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High-resolution melting analyses for genetic variants in ARID5B and IKZF1 with childhood acute lymphoblastic leukemia susceptibility loci in Taiwan
Blood Cells, Molecules and Diseases 52 (2014) 140–145
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High-resolution melting analyses for genetic variants in ARID5B and IKZF1 with childhood acute lymphoblastic leukemia susceptibility loci in Taiwan Chien-Yu Lin a,b, Meng-Ju Li c, Jan-Gowth Chang b,d,e, Su-Ching Liu f, Tefu Weng f, Kang-Hsi Wu f, Shu-Fen Yang b, Fu-Kuei Huang f, Wan-Yu Lo g,h,i,1, Ching-Tien Peng f,j,⁎,1 a
Graduate Institute of Clinical Medical Sciences, China Medical University, Taichung, Taiwan Department of Laboratory Medicine, China Medical University Hospital, Taichung, Taiwan c Department of Pediatrics, National Taiwan University Hospital Hsin-Chu Branch, Hsinchu, Taiwan d School of Medicine, China Medical University, Taichung, Taiwan e Epigenome Research Center, China Medical University Hospital, Taichung, Taiwan f Department of Pediatrics, Children's Hospital, China Medical University, Taichung, Taiwan g Division of Surgery, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan h Graduate Institute of Integrated Medicine, China Medical University, Taichung, Taiwan i Department of Life Science, National Chung Hsing University, Taichung, Taiwan j Department of Biotechnology, Asia University, Taichung, Taiwan b
a r t i c l e
i n f o
a b s t r a c t
Background: Childhood acute lymphoblastic leukemia (ALL), a heterogeneous disease that includes multiple subtypes is defined by cell lineage and chromosome anomalies. Previous genome-wide association studies have reported several ARID5B and IKZF1 single nucleotide polymorphisms (SNPs) associated with the incidence of ALL. High-resolution melting (HRM) analysis is a rapid and convenient technique to detect SNPs; we thereby detected SNPs in ARID5B and IKZF1 genes. (Communicated by M. Lichtman, M.D., 15 October 2013) Methods: We enrolled 79 pediatric ALL patients and 80 healthy controls. Polymorphic variants of IKZF1 (rs6964823, rs4132601, and rs6944602) and ARID5B (rs7073837, rs10740055, and rs7089424) were detected Keywords: by HRM, and SNPs were analyzed for association with childhood ALL. ARID5B Results: The distribution of genotype rs7073837 in ARID5B significantly differed between ALL and controls (P = Childhood acute lymphoblastic leukemia 0.046), while those of IKZF1 (rs6964823, rs4132601, and rs6944602) and ARID5B (rs10740055 and rs7089424) High-resolution melting analyses IKZF1 did not. We analyzed the association for SNPs with B lineage ALL to find rs7073837 in ARID5B, conferring a higher Single nucleotide polymorphisms risk for B lineage ALL (odds ratio, OR = 1.70, 95% confidence interval, CI = 1.01–2.87, P = 0.049). Conclusion: HRM is a practical method to detect SNPs in ARID5B and IKZF1 genes. We found that rs7073837 in ARID5B correlated with a risk for childhood B lineage ALL. © 2013 Elsevier Inc. All rights reserved. Article history: Submitted 25 September 2013 Revised 15 October 2013 Available online 5 November 2013
Introduction Acute lymphoblastic leukemia (ALL), the most common malignancy in children, is a heterogeneous disease, with respect to its underlying cellular and molecular biology, acquired genetic abnormalities, and associated clinical responses to combination chemotherapy [1]. Previous genome-wide association (GWA) studies show evidence of common germline variations that influence the risk of childhood ALL [2–4]. Papaemmanuil et al. [2], using single nucleotide polymorphism (SNP) array data from two large clinical studies, found that the most strongly ALL-associated loci were ARID5B and IKZF1. ⁎ Corresponding author at: Department of Pediatrics, Children's Hospital, China Medical University, No. 2 Yuh Der Road, Taichung, Taiwan. Fax: +886 4 22032798. E-mail address: [email protected] (C.-T. Peng). 1 Wan-Yu Lo and Ching-Tien Peng contributed equally to this article. 1079-9796/$ – see front matter © 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.bcmd.2013.10.003
