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. 2016 May 6;95(18):e3542. doi: 10.1097/MD.0000000000003542

Association Between PIP4K2A Polymorphisms and Acute Lymphoblastic Leukemia Susceptibility

Fei Liao 1, Dandan Yin 1, Yan Zhang 1, Qianqian Hou 1, Zhaoyue Zheng 1, Li Yang 1, Yang Shu 1, Heng Xu 1, Yu Li 1
Editor: Yinyuan Wu1
PMCID: PMC4863780  PMID: 27149463

Supplemental Digital Content is available in the text

Abstract

Acute lymphoblastic leukemia (ALL) is one of the most common pediatric cancers in the world. Several single-nucleotide polymorphisms (SNPs) locating at PIP4K2A locus were identified to be associated with ALL susceptibility through genome-wide association studies, however, followed by inconsistent reports in replication studies. In this study, we conducted a meta-analysis to investigate the association status of the top independent SNPs (rs7088318 and rs4748793) with ALL susceptibility by combining the data from 6 independent studies, totally including 3508 cases and 12,446 controls with multiethnic populations. Consistent association with ALL risk of both SNPs were observed (odds ratio [OR] 1.28 and 1.29, 95% confidence interval [CI] 1.20–1.36 and 1.19–1.40, respectively). Considering clinic characteristics, rs7088318 is more related to patients with African ancestry (OR 1.48, 95% CI 1.21–1.80) and hyperdiploid subtype (OR 1.42, 95% CI 1.25–1.61). Moreover, several SNPs (eg, rs45469096) were identified to be in high linage disequilibrium with rs7088318, and affected PIP4K2A expression in lymphocytes probably by altering the binding affinity of some transcriptional factors. In conclusion, we systematically investigated the relationship between SNPs at PIP4K2A locus and ALL susceptibility, and further found potential causal variant candidates, thus better elucidating the role of PIP4K2A gene in leukemogenesis.

INTRODUCTION

Acute lymphoblastic leukemia (ALL) (ICD: C91.01) is the most common pediatric cancer worldwide.1,2 Inherited genetic susceptibility basis of such deadly malignancy has been largely investigated through genome-wide association studies (GWAS), identifying common variants at 6 genetic loci: ARID5B, IKZF1, CEBPE, CDKN2A, PIP4K2A-BMI1, and GATA3.3–10 Multiple independent studies have been followed, and consistently replicated associations at some loci (eg, ARID5B), but not others (eg, CDKN2A).11–19 Patient characteristics (eg, ethnicities, age at diagnosis, and ALL subtypes) are considered to be important factors affecting the association status. For instance, risk allele of rs10821936 at ARID5B is enriched in patients with hyperdiploid subtype and Native American genetic ancestry,19 whereas genotype of rs3824662 at GATA3 is more significantly associated with ALL risk in older patients and Ph-like subtype.6,9,10 Recently, we identified 2 independent signals at 10p12.31–12.2 locus, with the strongest signals at rs7088318 (intronic region of PIP4K2A) and rs4748793 (upstream of COMMD3/BMI1), respectively, indicating multiple causal variants are located within this region.5 Both SNPs are significantly associated with ALL susceptibility across ethnicities in our discovery cohort. Association of rs7088318 can be validated in 3 ethnic groups (ie, European Americans, African Americans, and Hispanics) with varied odds ratio (OR), whereas rs4748793 can only be validated in Caucasians.11,14,20 Independent Illumina platform-based GWAS also identified the association signal at 10p12.2, with the top SNP rs10828317, which is in high linage disequilibrium (LD) with rs7088318 (r2 = 0.7 in Caucasians).10 The effect of this SNP is varied on the major subtypes of ALL (ie, TEL-AML1 and hyperdiploidy), partially explaining the inconsistent findings in some of the follow-up studies.21

Both rs7088318 and rs4748793 are located in intronic or intergenic regions, and no coding variant within this region has been identified through a large scale of exome chip-based GWAS,8 raising the possibility that the causal variants tagged by the GWAS SNPs could be associated with ALL risk by affecting epigenetic regulation rather than inducing functional change of the nearby genes.22 Indeed, rs7088318 is considered to be a strong expression quantitative trait loci (eQTL) for PIP4K2A in both immortalized lymphoblastoid cell lines (LCLs) and primary leukemia cells from patients, with risk allele of rs7088318 positively related to higher expression of PIP4K2A.5 Moreover, suppression of PIP4K2A expression can prevent tumor cell growth and induce apoptosis in cell line and mouse models,23 indicating causal variants on PIP4K2A could impact leukemogenesis through regulating its expression level.

