Risk Alleles Identified in Genome-Wide Association Studies Are Associated with Expression Quantitative Trait Loci in Chronic Lymphocytic Leukemia.

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 2875-2875
Author(s):  
Bethany Tesar ◽  
Lillian Werner ◽  
Megan Hanna ◽  
Ma Reina Improgo ◽  
Nathalie Pochet ◽  
...  

Abstract Abstract 2875 Genome wide association studies (GWAS) in chronic lymphocytic leukemia (CLL) have identified thirteen single nucleotide polymorphisms (SNPs) that are associated with the risk of developing CLL but do not affect the coding regions of genes. The functional targets of these SNPs remain largely unknown although they are thought to potentially serve as regulatory elements for nearby genes. We have previously published the results of a high resolution integrated genomic analysis of 161 CLLs with matched normal DNAs using Affymetrix 6.0 SNP arrays and Affymetrix U133 Plus 2.0 arrays run on the CLL lymphocytes. In this analysis, we sought to exploit this dataset to investigate whether SNP genotype at loci implicated in CLL risk by GWAS was associated with altered expression of genes in the CLL lymphocyte expression arrays. We therefore investigated 19 SNPs previously described in GWAS studies, either the SNP itself if present on the Affymetrix 6.0 SNP array, or one or more proxy SNPs for those not present on the array, chosen based on their high linkage disequilibrium (r2 > 0.7, usually > 0.9) with the GWAS SNP. Regions studied included 2q13 (1 SNP), 2q37.1 (1 SNP), 2q37.3 (1 SNP), 6p21.3 (1 SNP), 6p25.3 (2 SNPs), 8q24.2 (6 proxy SNPs), 11q24.1 (1 SNP), 15q21.3 (1 SNP), 15q23 (1 proxy SNP), 15q25.2 (1 SNP), 18q21.1 (1 proxy SNP), and 19q13.32 (2 proxy SNPs). We hypothesized that the genes most likely to be regulated by these loci would be located nearby, and therefore explored associations between SNP genotypes and the expression of genes located within 2 Mb of the relevant SNP using the Kruskal-Wallis test. The number of genes evaluated ranged from 11–22 depending on the locus. The analysis was performed independently for SNP genotypes derived from the tumor / lymphocyte samples (n=143) and from the normal / saliva samples (n=70–80). Discordant genotypes between tumor and normal samples were manually reviewed for reconciliation or excluded in the case of poor quality, indeterminate genotype or altered genomic copy number at the locus. Using the SNP genotypes from the tumor samples, we identified 13 genes with expression significantly associated with a risk SNP (using p value < 0.05). Using the SNP genotypes from the normal samples, we identified 15 genes using the same criteria. In both the tumor and normal analyses, eight SNPs were associated with a total of seven genes. The most significant associations were found between the risk allele of rs674313 on 6p21 and higher expression of HLA-DQA1 (p<0.0001), and between the risk allele of rs4802322 on 19q13 and higher expression of FKRP (p<0.0001), although the latter did not show a wide range of gene expression. IRF4 expression on 6p25 was also significantly associated with rs872071 (p=0.01), as we and others have previously shown. MYC expression was associated with two of the proxy SNPs at 8q24, rs17762878 (p=0.03) and rs7823764 (p<0.04). Additional significant associations were seen for rs4777184 on chromosome 15 with TLE3 expression (p<0.02), for rs783540 on chromosome 15 with CPEB1 expression (p<0.01), and for rs305088 on chromosome 16 with COX4NB expression (p<0.04). The regulation of IRF4 and MYC by GWAS SNP alleles is unsurprising; current work is focused on validating the associations with the other genes in an extension cohort and exploring their possible functions in CLL. Disclosures: No relevant conflicts of interest to declare.

Blood ◽  
2012 ◽  
Vol 120 (4) ◽  
pp. 843-846 ◽  
Author(s):  
Susan L. Slager ◽  
Christine F. Skibola ◽  
Maria Chiara Di Bernardo ◽  
Lucia Conde ◽  
Peter Broderick ◽  
...  

Abstract We performed a meta-analysis of 3 genome-wide association studies to identify additional common variants influencing chronic lymphocytic leukemia (CLL) risk. The discovery phase was composed of genome-wide association study data from 1121 cases and 3745 controls. Replication analysis was performed in 861 cases and 2033 controls. We identified a novel CLL risk locus at 6p21.33 (rs210142; intronic to the BAK1 gene, BCL2 antagonist killer 1; P = 9.47 × 10−16). A strong relationship between risk genotype and reduced BAK1 expression was shown in lymphoblastoid cell lines. This finding provides additional support for polygenic inheritance to CLL and provides further insight into the biologic basis of disease development.