AT-rich interactive domain 5B (ARID5B), belonging to the ARID family of transcription factors, plays an important role in the regulation of embryonic development and cell growth and differentiation [5–7]. Prior studies reported ARID5B SNPs (such as rs7073873, rs10740055, rs7089424, rs10821936, and rs10994982) to be strongly associated with the incidence of ALL [2,3,8–11] and several ARID5B SNPs to be associated with B-hyperdiploid ALL, which responds better to chemotherapy than other subtypes [2,3,10,12,13]. Ikaros zinc finger 1 (IKZF1), a DNA-binding zinc finger protein, is a vital hematopoietic transcription factor, particularly in the regulation of hematopoiesis of the lymphoid lineage [14], and it plays a pivotal role in the commitment of CD4 and CD8 T-cell lineages [15]. Previous studies have yielded robust evidence that IKZF1 acts as a tumor suppressor for childhood ALL; its loss is related to a dismal prognosis [16,17]. A functional basis for an association between rs4132601 and ALL emerged from the correlation between reduced IKZF1 expression
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Table 1 HRM primer sequence for IKZF1 and ARID5B genes. SNP (location) IKZF1 rs6964823 IKZF1 rs4132601 IKZF1 rs6944602 ARID5B rs7073837 ARID5B rs10740055 ARID5B rs7089424
Primer sequences
SNP sequence
F: 5′-ATTGCTGTTTTGCCTAATGCTCTGCGGGATTAAAAAAAAA-3′ R: 5′-CAATGCTCCTAGAGAGACGAATGGTCTTGTTCTTCTTCTT-3′
ANG
81
F: 5′-CCAATGCACTGAGTGAAGGA-3′ R: 5′-GGGATGGATGGAAAAGAACA-3′
ANC
176
F: 5′-AGCTTTCTTACTCATAAAACCGAGA-3′ R: 5′-CAGGTGGGCAAGTCTGTCTA-3′
GNA
100
F: 5′-CCAGAATGCACACAGTCTCC-3′ R: 5′-GTGGTTGGGGAAGAACAAAA-3′
CNA
125
F: 5′-GAAAGGCCTAGTCATCCCACT-3′ R: 5′-AACCACTATGCACTTATCGGAGA-3′
ANC
122
F: 5′-GGAGGTGGAGTTGGCTTTCT-3′ R: 5′-GCTTTTGCCCTCACTATTGC-3′
ANC
126
and risk genotype in lymphocytes [2]. Dysregulation of transcription factors can induce abnormal blood cell development and, eventually, leukemogenesis. SNPs located on 10q21.2 (ARID5B) and 7p12.2 (IKZF1) were noted to be related to childhood ALL, as well as to its subtypes and prognosis [2,3,8]. Several methods have been used to detect point mutations, including direct DNA sequencing, amplification refractory mutation systems (ARMS), pyrosequencing methods, PCR followed by restriction fragment length polymorphism (RFLP) gel electrophoresis, denaturing highperformance liquid chromatography (dHPLC), probe real-time PCR, and DNA melting-curve analysis [18–21]. Recently, high-resolution melting (HRM) analysis, a non-gel based, automated system, was introduced as a means of mutation scanning without the requirement of post-PCR handling. This simple method consists of PCR, followed by a short melting step and subsequent analysis [22]. It enables researchers to detect and categorize genetic mutations such as SNPs rapidly, to identify new genetic variants without sequencing (gene scanning), and to determine genetic variation in a population (viral diversity) prior to sequencing. To our knowledge, no previous study has dealt with HRM analysis for ARID5B and IKZF1 genes. In the present study, we applied this fast and convenient method to analyze SNPs in both genes.
DNA fragment size (bp)
HRM analysis Duplicate 10-μL PCR reactions were performed using 10 ng DNA and 1× LightCycler® 480 High-Resolution Melting Master buffer (reference 04909631001; Roche Diagnostics), containing Taq polymerase, nucleotides, and ResoLight dye. Primers and MgCl2 were used at a concentration of 2.5 mM to detect IKZF1 (rs6964823, rs4132601, and rs6944602) and ARID5B (rs7073837, rs10740055, and rs7089424) genes. HRM assays were conducted with a LightCycler® 480 Instrument (Roche Diagnostics), provided with LightCycler® 480 Gene Scanning Software version 1.5 (Roche Diagnostics). The PCR program required a SYBR Green I filter (533nm), and it consisted of an initial denaturation–activation step at 95 °C for 10 min, followed by a 45-cycle program (denaturation at 95 °C for 10 s, annealing at 60 °C 15 s, and elongation at 72 °C for 15 s, with a single acquisition mode for fluorescence signals). The melting program included denaturing at 95 °C for 1 min, annealing at 40 °C for 1 min, and subsequent melting that included a continuous fluorescent reading of fluorescence from 55 °C to 90 °C, at the rate of 25 acquisitions per degree Celsius. The shape and peak height of the plot curve of each DNA duplicate sample must be reproducible. To confirm the results of HRM analysis, sequencing analysis was also performed for all samples. Table 1 summarizes primer sequences and general information for each SNP.
Methods Statistical analysis Study population and sample collection A total of 79 pediatric patients (under 18 years old) diagnosed with ALL at the China Medical University Children's Hospital from 2005 to 2011 were recruited. All patients signed an informed consent prior to participation in the study and provided blood samples for genotyping. The research project was reviewed and approved by the Institutional Review Board of our hospital (DMR100-IRB-032).
