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Indian Journal of Clinical Biochemistry logoLink to Indian Journal of Clinical Biochemistry
. 2024 Apr 4;40(4):610–618. doi: 10.1007/s12291-024-01218-8

The IKAROS Transcription Factor Gene IKZF1 as a Critical Regulator in the Pathogenesis of Childhood Acute Lymphoblastic Leukemia: Insights from a Bangladeshi Population

Nurun Nahar Nila 1,#, Sonia Tamanna 1,#, Zimam Mahmud 1, Mubasshir Washif 1, Tasnim Ahmad 1, A T M Atikur Rahman 2, Md Zakir Hossain Howlader 1,✉
PMCID: PMC12420535  PMID: 40937382

Abstract

The IKZF1 transcription factor gene plays a pivotal role in the commitment of multipotent progenitors to common lymphoid progenitors during lymphopoiesis. Genome-wide association studies (GWASs) have revealed an intriguing link between childhood acute lymphoblastic leukemia (ALL) and IKZF1 polymorphisms. This study investigated whether two specific IKZF1 variants, rs10272724 (T > C) and rs4132601 (T > G), are potential risk factors for childhood ALL among Bangladeshi children. In this study, we found that ALL occurs with a significantly greater frequency in male children than in female children, shedding light on potential sex-specific susceptibility patterns. Subsequent association analyses utilizing codominant, dominant, and recessive inheritance models demonstrated that rs10272724 is associated with a 2.36-fold increased risk of ALL development according to the codominant model, a 3.6-fold increased risk according to the dominant model, and a 1.84-fold increased risk according to the recessive model. Similarly, rs4132601 exhibited a substantial risk association, with a 3.58-fold increase in risk in the codominant model, a 3.85-fold increase in risk in the dominant model, and a 1.75-fold increase in risk in the recessive model. Furthermore, the analysis of haplotype frequencies revealed that the predominant haplotype, CG, is associated with a 1.3-fold greater risk for ALL development. Notably, we observed significant linkage disequilibrium patterns and constancy in genotypic frequencies, further strengthening the association of IKZF1 polymorphisms with ALL susceptibility. In conclusion, our study provides compelling evidence that two single-nucleotide polymorphisms (SNPs) located within the 3′ UTR of the IKZF1 gene are strongly associated with the development of childhood ALL in the Bangladeshi population.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12291-024-01218-8.

Keywords: Pediatric acute lymphoblastic leukemia, IKZF1, 3′ UTR, SNPs, PCR–RFLP

Introduction

Acute lymphoblastic leukemia (ALL) is a hematologic disease that is heterogeneous in nature. The proliferation of immature lymphoid cells in the bone marrow, peripheral blood, and other organs is the hallmark of ALL [1]. Additionally, ALL accounts for 75–80% of pediatric acute leukemia cases, making it the most prevalent pediatric malignancy [2]. Acute lymphocytic leukemia is somewhat more common in males than in females [3], and it affects White people three times more often than Black people [4]. The median age at diagnosis for ALL patients was 15 years, and 55.4% of patients had a diagnosis before the age of 20 years. In contrast, only 12.3% of patients are diagnosed at age 65 or older, whereas 28% of patients are diagnosed at age 45 or older [5]. Although the cause of ALL is unclear, genetic variations and the interactions of numerous environmental and inherited factors are known to be important contributors to disease development [6, 7].

More than 85% of the genetic variability in humans can be attributed to single nucleotide polymorphisms (SNPs). In addition to being among the most common and widespread familial complex diseases, such as diabetes, obesity, hypertension, and psychiatric disorders, they also play a role in inter individual differences in drug responses [8]. The IKZF1 gene encodes an ikaros family of transcription factors that play major roles in immunity and lymphopoiesis through the commitment of multipotent progenitors to common lymphoid progenitors [9]. The IKZF1 gene has been identified on the human chromosomal band 7p12.2. The early transcription factor IKAROS is encoded by the 8-exon IKZF1 gene [10]. Six zinc fingers are observed on the IKAROS. For IKAROS to continue to function as a tumor suppressor, four of the genes in the DNA-binding domain are encoded by exons 4 to 6. The final exon, exon 8, encodes two of the six zinc finger domains of IKAROS, which are needed for IKAROS to dimerize as a homodimer or as a heterodimer with other transcription factors in its family, such as AIOLOS and HELIOS [10, 11].

The first significant function of the Ikaros protein was observed in lymphoid-primed multipotent progenitors (LMPPs) [12, 13]. On the one hand, Ikaros’ association with a higher-order epigenetic complex that contains a variety of chromatin remodeling functions triggers a transcriptional signature for the early lymphoid lineage while repressing the transcriptional signature for the stem cell lineage [14]. LMPPs lacking in ikaros cannot differentiate into lymphocytes. Instead, these cells continue to express a significant amount of stem cell-specific genes despite differentiating into the myeloid lineage [12, 14]. At the stages of T- and B-cell differentiation, when Ikaros mRNA and protein are highly expressed, Ikaros plays a second important role [15]. In both mice and humans, abnormal differentiation and leukemic transformation are related to decrease Ikaros levels in double-positive thymocytes and pre-B cells [16–20].

