Post-GWAS Functional Characterization of Susceptibility Variants for Chronic Lymphocytic Leukemia

Recent genome-wide association studies (GWAS) have identified several gene variants associated with sporadic chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL). Many of these CLL/SLL susceptibility loci are located in non-coding or intergenic regions, posing a significant challenge to determine their potential functional relevance. Here, we review the literature of all CLL/SLL GWAS and validation studies, and apply eQTL analysis to identify putatively functional SNPs that affect gene expression that may be causal in the pathogenesis of CLL/SLL. We tested 12 independent risk loci for their potential to alter gene expression through cis-acting mechanisms, using publicly available gene expression profiles with matching genotype information. Sixteen SNPs were identified that are linked to differential expression of SP140, a putative tumor suppressor gene previously associated with CLL/SLL. Three additional SNPs were associated with differential expression of DACT3 and GNG8, which are involved in the WNT/β-catenin- and G protein-coupled receptor signaling pathways, respectively, that have been previously implicated in CLL/SLL pathogenesis. Using in silico functional prediction tools, we found that 14 of the 19 significant eQTL SNPs lie in multiple putative regulatory elements, several of which have prior implications in CLL/SLL or other hematological malignancies. Although experimental validation is needed, our study shows that the use of existing GWAS data in combination with eQTL analysis and in silico methods represents a useful starting point to screen for putatively causal SNPs that may be involved in the etiology of CLL/SLL

Post-GWAS functional characterization of susceptibility variants for chronic lymphocytic leukemia.

Recent genome-wide association studies (GWAS) have identified several gene variants associated with sporadic chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL). Many of these CLL/SLL susceptibility loci are located in non-coding or intergenic regions, posing a significant challenge to determine their potential functional relevance. Here, we review the literature of all CLL/SLL GWAS and validation studies, and apply eQTL analysis to identify putatively functional SNPs that affect gene expression that may be causal in the pathogenesis of CLL/SLL. We tested 12 independent risk loci for their potential to alter gene expression through cis-acting mechanisms, using publicly available gene expression profiles with matching genotype information. Sixteen SNPs were identified that are linked to differential expression of SP140, a putative tumor suppressor gene previously associated with CLL/SLL. Three additional SNPs were associated with differential expression of DACT3 and GNG8, which are involved in the WNT/β-catenin- and G protein-coupled receptor signaling pathways, respectively, that have been previously implicated in CLL/SLL pathogenesis. Using in silico functional prediction tools, we found that 14 of the 19 significant eQTL SNPs lie in multiple putative regulatory elements, several of which have prior implications in CLL/SLL or other hematological malignancies. Although experimental validation is needed, our study shows that the use of existing GWAS data in combination with eQTL analysis and in silico methods represents a useful starting point to screen for putatively causal SNPs that may be involved in the etiology of CLL/SLL

CLL/SLL susceptibility loci identified through genome-wide association studies.

<p>Karyotype depicts CLL/SLL-associated SNPs and SNPs in LD with those SNPs that were identified through previous genome-wide association studies (GWAS) and follow-up studies. Independent loci are color-coded with the primary GWAS SNP in dark and SNPs in LD in a lighter shade. Chromosome locations are based on chromosome build 37.1 GRCh37.</p

CLL/SLL susceptibility loci identified through genome-wide association studies and follow-up studies.

<p><i>Notes:</i> In regular font are original independent SNPs identified through GWAS. In italics font are SNPs in LD with the original GWAS SNPs. In bold font are independently validated SNPs used for eQTL analysis and risk alleles as called by the primary study. Nearest gene(s) map within ∼200 kb of each SNP.</p>a<p>OR, CI and <i>P</i>-trend quoted are per copy of risk allele (bold in column 5) from all data combined in the primary study. <i>P-</i>trend, significance of the association between each SNP and risk of CLL/SLL.</p>b<p>Conditional analysis reportedly provided no evidence for an independent role compared to original SNP <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0029632#pone.0029632-DiBernardo1" target="_blank">[4]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0029632#pone.0029632-CrowtherSwanepoel1" target="_blank">[7]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0029632#pone.0029632-CrowtherSwanepoel4" target="_blank">[12]</a>.</p>c<p>Acquired after fine-scale mapping.</p>d<p>Significance obtained from combined analysis from refs <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0029632#pone.0029632-CrowtherSwanepoel4" target="_blank">[12]</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0029632#pone.0029632-CrowtherSwanepoel2" target="_blank">[8]</a>.</p><p><i>Abbreviations:</i> LD, Linkage disequilibrium; OR, odds ratio; CLL/SLL, chronic lymphocytic leukemia/small lymphocytic lymphoma; CI, confidence interval.</p

CLL/SLL-associated SNPs that alter gene expression through <i>cis</i>-acting mechanisms.