Statistical analysis used SPSS version 13.0 (Chicago, IL). Pearson Chisquare or Fisher's exact test (for cells with expected frequency of less than five) was used to compare the distribution of each genotype between cases and controls. Association of genotypes with ALL was derived by unconditional logistic regression, and the results are presented as odds ratios (ORs) with 95% confidence intervals (CIs). A P-value b0.05 was considered as the cut-off value for significance. Results
DNA extraction DNA was extracted from leukocytes with a QIAamp DNA Blood Mini Kit (Qiagen). Approximately 10 mL of whole blood was used to prepare buffy coat cells by centrifugation at 3000 ×g for 10 min at room temperature. The leukocyte layer was collected, cells were lysed, and DNA was extracted according to the manufacturer's protocol. DNA samples were stored at −20 °C in DNAse- and RNAse-free distilled water until analysis.
Complete IKZF1 (rs6964823, rs4132601, and rs6944602) and ARID5B (rs7073837, rs10740055, and rs7089424) gene mutation screening required investigation of SNP mutation assays. We evaluated six PCR amplicons (81–176 bp) by using the 96-well LightCycler system and the same PCR conditions. Melting curve data showed a difference in normalized temperature-shifted data between mutated and normal samples. We easily and accurately extended HRM analysis to genotyping of IKZF1 and ARID5B gene variants. Known mutations (rs6964823,
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Fig. 1. A: SNPs in IKZF1 detected by HRM analysis. (a) rs6964823; (b) rs4132601; (c) rs6944602. B: SNPs in ARID5B detected by HRM analysis. (a) rs7073837; (b) rs10740055; (c) rs7089424.
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Table 2 Correlation between SNP genotype and risk of childhood ALL. Genotypes
IKZF1 rs6964823 ANG AA AG GG G allele rs4132601 ANC AA AC CC C allele rs6944602 GNA GG AG AA A allele ARID5B rs7073837 CNA CC AC AA A allele rs10740055 ANC AA AC CC C allele rs7089424 ANC AA AC CC C allele
Control (n = 80)
Cases (n = 79)
N
%
n
%
0 23 57 137
0 28.8 71.3 85.6
0 21 58 137
0 26.6 73.4 86.7
61 19 0 19
76.3 23.8 0 11.9
60 19 0 19
75.9 24.1 0 12
75 5 0 5
93.8 6.3 0 3.1
68 11 0 11
86.1 13.9 0 7
24 37 19 75
30 46.3 23.8 46.9
25 23 31 85
31.6 29.1 39.2 53.8
46 34 0 34
57.5 42.5 0 21.3
48 31 0 31
60.8 39.2 0 19.6
36 26 18 62
45 32.5 22.5 38.8
31 25 23 71
39.2 31.6 29.1 44.9
P-value
OR
B-ALL (n = 45)
(95% CI)
n
1.0 1.11 (0.56–2.23) 1.11 (0.58–2.07)
0 16 29 74
0 35.6 64.4 82.2
39 6 0 6
86.7 13.3 0 6.7
0.449
0.871 0.556
1.01 (0.52–1.10) 1.0 2.43 (0.80–7.34)
0.132
2.32 (0.79–6.84)
45 0 0 0
100 0 0 0
1.0 0.60 (0.28–1.28) 1.57 (0.70–3.49) 1.32 (0.85–2.05)
14 8 23 54
31.1 17.8 51.1 60
1.0 0.87 (0.46–1.65) 0.91 (0.52–1.56)
33 12 0 12
73.3 26.7 0 13.3
1.0 1.12 (0.54–2.32) 1.48 (0.68–3.24) 1.29 (0.83–2.02)
20 17 8 33
44.4 37.8 17.8 36.7
0.046*
0.220 0.399
0.781 0.608
0.306
OR (95% CI)
0.431
1.0 1.02 (0.49–2.11) 1.000 0.89
P-value
%
0.474 0.244
1.0 0.73 (0.34–1.59) 0.78 (0.39–1.56) 1.0 0.49 (0.18–1.35)
0.272 0.159
0.53 (0.20–1.38)
0.163
0.002*
0.049* 0.086
1.0 0.37 (0.14–1.02) 2.08 (0.85–5.09) 1.70 (1.01–2.87)* 1.0 0.49 (0.22–1.09)
0.13 0.762
0.787
0.57 (0.28–1.17) 1.0 1.18 (0.52–2.67) 0.80 (0.30–2.17) 0.92 (0.54–1.56)
Odds ratios (ORs) and 95% confidence intervals (CIs) calculated by logistic regression and by the Chi-square test or Fisher's exact test when the expected frequency for cells was less than five.