Genome-wide association studies (GWASs) have shown that more than 100 common SNPs are associated with ALL susceptibility, and recurrent intronic and intergenic germline variants in the IKZF1 gene (rs4132601 and rs10272724) have been identified and described to influence the risk of pediatric BCP-ALL. The discovery that IKZF1 is a leukemia predisposition gene and that familial pediatric ALL patients and 0.9% of unselected BCP-ALL patients have predominantly adverse germline IKZF1 variants is of particular significance [21]. It is also important to determine the underlying mechanisms of the effects of SNPs to fully grasp the molecular mechanisms of distinct malignancies. SNPs may serve as therapeutic and diagnostic indicators in a variety of cancer types due to their high incidence throughout the genome [22, 23].

In this study, our objective was to elucidate whether there is any potential correlation between pediatric acute lymphoblastic leukemia and IKZF1 gene polymorphisms within the Bangladeshi population. This research represents a pioneering effort, as no prior studies have explored this particular association within the context of the Bangladeshi populace. Our focus was directed toward the allelic variants rs10272724 and rs4132601 of the IKZF1 gene, both of which have demonstrated significant associations with pediatric acute lymphoblastic leukemia in diverse populations, as reported in previous studies [24].

Methods

Study Subjects

This was a population-based case‒control study. For rs10272724, we studied 165 children with ALL and 160 healthy children. For rs4132601, the numbers of pediatric ALL patients and healthy controls were 170 and 135, respectively. All patients included in this study were carefully chosen from those who were admitted to the Department of Pediatric Hematology and Oncology of Bangabandhu Sheikh Mujib Medical University (BSMMU). All patients in the study underwent a rigorous diagnostic process involving the use of standardized methodologies that included cytomorphology, cytochemistry, and immunophenotyping techniques. Of these patients, 150 were diagnosed with B-ALL, and 20 were diagnosed with T-ALL. The pool of control subjects was recruited from the same geographic area, ethnic background, and approximately similar age group. Informed consent was obtained from the parents of the patients and controls. The Institutional Ethical Review Committee of the Department of Biochemistry and Molecular Biology at the University of Dhaka granted approval for the study under reference number BMBDU-ERC/EC/20/12/16 June 2020.

The stringent clinical criteria for case selection ensured that only recently diagnosed acute lymphoblastic leukemia (ALL) patients who had not undergone any prior treatment were included in the study. Individuals with a prior history of chemotherapy or radiotherapy exposure were excluded from this investigation. A comprehensive evaluation, including a detailed review of medical history and clinical examinations, with particular attention given to the liver, spleen, and lymph nodes, was performed on all patients. Patient data were meticulously gathered from their medical records and archives.

Healthy children without a history of chronic health conditions or blood diseases were selected from the Department of Pediatrics of Bangabandhu Sheikh Mujib Medical University (BSMMU) and from children attending the outpatient clinic of Mugdha Medical College, Dhaka, for regular checkups.

Blood Collection and DNA Isolation

From each subject, 5 mL of venous blood was drawn, and 2 mL of blood was immediately transferred to a tube containing EDTA. The other 3 mL of blood was transferred to an Eppendorf tube (for serum). EDTA-containing blood was stored at −20 °C until DNA extraction. The tube containing the remaining 3 mL of blood was centrifuged for 15 min at 2,000 rpm (Digisystem Laboratory Instrument, Inc.), and the serum was collected with a Pasteur pipette in Eppendorf tubes and stored at −20 °C until further use. DNA was extracted from blood using the organic method of phenol:chloroform:isoamyl alcohol. The presence and integrity of the extracted genomic DNA (gDNA) were evaluated by electrophoresis in a 1% agarose gel, staining in EtBr solution, and visualization under UV light on a gel-doc imaging system. The quality and concentration of gDNA were measured by a NanoDrop spectrophotometer.

Genotyping

Polymerase chain reaction (PCR)-restriction fragment length polymorphism (RFLP) was performed to determine the SNP genotypes rs10272724 and rs4132601 of the IKZF1 gene. The primer sequences of these 2 SNPs are given in Supplementary Table 1. PCR was performed in a DNA thermal cycler (GeneAtlas, ASTEC) and AnalytikJena (Biometra TADVANCED). The PCR conditions were set according to the protocol of the GoTaq master mix (Promega), except for the annealing temperature, which was set after performing gradient PCR in an AnalytikJena (Biometra TADVANCED) Thermal Cycler. A 15 µl PCR mixture contained GoTaq master mix (Promega) and 60 ng of genomic DNA (gDNA). The presence of PCR amplicons was confirmed by running in a 2% agarose gel. PCR products of rs4132601 and rs272724 were subjected to digestion with MboI and Hinf1 restriction enzymes, respectively, at 37 °C. The digested DNA fragments characterizing each genotype/allele are summarized in Supplementary Table 2. Hinf1- and Mbo1-digested PCR products were resolved on 2% and 3% agarose gels, stained with EtBr solution, and observed under UV light.