In this study, we searched all the related publications and conducted a meta-analysis with a large sample size (3508 cases and 12,446 controls), to ascertain the effects of SNPs at 10p12.31–12.2 (including rs7088318 and rs4748793) on ALL risk in terms of ethnicities and subtypes, and further screened the potential causal variants accounting for the association.

METHODS

Literature and Study Acquisition

Systematically, literature searching carried out independently by 2 investigators from PubMed, Google Scholar, and the Chinese National Knowledge Infrastructure (CNKI) date to December 20, 2015, according to following search terms: “rs7088318” or “rs4748793,” or “acute lymphoblastic leukemia” and “polymorphisms” and “PIP4K2A,” or “genetic polymorphism” and “acute lymphoblastic leukemia” and “GWAS.” All papers were restricted to English (N = 40). Initially, checking of the titles, and also the abstracts, was conducted to remove the duplicated articles, along with papers which do not meet our subject. Then, reading was conducted through every remaining studies and retained valuable papers which met the following criteria: used the case-control design, evaluated the association of SNPs at PIP4K2A and ALL susceptibility, providing the numbers of cases and controls, providing the genotype count or sufficient data to impute the genotypes, data without overlap (n = 4). When multiple publications were reported on the same or overlapping data, only the publication with the most updated or detailed data was included. The literature screening flow presented in Figure 1 and ethical approval, and also patient consent, were needless, because all the information was acquired from published studies.

FIGURE 1.

FIGURE 1

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Flow chart of included studies for the meta-analysis.

Data Extraction and Verification

The following information from each publication was independently extracted by two authors: the first author; the publication date; the population and ethnicity of subjects enrolled in each study; the studying cohort; the genotyping platform; the country or institution of each publication; the sample size, and also genotype count or other available data; the study design; and the sex and age of study populations. When datasets were not accessible or incomplete for the required data, corresponding authors were contacted for additional information. For accuracy, all the information was double-checked and the third reviewer was in discussion once encountering controversy information. Detailed information on the included papers is listed in Table 1.

TABLE 1.

Principle Characteristics of the Studies Included in the Meta-analysis for SNPs at PIP4K2A-BMI1 Locus

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Choice of Genetic Model

The rs7088318 polymorphism has 2 alleles, with variant allele T and wild-type allele C. we intended to analyze the association between rs7088318 polymorphism and childhood ALL susceptibility by using the allele model (T allele vs C allele), the dominant model (TT + TC vs CC), and the recessive model (TT vs TC + CC). Equally, the rs4748793 polymorphism has wild-type C allele and variant T allele. We also adopted the similar genetic model to analyze the association between rs4748793 polymorphism and childhood ALL susceptibility.

Heterogeneity Test

Heterogeneity among studies was evaluated by the Q statistic and the I2 statistic, of which Q approximately follows a chi-square distribution with k − 1 (k indicates the number of studies) degrees of freedom. P value was used to measure the significance level of heterogeneity. I2 = (Q − [k − 1])/Q × 100%, ranging from 0% to 100%. I2 was considered as a critical value, when I2 <50% and P value >0.1, fixed-effect model was superior to random-effect model to calculate summary OR and 95% confidence interval (CI), whereas the random-effect model was employed if I2 >50% and P value <0.1 because of high heterogeneity.

Linage Disequilibrium Region Determination and Epigenomic Information Analyses

The r2 value is used to determine the LD block around rs7088318 in 4 ethnic groups (ie, EUR [European and American Caucasians], AFR [African Americans], ASI [Asians], and HIS [Hispanics]). Chromosome positions were determined by using Haploreg (http://www.broadinstitute.org/mammals/haploreg/haploreg.php) in each ethnic group, respectively, and the overlapped region was determined at Chr10: 22805109 to 22857245. Further, epigenomics information from ENCODE was illustrated with Epigenome Browser (http://epigenomegateway.wustl.edu/).

Expression QTL Analyses

The PIP4K2A expression was obtained for HapMap CEU LCLs (GSE785124), and PIP4K2A SNP genotypes of HapMap CEU cell lines were obtained from the 1000 genome project web site (http://browser.1000genomes.org/). Genotype expression association was assessed using a linear regression model for the available individuals (n = 41).