rs4132601, rs6944602, rs7073837, rs10740055, and rs7089424) served to assess sensitivity of the HRM method for mutation scanning (Figs. 1A–B). We also recruited 79 pediatric ALL patients and 80 healthy controls and screened for IKZF1 and ARID5B mutations according to our previously established method. Each mutation could be readily and accurately identified by difference plot curves (data not shown). Table 2 plots genotype distribution along with allelic frequencies of IKZF1 (rs6964823, rs4132601, and rs6944602) and ARID5B (rs7073837, rs10740055, and rs7089424) polymorphisms among cases and controls, as well as their association with risk for childhood ALL. The genotype distribution of ARID5B (rs7073837) proved statistically significant between cases and controls (P = 0.046), whereas those for IKZF1 (rs6964823, rs4132601, and rs6944602) and ARID5B (rs10740055 and rs7089424) genes did not. Overall, our data indicated that the ARID5B (rs7073837) homozygote A mutation was associated with an increased risk of childhood ALL. We further analyzed the association of these polymorphisms with the risk of childhood B lineage ALL (Table 2). The genotype distribution of ARID5B (rs7073837) was statistically significant between cases and controls (P = 0.002), whereas those for IKZF1 (rs6964823, rs4132601, and rs6944602) and ARID5B (rs10740055 and rs7089424) were not. Allelic frequency distributions of ARID5B (rs7073837) allele A were 60% and 46.9% in patient and control groups, respectively; subjects carrying the A allele had a 1.70-fold higher risk of developing B lineage ALL (OR = 1.70, 95% CI = 1.01– 2.87, P = 0.049). To summarize, an A allele at ARID5B (rs7073837) appeared to be associated with higher susceptibility for childhood B lineage ALL (Table 2).
Discussion HRM analysis is a feasible and powerful method for mutation scanning for sequence variants. In this study, the melting curve shape of HRM was clear, and HRM was a practical method for detecting SNPs in ARID5B and IKZF1 genes. We determined an association of SNP rs7073837 in ARID5B with a risk for childhood B lineage ALL; A allele carriers had a higher risk for B lineage ALL than did C homozygous carriers. We hypothesized that the A allele may be an independent predictive marker for childhood B lineage ALL. Our results suggest that this polymorphism in ARID5B would be a genetic susceptibility marker for ALL in the Taiwanese population. Previous GWA studies found the SNPs investigated in our study to be strongly associated with ALL risk in Caucasian populations [2,3,10,11]. Several research groups have reported an association between SNPs in the ARID5B and IKZF1 genes and ALL [8,9,23]. Compared to that study, we found the ARID5B rs7073837 genotypes to be marginally statistically significant associated with B lineage ALL (OR: 1.7, 95% CI: 1.007–2.87; P = 0.049). No association with ALL or with subgroup B lineage ALL was found for other SNPs. The difference in allelic frequency of rs7073837 in ARID5B between patient and control groups was small. Although marginally statistically significant, further experimentation is needed to clarify in large samples and undergo multiple comparison confirmation. Consistent with our findings, study groups in China and Korea reported no association of IKZF1 rs4132601 with ALL [8,23], whereas a Thai research group confirmed this association [9]. However, the Thai group found no association for ARID5B rs7089424 with ALL [9], consistent with our findings, whereas the Korean group found rs7089424 to
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be closely linked with rs7896246 in ARID5B and associated with ALL risk [23]. Inconsistencies may relate to the small sample size used in our study and differences between populations. Vijayakrishnan et al. [9] reported differences in allelic frequencies in SNPs observed between Thai and Caucasian populations (IKZF1, rs4132601; risk allele frequency [RAF] ratio of 0.36 for Thai/Caucasian). We hypothesize that the population differences in linkage disequilibrium (LD) patterns at these loci, which disrupt linkage between causal variants and tagging SNPs, are the reason for the observed differences in the results. Risk variants for ALL may thus confer different magnitudes of increased risk in different populations for a variety of reasons, such as allele frequency and LD structure and genetic and environmental backgrounds interacting with variants. Because of the newly found SNPs such as IKZF1 rs4132601, there is currently no LD pattern in HapMap [8]. Future systematic investigation of these and other risk loci will shed fresh light on the etiology of ALL within different populations. Zhang et al. [24] assessed performance indexes (accuracy, sensitivity, and specificity) of HRM, considering Sanger sequencing as the reference test, and HRM analysis gave excellent results. SNPs in our study all have a base exchange, between A::C and A::G. Homozygotes melted in a single transition, with the order of melting correctly predicted by nearest-neighbor calculations as A/A b T/T b C/C b G/G [25]. Heterozygotes produced complex melting curves, arising from contributions of two homoduplexes and two heteroduplexes [26]. The unique melting curve traced by each heterozygote occurred from the melting temperatures (Tm) of the four duplexes. The order of melting was again according to nearest-neighbor calculations (A/T b A/C b C/T b A/G b G/T b C/G) based on the mean of the two homoduplex Tms. The six heterozygote curves merged at high temperatures, into three traces, as predicted by the highest melting homoduplex present (T/T for A/T heterozygote, C/C for A/C and C/T heterozygotes, and G/G for A/G, G/T, and C/G heterozygotes). All genotypes were distinguished by high-resolution melting analysis [27]. Theoretically, approximately 84% of human SNPs involve a base exchange between A::T and G::C base pairs, and homozygotes are easily genotyped by Tms that differ by 0.8–1.4 °C. However, in approximately 16% of SNPs, the bases only switch strands and preserve the base pair, yielding very small Tm differences between homozygotes (b0.4 °C). Although most of these cases can be genotyped by Tm, onefourth (4% of total SNPs) show nearest-neighbor symmetry, and as predicted, homozygotes cannot be resolved from each other. In these cases, adding 15% of a known homozygous genotype to unknown samples allows melting curve separation of three genotypes [27]. Reed and Wittwer [28] reported that for PCR products of 300 bp or less, all 280 heterozygous and 296 wild-type cases were correctly called without error. However, when the PCR products increased to between 400 and 1000 bp, sensitivity and specificity decreased to 96.1% and 99.4%, respectively. We designed our protocol to generate PCR products of less than 300 bp and avoided the A/T heterozygote, which has previously been associated with false-negative results [28–30]. We believe this to be the reason for our successful HRM analysis, which worked well to reveal differences in melting curve shape that correlates with genotype and the presence of SNP. Another limitation of our study includes a lack of functional information. ARID5B plays a role in defining B-cell lineage, as supported by data from homozygous knockout mice that, in addition to a growth retardation phenotype, have decreased bone marrow cellularity and reduced numbers of B-cell progenitors [6]. Furthermore, it has been reported that ARID5B polymorphisms are important determinants of treatment outcome for childhood ALL [31]. Thus, we are collecting therapeutic information on our patients and conducting a long-term follow-up study to monitor the survival status and sequelae of each patient, in order to study the pivotal role of the rs7073837 polymorphism in predicting the prognosis of ALL patients. In conclusion, we successfully applied HRM to detect SNPs rs7073837, rs10740055, and rs7089424 in the ARID5B gene and SNPs rs6964823,
rs4132601, and rs6944602 in the IKZF1 gene. SNP rs7073837 in ARID5B is associated with childhood B lineage ALL and may serve as a potential biomarker for assessing the risk of childhood B lineage ALL in Taiwanese children. Conflicts of interest statement All authors have no conflict of interest. Acknowledgments This study was supported by the Research Laboratory of Pediatrics, Children's Hospital, China Medical University, and research grants from the Department of Health, Executive Yuan, ROC (DOH102-TD-C111-005), and the China Medical University Hospital (DMR-99-132). References [1] C.H. Pui, M.V. Relling, J.R. Downing, Acute lymphoblastic leukemia, N. Engl. J. Med. 350 (2004) 1535–1548. [2] E. Papaemmanuil, F.J. Hosking, J. Vijayakrishnan, et al., Loci on 7p12.2, 10q21.2 and 14q11.2 are associated with risk of childhood acute lymphoblastic leukemia, Nat. Genet. 41 (2009) 1006–1010. [3] L.R. Trevino, W. Yang, D. 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High-resolution melting analyses for genetic variants in ARID5B and IKZF1 with childhood acute lymphoblastic leukemia susceptibility loci in Taiwan Chien-Yu Lin a,b, Meng-Ju Li c, Jan-Gowth Chang b,d,e, Su-Ching Liu f, Tefu Weng f, Kang-Hsi Wu f, Shu-Fen Yang b, Fu-Kuei Huang f, Wan-Yu Lo g,h,i,1, Ching-Tien Peng f,j,⁎,1 a
Graduate Institute of Clinical Medical Sciences, China Medical University, Taichung, Taiwan Department of Laboratory Medicine, China Medical University Hospital, Taichung, Taiwan c Department of Pediatrics, National Taiwan University Hospital Hsin-Chu Branch, Hsinchu, Taiwan d School of Medicine, China Medical University, Taichung, Taiwan e Epigenome Research Center, China Medical University Hospital, Taichung, Taiwan f Department of Pediatrics, Children's Hospital, China Medical University, Taichung, Taiwan g Division of Surgery, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan h Graduate Institute of Integrated Medicine, China Medical University, Taichung, Taiwan i Department of Life Science, National Chung Hsing University, Taichung, Taiwan j Department of Biotechnology, Asia University, Taichung, Taiwan b
a r t i c l e
i n f o
a b s t r a c t