<p><i>Notes:</i> Depicted are CLL/SLL-associated SNPs and SNPs in LD that are significantly linked to differential gene expression (BH<0.20). Highlighted in bold are the original GWAS SNPs and the risk allele, or the minor allele when the risk allele is not known.</p>a,b<p>Same SNP influencing expression of two distinct genes.</p>c<p>The synonymous rs28445040 variation (TCC→TCT) does not lead to a substitution for the serine ([Ser]→[Ser]) at amino acid position 223.</p><p><i>Abbreviations:</i> BH, Benjamini-Hochberg; ChrPos, chromosome position; CLL/SLL, chronic lymphocytic leukemia/small lymphocytic lymphoma.</p

CLL/SLL-associated SNPs that significantly alter gene expression.

<p>Expression quantitative trait loci (eQTL) analysis identified 19 significant CLL/SLL-associated SNPs linked to differential expression of <i>SP140</i> on chromosome 2 (A), and <i>DACT3</i> and <i>GNG8</i> on chromosome 19 (BH<0.20) (B). eQTL SNPs are depicted on a partial chromosome map that includes the differentially expressed gene(s). Chromosome locations are based on chromosome build 37.1 GRCh37.</p

Improving Power to Detect Changes in Blood miRNA Expression by Accounting for Sources of Variability in Experimental Designs

BACKGROUND: Blood microRNAs (miRs) are a new promising area of disease research, but variability in miR measurements may limit detection of true-positive findings. Here, we measured sources of miR variability and determine whether repeated measures can improve power to detect fold-change differences between comparison groups. METHODS: Blood from healthy volunteers (N=12) was collected at three time points. The miRs were extracted by a method predetermined to give the highest miR-yield. Nine different miRs were quantified using different qPCR assays and analyzed using mixed models to identify sources of variability. A larger number of miRs from a publicly-available blood miR microarray dataset with repeated measures was used for a bootstrapping procedure to investigate effects of repeated-measures on power to detect fold-changes in miR expression for a theoretical case-control study. RESULTS: Technical variability in qPCR replicates was identified as a significant source of variability (p<0.05) for all nine miRs tested. Variability was larger in the TaqMan qPCR assays (SD = 0.15–0.61) versus the qScript qPCR assays (SD = 0.08–0.14). Inter- and intra- individual and extraction variability also contributed significantly for two miRs. The bootstrapping procedure demonstrated that repeated measures (20–50% of N) increased detection of a 2-fold change for ~10–45% more miRs. CONCLUSION: Statistical power to detect small-fold changes in blood miRs can be improved by accounting for sources of variability using repeated measures and choosing appropriate methods to minimize variability in miR quantification. IMPACT: This study demonstrates the importance of including repeated measures in experimental designs for blood miR research

A meta-analysis of genome-wide association studies of follicular lymphoma

<p>Abstract</p> <p>Background</p> <p>B-cell non-Hodgkin lymphoma represents a diverse group of hematological malignancies, of which follicular lymphoma (FL) is one of the most common subtypes. Family and epidemiological studies suggest an important genetic role in the etiology of FL. In recent genome-wide association studies (GWAS) of FL, several genetic susceptibility loci have been identified on chromosome 6p21.33 (rs6457327) and 6p21.32 (rs10484561, rs2647012) in the human leukocyte antigen class I and class II regions. To identify new genetic variants and further elucidate the genetic basis of FL, a meta-analysis was performed of the top 1000 SNPs associated with FL risk from two GWAS in the US, Denmark and Sweden (592 cases, 1541 controls), with independent validation in 107 cases and 681 controls.</p> <p>Results</p> <p>rs9275517 and rs3117222 in the HLA class II region were validated and inversely associated with FL risk (rs9275517: OR = 0.63, 95% CI = 0.55-0.73, p = 4.03 × 10^-11; rs3117222: OR = 0.66, 95% CI = 0.57-0.77, p = 1.45 × 10^-7). rs9275517, which is in high linkage disequilibrium with rs2647012 (r2 = 0.9), was no longer associated with FL after conditioning on rs2647012. The rs3117222 association was independent of established FL SNPs, but not of the <it>HLA-DPB1*0301</it> allele. Using publicly available gene expression profiles with matching genotype information, we found that rs3117222 also was significantly correlated with increased <it>HLA-DPB1</it> expression.</p> <p>Conclusions</p> <p>By performing a meta-analysis of two GWAS of FL, we further validated the relevance of <it>HLA-DPB1*0301</it> as a protective allele in the pathogenesis of FL. Moreover, the protective rs3117222 A allele correlated with increased levels of <it>HLA-DPB1</it>, suggesting a possible disease mechanism involving <it>HLA-DPB1</it> expression regulation. Our results add further support to the major role of HLA genetic variation in the pathogenesis of FL.</p