Statistical Analysis of the Data in R Studio

The statistical analysis was performed in R Studio using the R programming language. Fisher’s exact test was performed to analyze the association between IKZF1 polymorphisms and ALL. The odds ratios (ORs), 95% confidence intervals (95% CIs), and p values were estimated using Fisher’s test function. The chisq.test function was used to investigate associations within the data. To assess whether the variable data followed a normal distribution, the Shapiro‒Wilk normality test was performed utilizing the shapiro.test function. The homogeneity of variances between two populations was assessed using the F test with the var.test function. One-sample and unpaired two-sample t tests were conducted using the t test function. In all the statistical analyses, a significance level of p < 0.05 was used to determine statistical significance. Bar plots and boxplots were created for data visualization using the barplot and ggboxplot functions, respectively.

Other Web-Based Analyses

The Hardy‒Weinberg equilibrium test, haplotype, and linkage disequilibrium analysis of the 2 SNPs were performed by using “Shesis” web-based software [25]. The impact of SNPs on miRNA‒mRNA binding was evaluated at the PolymiRTS site [26].

Results

Study Subjects

Our study included 170 pediatric ALL patients (patients) and 160 healthy children (controls). The demographic characteristics and the clinical and biochemical characteristics of the ALL patients and control subjects are shown in Table 1. An unpaired 2-sample t test of age in the case and control groups showed that there was no statistically significant difference between the mean age of the case and control subjects (p = 0.6). The number of male and female subjects in the control group did not significantly differ. However, for the ALL patients, the number of males and females differed significantly (p = 0.03). Serum alanine transaminase (ALT) and lactate dehydrogenase (LDH) levels were significantly greater in the case group than in the control group. However, in the case of serum Ca2+, it was significantly lower in the case subjects. The serum GST and creatinine levels and platelet count did not significantly differ between the case and control subjects. The total WBC, RBC, hemoglobin and neutrophil counts were significantly lower in ALL patients than in controls.

Table 1.

Biochemical and clinical parameters of the case and control subjects

Biochemical and clinical parameters Cases (N = 170)
(mean ± SEM)
Controls (N = 160)
(mean ± SEM)
p Value
Mean Age (years) 7.00 ± 0.29 7.10 ± 0.21 0.6
Gender (Male: Female) 1.83 1.13 0.03
Serum ALT (U/L) 58.58 ± 6.58 34.04 ± 3.63 0.0005
Serum Creatinine (mg/dL) 0.51 ± 0.009 0.49 ± 0.013 0.2
Serum LDH (U/L) 907.4 ± 19.60 270.87 ± 12.49 0.0002
Ca +  + (mg/µL) 8.61 ± 0.18 9.92 ± 0.089  < 0.0001
WBC (10^9/L) 3.45 ± 0.39 4.84 ± 0.103  < 0.001
RBC (10^9/L) 3.68 ± 0.079 4.61 ± 0.07  < 0.0001
Hemoglobin (g/dL) 10.55 ± 0.21 11.45 ± 0.16 0.00074
Platelet (10^9/L) 175.61 ± 16.51 187.73 ± 9.37 0.52
Lymphocyte (%) 52.73 ± 2.84 27.69 ± 0.85  < 0.0001
Neutrophil (%) 40.78 ± 2.59 46.4 ± 1.08 0.04
GST Enzyme activity (U/L) 3.5 ± 0.24 3.51 ± 0.34 0.9

The data are presented as the mean ± SEM (standard error of the mean); LDH lactate dehydrogenase, ALT alanine transaminase, WBC white blood cell, RBC red blood corpuscle, and GST glutathione S-transferase

Associations Between rs10272724 and rs4132601 of the IKZF1 Gene and ALL Susceptibility

The digested PCR products of 2 SNPs (rs10272724 and rs4132601) are shown in Supplementary Figs. 1, 2 and 3 in accordance with their characteristic genotypes. The genotypic and allelic frequencies of the rs10272724 polymorphism in the patients and controls are presented in Table 2. There are 2 alleles of this SNP: the wild-type T allele and the minor C allele. Fisher’s exact test and chi-square test revealed that there was a statistically significant difference between patients and controls in allelic and genotypic frequencies. The genotypic frequencies in case and control subjects show that TC and CC genotype is higher in case but TT is higher in control.

Table 2.