Background: Childhood acute lymphoblastic leukemia (ALL), a heterogeneous disease that includes multiple subtypes is defined by cell lineage and chromosome anomalies. Previous genome-wide association studies have reported several ARID5B and IKZF1 single nucleotide polymorphisms (SNPs) associated with the incidence of ALL. High-resolution melting (HRM) analysis is a rapid and convenient technique to detect SNPs; we thereby detected SNPs in ARID5B and IKZF1 genes. (Communicated by M. Lichtman, M.D., 15 October 2013) Methods: We enrolled 79 pediatric ALL patients and 80 healthy controls. Polymorphic variants of IKZF1 (rs6964823, rs4132601, and rs6944602) and ARID5B (rs7073837, rs10740055, and rs7089424) were detected Keywords: by HRM, and SNPs were analyzed for association with childhood ALL. ARID5B Results: The distribution of genotype rs7073837 in ARID5B significantly differed between ALL and controls (P = Childhood acute lymphoblastic leukemia 0.046), while those of IKZF1 (rs6964823, rs4132601, and rs6944602) and ARID5B (rs10740055 and rs7089424) High-resolution melting analyses IKZF1 did not. We analyzed the association for SNPs with B lineage ALL to find rs7073837 in ARID5B, conferring a higher Single nucleotide polymorphisms risk for B lineage ALL (odds ratio, OR = 1.70, 95% confidence interval, CI = 1.01–2.87, P = 0.049). Conclusion: HRM is a practical method to detect SNPs in ARID5B and IKZF1 genes. We found that rs7073837 in ARID5B correlated with a risk for childhood B lineage ALL. © 2013 Elsevier Inc. All rights reserved. Article history: Submitted 25 September 2013 Revised 15 October 2013 Available online 5 November 2013
Introduction Acute lymphoblastic leukemia (ALL), the most common malignancy in children, is a heterogeneous disease, with respect to its underlying cellular and molecular biology, acquired genetic abnormalities, and associated clinical responses to combination chemotherapy [1]. Previous genome-wide association (GWA) studies show evidence of common germline variations that influence the risk of childhood ALL [2–4]. Papaemmanuil et al. [2], using single nucleotide polymorphism (SNP) array data from two large clinical studies, found that the most strongly ALL-associated loci were ARID5B and IKZF1. ⁎ Corresponding author at: Department of Pediatrics, Children's Hospital, China Medical University, No. 2 Yuh Der Road, Taichung, Taiwan. Fax: +886 4 22032798. E-mail address: [email protected] (C.-T. Peng). 1 Wan-Yu Lo and Ching-Tien Peng contributed equally to this article. 1079-9796/$ – see front matter © 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.bcmd.2013.10.003
AT-rich interactive domain 5B (ARID5B), belonging to the ARID family of transcription factors, plays an important role in the regulation of embryonic development and cell growth and differentiation [5–7]. Prior studies reported ARID5B SNPs (such as rs7073873, rs10740055, rs7089424, rs10821936, and rs10994982) to be strongly associated with the incidence of ALL [2,3,8–11] and several ARID5B SNPs to be associated with B-hyperdiploid ALL, which responds better to chemotherapy than other subtypes [2,3,10,12,13]. Ikaros zinc finger 1 (IKZF1), a DNA-binding zinc finger protein, is a vital hematopoietic transcription factor, particularly in the regulation of hematopoiesis of the lymphoid lineage [14], and it plays a pivotal role in the commitment of CD4 and CD8 T-cell lineages [15]. Previous studies have yielded robust evidence that IKZF1 acts as a tumor suppressor for childhood ALL; its loss is related to a dismal prognosis [16,17]. A functional basis for an association between rs4132601 and ALL emerged from the correlation between reduced IKZF1 expression
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Table 1 HRM primer sequence for IKZF1 and ARID5B genes. SNP (location) IKZF1 rs6964823 IKZF1 rs4132601 IKZF1 rs6944602 ARID5B rs7073837 ARID5B rs10740055 ARID5B rs7089424
Primer sequences
SNP sequence
F: 5′-ATTGCTGTTTTGCCTAATGCTCTGCGGGATTAAAAAAAAA-3′ R: 5′-CAATGCTCCTAGAGAGACGAATGGTCTTGTTCTTCTTCTT-3′
ANG
81
F: 5′-CCAATGCACTGAGTGAAGGA-3′ R: 5′-GGGATGGATGGAAAAGAACA-3′
ANC
176
F: 5′-AGCTTTCTTACTCATAAAACCGAGA-3′ R: 5′-CAGGTGGGCAAGTCTGTCTA-3′
GNA
100
F: 5′-CCAGAATGCACACAGTCTCC-3′ R: 5′-GTGGTTGGGGAAGAACAAAA-3′
CNA
125
F: 5′-GAAAGGCCTAGTCATCCCACT-3′ R: 5′-AACCACTATGCACTTATCGGAGA-3′
ANC
122
F: 5′-GGAGGTGGAGTTGGCTTTCT-3′ R: 5′-GCTTTTGCCCTCACTATTGC-3′
ANC
126
and risk genotype in lymphocytes [2]. Dysregulation of transcription factors can induce abnormal blood cell development and, eventually, leukemogenesis. SNPs located on 10q21.2 (ARID5B) and 7p12.2 (IKZF1) were noted to be related to childhood ALL, as well as to its subtypes and prognosis [2,3,8]. Several methods have been used to detect point mutations, including direct DNA sequencing, amplification refractory mutation systems (ARMS), pyrosequencing methods, PCR followed by restriction fragment length polymorphism (RFLP) gel electrophoresis, denaturing highperformance liquid chromatography (dHPLC), probe real-time PCR, and DNA melting-curve analysis [18–21]. Recently, high-resolution melting (HRM) analysis, a non-gel based, automated system, was introduced as a means of mutation scanning without the requirement of post-PCR handling. This simple method consists of PCR, followed by a short melting step and subsequent analysis [22]. It enables researchers to detect and categorize genetic mutations such as SNPs rapidly, to identify new genetic variants without sequencing (gene scanning), and to determine genetic variation in a population (viral diversity) prior to sequencing. To our knowledge, no previous study has dealt with HRM analysis for ARID5B and IKZF1 genes. In the present study, we applied this fast and convenient method to analyze SNPs in both genes.
