A Panel of Ancestry Informative Markers for the Complex Five-Way Admixed South African Coloured Population

Admixture is a well known confounder in genetic association studies. If genome-wide data is not available, as would be the case for candidate gene studies, ancestry informative markers (AIMs) are required in order to adjust for admixture. The predominant population group in the Western Cape, South Africa, is the admixed group known as the South African Coloured (SAC). A small set of AIMs that is optimized to distinguish between the five source populations of this population (African San, African non-San, European, South Asian, and East Asian) will enable researchers to cost-effectively reduce false-positive findings resulting from ignoring admixture in genetic association studies of the population. Using genome-wide data to find SNPs with large allele frequency differences between the source populations of the SAC, as quantified by Rosenberg et. al's -statistic, we developed a panel of AIMs by experimenting with various selection strategies. Subsets of different sizes were evaluated by measuring the correlation between ancestry proportions estimated by each AIM subset with ancestry proportions estimated using genome-wide data. We show that a panel of 96 AIMs can be used to assess ancestry proportions and to adjust for the confounding effect of the complex five-way admixture that occurred in the South African Coloured population.Department of HE and Training approved lis

A Sex-Stratified Genome-Wide Association Study of Tuberculosis Using a Multi-Ethnic Genotyping Array

Tuberculosis (TB), caused by Mycobacterium tuberculosis, is a complex disease with a known human genetic component. Males seem to be more affected than females and in most countries the TB notification rate is twice as high in males than in females. While socio-economic status, behavior and sex hormones influence the male bias they do not fully account for it. Males have only one copy of the X chromosome, while diploid females are subject to X chromosome inactivation. In addition, the X chromosome codes for many immune-related genes, supporting the hypothesis that X-linked genes could contribute to TB susceptibility in a sex-biased manner. We report the first TB susceptibility genome-wide association study (GWAS) with a specific focus on sex-stratified autosomal analysis and the X chromosome. A total of 810 individuals (410 cases and 405 controls) from an admixed South African population were genotyped using the Illumina Multi Ethnic Genotyping Array, specifically designed as a suitable platform for diverse and admixed populations. Association testing was done on the autosome (8,27,386 variants) and X chromosome (20,939 variants) in a sex stratified and combined manner. SNP association testing was not statistically significant using a stringent cut-off for significance but revealed likely candidate genes that warrant further investigation. A genome wide interaction analysis detected 16 significant interactions. Finally, the results highlight the importance of sex-stratified analysis as strong sex-specific effects were identified on both the autosome and X chromosome

Identification of KIF3A as a Novel Candidate Gene for Childhood Asthma Using RNA Expression and Population Allelic Frequencies Differences

Asthma is a chronic inflammatory disease with a strong genetic predisposition. A major challenge for candidate gene association studies in asthma is the selection of biologically relevant genes.Using epithelial RNA expression arrays, HapMap allele frequency variation, and the literature, we identified six possible candidate susceptibility genes for childhood asthma including ADCY2, DNAH5, KIF3A, PDE4B, PLAU, SPRR2B. To evaluate these genes, we compared the genotypes of 194 predominantly tagging SNPs in 790 asthmatic, allergic and non-allergic children. We found that SNPs in all six genes were nominally associated with asthma (p<0.05) in our discovery cohort and in three independent cohorts at either the SNP or gene level (p<0.05). Further, we determined that our selection approach was superior to random selection of genes either differentially expressed in asthmatics compared to controls (p = 0.0049) or selected based on the literature alone (p = 0.0049), substantiating the validity of our gene selection approach. Importantly, we observed that 7 of 9 SNPs in the KIF3A gene more than doubled the odds of asthma (OR = 2.3, p<0.0001) and increased the odds of allergic disease (OR = 1.8, p<0.008). Our data indicate that KIF3A rs7737031 (T-allele) has an asthma population attributable risk of 18.5%. The association between KIF3A rs7737031 and asthma was validated in 3 independent populations, further substantiating the validity of our gene selection approach.Our study demonstrates that KIF3A, a member of the kinesin superfamily of microtubule associated motors that are important in the transport of protein complexes within cilia, is a novel candidate gene for childhood asthma. Polymorphisms in KIF3A may in part be responsible for poor mucus and/or allergen clearance from the airways. Furthermore, our study provides a promising framework for the identification and evaluation of novel candidate susceptibility genes