Genetic model analysis of rs10272724 and rs4132601 in ALL patients and control subjects for determination of association with ALL

Genetic models Genotype/Allele Control Case Chi sq
p value
Fisher’s p value 95% CI OR
rs10272724
Co-Dominant Model TT 68 37 0.0003 1
TC 69 89 0.001 1.38 to 4.08 2.36
CC 23 39 0.0007 1.55 to 6.32 3.1
Dominant Model CC + TC 92 128 0.0001 1.54 to 4.27 3.6
Recessive Model TT + TC 137 126 0.03 0.03 1
CC 23 39 1.0 to 3.42 1.84
Allelic Frequency T 0.64 0.49 0.04 0.04 -
C 0.36 0.51
Percentage of Genotype TT 42.5 22.42 0.008 0.006 -
TC 43.13 53.94
CC 14.37 23.64
rs4132601
Co-Dominant Model TT 62 32  < 0.0001 1
TG 50 93  < 0.0001 2.01 to 6.48 3.58
GG 23 45  < 0.0001 1.87 to 7.74 3.76
Dominant Model GG + TG 73 138  < 0.0001 2.13 to 6.33 3.85
Recessive Model TT + TG 112 125 0.04  < 0.05 1
GG 23 45 0.97 to 3.23 1.75
Allelic Frequency T 0.65 0.46 0.01 0.01 -
G 0.35 0.54
Percentage of Genotype TT 45.93 18.8 0.0002 0.0002 -
TG 37.03 54.7
GG 17.04 26.5

OR odds ratio; 95% CI, 95% confidence interval; chi-square test; and Fisher’s exact test were used to assess the significance of the difference between genotypic groups. P < 0.05 was considered to indicate statistical significance

According to the codominant model, the heterozygous mutant (TC) and homozygous mutant (CC) genotypes of rs10272724 had 2.36-fold and 3.1-fold greater risk of developing ALL in children, respectively, than did the homozygous wild-type (TT) genotype (OR = 2.36, 95% CI = 1.38 to 4.08; P = 0.001; TC vs TT; and OR = 3.1, 95% CI = 1.55 to 6.32; P = 0.0007; CC vs TT; Table 2). Dominant model and recessive model showed that CC + TC and CC genotype carriers increase the risk by 3.6-fold and 1.84-fold (OR = 3.55, 95% CI = 1.54 to 4.27, P = 0.0001, CC + TC vs TT; and OR = 1.84, 95% CI = 1.0 to 3.42, P = 0.03, CC vs TT + TC).

On the other hand, the alleles of rs4132601 are the wild-type T allele and minor G allele (Table 2). There are 3 genotypes of the SNP: the homozygous wild type (TT), homozygous mutant (GG) and heterozygous mutant (TG) genotypes. The chi-square test and Fisher’s exact test showed that there was a significant difference in allelic and genotypic frequencies between the patients and controls (Table 2). The TG and GG genotypes were more common in the case group than in the control group, whereas in the case of TT, the opposite was true.

The results showed that TG and GG increased the risk of ALL by 3.58-fold and 3.76-fold, respectively, in the codominant inheritance model (OR = 3.58, 95% CI = 2.01 to 6.48; P < 0.0001; TG vs TT; and OR = 3.76, 95% CI = 1.87 to 7.74, p < 0.0001; GG vs TT; Table 2). According to the dominant and recessive models, the GG + TG and GG genotypes increased the risk by 3.85-fold and 1.75-fold, respectively (OR = 3.85, 95% CI = 2.13 to 6.33, p < 0.0001; GG + TG vs TT; and OR = 1.75, 95% CI = 0.97 to 3.23, p < 0.05; GG vs TT + TG).

miR Site Analysis for SNPs

The prediction of PolymiRTS for rs4132601 showed that the miR sites of the hsa-miR-1261, hsa-miR-524-3p, and hsa-miR-525-3p miRNAs were disrupted due to the T allele (Table 3). However, for the G allele, 2 new miR sites were created for the hsa-miR-3937 and hsa-miR-4772-5p miRNAs.

Table 3.

Prediction of poly (miRTS) for rs4132601, which resides at multiple miR sites and has an impact on miRNA‒mRNA binding

dbSNP ID Allele miR ID Conservation miRSite Function class
rs4132601 T hsa-miR-1261 5 gcgccTTATCCAA D
hsa-miR-524-3p 2 GCGCCTTAtccaa D
hsa-miR-525-3p 2 GCGCCTTAtccaa D
G hsa-miR-3937 5 gCGCCTGAtccaa C
hsa-miR-4772-5p 6 gcgCCTGATCcaa C
hsa-miR-4772-5p 6 gcgCCTGATCcaa C

D miR site “disrupted”, C miR site “created”

Constancy of Genotypic Frequency, Haplotype, and Linkage Disequilibrium Analysis

To analyze the consistency of the genotype frequency in the study subjects, the Hardy‒Weinberg equilibrium test was performed using the “Shesis” tool (Table 4). Pearson’s p value and Fisher’s p value were < 0.05, which indicates that there was no deviation from the Hardy‒Weinberg principle in the case of 2 SNPs.

Table 4.