RESULTS

Study Characteristics

Through literature searching with keywords (see “Methods” section), 6 independent studies demonstrated in 4 articles met the inclusion criteria and were selected for meta-analyses (Figure 1). Characteristics of these studies in totality are summarized in Table 1.

Meta-analysis of the rs7088318 Polymorphism and ALL Susceptibility

Six studies assessed the association between rs7088318 and ALL susceptibility with a total of 3508 cases and 12,446 controls, and 3269 cases and 9542 controls were used for meta-analysis after excluding admixture populations (Table 1 and Supplementary Table 1). Because no heterogeneity was observed in the allele model (P = 0.63, and I2 = 0%), we used fixed -effect model to conduct the meta-analysis, and found that T allele significantly exhibited a 1.28-fold (OR 1.28, 95% CI 1.20–1.36) increased risk to develop ALL (P < 0.001; Figure 2) compared with C allele. In addition, no heterogeneity was observed in the dominant model (P = 0.45, I2 = 0%) and recessive model (P = 0.33, I2 = 13%). T allele was consistently associated with higher ALL risk in dominant model (P < 0.001, OR 1.36, 95% CI 1.20–1.54) and recessive model (P < 0.001, OR 1.40, 95% CI 1.28–1.53) in fixed model. We next examined the effect of rs7088318 by patient characteristics (eg, ethnicity and ALL subtype). For ethnicities, rs7088318 was significantly related to ALL susceptibility in all ethnic groups with varied risk coefficients (OR 1.24 in Caucasians, OR 1.29 in Hispanics, OR 1.48 in African Americans, and OR 1.24 in Asians), whereas for subtypes, rs7088318 had a larger effect on hyperdiploidy subtypes (OR 1.42, P < 0.001 in 657 cases/8527 controls). Detail information is summarized in Table 2.

FIGURE 2.

FIGURE 2

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Forest plot of ALL susceptibility associated with rs7088318 of PIP4K2A locus with allele model. For each study, the estimates of OR and its 95% CI are plotted with square and a horizontal line. The area of the squares reflects the weight. The diamond represents the summary OR and 95% CI. Abbreviations: AFR = African Americans, ALL = acute lymphoblastic leukemia, ASI = Asians, CI = confidence interval, EUR = European and American Caucasians, HIS = Hispanics, MAF = minor allele frequency, OR = odds ratio.

TABLE 2.

PIP4K2A Polymorphisms With ALL Susceptibility

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Meta-analysis of the rs4748793 Polymorphism and ALL Susceptibility

Relatively fewer studies assessed the association between rs4748793 and ALL susceptibility with a total of 3317 cases and 12,104 controls from 5 studies, and 3068 cases and 9200 controls were used for meta-analysis after excluding admixture populations (Table 1 and Supplementary Table 1). Because no significant heterogeneity was observed in the allele model (P = 0.22, and I2 = 30%), we used fixed-effect model to conduct the meta-analysis, and found that T allele significantly exhibited a 1.29-fold (95% CI 1.19–1.40) increased risk to develop ALL (P < 0.001; Figure 3) compared with C allele. Consistent association was observed in dominant model (I2 = 0%, P = 0.003, OR 1.45, 95% CI 1.44–1.84) and recessive model (I2 = 31%, P < 0.001, OR 1.36, 95% CI 1.23–1.49). Ethnicities could be an important factor, because significances were only observed in Caucasians (P < 0.001, OR 1.38, 95% CI 1.24–1.55) and Hispanics (P = 0.008, OR 1.23, 95% CI 1.06–1.43), rather than in African Americans (P = 0.18, OR 1.29, 95% CI 0.89–1.86) and Asians (P = 0.44, OR 1.08, 95% CI 0.88–1.32). Similar to rs7088318, rs4748793 also exhibited higher OR in hyperdiploid subtype ALL (P < 0.001, OR 1.58, 95% CI 1.35–1.86). Detailed information is summarized in Table 2.

FIGURE 3.

FIGURE 3

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Forest plot of ALL susceptibility associated with rs4748793 of PIP4K2A locus with allele model. For each study, the estimates of OR and its 95% CI are plotted with square and a horizontal line. The area of the squares reflects the weight. The diamond represents the summary OR and 95% CI. Abbreviations: AFR = African Americans, ALL = acute lymphoblastic leukemia, ASI = Asians, CI = confidence interval, EUR = European and American Caucasians, HIS = Hispanics, MAF = minor allele frequency, OR = odds ratio.

