors. Validation of our assembly using k-mer based and alignment approaches suggests that it has high accuracy, with estimated base-level error rates below 1 in 10 kb, although we identify a small number of remaining structural errors. We use the assembly to identify heterozygous and homozygous structural variation in comparison to GRCh38. Despite analyzing only a single individual, we find multiple large structural variants affecting core genes at all three immunoglobulin regions and at two of the three T cell receptor regions. Several of these variants are not accurately callable using current algorithms, implying that further methodological improvements are needed. Our results demonstrate that assessing haplotype variation in these regions is possible given sufficiently accurate long-read and associated data. Continued reductions in the cost of these technologies will enable application of these methods to larger samples and provide a broader catalogue of germline structural variation at these loci, an important step toward making these regions accessible to large-scale genetic association studies.
Non-O ABO blood group genotypes differ in their associations with Plasmodium falciparum rosetting and severe malaria
Blood group O is associated with protection against severe malaria and reduced size and stability of P . falciparum- host red blood cell (RBC) rosettes compared to non-O blood groups. Whether the non-O blood groups encoded by the specific ABO genotypes AO , BO , AA , BB and AB differ in their associations with severe malaria and rosetting is unknown. The A and B antigens are host RBC receptors for rosetting, hence we hypothesized that the higher levels of A and/or B antigen on RBCs from AA , BB and AB genotypes compared to AO/BO genotypes could lead to larger rosettes, increased microvascular obstruction and higher risk of malaria pathology. We used a case-control study of Kenyan children and in vitro adhesion assays to test the hypothesis that “double dose” non- O genotypes ( AA , BB , AB ) are associated with increased risk of severe malaria and larger rosettes than “single dose” heterozygotes ( AO , BO ). In the case-control study, compared to OO , the double dose genotypes consistently had higher odds ratios (OR) for severe malaria than single dose genotypes, with AB (OR 1.93) and AO (OR 1.27) showing most marked difference ( p = 0.02, Wald test). In vitro experiments with blood group A-preferring P . falciparum parasites showed that significantly larger rosettes were formed with AA and AB host RBCs compared to OO , whereas AO and BO genotypes rosettes were indistinguishable from OO . Overall, the data show that ABO genotype influences P . falciparum rosetting and support the hypothesis that double dose non- O genotypes confer a greater risk of severe malaria than AO/BO heterozygosity.
Genome-wide association study of leprosy in Malawi and Mali
Leprosy is a chronic infection of the skin and peripheral nerves caused by Mycobacterium leprae . Despite recent improvements in disease control, leprosy remains an important cause of infectious disability globally. Large-scale genetic association studies in Chinese, Vietnamese and Indian populations have identified over 30 susceptibility loci for leprosy. There is a significant burden of leprosy in Africa, however it is uncertain whether the findings of published genetic association studies are generalizable to African populations. To address this, we conducted a genome-wide association study (GWAS) of leprosy in Malawian (327 cases, 436 controls) and Malian (247 cases, 368 controls) individuals. In that analysis, we replicated four risk loci previously reported in China, Vietnam and India; MHC Class I and II, LACC1 and SLC29A3 . We further identified a novel leprosy susceptibility locus at 10q24 (rs2015583; combined p = 8.81 × 10 −9 ; OR = 0.51 [95% CI 0.40 − 0.64]). Using publicly-available data we characterise regulatory activity at this locus, identifying ACTR1A as a candidate mediator of leprosy risk. This locus shows evidence of recent positive selection and demonstrates pleiotropy with established risk loci for inflammatory bowel disease and childhood-onset asthma. A shared genetic architecture for leprosy and inflammatory bowel disease has been previously described. We expand on this, strengthening the hypothesis that selection pressure driven by leprosy has shaped the evolution of autoimmune and atopic disease in modern populations. More broadly, our data highlights the importance of defining the genetic architecture of disease across genetically diverse populations, and that disease insights derived from GWAS in one population may not translate to all affected populations.