Hardy‒Weinberg equilibrium test of 2 SNPs (rs10272724 and rs4132601) in study subjects performed by using “Shesis” web-based software

SNPs Study subjects Fisher’s P value Pearson’s P value Chi2 df
rs10272724 Control 0.025 0.024 4.97 1
Case 0.02 0.02 5.03 1
rs4132601 Control 0.04 0.04 4.14 1
Case 0.03 0.03 4.59 1

Haplotype analysis by “Shesis” showed that CG* was the predominant haplotype and CT* was the minor haplotype in ALL patients, whereas in the control, the minor haplotype was the same but predominant was TT* (Table 5). The CG* haplotype was associated with a 1.3-fold increased risk of ALL development (P < 0.04, OR = 1.3, 95% CI = 1.0 ~ 1.923, CG* vs TT*). On the other hand, the CT* and TG* haplotypes increased the risk by 2.2-fold (p value = 0.002, OR = 2.2, 95% CI = 1.34 to 3.69 CT* vs TT*; and OR = 2.2, 95% CI = 1.39 to 3.56, p value = 0.0007, TG* vs TT*). The TT* haplotype had a protective effect on the development of ALL (P < 0.0001, OR = 0.3, 95% CI = 0.23 to 0.45), with an odds ratio of 0.3.

Table 5.

Haplotype analysis of 2 SNPs (rs10272724 and rs4132601) in the study subjects performed by using “Shesis” web-based software

Haplotype Case (Frequency) Control (Frequency) Chi2 Fisher’s p value Pearson’s p value OR
[95% CI]
C G* 91.73(0.31) 65.34(0.26) 2.16 0.04 0.04 1.3 [1.0 ~ 1.92]
C T* 56.27(0.19) 24.66(0.10) 9.859 0.002 0.002 2.2 [1.34 ~ 3.69]
T G* 66.27(0.23) 29.66(0.12) 11.41 0.0007 0.0007 2.2 [1.39 ~ 3.56]
T T* 79.73(0.27) 136.34(0.53) 39.20  < 0.0001  < 0.0001 0.3 [0.23 ~ 0.45]

OR Odds ratio; 95% confidence interval, 95% CI. chi-square test

According to the linkage disequilibrium (LD) pattern of the control subjects, D´ was 0.564 (Table 6), which indicates that the 2 SNPs coherent approximately 56.4% of the time (Supplementary Fig. 4). However, a r2 of 0.293 indicated that the micro allele occurred at a good frequency and was not a rare allele (Table 6). Linkage disequilibrium analysis was performed using “Shesis” web-based software. The LD patterns (D´ and r2) for the control, case, and both case and control groups are given in Table 6. In the case of ALL patients, the D´ value was 0.18, and the r2 was 0.028. On the other hand, the LD pattern in the control and case groups was significant, with D´ = 0.444 and r2 = 0.177. Furthermore, from Supplementary Fig. 5, it is clear that these 2 SNPs were inherited approximately 44.4% of the time.

Table 6.

Values of linkage disequilibrium (D´ and r2) for the control, case and both case and control groups

LD for D’ value R2 value
Control 0.564 0.293
Case 0.18 0.028
Both 0.444 0.177

Discussion

Acute lymphoblastic leukemia (ALL) is the most prevalent form of pediatric cancer and is characterized by the proliferation of aberrant and immature lymphoid cells in the bone marrow [27]. In recent decades, there has been a remarkable improvement in the survival rate of pediatric patients with ALL [28], with primary therapy success rates reaching 85% [11]. This progress can be attributed to the implementation of treatment stratification strategies, incorporating the profiling of prognostic and genomic markers, including deletions, mutations, and single nucleotide polymorphisms (SNPs), associated with ALL development, severity, and relapse [11, 29, 30]. One such genomic marker that has garnered significant attention is the IKAROS family transcription factor gene IKZF1. This gene plays a crucial role in the early commitment of multipotent progenitor (MPP) cells to common lymphoid progenitors during lymphopoiesis [9]. Notably, germline mutations in IKZF1 have been primarily associated with a predisposition to pediatric ALL [21].

To assess the association of the IKZF1 polymorphism with pediatric ALL, we selected rs10272724 and rs4132601, which were found to be associated with ALL by GWAS and in other populations [11, 24, 31].

The results yielded compelling insights into the genetic underpinnings of this disease. A noteworthy difference emerged in terms of sex distribution, with a considerably lower incidence of ALL in female subjects than in male subjects (Table 1), a finding that warrants further investigation.

The genetic variant rs10272724 is significantly associated with an increased risk of developing acute lymphoblastic leukemia (ALL). In the patient group, the minor allele (C) had a greater frequency than in the control group, indicating a dominant effect (p = 0.04; Table 2). The risk of ALL development associated with this allele was 2.36-fold in the codominant model, 3.6-fold in the dominant model, and 1.84-fold in the recessive model (Table 2). These findings are consistent with previous studies [24], suggesting that the C allele represents a dominant risk factor for pediatric ALL.