Publication Bias and Sensitivity Analysis

We used Begg test and Egger test to measure the publication bias for all model; no evidence of obvious asymmetry was observed (Figure 4). Quality evaluation of the included studies was also estimated according to John P A Ioannidis's guidelines proposed in 2007,25 showing low risk of bias (Supplementary Table 2). The result of sensitivity analysis showed that the association between rs7088318 (but not rs4748793) and ALL risk does not significantly change when removing each of the studies.

FIGURE 4.

FIGURE 4

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Funnel plot of publication bias test for rs7088318. Each point represents a separate study for the indicated association.

Causal Variant Candidate Determination

No coding region located SNP was significantly associated with ALL susceptibility according to the exome-based GWAS approach. Additionally, rs7088318 was considered as an eQTL locus, affecting the expression level of PIP4K2A in both cell line and clinic level. Therefore, we investigated the potential causal variant tagged by rs7088318 through webtools (Haploreg and Epigenome Browser),26,27 and summarized the moderate LD region (r2 > 0.6) with rs7088318 in Table 3. Because rs7088318 was associated with ALL susceptibility in all ethnicities, we considered the causal variant tend to be in their overlapped region at Chr10: 22805109 to 22857245 (Table 3). Based on the chromatin state information from ENCODE database, a strong regulatory region (Chr10: 22839650–22840400) tagged by Dnase-sequencing signals were observed in LCLs (Figure 5A). Several transcriptional factor-binding signals were detected by CHIP-sequencing assay, including CTCF, YY1, and RAD21 (Figure 5A and B). Moreover, this region was also conserved across species (Figure 5B), suggesting SNPs located at this enhancer could strongly impact gene regulation and thus be considered as potential causal variants. Therefore, 3 SNPs (ie, rs45469096, rs74587525, and rs7084761) within this region were listed in Table 4, and minor allele of these SNPs was associated with protect allele of rs7088318. We next investigated the effect of these SNPs on PIP4K2A expression in LCLs from Hapmap. Five and 2 individuals having variant alleles were found for rs45469096 and rs7084761, respectively. Minor allele of both SNPs were related to lower expression of PIP4K2A compared with the major allele according to eQTL analyses, with P = 0.015 and 0.09, respectively (Figure 6 A and B). Interestingly, minor allele of rs45469096 and rs7084761were mutually exclusively related, LCLs with either minor allele of these 2 SNPs would have significantly lower expression of PIP4K2A (P = 0.001) (Figure 6C), suggesting these 2 SNPs could account for the association of rs7088318 with ALL risk, and thus be considered as causal variant candidates for PIP4K2A locus.

TABLE 3.

Definition of rs7088318 Located LD Block (r2 > 0.6)

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FIGURE 5.

FIGURE 5

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Epigenomic signals at PIP4K2A locus. A, Dnase-sequencing and transcriptional factor binding signals in the overlapped LD block (described in Table 3) at Chr10: 22805109 to 22857245, the orange line indicated location of rs7088318, and the red triangles indicates the strongest epigenomic signals. B, Illustration of the strongest epigenomic signal around rs45469096.

TABLE 4.

Characteristics of the Causal Variant Candidates

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FIGURE 6.

FIGURE 6

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eQTL analyses of the causal variant candidates rs45469096 (A), rs7084761(B), and their combination (C). eQTL = expression quantitative trait loci.

Significant publication bias was detected for rs4748793, indicating more independent studies would be needed to confirm its association with ALL susceptibility. Therefore, we did not conduct epigenomic analyses and causal variant screening at this locus.

DISCUSSION

A series of GWAS has identified at least 6 loci, which are significantly associated with ALL susceptibility. After the extensive replication studies, some loci can be validated in all independent cohorts (eg, ARID5B), whereas inconsistent associations were noticed in other loci (eg, PIP4K2A), mostly due to small sample size and diverse patient characteristics. Systematic review and meta-analyses have been conducted for signals at ARID5B, IKZF1, and CEBPE loci,16–18 but not for PIP4K2A-BMI1 locus, which was firstly identified in our multiethnic GWAS.5 Under this case, meta-analyses acted as a powerful tool to figure out the affecting factors, and potentially provided a clue on searching causal variants. In this study, we found that rs7088318 was significantly associated with ALL risk susceptibility in all ethnicities with a large-scale population. Considering the patient characteristics, risk allele of rs7088318 has stronger effect on patients with African ancestry and hyperdiploid subtypes. Interestingly, with different platform (Illumina SNP array), the association of PIP4K2A-BMI1 locus was validated, identifying rs10828317 (in LD with rs7088318) as the top signal, and significantly associated with ALL susceptibility in hyperdiploid but not TEL-AML1 subtype.10 For rs4748793, which is in weak LD with rs7088318 (r2 < 0.1), its effect on ALL risk can only be detected in Caucasians. However, association signals around this region were also identified in Hispanics, suggesting an independent causal variant may be shared in diverse ethnicities.11 Moreover, significant publication bias was detected in meta-analysis, indicating more replication studies were needed.

