scholarly journals Local Ancestry Adjusted Allelic Association Analysis Robustly Captures Tuberculosis Susceptibility Loci

2021 ◽  
Vol 12 ◽  
Author(s):  
Yolandi Swart ◽  
Caitlin Uren ◽  
Paul D. van Helden ◽  
Eileen G. Hoal ◽  
Marlo Möller
Keyword(s):  
South Africa ◽  
Complex Disease ◽  
Disease Risk ◽  
African Ancestry ◽  
False Negative ◽  
Genetic Admixture ◽  
Allelic Association ◽  
Local Ancestry ◽  
Asian Populations ◽  
Risk Alleles

Pulmonary tuberculosis (TB), caused by Mycobacterium tuberculosis, is a complex disease. The risk of developing active TB is in part determined by host genetic factors. Most genetic studies investigating TB susceptibility fail to replicate association signals particularly across diverse populations. South African populations arose because of multi-wave genetic admixture from the indigenous KhoeSan, Bantu-speaking Africans, Europeans, Southeast Asian-and East Asian populations. This has led to complex genetic admixture with heterogenous patterns of linkage disequilibrium and associated traits. As a result, precise estimation of both global and local ancestry is required to prevent both false positive and false-negative associations. Here, 820 individuals from South Africa were genotyped on the SNP-dense Illumina Multi-Ethnic Genotyping Array (∼1.7M SNPs) followed by local and global ancestry inference using RFMix. Local ancestry adjusted allelic association (LAAA) models were utilized owing to the extensive genetic heterogeneity present in this population. Hence, an interaction term, comprising the identification of the minor allele that corresponds to the ancestry present at the specific locus under investigation, was included as a covariate. One SNP (rs28647531) located on chromosome 4q22 was significantly associated with TB susceptibility and displayed a SNP minor allelic effect (G allele, frequency = 0.204) whilst correcting for local ancestry for Bantu-speaking African ancestry (p-value = 5.518 × 10−7; OR = 3.065; SE = 0.224). Although no other variants passed the significant threshold, clear differences were observed between the lead variants identified for each ancestry. Furthermore, the LAAA model robustly captured the source of association signals in multi-way admixed individuals from South Africa and allowed the identification of ancestry-specific disease risk alleles associated with TB susceptibility that have previously been missed.

scholarly journals Ancestry-dependent Enrichment of Deleterious Homozygotes in Runs of Homozygosity

2018 ◽  
Author(s):  
Zachary A. Szpiech ◽  
Angel C.Y. Mak ◽  
Marquitta J. White ◽  
Donglei Hu ◽  
Celeste Eng ◽  
...  
Keyword(s):  
Native American ◽  
Mexican American ◽  
Complex Disease ◽  
Disease Risk ◽  
African Ancestry ◽  
Population History ◽  
Whole Genome Sequencing Data ◽  
Runs Of Homozygosity ◽  
Sequencing Data ◽  
Local Ancestry

AbstractRuns of homozygosity (ROH) are important genomic features that manifest when an individual inherits two haplotypes that are identical-by-descent. Their length distributions are informative about population history, and their genomic locations are useful for mapping recessive loci contributing to both Mendelian and complex disease risk. We have previously shown that ROH, and especially long ROH that are likely the result of recent parental relatedness, are enriched for homozygous deleterious coding variation in a worldwide sample of outbred individuals. However, the distribution of ROH in admixed populations and their relationship to deleterious homozygous genotypes is understudied. Here we analyze whole genome sequencing data from 1,441 individuals from self-identified African American, Puerto Rican, and Mexican American populations. These populations are three-way admixed between European, African, and Native American ancestries and provide an opportunity to study the distribution of deleterious alleles partitioned by local ancestry and ROH. We re-capitulate previous findings that long ROH are enriched for deleterious variation genome-wide. We then partition by local ancestry and show that deleterious homozygotes arise at a higher rate when ROH overlap African ancestry segments than when they overlap European or Native American ancestry segments of the genome. These results suggest that, while ROH on any haplotype background are associated with an inflation of deleterious homozygous variation, African haplotype backgrounds may play a particularly important role in the genetic architecture of complex diseases for admixed individuals, highlighting the need for further study of these populations.

scholarly journals Calibrated rare variant genetic risk scores for complex disease prediction using large exome sequence repositories

