Genome-wide comparisons of variation in linkage disequilibrium.

Current genome-wide surveys of common diseases and complex traits fundamentally aim to detect indirect associations where the single nucleotide polymorphisms (SNPs) carrying the association signals are not biologically active but are in linkage disequilibrium (LD) with some unknown functional polymorphisms. Reproducing any novel discoveries from these genome-wide scans in independent studies is now a prerequisite for the putative findings to be accepted. Significant differences in patterns of LD between populations can affect the portability of phenotypic associations when the replication effort or meta-analyses are attempted in populations that are distinct from the original population in which the genome-wide study is performed. Here, we introduce a novel method for genome-wide analyses of LD variations between populations that allow the identification of candidate regions with different patterns of LD. The evidence of LD variation provided by the introduced method correlated with the degree of differences in the frequencies of the most common haplotype across the populations. Identified regions also resulted in greater variation in the success of replication attempts compared with random regions in the genome. A separate permutation strategy introduced for assessing LD variation in the absence of genome-wide data also correctly identified the expected variation in LD patterns in two well-established regions undergoing strong population-specific evolutionary pressure. Importantly, this method addresses whether a failure to reproduce a disease association in a disparate population is due to underlying differences in LD structure with an unknown functional polymorphism, which is vital in the current climate of replicating and fine-mapping established findings from genome-wide association studies.

Leprosy and the adaptation of human toll-like receptor 1.

Leprosy is an infectious disease caused by the obligate intracellular pathogen Mycobacterium leprae and remains endemic in many parts of the world. Despite several major studies on susceptibility to leprosy, few genomic loci have been replicated independently. We have conducted an association analysis of more than 1,500 individuals from different case-control and family studies, and observed consistent associations between genetic variants in both TLR1 and the HLA-DRB1/DQA1 regions with susceptibility to leprosy (TLR1 I602S, case-control P = 5.7 x 10(-8), OR = 0.31, 95% CI = 0.20-0.48, and HLA-DQA1 rs1071630, case-control P = 4.9 x 10(-14), OR = 0.43, 95% CI = 0.35-0.54). The effect sizes of these associations suggest that TLR1 and HLA-DRB1/DQA1 are major susceptibility genes in susceptibility to leprosy. Further population differentiation analysis shows that the TLR1 locus is extremely differentiated. The protective dysfunctional 602S allele is rare in Africa but expands to become the dominant allele among individuals of European descent. This supports the hypothesis that this locus may be under selection from mycobacteria or other pathogens that are recognized by TLR1 and its co-receptors. These observations provide insight into the long standing host-pathogen relationship between human and mycobacteria and highlight the key role of the TLR pathway in infectious diseases.

A novel method for haplotype clustering and visualization.

In population genetics, it is common to represent the haplotype diversity at a genomic region between multiple populations using well-constructed visual representations. This typically requires the chromosomes from these populations to be grouped according to some definition of haplotypic similarity. Here, we introduce a novel algorithm for clustering haplotypes with the specific aim of addressing haplotype diversity within or between populations. The algorithm allows for missing data in the haplotypes and appropriately downweighs single nucleotide polymorphisms with higher extent of missingness. By identifying the canonical haplotypes in a genomic region, defined as the haplotype forms, which most chromosomes are similar to, the algorithm maps each chromosome to either a unique canonical haplotype or as a mosaic of the identified canonical haplotypes. This mapping can subsequently be utilized for producing graphical visualizations of the haplotype clustering for understanding the extent of haplotype diversity in the region. The clustering application has been implemented in R for distribution as haplosim, and we also provide a visualization script hapvisual for graphical display of the clustering results. The outcome of such analysis can be informative in understanding the extent of haplotype diversity between populations, in addressing the reproducibility of established association signals across multiple populations, and also in the investigation of positive selection in the human genome.

Positive selection of a CD36 nonsense variant in sub-Saharan Africa, but no association with severe malaria phenotypes.