By September 2014, approximately 1700 GWAS had been published, reporting around 6000 genome-wide significant (P < 5 × 10–8) SNPs associated with >500 traits (http://www.ebi.ac.uk/gwas/), but the vast majority of the GWAS signals are intronic or intergenic SNPs, and are considered to be tags for the nearby causal variants.22 As large effort has been taken to search the causal variants through fine mapping,22 more and more evidences indicate that causal variants are located in the epigenomic regulatory regions (eg, promoter, enhancer, etc) and possibly affect the phenotypes by impacting the expression level of the nearby genes, such as rs1427407, which alters the TAL-binding motifs of BCL11A enhancer region and impacts BCL11A expression.28 For PIP4K2A, this gene encodes PtdIns5P 4-kinaseIIα, which is the major component of type II PtdIns5P 4-kinases, catalyzing the phosphorylation of phosphatidylinositol-5-phosphate on hydroxyl of the myo-inositol ring to form phosphatidylinositol-4,5-bisphosphate.29 This gene is highly expressed in peripheral blood cells,30 and is located in cytoplasm and nucleus. Functional studies indicate PIP4K2A could involve in TP53 and PI3K/AKT pathway,31,32 which play important roles on leukemogenesis. Interestingly, PIP4K2A expression is positively related to increased cell growth and decreased apoptosis rate in vitro.23 Also, knockout of PIP4K2A abrogated TP53 deficiency-based tumor development in mice, and inhibition of PIP4K2A can be compelling target for anticancer therapeutics.32 These facts indicate the important role of PIP4K2A on leukemogenesis, and suggest the causal variant for ALL risk at this locus could impact on leukemogenesis through regulating gene expression. Indeed, rs7088318 is considered as an eQTL in blood cells with the risk allele associated with higher PIP4K2A expression5; we therefore screened the epigenomic regulatory elements for potential causal variants through webtools (Haploreg26 and Epigenome Browser27) and found rs45469096 and rs7084761 as the strongest candidates. These 2 SNPs locate at binding sites of multiple regulatory factors and impact the PIP4K2A expression independently, indicating variant alleles of these SNPs could alter the binding affinity of the binding elements (eg, transcriptional factors), thus impacting ALL susceptibility. However, further functional experiments are needed to confirm their functional status.

In conclusion, our meta-analysis demonstrates the significant association of these 2 SNPs (ie, rs7088318 and rs4748793) at PIP4K2A-BMI1 locus with ALL susceptibility, and the effect of these SNPs varied in terms of patient characteristics. Also, potential causal variants (eg, rs45469096 and rs7084761) accounting for rs7088318 were determined, and further population-based validation and functional experiments were needed.

Supplementary Material

Supplemental Digital Content
medi-95-e3542-s001.pdf (80.7KB, pdf)

Acknowledgments

We would like to thank Dr Walsh for providing the detail genotype information of their study.

Footnotes

Abbreviations: 95% CI = 95% confidence interval, AFR = African Americans, ALL = acute lymphoblastic leukemia, ASI = Asians, CNKI = Chinese National Knowledge Infrastructure, eQTLexpression = quantitative trait loci, EUR = European and American Caucasians, GWAS = genome-wide association study, HIS = Hispanics, HWE = Hardy–Weinberg equilibrium, ICD = International Classification of Disease, LCL = lymphoblastoid cell line, LD = linage disequilibrium, MAF = minor allele frequency, NA = not available, OR = odds ratio, SNP = single-nucleotide polymorphism.

FL, DY, and YZ contributed equally to this study.

Funding: This work was supported by the National Natural Science Foundation of China (No. 81400120, No. 81522028, and No. 81402561).

The authors have no conflicts of interest to disclose.

Supplemental Digital Content is available for this article.

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Supplementary Materials

Supplemental Digital Content
medi-95-e3542-s001.pdf (80.7KB, pdf)

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