2020 ◽  
Author(s):  
Ricky Lali ◽  
Michael Chong ◽  
Arghavan Omidi ◽  
Pedrum Mohammadi-Shemirani ◽  
Ann Le ◽  
...  
Keyword(s):  
Rare Variant ◽  
Genetic Risk ◽  
Complex Disease ◽  
Rare Variants ◽  
Disease Risk ◽  
Genetic Risk Score ◽  
Risk Scores ◽  
Considerable Proportion ◽  
Asian Populations ◽  
Artery Disease

ABSTRACTRare variants are collectively numerous and may underlie a considerable proportion of complex disease risk. However, identifying genuine rare variant associations is challenging due to small effect sizes, presence of technical artefacts, and heterogeneity in population structure. We hypothesized that rare variant burden over a large number of genes can be combined into predictive rare variant genetic risk score (RVGRS). We propose a novel method (RV-EXCALIBER) that leverages summary-level data from a large public exome sequencing database (gnomAD) as controls and robustly calibrates rare variant burden to account for the aforementioned biases. A RVGRS was found to strongly associate with coronary artery disease (CAD) in European and South Asian populations. Calibrated RVGRS capture the aggregate effect of rare variants through a polygenic model of inheritance, identifies 1.5% of the population with substantial risk of early CAD, and confers risk even when adjusting for known Mendelian CAD genes, clinical risk factors, and common variant gene scores.

scholarly journals UBD modifies APOL1-induced kidney disease risk

2018 ◽  
Vol 115 (13) ◽  
pp. 3446-3451 ◽  
Author(s):  
Jia-Yue Zhang ◽  
Minxian Wang ◽  
Lei Tian ◽  
Giulio Genovese ◽  
Paul Yan ◽  
...  
Keyword(s):  
Kidney Disease ◽  
Disease Risk ◽  
African Ancestry ◽  
Genetic Modifiers ◽  
Cell Toxicity ◽  
Mapping Study ◽  
Risk Alleles ◽  
Inflammatory Stimuli ◽  
Coding Variants ◽  
Apolipoprotein L1

People of recent African ancestry develop kidney disease at much higher rates than most other groups. Two specific coding variants in the Apolipoprotein-L1 gene APOL1 termed G1 and G2 are the causal drivers of much of this difference in risk, following a recessive pattern of inheritance. However, most individuals with a high-risk APOL1 genotype do not develop overt kidney disease, prompting interest in identifying those factors that interact with APOL1. We performed an admixture mapping study to identify genetic modifiers of APOL1-associated kidney disease. Individuals with two APOL1 risk alleles and focal segmental glomerulosclerosis (FSGS) have significantly increased African ancestry at the UBD (also known as FAT10) locus. UBD is a ubiquitin-like protein modifier that targets proteins for proteasomal degradation. African ancestry at the UBD locus correlates with lower levels of UBD expression. In cell-based experiments, the disease-associated APOL1 alleles (known as G1 and G2) lead to increased abundance of UBD mRNA but to decreased levels of UBD protein. UBD gene expression inversely correlates with G1 and G2 APOL1-mediated cell toxicity, as well as with levels of G1 and G2 APOL1 protein in cells. These studies support a model whereby inflammatory stimuli up-regulate both UBD and APOL1, which interact in a functionally important manner. UBD appears to mitigate APOL1-mediated toxicity by targeting it for destruction. Thus, genetically encoded differences in UBD and UBD expression appear to modify the APOL1-associated kidney phenotype.

scholarly journals Calibrated rare variant genetic risk scores for complex disease prediction using large exome sequence repositories

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Ricky Lali ◽  
Michael Chong ◽  
Arghavan Omidi ◽  
Pedrum Mohammadi-Shemirani ◽  
Ann Le ◽  
...  
Keyword(s):  
Rare Variant ◽  
Risk Score ◽  
Genetic Risk ◽  
Complex Disease ◽  
Rare Variants ◽  
Disease Risk ◽  
Genetic Risk Score ◽  
Risk Scores ◽  
Considerable Proportion ◽  
Asian Populations