Imputation-Based Meta-Analysis of Severe Malaria in Three African Populations
Combining data from genome-wide association studies (GWAS) conducted at different locations, using genotype imputation and fixed-effects meta-analysis, has been a powerful approach for dissecting complex disease genetics in populations of European ancestry. Here we investigate the feasibility of applying the same approach in Africa, where genetic diversity, both within and between populations, is far more extensive. We analyse genome-wide data from approximately 5,000 individuals with severe malaria and 7,000 population controls from three different locations in Africa. Our results show that the standard approach is well powered to detect known malaria susceptibility loci when sample sizes are large, and that modern methods for association analysis can control the potential confounding effects of population structure. We show that pattern of association around the haemoglobin S allele differs substantially across populations due to differences in haplotype structure. Motivated by these observations we consider new approaches to association analysis that might prove valuable for multicentre GWAS in Africa: we relax the assumptions of SNP-based fixed effect analysis; we apply Bayesian approaches to allow for heterogeneity in the effect of an allele on risk across studies; and we introduce a region-based test to allow for heterogeneity in the location of causal alleles.
BIRC6 modifies risk of invasive bacterial infection in Kenyan children
Invasive bacterial disease is a major cause of morbidity and mortality in African children. Despite being caused by diverse pathogens, children with sepsis are clinically indistinguishable from one another. In spite of this, most genetic susceptibility loci for invasive infection that have been discovered to date are pathogen specific and are not therefore suggestive of a shared genetic architecture of bacterial sepsis. Here, we utilise probabilistic diagnostic models to identify children with a high probability of invasive bacterial disease among critically unwell Kenyan children with Plasmodium falciparum parasitaemia. We construct a joint dataset including 1445 bacteraemia cases and 1143 severe malaria cases, and population controls, among critically unwell Kenyan children that have previously been genotyped for human genetic variation. Using these data, we perform a cross-trait genome-wide association study of invasive bacterial infection, weighting cases according to their probability of bacterial disease. In doing so, we identify and validate a novel risk locus for invasive infection secondary to multiple bacterial pathogens, that has no apparent effect on malaria risk. The locus identified modifies splicing of BIRC6 in stimulated monocytes, implicating regulation of apoptosis and autophagy in the pathogenesis of sepsis in Kenyan children. Bacterial infections are a major cause of severe illness and death in African children. Understanding which children are at risk of life-threatening infection and why, is key to designing new tools to help protect them. Some risk is likely inherited, but scientists do not know which genes are responsible. Genome-wide association studies (GWAS) may be one way to identify bacterial infection risk genes. GWAS look for genetic differences associated with a particular disease. But previous GWAS studies have failed to find genes linked with bacterial infections in African children because they were too small. Malaria is another frequent cause of life-threatening illness in African children. It can be hard for clinicians to determine if a child's illness is caused by malaria, a bacterial infection, or both. Many children in Africa have malaria parasites in their blood, but they do not always cause disease. Most children with suspected severe malaria are treated with antibiotics in case of bacterial infection. Clinicians may then conduct further testing to determine the illness’s actual cause. Scientists may be able to use this data on children with suspected malaria to study bacterial infections. Gilchrist et al. show that children with an unusual alteration in the BIRC6 gene are at increased risk of bacterial infections. In the experiments, Gilchrist et al. used computer modeling to identify a subset of children with likely bacterial infections among 2,200 children admitted to a hospital in Kenya with a high fever and malaria parasites. By combining information on this subset of children with data on children with confirmed bacterial infections and healthy children, Gilchrist created a sample of 5,400 children for a GWAS. The analyses found that children with a variation in the BIRC6 gene on chromosome 2 had a higher risk of bacterial infections. This genetic change is linked with the production of a modified form of BIRC6 in infection-fighting immune cells called monocytes. More studies will help scientists understand how this change might contribute to severe bacterial infections. Learning more may help scientists develop new treatment strategies and identify children most at risk.