Combining Asian and European genome-wide association studies of colorectal cancer improves risk prediction across racial and ethnic populations

Polygenic risk scores (PRS) have great potential to guide precision colorectal cancer (CRC) prevention by identifying those at higher risk to undertake targeted screening. However, current PRS using European ancestry data have sub-optimal performance in non-European ancestry populations, limiting their utility among these populations. Towards addressing this deficiency, we expand PRS development for CRC by incorporating Asian ancestry data (21,731 cases; 47,444 controls) into European ancestry training datasets (78,473 cases; 107,143 controls). The AUC estimates (95% CI) of PRS are 0.63(0.62-0.64), 0.59(0.57-0.61), 0.62(0.60-0.63), and 0.65(0.63-0.66) in independent datasets including 1681-3651 cases and 8696-115,105 controls of Asian, Black/African American, Latinx/Hispanic, and non-Hispanic White, respectively. They are significantly better than the European-centric PRS in all four major US racial and ethnic groups (p-values < 0.05). Further inclusion of non-European ancestry populations, especially Black/African American and Latinx/Hispanic, is needed to improve the risk prediction and enhance equity in applying PRS in clinical practice

Integrating sequence and array data to create an improved 1000 Genomes Project haplotype reference panel

A major use of the 1000 Genomes Project (1000GP) data is genotype imputation in genome-wide association studies (GWAS). Here we develop a method to estimate haplotypes from low-coverage sequencing data that can take advantage of single-nucleotide polymorphism (SNP) microarray genotypes on the same samples. First the SNP array data are phased to build a backbone (or 'scaffold') of haplotypes across each chromosome. We then phase the sequence data 'onto' this haplotype scaffold. This approach can take advantage of relatedness between sequenced and non-sequenced samples to improve accuracy. We use this method to create a new 1000GP haplotype reference set for use by the human genetic community. Using a set of validation genotypes at SNP and bi-allelic indels we show that these haplotypes have lower genotype discordance and improved imputation performance into downstream GWAS samples, especially at low-frequency variants. © 2014 Macmillan Publishers Limited. All rights reserved

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

A first update on mapping the human genetic architecture of COVID-19

peer reviewe

A Sex-Stratified Genome-Wide Association Study of Tuberculosis Using a Multi-Ethnic Genotyping Array.

Tuberculosis (TB), caused by Mycobacterium tuberculosis, is a complex disease with a known human genetic component. Males seem to be more affected than females and in most countries the TB notification rate is twice as high in males than in females. While socio-economic status, behavior and sex hormones influence the male bias they do not fully account for it. Males have only one copy of the X chromosome, while diploid females are subject to X chromosome inactivation. In addition, the X chromosome codes for many immune-related genes, supporting the hypothesis that X-linked genes could contribute to TB susceptibility in a sex-biased manner. We report the first TB susceptibility genome-wide association study (GWAS) with a specific focus on sex-stratified autosomal analysis and the X chromosome. A total of 810 individuals (410 cases and 405 controls) from an admixed South African population were genotyped using the Illumina Multi Ethnic Genotyping Array, specifically designed as a suitable platform for diverse and admixed populations. Association testing was done on the autosome (8,27,386 variants) and X chromosome (20,939 variants) in a sex stratified and combined manner. SNP association testing was not statistically significant using a stringent cut-off for significance but revealed likely candidate genes that warrant further investigation. A genome wide interaction analysis detected 16 significant interactions. Finally, the results highlight the importance of sex-stratified analysis as strong sex-specific effects were identified on both the autosome and X chromosome