The prevalence of CD36 deficiency in East Asian and African populations suggests that the causal variants are under selection by severe malaria. Previous analysis of data from the International HapMap Project indicated that a CD36 haplotype bearing a nonsense mutation (T1264G; rs3211938) had undergone recent positive selection in the Yoruba of Nigeria. To investigate the global distribution of this putative selection event, we genotyped T1264G in 3420 individuals from 66 populations. We confirmed the high frequency of 1264G in the Yoruba (26%). However, the 1264G allele is less common in other African populations and absent from all non-African populations without recent African admixture. Using long-range linkage disequilibrium, we studied two West African groups in depth. Evidence for recent positive selection at the locus was demonstrable in the Yoruba, although not in Gambians. We screened 70 variants from across CD36 for an association with severe malaria phenotypes, employing a case-control study of 1350 subjects and a family study of 1288 parent-offspring trios. No marker was significantly associated with severe malaria. We focused on T1264G, genotyping 10,922 samples from four African populations. The nonsense allele was not associated with severe malaria (pooled allelic odds ratio 1.0; 95% confidence interval 0.89-1.12; P = 0.98). These results suggest a range of possible explanations including the existence of alternative selection pressures on CD36, co-evolution between host and parasite or confounding caused by allelic heterogeneity of CD36 deficiency.

Severe anemia in Malawian children.

BACKGROUND: Severe anemia is a major cause of sickness and death in African children, yet the causes of anemia in this population have been inadequately studied. METHODS: We conducted a case-control study of 381 preschool children with severe anemia (hemoglobin concentration, <5.0 g per deciliter) and 757 preschool children without severe anemia in urban and rural settings in Malawi. Causal factors previously associated with severe anemia were studied. The data were examined by multivariate analysis and structural equation modeling. RESULTS: Bacteremia (adjusted odds ratio, 5.3; 95% confidence interval [CI], 2.6 to 10.9), malaria (adjusted odds ratio, 2.3; 95% CI, 1.6 to 3.3), hookworm (adjusted odds ratio, 4.8; 95% CI, 2.0 to 11.8), human immunodeficiency virus infection (adjusted odds ratio, 2.0; 95% CI, 1.0 to 3.8), the G6PD(-202/-376) genetic disorder (adjusted odds ratio, 2.4; 95% CI, 1.3 to 4.4), vitamin A deficiency (adjusted odds ratio, 2.8; 95% CI, 1.3 to 5.8), and vitamin B12 deficiency (adjusted odds ratio, 2.2; 95% CI, 1.4 to 3.6) were associated with severe anemia. Folate deficiency, sickle cell disease, and laboratory signs of an abnormal inflammatory response were uncommon. Iron deficiency was not prevalent in case patients (adjusted odds ratio, 0.37; 95% CI, 0.22 to 0.60) and was negatively associated with bacteremia. Malaria was associated with severe anemia in the urban site (with seasonal transmission) but not in the rural site (where malaria was holoendemic). Seventy-six percent of hookworm infections were found in children under 2 years of age. CONCLUSIONS: There are multiple causes of severe anemia in Malawian preschool children, but folate and iron deficiencies are not prominent among them. Even in the presence of malaria parasites, additional or alternative causes of severe anemia should be considered.

Exploratory data analysis in large-scale genetic studies.

Genome-wide association studies (GWAS) have become the method of choice for investigating the genetic basis of common diseases and complex traits. The immense scale of these experiments is unprecedented, involving thousands of samples and up to a million variables. The careful execution of exploratory data analysis (EDA) prior to the actual genotype-phenotype association analysis is crucial as this identifies problematic samples and poorly assayed genetic polymorphisms that, if undetected, can compromise the outcome of the experiment. EDA of such large-scale genetic data sets thus requires specialized numerical and graphical strategies, and this article provides a review of the current exploratory tools commonly used in GWAS.

A Bayesian approach using covariance of single nucleotide polymorphism data to detect differences in linkage disequilibrium patterns between groups of individuals.

MOTIVATION: Quantifying differences in linkage disequilibrium (LD) between sub-groups can highlight genetic regions or sites under selection and/or associated with disease, and may have utility in trans-ethnic mapping studies. RESULTS: We present a novel pseudo Bayes factor (PBF) approach that assess differences in covariance of genotype frequencies from single nucleotide polymorphism (SNP) data from a genome-wide study. The magnitude of the PBF reflects the strength of evidence for a difference, while accounting for the sample size and number of SNPs, without the requirement for permutation testing to establish statistical significance. Application of the PBF to HapMap and Gambian malaria SNP data reveals regional LD differences, some known to be under selection. AVAILABILITY AND IMPLEMENTATION: The PBF approach has been implemented in the BALD (Bayesian analysis of LD differences) C++ software, and is available from http://homepages.lshtm.ac.uk/tgclark/downloads.