The microallele rs4132601 exhibited a G variant, which was markedly more prevalent within the case group than in the control group, as delineated in Table 2. Further examination of the genotypic frequencies revealed statistically significant differences, with the TG and GG genotypes demonstrating greater prevalence in all patients with acute lymphoblastic leukemia (ALL) than in the healthy individuals, while the TT genotype exhibited the opposite pattern.

By conducting an in-depth exploration within the framework of codominant, dominant, and recessive inheritance models, we revealed compelling evidence that underscores the role of rs4132601 within the IKZF1 gene. Notably, these genetic models revealed that this variant is associated with 3.58-fold, 3.85-fold, and 1.75-fold increased risk of ALL development, as shown in Table 2. Notably, a parallel investigation was performed on the Iranian population [24], where the rs4132601 SNP was similarly found to pose a risk, albeit at slightly different odds ratios, specifically 2.96, 2.89, and 1.44-fold.

Intriguingly, a comprehensive meta-analysis conducted by Dai et al. [32] substantiated these findings, establishing the significant risk augmentation attributable to the rs4132601 polymorphism in all examined genetic models and affirming its role in pediatric acute leukemia (AL) susceptibility. Furthermore, Li et al. [33] also conducted a meticulous meta-analysis, reiterating the heightened risk associated with the IKZF1 rs4132601 polymorphism in ALL, underlining its relevance across diverse populations. Similarly, within the French population, this SNP exhibited a robust association with ALL development [34].

However, it is important to note that the study by Lin et al. [35] stands in contrast to the prevailing trend. Their findings did not corroborate any association between this SNP and ALL development, suggesting potential population-specific variations or methodological differences.

Gorniak et al. [36] contributed noteworthy insights by highlighting a link between the rs4132601 polymorphic site within the IKZF1 gene and the age at diagnosis of childhood ALL in the Polish population, further emphasizing the complex interplay between genetics and disease manifestation.

A compelling functional basis for the association between this SNP and ALL was observed in the correlation between reduced IKZF1 gene expression and the risk genotype in lymphocytes, providing mechanistic insight into the etiology of this disease, as elucidated by previous research [37].

miR site analysis of rs4132601 in the IKZF1 gene revealed that the T allele disrupted the binding of the 3 abovementioned miRNAs, hsa-miR-1261, hsa-miR-524-3p, and hsa-miR-525-3p, and thus had a negative impact on the binding of IKZF1 mRNA to miRNAs (Table 3). This may have an impact on the regulation and abundance of this gene and gene products. On the other hand, the G allele creates 2 new miRNA sites for IKZF1 mRNA and new miRNA interactions. Therefore, this process might eventually alter the regulation of the IKZF1 gene and the abundance of its product.

Assessment of constancy revealed that there was no deviation in the allelic or genotypic frequencies of 2 SNPs according to the Hardy‒Weinberg principle (p > 0.05). This finding suggested that the allelic and genotypic frequencies of rs10272724 and rs4132601 remain constant from generation to generation without mutational interruption (Table 4).

Haplotype analysis of rs10272724 and rs4132601 in patients and controls was performed. CG* was the predominant haplotype, and CT* was the minor haplotype in ALL patients. However, in the control group, the minor haplotype was the same, but the predominant haplotype was TT* (Table 5). The TT* haplotype has a protective role against the development of ALL. The predominant CG* haplotype was associated with a 1.3-fold increased risk of pediatric ALL development, while the CT* and TG* haplotypes were associated with a 2.2-fold increased risk.

From the linkage disequilibrium (LD) patterns of the control, case and both case as well as control subjects, it is clear that rs4132601 and rs10272724 coinherit nearly 56.4%, 18%, and 44.4%, respectively, of the time, and the minor alleles G and C are not rare alleles but occur at a significant level (Table 6, Supplementary Figs. 4 and 5).

Finally, we have to acknowledge that our study has some limitations due to resource constraints and logistical challenges. For instance, we were unable to replicate the result in an independent cohort in the current study. However, we believe it is essential to highlight that our work serves as an initial exploration into the association between IKZF1 and ALL in Bangladeshi population.

In addition, we opted for the Chi-square test over Logistic regression in the association study due to the categorical nature of our data and research objectives. The Chi-square test is well-suited for analyzing associations between categorical variables, particularly when examining non-continuous data without assuming a linear relationship. The simplicity and interpretability of the Chi-square test align with the study’s goal of providing clear and accessible results, avoiding complexities introduced by Logistic regression.

In conclusion, our study has illuminated the profound influence of IKZF1 polymorphisms on susceptibility to childhood acute lymphoblastic leukemia (ALL) among children within the Bangladeshi population. Furthermore, the robustness of these findings, when subjected to scrutiny on a broader, more expansive scale, suggests that these IKZF1 polymorphisms hold the potential to serve as invaluable genetic markers. These markers might hold promise for their application in screening, diagnostic endeavors, and the unfurling frontier of ALL research, collectively advancing our understanding and ability to combat this formidable disease.

