scholarly journals Chronic lymphocytic leukemia (CLL) risk is mediated by multiple enhancer variants within CLL risk loci

2020 ◽  
Vol 29 (16) ◽  
pp. 2761-2774
Author(s):  
Huihuang Yan ◽  
Shulan Tian ◽  
Geffen Kleinstern ◽  
Zhiquan Wang ◽  
Jeong-Heon Lee ◽  
...  

Abstract Chronic lymphocytic leukemia (CLL) is the most common adult leukemia in Western countries. It has a strong genetic basis, showing a ~ 8-fold increased risk of CLL in first-degree relatives. Genome-wide association studies (GWAS) have identified 41 risk variants across 41 loci. However, for a majority of the loci, the functional variants and the mechanisms underlying their causal roles remain undefined. Here, we examined the genetic and epigenetic features associated with 12 index variants, along with any correlated (r2 ≥ 0.5) variants, at the CLL risk loci located outside of gene promoters. Based on publicly available ChIP-seq and chromatin accessibility data as well as our own ChIP-seq data from CLL patients, we identified six candidate functional variants at six loci and at least two candidate functional variants at each of the remaining six loci. The functional variants are predominantly located within enhancers or super-enhancers, including bi-directionally transcribed enhancers, which are often restricted to immune cell types. Furthermore, we found that, at 78% of the functional variants, the alternative alleles altered the transcription factor binding motifs or histone modifications, indicating the involvement of these variants in the change of local chromatin state. Finally, the enhancers carrying functional variants physically interacted with genes enriched in the type I interferon signaling pathway, apoptosis, or TP53 network that are known to play key roles in CLL. These results support the regulatory roles for inherited noncoding variants in the pathogenesis of CLL.

Leukemia ◽  
2021 ◽  
Author(s):  
Laura Llaó-Cid ◽  
Philipp M. Roessner ◽  
Vicente Chapaprieta ◽  
Selcen Öztürk ◽  
Tobias Roider ◽  
...  

AbstractGenome-wide association studies identified a single-nucleotide polymorphism (SNP) affecting the transcription factor Eomesodermin (EOMES) associated with a significantly increased risk to develop chronic lymphocytic leukemia (CLL). Epigenetic analyses, RNA sequencing, and flow cytometry revealed that EOMES is not expressed in CLL cells, but in CD8+ T cells for which EOMES is a known master regulator. We thus hypothesized that the increased CLL risk associated with the EOMES SNP might be explained by its negative impact on CD8+ T-cell-mediated immune control of CLL. Flow cytometry analyses revealed a higher EOMES expression in CD8+ T cells of CLL patients compared to healthy individuals, and an accumulation of PD-1+ EOMES+ CD8+ T cells in lymph nodes rather than blood or bone marrow in CLL. This was in line with an observed expansion of EOMES+ CD8+ T cells in the spleen of leukemic Eµ-TCL1 mice. As EOMES expression was highest in CD8+ T cells that express inhibitory receptors, an involvement of EOMES in T-cell exhaustion and dysfunction seems likely. Interestingly, Eomes-deficiency in CD8+ T cells resulted in their impaired expansion associated with decreased CLL control in mice. Overall, these observations suggest that EOMES is essential for CD8+ T-cell expansion and/or maintenance, and therefore involved in adaptive immune control of CLL.


2021 ◽  
Author(s):  
Jin Jin ◽  
Guanghao Qi ◽  
Zhi Yu ◽  
Nilanjan Chatterjee

AbstractMendelian Randomization (MR) analysis is increasingly popular for testing the causal effect of exposures on disease outcomes using data from genome-wide association studies. In some settings, the underlying exposure, such as systematic inflammation, may not be directly observable, but measurements can be available on multiple biomarkers, or other types of traits, that are co-regulated by the exposure. We propose method MRLE, which tests the significance for, and the direction of, the effect of a latent exposure by leveraging information from multiple related traits. The method is developed by constructing a set of estimating functions based on the second-order moments of summary association statistics, under a structural equation model where genetic variants are assumed to have indirect effects through the latent exposure and potentially direct effects on the traits. Simulation studies showed that MRLE has well-controlled type I error rates and increased power compared to single-trait MR tests under various types of pleiotropy. Applications of MRLE using genetic association statistics across five inflammatory biomarkers (CRP, IL-6, IL-8, TNF-α and MCP-1) provided evidence for potential causal effects of inflammation on increased risk of coronary artery disease, colorectal cancer and rheumatoid arthritis, while standard MR analysis for individual biomarkers often failed to detect consistent evidence for such effects.


2022 ◽  
Vol 8 ◽  
Author(s):  
Senlin Hu ◽  
Dong Hu ◽  
Haoran Wei ◽  
Shi-yang Li ◽  
Dong Wang ◽  
...  