Power consequences of linkage disequilibrium variation between populations.

We quantify the degree to which LD differences exist in the human genome and investigates the consequences that variations in patterns of LD between populations can have on the power of case-control or family-trio association studies. Although only a small proportion of SNPs show significant LD differences (0.8-5%), these can introduce artificial signals of associations and reduce the power to detect true associations in case-control designs, even when meta-analytic approaches are used to account for stratification. We show that combining trios from different populations in the presence of significant LD differences can adversely affect power even though the number of trios has increased. Our results have implications on genetic studies conducted in populations with substantial population structure and show that the use of meta-analytic approaches or family-based designs to protect Type 1 error does not prevent loss of power due to differences in LD across populations.

Typhoid in Kenya is associated with a dominant multidrug-resistant Salmonella enterica serovar Typhi haplotype that is also widespread in Southeast Asia.

In sub-Saharan Africa, the burden of typhoid fever, caused by Salmonella enterica serovar Typhi, remains largely unknown, in part because of a lack of blood or bone marrow culture facilities. We characterized a total of 323 S. Typhi isolates from outbreaks in Kenya over the period 1988 to 2008 for antimicrobial susceptibilities and phylogenetic relationships using single-nucleotide polymorphism (SNP) analysis. There was a dramatic increase in the number and percentage of multidrug-resistant (MDR) S. Typhi isolates over the study period. Overall, only 54 (16.7%) S. Typhi isolates were fully sensitive, while the majority, 195 (60.4%), were multiply resistant to most commonly available drugs-ampicillin, chloramphenicol, tetracycline, and cotrimoxazole; 74 (22.9%) isolates were resistant to a single antimicrobial, usually ampicillin, cotrimoxazole, or tetracycline. Resistance to these antibiotics was encoded on self-transferrable IncHI1 plasmids of the ST6 sequence type. Of the 94 representative S. Typhi isolates selected for genome-wide haplotype analysis, sensitive isolates fell into several phylogenetically different groups, whereas MDR isolates all belonged to a single haplotype, H58, associated with MDR and decreased ciprofloxacin susceptibility, which is also dominant in many parts of Southeast Asia. Derivatives of the same S. Typhi lineage, H58, are responsible for multidrug resistance in Kenya and parts of Southeast Asia, suggesting intercontinental spread of a single MDR clone. Given the emergence of this aggressive MDR haplotype, careful selection and monitoring of antibiotic usage will be required in Kenya, and potentially other regions of sub-Saharan Africa.

Detecting SNPs and estimating allele frequencies in clonal bacterial populations by sequencing pooled DNA.

SUMMARY: Here, we present a method for estimating the frequencies of SNP alleles present within pooled samples of DNA using high-throughput short-read sequencing. The method was tested on real data from six strains of the highly monomorphic pathogen Salmonella Paratyphi A, sequenced individually and in a pool. A variety of read mapping and quality-weighting procedures were tested to determine the optimal parameters, which afforded > or =80% sensitivity of SNP detection and strong correlation with true SNP frequency at poolwide read depth of 40x, declining only slightly at read depths 20-40x. AVAILABILITY: The method was implemented in Perl and relies on the opensource software Maq for read mapping and SNP calling. The Perl script is freely available from ftp://ftp.sanger.ac.uk/pub/pathogens/pools/.

Identification of tuberculosis susceptibility genes with human macrophage gene expression profiles.

Although host genetics influences susceptibility to tuberculosis (TB), few genes determining disease outcome have been identified. We hypothesized that macrophages from individuals with different clinical manifestations of Mycobacterium tuberculosis (Mtb) infection would have distinct gene expression profiles and that polymorphisms in these genes may also be associated with susceptibility to TB. We measured gene expression levels of >38,500 genes from ex vivo Mtb-stimulated macrophages in 12 subjects with 3 clinical phenotypes: latent, pulmonary, and meningeal TB (n = 4 per group). After identifying differentially expressed genes, we confirmed these results in 34 additional subjects by real-time PCR. We also used a case-control study design to examine whether polymorphisms in differentially regulated genes were associated with susceptibility to these different clinical forms of TB. We compared gene expression profiles in Mtb-stimulated and unstimulated macrophages and identified 1,608 and 199 genes that were differentially expressed by >2- and >5-fold, respectively. In an independent sample set of 34 individuals and a subset of highly regulated genes, 90% of the microarray results were confirmed by RT-PCR, including expression levels of CCL1, which distinguished the 3 clinical groups. Furthermore, 6 single nucleotide polymorphisms (SNPs) in CCL1 were found to be associated with TB in a case-control genetic association study with 273 TB cases and 188 controls. To our knowledge, this is the first identification of CCL1 as a gene involved in host susceptibility to TB and the first study to combine microarray and DNA polymorphism studies to identify genes associated with TB susceptibility. These results suggest that genome-wide studies can provide an unbiased method to identify critical macrophage response genes that are associated with different clinical outcomes and that variation in innate immune response genes regulate susceptibility to TB.