Supplementary Information

Below is the link to the electronic supplementary material.

Acknowledgements

We would like to acknowledge the participants of this study who communicated and provided valuable information.

Funding

This study was funded by the Bangladesh Bureau of Educational Information and Statistics (BANBEIS) under the Ministry of Education (MOE) Bangladesh [Grant number: bs- 37.20.0000.004.033.020.2016.2297, 2018].

Data Availability

All the data generated or analyzed during this study are included in this published article.

Declarations

Conflicting Interests

The authors declare no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Footnotes

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Nurun Nahar Nila and Sonia Tamanna contributed equally as co-first authors.

References

  • 1.Brown P, Inaba H, Annesley C, Beck J, Colace S, Dallas M, et al. Pediatric acute lymphoblastic leukemia, version 2.2020, NCCN clinical practice guidelines in oncology. J Natl Compr Canc Netw. 2020;18(1):81–112. [DOI] [PubMed]
  • 2.SD Esparza KM Sakamoto 2005 Topics in pediatric leukemia–acute lymphoblastic leukemia MedGenMed 7 1 23 [PMC free article] [PubMed] [Google Scholar]
  • 3.Kumar V, Rathee R, Vashist M, Neelkamal, Singh S, Gupta S. Acute lymphocytic leukemia: an epidemiological and hematological study from Haryana. Biosci Biotech Res Asia. 2012;9(2):813-7.
  • 4.Puckett Y, Chan O. Acute lymphocytic leukemia. StatPearls. Treasure Island (FL) ineligible companies. Disclosure: Onyee Chan declares no relevant financial relationships with ineligible companies. StatPearls Publishing. Copyright © 2023, StatPearls Publishing LLC.; 2023.
  • 5.Noone AM, Howlader N, Krapcho M, Miller D, Brest A, Yu M, Ruhl J, Tatalovich Z, Mariotto A, Lewis DR, Chen HS, Feuer EJ, Cronin KA, editors. SEER Cancer Statistics Review, 1975–2015. Bethesda, MD: National Cancer Institute, https://seer.cancer.gov/csr/1975_2015/, based on November 2017 SEER data submission, posted to the SEER website, April 2018.
  • 6.Y Ma Y Sui L Wang H Li 2014 Effect of GSTM1 null genotype on risk of childhood acute leukemia: a meta-analysis Tumour Biol 35 1 397 402 [DOI] [PubMed] [Google Scholar]
  • 7.M Belson B Kingsley A Holmes 2007 Risk factors for acute leukemia in children: a review Environ Health Perspect 115 1 138 145 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.BS Shastry 2009 SNPs: impact on gene function and phenotype Methods Mol Biol (Clifton, NJ) 578 3 22 [DOI] [PubMed] [Google Scholar]
  • 9.JL Kurkewich J Hansen N Klopfenstein H Zhang C Wood A Boucher 2017 The miR-23a~27a~24-2 microRNA cluster buffers transcription and signaling pathways during hematopoiesis PLoS Genet 13 7 e1006887 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.A Molnár P Wu DA Largespada A Vortkamp S Scherer NG Copeland 1996 The Ikaros gene encodes a family of lymphocyte-restricted zinc finger DNA binding proteins, highly conserved in human and mouse J Immunol 156 2 585 592 [PubMed] [Google Scholar]
  • 11.M Stanulla H Cavé AV Moorman 2020 IKZF1 deletions in pediatric acute lymphoblastic leukemia: still a poor prognostic marker? Blood 135 4 252 260 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.T Yoshida SY Ng JC Zuniga-Pflucker K Georgopoulos 2006 Early hematopoietic lineage restrictions directed by Ikaros Nat Immunol 7 4 382 391 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.AY Lai M Kondo 2006 Asymmetrical lymphoid and myeloid lineage commitment in multipotent hematopoietic progenitors J Exp Med 203 8 1867 1873 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.SY Ng T Yoshida J Zhang K Georgopoulos 2009 Genome-wide lineage-specific transcriptional networks underscore Ikaros-dependent lymphoid priming in hematopoietic stem cells Immunity 30 4 493 507 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.CM Kelley T Ikeda J Koipally N Avitahl L Wu K Georgopoulos 1998 Helios, a novel dimerization partner of Ikaros expressed in the earliest hematopoietic progenitors Curr Biol 8 9 508 515 [DOI] [PubMed] [Google Scholar]
  • 16.CG Mullighan X Su J Zhang I Radtke LAA Phillips CB Miller 2009 Deletion of IKZF1 and prognosis in acute lymphoblastic leukemia New Engl J Med 360 5 470 480 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.K Georgopoulos 2009 Acute lymphoblastic leukemia — On the Wings of IKAROS New Engl J Med 360 5 524 526 [DOI] [PubMed] [Google Scholar]