2017 ◽  
Author(s):  
Clare Bycroft ◽  
Colin Freeman ◽  
Desislava Petkova ◽  
Gavin Band ◽  
Lloyd T. Elliott ◽  
...  

AbstractThe UK Biobank project is a large prospective cohort study of ~500,000 individuals from across the United Kingdom, aged between 40-69 at recruitment. A rich variety of phenotypic and health-related information is available on each participant, making the resource unprecedented in its size and scope. Here we describe the genome-wide genotype data (~805,000 markers) collected on all individuals in the cohort and its quality control procedures. Genotype data on this scale offers novel opportunities for assessing quality issues, although the wide range of ancestries of the individuals in the cohort also creates particular challenges. We also conducted a set of analyses that reveal properties of the genetic data – such as population structure and relatedness – that can be important for downstream analyses. In addition, we phased and imputed genotypes into the dataset, using computationally efficient methods combined with the Haplotype Reference Consortium (HRC) and UK10K haplotype resource. This increases the number of testable variants by over 100-fold to ~96 million variants. We also imputed classical allelic variation at 11 human leukocyte antigen (HLA) genes, and as a quality control check of this imputation, we replicate signals of known associations between HLA alleles and many common diseases. We describe tools that allow efficient genome-wide association studies (GWAS) of multiple traits and fast phenome-wide association studies (PheWAS), which work together with a new compressed file format that has been used to distribute the dataset. As a further check of the genotyped and imputed datasets, we performed a test-case genome-wide association scan on a well-studied human trait, standing height.


2021 ◽  
Vol 12 ◽  
Author(s):  
Chandra Bhan Yadav ◽  
Jayanti Tokas ◽  
Devvart Yadav ◽  
Ana Winters ◽  
Ram B. Singh ◽  
...  

Pearl millet [Pennisetum glaucum (L.) R Br.] is an important staple food crop in the semi-arid tropics of Asia and Africa. It is a cereal grain that has the prospect to be used as a substitute for wheat flour for celiac patients. It is an important antioxidant food resource present with a wide range of phenolic compounds that are good sources of natural antioxidants. The present study aimed to identify the total antioxidant content of pearl millet flour and apply it to evaluate the antioxidant activity of its 222 genotypes drawn randomly from the pearl millet inbred germplasm association panel (PMiGAP), a world diversity panel of this crop. The total phenolic content (TPC) significantly correlated with DPPH (1,1-diphenyl-2-picrylhydrazyl) radical scavenging activity (% inhibition), which ranged from 2.32 to 112.45% and ferric-reducing antioxidant power (FRAP) activity ranging from 21.68 to 179.66 (mg ascorbic acid eq./100 g). Genome-wide association studies (GWAS) were conducted using 222 diverse accessions and 67 K SNPs distributed across all the seven pearl millet chromosomes. Approximately, 218 SNPs were found to be strongly associated with DPPH and FRAP activity at high confidence [–log (p) &gt; 3.0–7.4]. Furthermore, flanking regions of significantly associated SNPs were explored for candidate gene harvesting. This identified 18 candidate genes related to antioxidant pathway genes (flavanone 7-O-beta-glycosyltransferase, GDSL esterase/lipase, glutathione S-transferase) residing within or near the association signal that can be selected for further functional characterization. Patterns of genetic variability and the associated genes reported in this study are useful findings, which would need further validation before their utilization in molecular breeding for high antioxidant-containing pearl millet cultivars.


2018 ◽  
Author(s):  
Holly Trochet ◽  
Matti Pirinen ◽  
Gavin Band ◽  
Luke Jostins ◽  
Gilean McVean ◽  
...  

AbstractGenome-wide association studies (GWAS) are a powerful tool for understanding the genetic basis of diseases and traits, but most studies have been conducted in isolation, with a focus on either a single or a set of closely related phenotypes. We describe MetABF, a simple Bayesian framework for performing integrative meta-analysis across multiple GWAS using summary statistics. The approach is applicable across a wide range of study designs and can increase the power by 50% compared to standard frequentist tests when only a subset of studies have a true effect. We demonstrate its utility in a meta-analysis of 20 diverse GWAS which were part of the Wellcome Trust Case-Control Consortium 2. The novelty of the approach is its ability to explore, and assess the evidence for, a range of possible true patterns of association across studies in a computationally efficient framework.