Assessing genuine parents-offspring trios for genetic association studies.

OBJECTIVES: Family-based association tests such as the transmission disequilibrium test (TDT) are dependent on the successful ascertainment of true nuclear family trios. Relationship misspecification inevitably occurs in a proportion of trios collected for genotyping which undetected can lead to a loss of power and increased Type I error due to biases in over-transmission of common alleles. Here, we introduce a method for evaluating the authenticity of nuclear family trios. METHODS: Operating in a Bayesian framework, our approach assesses the extent of pedigree inconsistent genotype configurations in the presence of genotyping errors. Unlike other approaches, our method: (i) utilizes information from three individuals collectively (the whole trio) rather than consider two independent pairwise relationships; (ii) down-weighs SNPs with poor performance; (iii) does not require the user to pre-define a rate of genotyping error, which is often unknown to the user and seldom fixed across the different SNPs considered which available methods unrealistically assumed. RESULTS: Simulation studies and comparisons with a real set of data showed that our approach is more likely to correctly identify the presence of true and misspecified trios compared to available software, accurately infers the extent of relationship misspecification in a trio and accurately estimates the genotyping error rates. CONCLUSIONS: Assessing relationship misspecification depends on the fidelity of the genotype data used. Available algorithms are not optimised for genotyping technology with varying rates of errors across the markers. Through our comparison studies, our approach is shown to outperform available methods for assessing relationship misspecifications.

A genotype calling algorithm for the Illumina BeadArray platform.

MOTIVATION: Large-scale genotyping relies on the use of unsupervised automated calling algorithms to assign genotypes to hybridization data. A number of such calling algorithms have been recently established for the Affymetrix GeneChip genotyping technology. Here, we present a fast and accurate genotype calling algorithm for the Illumina BeadArray genotyping platforms. As the technology moves towards assaying millions of genetic polymorphisms simultaneously, there is a need for an integrated and easy-to-use software for calling genotypes. RESULTS: We have introduced a model-based genotype calling algorithm which does not rely on having prior training data or require computationally intensive procedures. The algorithm can assign genotypes to hybridization data from thousands of individuals simultaneously and pools information across multiple individuals to improve the calling. The method can accommodate variations in hybridization intensities which result in dramatic shifts of the position of the genotype clouds by identifying the optimal coordinates to initialize the algorithm. By incorporating the process of perturbation analysis, we can obtain a quality metric measuring the stability of the assigned genotype calls. We show that this quality metric can be used to identify SNPs with low call rates and accuracy. AVAILABILITY: The C++ executable for the algorithm described here is available by request from the authors.

Severe anemia in Malawian children.

BACKGROUND: Severe anemia is a major cause of sickness and death in African children, yet the causes of anemia in this population have been inadequately studied. METHODS: We conducted a case-control study of 381 preschool children with severe anemia (hemoglobin concentration, <5.0 g per deciliter) and 757 preschool children without severe anemia in urban and rural settings in Malawi. Causal factors previously associated with severe anemia were studied. The data were examined by multivariate analysis and structural equation modeling. RESULTS: Bacteremia (adjusted odds ratio, 5.3; 95% confidence interval [CI], 2.6 to 10.9), malaria (adjusted odds ratio, 2.3; 95% CI, 1.6 to 3.3), hookworm (adjusted odds ratio, 4.8; 95% CI, 2.0 to 11.8), human immunodeficiency virus infection (adjusted odds ratio, 2.0; 95% CI, 1.0 to 3.8), the G6PD-202/-376 genetic disorder (adjusted odds ratio, 2.4; 95% CI, 1.3 to 4.4), vitamin A deficiency (adjusted odds ratio, 2.8; 95% CI, 1.3 to 5.8), and vitamin B12 deficiency (adjusted odds ratio, 2.2; 95% CI, 1.4 to 3.6) were associated with severe anemia. Folate deficiency, sickle cell disease, and laboratory signs of an abnormal inflammatory response were uncommon. Iron deficiency was not prevalent in case patients (adjusted odds ratio, 0.37; 95% CI, 0.22 to 0.60) and was negatively associated with bacteremia. Malaria was associated with severe anemia in the urban site (with seasonal transmission) but not in the rural site (where malaria was holoendemic). Seventy-six percent of hookworm infections were found in children under 2 years of age. CONCLUSIONS: There are multiple causes of severe anemia in Malawian preschool children, but folate and iron deficiencies are not prominent among them. Even in the presence of malaria parasites, additional or alternative causes of severe anemia should be considered.