Two complement receptor one alleles have opposing associations with cerebral malaria and interact with α+thalassaemia
Malaria has been a major driving force in the evolution of the human genome. In sub-Saharan African populations, two neighbouring polymorphisms in the Complement Receptor One (CR1) gene, named Sl2 and McCb, occur at high frequencies, consistent with selection by malaria. Previous studies have been inconclusive. Using a large case-control study of severe malaria in Kenyan children and statistical models adjusted for confounders, we estimate the relationship between Sl2 and McCb and malaria phenotypes, and find they have opposing associations. The Sl2 polymorphism is associated with markedly reduced odds of cerebral malaria and death, while the McCb polymorphism is associated with increased odds of cerebral malaria. We also identify an apparent interaction between Sl2 and α+thalassaemia, with the protective association of Sl2 greatest in children with normal α-globin. The complex relationship between these three mutations may explain previous conflicting findings, highlighting the importance of considering genetic interactions in disease-association studies. Malaria kills more than half a million children in Africa every year. The disease is caused by the Plasmodium falciparum parasite, and mosquitos infected with the parasites spread them to humans when they bite. Once inside a human, the parasites infect the red blood cells. In severe cases, these red blood cells can stick to the walls of small blood vessels that supply the brain and so hinder the flow of oxygen, causing a coma. This is called cerebral malaria. Malaria can also result in the destruction of many oxygen-carrying red blood cells, which causes severe anemia. Both cerebral malaria and severe anemia can lead to death. Small changes (called mutations) in certain human genes can protect against malaria. Over time, mutations that protect people living in Africa from dying from malaria have been passed down through generations. A good example is the sickle cell mutation, which causes red blood cells to be of an unusual shape, but also affects the ability of malaria parasites to grow normally within red cells. Finding new mutations that protect against malaria may help scientists understand how severe malaria happens and eventually develop new drugs and vaccines against the disease. Some studies have found that mutations in a gene called complement receptor 1 (CR1) may be protective, although others have disagreed. Now, Opi, Swann et al. show that children with one of the CR1 mutations were one-third less likely to get cerebral malaria and half as likely to die as children without the mutation. In the study, genetic and health information on more than 5,500 children in Kenya were analyzed to see if the severity of malaria differed depending on whether they had a CR1 mutation. They also found that the CR1 mutation is only protective against severe malaria when the child does not have another malaria- protective mutation called α-thalassemia. In children with α-thalassemia, the CR1 mutation does not make a difference. The interaction between the CR1 mutation and α-thalassemia may explain why some studies did not show a benefit of CR1. If the researchers did not include α-thalassemia in their assessment, they could not have seen the whole picture. Future studies showing how the CR1 mutation protects against cerebral malaria could help identify new treatments that prevent severe disease or death. More study of interactions between genes that play a role in malaria may also be helpful.
The UK Biobank resource with deep phenotyping and genomic data
The UK Biobank project is a prospective cohort study with deep genetic and phenotypic data collected on approximately 500,000 individuals from across the United Kingdom, aged between 40 and 69 at recruitment. The open resource is unique in its size and scope. A rich variety of phenotypic and health-related information is available on each participant, including biological measurements, lifestyle indicators, biomarkers in blood and urine, and imaging of the body and brain. Follow-up information is provided by linking health and medical records. Genome-wide genotype data have been collected on all participants, providing many opportunities for the discovery of new genetic associations and the genetic bases of complex traits. Here we describe the centralized analysis of the genetic data, including genotype quality, properties of population structure and relatedness of the genetic data, and efficient phasing and genotype imputation that increases the number of testable variants to around 96 million. Classical allelic variation at 11 human leukocyte antigen genes was imputed, resulting in the recovery of signals with known associations between human leukocyte antigen alleles and many diseases. Deep phenotype and genome-wide genetic data from 500,000 individuals from the UK Biobank, describing population structure and relatedness in the cohort, and imputation to increase the number of testable variants to 96 million.