2021 ◽  
Vol 12 ◽  
Author(s):  
Che Kang Lim ◽  
Paola G. Bronson ◽  
Jezabel Varade ◽  
Timothy W. Behrens ◽  
Lennart Hammarström

Immunoglobulin A Deficiency (IgAD) is a polygenic primary immune deficiency, with a strong genetic association to the human leukocyte antigen (HLA) region. Previous genome-wide association studies (GWAS) have identified five non-HLA risk loci (IFIH1, PVT1, ATG13-AMBRA1, AHI1 and CLEC16A). In this study, we investigated the genetic interactions between different HLA susceptibility haplotypes and non-MHC genes in IgAD. To do this, we stratified IgAD subjects and healthy controls based on HLA haplotypes (N = 10,993), and then performed GWAS to identify novel genetic regions contributing to IgAD susceptibility. After replicating previously published HLA risk haplotypes, we compared individuals carrying at least one HLA risk allele (HLA-B*08:01-DRB1*03:01-DQB1*02:01 or HLA-DRB1*07:01-DQB1*02:02 or HLA-DRB1*01-DQB1*05:01) with individuals lacking an HLA risk allele. Subsequently, we stratified subjects based on the susceptibility alleles/haplotypes and performed gene-based association analysis using 572,856 SNPs and 24,125 genes. A significant genome-wide association in STXBP6 (rs4097492; p = 7.63 × 10−9) was observed in the cohort carrying at least one MHC risk allele. We also identified a significant gene-based association for B3GNT6 (PGene = 2.1 × 10–6) in patients not carrying known HLA susceptibility alleles. Our findings indicate that the etiology of IgAD differs depending on the genetic background of HLA susceptibility haplotypes.


2020 ◽  
Vol 22 (1) ◽  
pp. 122
Author(s):  
Isaias Hernández-Verdin ◽  
Karim Labreche ◽  
Marion Benazra ◽  
Karima Mokhtari ◽  
Khê Hoang-Xuan ◽  
...  

B-cell non-Hodgkin’s lymphoma (NHL) risk associations had been mainly attributed to family history of the disease, inflammation, and immune components including human leukocyte antigen (HLA) genetic variations. Nevertheless, a broad range of genome-wide association studies (GWAS) have shed light into the identification of several genetic variants presumptively associated with B-cell NHL etiologies, survival or shared genetic risk with other diseases. The present review aims to overview HLA structure and diversity and summarize the evidence of genetic variations, by GWAS, on five NHL subtypes (diffuse large B-cell lymphoma DLBCL, follicular lymphoma FL, chronic lymphocytic leukemia CLL, marginal zone lymphoma MZL, and primary central nervous system lymphoma PCNSL). Evidence indicates that the HLA zygosity status in B-cell NHL might promote immune escape and that genome-wide significance variants can give biological insight but also potential therapeutic markers such as WEE1 in DLBCL. However, additional studies are needed, especially for non-DLBCL, to replicate the associations found to date.


2016 ◽  
Author(s):  
Xiang Zhu ◽  
Matthew Stephens

Bayesian methods for large-scale multiple regression provide attractive approaches to the analysis of genome-wide association studies (GWAS). For example, they can estimate heritability of complex traits, allowing for both polygenic and sparse models; and by incorporating external genomic data into the priors they can increase power and yield new biological insights. However, these methods require access to individual genotypes and phenotypes, which are often not easily available. Here we provide a framework for performing these analyses without individual-level data. Specifically, we introduce a “Regression with Summary Statistics” (RSS) likelihood, which relates the multiple regression coefficients to univariate regression results that are often easily available. The RSS likelihood requires estimates of correlations among covariates (SNPs), which also can be obtained from public databases. We perform Bayesian multiple regression analysis by combining the RSS likelihood with previously-proposed prior distributions, sampling posteriors by Markov chain Monte Carlo. In a wide range of simulations RSS performs similarly to analyses using the individual data, both for estimating heritability and detecting associations. We apply RSS to a GWAS of human height that contains 253,288 individuals typed at 1.06 million SNPs, for which analyses of individual-level data are practically impossible. Estimates of heritability (52%) are consistent with, but more precise, than previous results using subsets of these data. We also identify many previously-unreported loci that show evidence for association with height in our analyses. Software is available at https://github.com/stephenslab/rss.


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