Genome-wide association analyses identifies a susceptibility locus for tuberculosis on chromosome 18q11.2.

We combined two tuberculosis genome-wide association studies from Ghana and The Gambia with subsequent replication in a combined 11,425 individuals. rs4331426, located in a gene-poor region on chromosome 18q11.2, was associated with disease (combined P = 6.8 x 10(-9), odds ratio = 1.19, 95% CI = 1.13-1.27). Our study demonstrates that genome-wide association studies can identify new susceptibility loci for infectious diseases, even in African populations, in which levels of linkage disequilibrium are particularly low.

Allelic heterogeneity of G6PD deficiency in West Africa and severe malaria susceptibility.

Several lines of evidence link glucose-6-phosphate dehydrogenase (G6PD) deficiency to protection from severe malaria. Early reports suggested most G6PD deficiency in sub-Saharan Africa was because of the 202A/376G G6PD A- allele, and recent association studies of G6PD deficiency have employed genotyping as a convenient way to determine enzyme status. However, further work has suggested that other G6PD deficiency alleles are relatively common in some regions of West Africa. To investigate the consequences of unrecognized allelic heterogeneity on association studies, in particular studies of G6PD deficiency and malaria, we carried out a case-control analysis of 2488 Gambian children with severe malaria and 3875 controls. No significant association was found between severe malaria and the 202A/376G G6PD A- allele when analyzed alone, but pooling 202A/376G with other deficiency alleles revealed the signal of protection (male odds ratio (OR) 0.77, 95% CI 0.62-0.95, P=0.016; female OR 0.71, 95% CI 0.56-0.89, P=0.004). We have identified the 968C mutation as the most common G6PD A- allele in The Gambia. Our results highlight some of the consequences of allelic heterogeneity, particularly the increased type I error. They also suggest that G6PD-deficient male hemizygotes and female heterozygotes are protected from severe malaria.

Tumor necrosis factor and lymphotoxin-alpha polymorphisms and severe malaria in African populations.

The tumor necrosis factor gene (TNF) and lymphotoxin-alpha gene (LTA) have long attracted attention as candidate genes for susceptibility traits for malaria, and several of their polymorphisms have been found to be associated with severe malaria (SM) phenotypes. In a large study involving >10,000 individuals and encompassing 3 African populations, we found evidence to support the reported associations between the TNF -238 polymorphism and SM in The Gambia. However, no TNF/LTA polymorphisms were found to be associated with SM in cohorts in Kenya and Malawi. It has been suggested that the causal polymorphisms regulating the TNF and LTA responses may be located some distance from the genes. Therefore, more-detailed mapping of variants across TNF/LTA genes and their flanking regions in the Gambian and allied populations may need to be undertaken to find any causal polymorphisms.

Common statistical issues in genome-wide association studies: a review on power, data quality control, genotype calling and population structure.

PURPOSE OF REVIEW: Genetic association studies which survey the entire genome have become a common design for uncovering the genetic basis of common diseases, including lipid-related traits. Such studies have identified several novel loci which influence blood lipids. The present review highlights the statistical challenges associated with such large-scale genetic studies and discusses the available methodological strategies for handling these issues. RECENT FINDINGS: The successful analysis of genome-wide data assayed on commercial genotyping arrays depends on careful exploration of the data. Unaccounted sample failures, genotyping errors and population structure can introduce misleading signals that mimic genuine association. Careful interpretation of useful summary statistics and graphical data displays can minimize the extent of false associations that need to be followed up in replication or fine-mapping experiments. SUMMARY: Recently published genome-wide studies are beginning to yield valuable insights into the importance of well designed methodological and statistical techniques for sensible interpretation of the plethora of genetic data generated.