DNA fragment size (bp)
HRM analysis Duplicate 10-μL PCR reactions were performed using 10 ng DNA and 1× LightCycler® 480 High-Resolution Melting Master buffer (reference 04909631001; Roche Diagnostics), containing Taq polymerase, nucleotides, and ResoLight dye. Primers and MgCl2 were used at a concentration of 2.5 mM to detect IKZF1 (rs6964823, rs4132601, and rs6944602) and ARID5B (rs7073837, rs10740055, and rs7089424) genes. HRM assays were conducted with a LightCycler® 480 Instrument (Roche Diagnostics), provided with LightCycler® 480 Gene Scanning Software version 1.5 (Roche Diagnostics). The PCR program required a SYBR Green I filter (533nm), and it consisted of an initial denaturation–activation step at 95 °C for 10 min, followed by a 45-cycle program (denaturation at 95 °C for 10 s, annealing at 60 °C 15 s, and elongation at 72 °C for 15 s, with a single acquisition mode for fluorescence signals). The melting program included denaturing at 95 °C for 1 min, annealing at 40 °C for 1 min, and subsequent melting that included a continuous fluorescent reading of fluorescence from 55 °C to 90 °C, at the rate of 25 acquisitions per degree Celsius. The shape and peak height of the plot curve of each DNA duplicate sample must be reproducible. To confirm the results of HRM analysis, sequencing analysis was also performed for all samples. Table 1 summarizes primer sequences and general information for each SNP.
Methods Statistical analysis Study population and sample collection A total of 79 pediatric patients (under 18 years old) diagnosed with ALL at the China Medical University Children's Hospital from 2005 to 2011 were recruited. All patients signed an informed consent prior to participation in the study and provided blood samples for genotyping. The research project was reviewed and approved by the Institutional Review Board of our hospital (DMR100-IRB-032).
Statistical analysis used SPSS version 13.0 (Chicago, IL). Pearson Chisquare or Fisher's exact test (for cells with expected frequency of less than five) was used to compare the distribution of each genotype between cases and controls. Association of genotypes with ALL was derived by unconditional logistic regression, and the results are presented as odds ratios (ORs) with 95% confidence intervals (CIs). A P-value b0.05 was considered as the cut-off value for significance. Results
DNA extraction DNA was extracted from leukocytes with a QIAamp DNA Blood Mini Kit (Qiagen). Approximately 10 mL of whole blood was used to prepare buffy coat cells by centrifugation at 3000 ×g for 10 min at room temperature. The leukocyte layer was collected, cells were lysed, and DNA was extracted according to the manufacturer's protocol. DNA samples were stored at −20 °C in DNAse- and RNAse-free distilled water until analysis.
Complete IKZF1 (rs6964823, rs4132601, and rs6944602) and ARID5B (rs7073837, rs10740055, and rs7089424) gene mutation screening required investigation of SNP mutation assays. We evaluated six PCR amplicons (81–176 bp) by using the 96-well LightCycler system and the same PCR conditions. Melting curve data showed a difference in normalized temperature-shifted data between mutated and normal samples. We easily and accurately extended HRM analysis to genotyping of IKZF1 and ARID5B gene variants. Known mutations (rs6964823,
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Fig. 1. A: SNPs in IKZF1 detected by HRM analysis. (a) rs6964823; (b) rs4132601; (c) rs6944602. B: SNPs in ARID5B detected by HRM analysis. (a) rs7073837; (b) rs10740055; (c) rs7089424.
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Table 2 Correlation between SNP genotype and risk of childhood ALL. Genotypes
IKZF1 rs6964823 ANG AA AG GG G allele rs4132601 ANC AA AC CC C allele rs6944602 GNA GG AG AA A allele ARID5B rs7073837 CNA CC AC AA A allele rs10740055 ANC AA AC CC C allele rs7089424 ANC AA AC CC C allele
Control (n = 80)
Cases (n = 79)
N
%
n
%
0 23 57 137
0 28.8 71.3 85.6
0 21 58 137
0 26.6 73.4 86.7
61 19 0 19
76.3 23.8 0 11.9
60 19 0 19
75.9 24.1 0 12
75 5 0 5
93.8 6.3 0 3.1
68 11 0 11
86.1 13.9 0 7
24 37 19 75
30 46.3 23.8 46.9
25 23 31 85
31.6 29.1 39.2 53.8
46 34 0 34
57.5 42.5 0 21.3
48 31 0 31
60.8 39.2 0 19.6
36 26 18 62
45 32.5 22.5 38.8
31 25 23 71
39.2 31.6 29.1 44.9
P-value
OR
B-ALL (n = 45)
(95% CI)
n
1.0 1.11 (0.56–2.23) 1.11 (0.58–2.07)
0 16 29 74
0 35.6 64.4 82.2
39 6 0 6
86.7 13.3 0 6.7
0.449
0.871 0.556
1.01 (0.52–1.10) 1.0 2.43 (0.80–7.34)
0.132
2.32 (0.79–6.84)
45 0 0 0
100 0 0 0
1.0 0.60 (0.28–1.28) 1.57 (0.70–3.49) 1.32 (0.85–2.05)
14 8 23 54
31.1 17.8 51.1 60
1.0 0.87 (0.46–1.65) 0.91 (0.52–1.56)
33 12 0 12
73.3 26.7 0 13.3
1.0 1.12 (0.54–2.32) 1.48 (0.68–3.24) 1.29 (0.83–2.02)
20 17 8 33
44.4 37.8 17.8 36.7
0.046*
0.220 0.399
0.781 0.608
0.306
OR (95% CI)
0.431
1.0 1.02 (0.49–2.11) 1.000 0.89
P-value
%
0.474 0.244
1.0 0.73 (0.34–1.59) 0.78 (0.39–1.56) 1.0 0.49 (0.18–1.35)
0.272 0.159
0.53 (0.20–1.38)
0.163
0.002*
0.049* 0.086
1.0 0.37 (0.14–1.02) 2.08 (0.85–5.09) 1.70 (1.01–2.87)* 1.0 0.49 (0.22–1.09)
0.13 0.762
0.787
0.57 (0.28–1.17) 1.0 1.18 (0.52–2.67) 0.80 (0.30–2.17) 0.92 (0.54–1.56)
Odds ratios (ORs) and 95% confidence intervals (CIs) calculated by logistic regression and by the Chi-square test or Fisher's exact test when the expected frequency for cells was less than five.