  • 18.CG Mullighan S Goorha I Radtke CB Miller E Coustan-Smith JD Dalton 2007 Genome-wide analysis of genetic alterations in acute lymphoblastic leukaemia Nature 446 7137 758 764 [DOI] [PubMed] [Google Scholar]
  • 19.Jeannet R, Mastio J, Macias-Garcia A, Oravecz A, Ashworth T, Geimer Le Lay A-S, et al. Oncogenic activation of the Notch1 gene by deletion of its promoter in Ikaros-deficient T-ALL. Blood. 2010;116(25):5443–54. [DOI] [PMC free article] [PubMed]
  • 20.P Gómez-del Arco M Kashiwagi AF Jackson T Naito J Zhang F Liu 2010 Alternative promoter usage at the Notch1 locus supports ligand-independent signaling in T cell development and leukemogenesis Immunity 33 5 685 698 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.ML Churchman M Qian G Kronnie Te R Zhang W Yang H Zhang 2018 Germline genetic IKZF1 variation and predisposition to childhood acute lymphoblastic leukemia Cancer Cell 33 5 937 48.e8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.N Deng H Zhou H Fan Y Yuan 2017 Single nucleotide polymorphisms and cancer susceptibility Oncotarget 8 66 110635 110649 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Hubner R, Houlston R. Single nucleotide polymorphisms and cancer susceptibility. 2017. p. 231–9.
  • 24.G Bahari M Hashemi M Naderi M Taheri 2016 IKZF1 gene polymorphisms increased the risk of childhood acute lymphoblastic leukemia in an Iranian population Tumour Biol 37 7 9579 9586 [DOI] [PubMed] [Google Scholar]
  • 25.YY Shi L He 2005 SHEsis, a powerful software platform for analyses of linkage disequilibrium, haplotype construction, and genetic association at polymorphism loci Cell Res 15 2 97 98 [DOI] [PubMed] [Google Scholar]
  • 26.Bhattacharya A, Ziebarth JD, Cui Y. PolymiRTS Database 3.0: linking polymorphisms in microRNAs and their target sites with human diseases and biological pathways. Nucleic Acids Res. 2014;42(Database issue):D86–91. [DOI] [PMC free article] [PubMed]
  • 27.V Senadhi D Emuron R Gupta 2010 Acute hepatitis A induction of precursor B-cell acute lymphoblastic leukemia: a causal relationship? Case Rep Oncol 3 3 505 509 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.H Ma H Sun X Sun 2014 Survival improvement by decade of patients aged 0–14 years with acute lymphoblastic leukemia: a SEER analysis Sci Rep 4 1 4227 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.SP Hunger CG Mullighan 2015 Redefining ALL classification: toward detecting high-risk ALL and implementing precision medicine Blood 125 26 3977 3987 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.LM Vrooman LB Silverman 2016 Treatment of childhood acute lymphoblastic leukemia: prognostic factors and clinical advances Curr Hematol Malig Rep 11 5 385 394 [DOI] [PubMed] [Google Scholar]
  • 31.S Mahjoub V Chayeb H Zitouni RM Ghali H Regaieg WY Almawi 2019 IKZF1 genetic variants rs4132601 and rs11978267 and acute lymphoblastic leukemia risk in Tunisian children: a case-control study BMC Med Genet 20 1 159 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Y-E Dai L Tang J Healy D Sinnett 2014 Contribution of polymorphisms in IKZF1 gene to childhood acute leukemia: a meta-analysis of 33 case-control studies PLoS ONE 9 11 e113748 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.S Li L Ren L Fan G Wang 2015 IKZF1 rs4132601 polymorphism and acute lymphoblastic leukemia susceptibility: a meta-analysis Leuk Lymphoma 56 4 978 982 [DOI] [PubMed] [Google Scholar]
  • 34.J Rudant L Orsi A Bonaventure S Goujon-Bellec A Baruchel A Petit 2015 ARID5B, IKZF1 and non-genetic factors in the etiology of childhood acute lymphoblastic leukemia: the ESCALE study PLoS ONE 10 3 e0121348 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.CY Lin MJ Li JG Chang SC Liu T Weng KH Wu 2014 High-resolution melting analyses for genetic variants in ARID5B and IKZF1 with childhood acute lymphoblastic leukemia susceptibility loci in Taiwan Blood Cells Mol Dis 52 2–3 140 145 [DOI] [PubMed] [Google Scholar]
  • 36.P Górniak A Pastorczak B Zalewska-Szewczyk M Lejman J Trelińska M Chmielewska 2014 Polymorphism in IKZF1 gene affects age at onset of childhood acute lymphoblastic leukemia Leuk Lymphoma 55 9 2174 2178 [DOI] [PubMed] [Google Scholar]
  • 37.Papaemmanuil E, Hosking FJ, Vijayakrishnan J, Price A, Olver B, Sheridan E, et al. Loci on 7p12.2, 10q21.2 and 14q11.2 are associated with risk of childhood acute lymphoblastic leukemia. Nat Genet. 2009;41(9):1006–10. [DOI] [PMC free article] [PubMed]

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