AbstractRare variants are collectively numerous and may underlie a considerable proportion of complex disease risk. However, identifying genuine rare variant associations is challenging due to small effect sizes, presence of technical artefacts, and heterogeneity in population structure. We hypothesize that rare variant burden over a large number of genes can be combined into a predictive rare variant genetic risk score (RVGRS). We propose a method (RV-EXCALIBER) that leverages summary-level data from a large public exome sequencing database (gnomAD) as controls and robustly calibrates rare variant burden to account for the aforementioned biases. A calibrated RVGRS strongly associates with coronary artery disease (CAD) in European and South Asian populations by capturing the aggregate effect of rare variants through a polygenic model of inheritance. The RVGRS identifies 1.5% of the population with substantial risk of early CAD and confers risk even when adjusting for known Mendelian CAD genes, clinical risk factors, and a common variant genetic risk score.

scholarly journals Human leukocyte antigen B*0702 is protective against ocular Stevens–Johnson syndrome/toxic epidermal necrolysis in the UK population

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Gibran F. Butt ◽  
Ali Hassan ◽  
Graham R. Wallace ◽  
Shigeru Kinoshita ◽  
Sajjad Ahmad ◽  
...  
Keyword(s):  
Human Leukocyte Antigen ◽  
Toxic Epidermal Necrolysis ◽  
Human Leukocyte ◽  
Stevens Johnson Syndrome ◽  
Ocular Complications ◽  
Leukocyte Antigen ◽  
Asian Populations ◽  
Risk Alleles ◽  
Johnson Syndrome ◽  
The Uk

AbstractStevens–Johnson Syndrome and Toxic Epidermal Necrolysis (SJS/TEN) are part of a disease continuum of vesiculobullous mucocutaneous reactions affecting the skin and mucous membranes including the ocular surface. Manifestations of disease range from mild dry eye to progressive conjunctival cicatrisation, limbal epithelial stem cell failure and corneal blindness. In Far Eastern and South East Asian populations where SJS/TEN is prevalent, numerous human leukocyte antigen (HLA) gene variants at the A, B and C loci have been identified as risk factors for developing SJS/TEN with severe ocular complications (SOC). By contrast, the incidence of SJS/TEN with SOC in European countries is relatively low. To date, ocular SJS/TEN risk altering alleles have not been widely investigated in European populations. In this study, we analysed the association of HLA -A, -B and -C alleles with SJS/TEN in 33 patients residing in the UK with age matched controls. The data showed statistically significant novel negative allele association with HLA-B*0702 and a trend with HLA-C*0702 in the patient group, indicating these alleles are protective. Further characterisation of protective and risk alleles in other ethnic groups is required to fully elucidate the putative role of these alleles in the susceptibility of SJS/TEN with or without severe ocular complications in patients in the UK.

Application of the Optimized Summed Score Attributes Method for Sex Estimation

2021 ◽  
Author(s):  
Holly Long ◽  
Alexandra Klales
Keyword(s):  
Sexual Dimorphism ◽  
African Ancestry ◽  
European Ancestry ◽  
Sex Bias ◽  
Sex Estimation ◽  
Black African ◽  
Asian Populations ◽  
Novel Approach ◽  
Calibration Sample ◽  
Accuracy Rates

The optimized summed scored attributes (OSSA) method was first developed for cranial ancestry estimation (Hefner & Ousley 2014). Tallman and Go (2018) adapted this method for sex estimation with the five skull traits described by Buikstra and Ubelaker (1994) and Walker (2008). Using an Asian sample, Tallman and Go (2018) achieved moderate accuracy rates (83.7% calibration; 81.9% validation) but also high sex bias (29.1% calibration; 34.5% validation), possibly due to lower levels of sexual dimorphism in Asian populations. To further explore this novel approach to sex estimation, the OSSA method was applied to a U.S. Black/African ancestry and White/European ancestry calibration sample (N = 700). Accuracy rates were 77.4% in Black individuals and 77.2% in White individuals. Despite generally higher levels of sexual dimorphism in these groups, a high sex bias still occurred (15.4% Black individuals; –20.5% White individuals) using OSSA. The method was tested in a separate validation sample (N = 200) with accuracy of 78.0% in Black individuals (8.0% sex bias) and 70.0% in White individuals (–56.0% sex bias). When these same traits were tested with Walker’s (2008) logistic regression and in the MorphoPASSE Program (Klales 2018) using random forest modeling, accuracy rates varied ,with OSSA (77.3% correct), performing slightly better than Walker’s (2008) method (75.6% correct) but worse than MorphoPASSE (85.3% correct). The higher accuracy and lower sex bias in MorphoPASSE suggests that the Walker (2008) traits can be used to accurately estimate sex with statistical approaches more appropriate and robust than OSSA.

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