Background: Genetic variants in Scavenger receptor Class B Type 1 (SCARB1) influencing high-density lipoprotein cholesterol (HDL-C) and coronary heart disease (CHD) risk were identified by recent genome-wide association studies. Further study of potential functional variants in SCARB1 may provide new ideas of the complicated relationship between HDL-C and CHD.Methods: 2000 bp in SCARB1 promoter region was re-sequenced in 168 participants with extremely high plasma HDL-C and 400 control subjects. Putative risk alleles were identified using bioinformatics analysis and reporter-gene assays. Two indel variants, rs144334493 and rs557348251, respectively, were genotyped in 5,002 CHD patients and 5,175 control subjects. The underlying mechanisms were investigated.Results: Through resequencing, 27 genetic variants were identified. Results of genotyping in 5,002 CHD patients and 5,175 control subjects revealed that rs144334493 and rs557348251 were significantly associated with increased risk of CHD [odds ratio (OR): 1.28, 95% confidence interval (CI): 1.09 to 1.52, p = 0.003; OR: 2.65, 95% CI: 1.66–4.24, p = 4.4 × 10−5). Subsequent mechanism experiments demonstrated that rs144334493 deletion allele attenuated forkhead box A1 (FOXA1) binding to the promoter region of SCARB1, while FOXA1 overexpression reversely increased SR-BI expression.Conclusion: Genetic variants in SCARB1 promoter region significantly associated with the plasma lipid levels by affecting SR-BI expression and contribute to the susceptibility of CHD.


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.


2015 ◽  
Vol 56 (1) ◽  
pp. R1-R20 ◽  
Author(s):  
Inês Cebola ◽  
Lorenzo Pasquali

Most of the genetic variation associated with diabetes, through genome-wide association studies, does not reside in protein-coding regions, making the identification of functional variants and their eventual translation to the clinic challenging. In recent years, high-throughput sequencing-based methods have enabled genome-scale high-resolution epigenomic profiling in a variety of human tissues, allowing the exploration of the human genome outside of the well-studied coding regions. These experiments unmasked tens of thousands of regulatory elements across several cell types, including diabetes-relevant tissues, providing new insights into their mechanisms of gene regulation. Regulatory landscapes are highly dynamic and cell-type specific and, being sensitive to DNA sequence variation, can vary with individual genomes. The scientific community is now in place to exploit the regulatory maps of tissues central to diabetes etiology, such as pancreatic progenitors and adult islets. This giant leap forward in the understanding of pancreatic gene regulation is revolutionizing our capacity to discriminate between functional and non-functional non-coding variants, opening opportunities to uncover regulatory links between sequence variation and diabetes susceptibility. In this review, we focus on the non-coding regulatory landscape of the pancreatic endocrine cells and provide an overview of the recent developments in this field.


F1000Research ◽  
2014 ◽  
Vol 3 ◽  
pp. 231
Author(s):  
Lisa Mirabello ◽  
Charles C. Chung ◽  
Meredith Yeager ◽  
Sharon A Savage

Background:TERTencodes the telomerase reverse transcriptase, which is responsible for maintaining telomere ends by addition of (TTAGGG)nnucleotide repeats at the telomere.  Recent genome-wide association studies have found common genetic variants at theTERT-CLPTM1Llocus (5p15.33) associated with an increased risk of several cancers. Results:Data were acquired for 1627 variants in 1092 unrelated individuals from 14 populations within the 1000 Genomes Project.  We assessed the population genetics of the 5p15.33 region, including recombination hotspots, diversity, heterozygosity, differentiation among populations, and potential functional impacts. There were significantly lower polymorphism rates, divergence, and heterozygosity for the coding variants, particularly for non-synonymous sites, compared with non-coding and silent changes. Many of the cancer-associated SNPs had differing genotype frequencies among ancestral groups and were associated with potential regulatory changes. Conclusions:Surrogate SNPs in linkage disequilibrium with the majority of cancer-associated SNPs were functional variants with a likely role in regulation ofTERTand/orCLPTM1L. Our findings highlight several SNPs that future studies should prioritize for evaluation of functional consequences.


2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Xiangyu Ge ◽  
Mojca Frank-Bertoncelj ◽  
Kerstin Klein ◽  
Amanda McGovern ◽  
Tadeja Kuret ◽  
...  

Abstract Background Genome-wide association studies have reported more than 100 risk loci for rheumatoid arthritis (RA). These loci are shown to be enriched in immune cell-specific enhancers, but the analysis so far has excluded stromal cells, such as synovial fibroblasts (FLS), despite their crucial involvement in the pathogenesis of RA. Here we integrate DNA architecture, 3D chromatin interactions, DNA accessibility, and gene expression in FLS, B cells, and T cells with genetic fine mapping of RA loci. Results We identify putative causal variants, enhancers, genes, and cell types for 30–60% of RA loci and demonstrate that FLS account for up to 24% of RA heritability. TNF stimulation of FLS alters the organization of topologically associating domains, chromatin state, and the expression of putative causal genes such as TNFAIP3 and IFNAR1. Several putative causal genes constitute RA-relevant functional networks in FLS with roles in cellular proliferation and activation. Finally, we demonstrate that risk variants can have joint-specific effects on target gene expression in RA FLS, which may contribute to the development of the characteristic pattern of joint involvement in RA. Conclusion Overall, our research provides the first direct evidence for a causal role of FLS in the genetic susceptibility for RA accounting for up to a quarter of RA heritability.


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.


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