rs4132601, rs6944602, rs7073837, rs10740055, and rs7089424) served to assess sensitivity of the HRM method for mutation scanning (Figs. 1A–B). We also recruited 79 pediatric ALL patients and 80 healthy controls and screened for IKZF1 and ARID5B mutations according to our previously established method. Each mutation could be readily and accurately identified by difference plot curves (data not shown). Table 2 plots genotype distribution along with allelic frequencies of IKZF1 (rs6964823, rs4132601, and rs6944602) and ARID5B (rs7073837, rs10740055, and rs7089424) polymorphisms among cases and controls, as well as their association with risk for childhood ALL. The genotype distribution of ARID5B (rs7073837) proved statistically significant between cases and controls (P = 0.046), whereas those for IKZF1 (rs6964823, rs4132601, and rs6944602) and ARID5B (rs10740055 and rs7089424) genes did not. Overall, our data indicated that the ARID5B (rs7073837) homozygote A mutation was associated with an increased risk of childhood ALL. We further analyzed the association of these polymorphisms with the risk of childhood B lineage ALL (Table 2). The genotype distribution of ARID5B (rs7073837) was statistically significant between cases and controls (P = 0.002), whereas those for IKZF1 (rs6964823, rs4132601, and rs6944602) and ARID5B (rs10740055 and rs7089424) were not. Allelic frequency distributions of ARID5B (rs7073837) allele A were 60% and 46.9% in patient and control groups, respectively; subjects carrying the A allele had a 1.70-fold higher risk of developing B lineage ALL (OR = 1.70, 95% CI = 1.01– 2.87, P = 0.049). To summarize, an A allele at ARID5B (rs7073837) appeared to be associated with higher susceptibility for childhood B lineage ALL (Table 2).
Discussion HRM analysis is a feasible and powerful method for mutation scanning for sequence variants. In this study, the melting curve shape of HRM was clear, and HRM was a practical method for detecting SNPs in ARID5B and IKZF1 genes. We determined an association of SNP rs7073837 in ARID5B with a risk for childhood B lineage ALL; A allele carriers had a higher risk for B lineage ALL than did C homozygous carriers. We hypothesized that the A allele may be an independent predictive marker for childhood B lineage ALL. Our results suggest that this polymorphism in ARID5B would be a genetic susceptibility marker for ALL in the Taiwanese population. Previous GWA studies found the SNPs investigated in our study to be strongly associated with ALL risk in Caucasian populations [2,3,10,11]. Several research groups have reported an association between SNPs in the ARID5B and IKZF1 genes and ALL [8,9,23]. Compared to that study, we found the ARID5B rs7073837 genotypes to be marginally statistically significant associated with B lineage ALL (OR: 1.7, 95% CI: 1.007–2.87; P = 0.049). No association with ALL or with subgroup B lineage ALL was found for other SNPs. The difference in allelic frequency of rs7073837 in ARID5B between patient and control groups was small. Although marginally statistically significant, further experimentation is needed to clarify in large samples and undergo multiple comparison confirmation. Consistent with our findings, study groups in China and Korea reported no association of IKZF1 rs4132601 with ALL [8,23], whereas a Thai research group confirmed this association [9]. However, the Thai group found no association for ARID5B rs7089424 with ALL [9], consistent with our findings, whereas the Korean group found rs7089424 to
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be closely linked with rs7896246 in ARID5B and associated with ALL risk [23]. Inconsistencies may relate to the small sample size used in our study and differences between populations. Vijayakrishnan et al. [9] reported differences in allelic frequencies in SNPs observed between Thai and Caucasian populations (IKZF1, rs4132601; risk allele frequency [RAF] ratio of 0.36 for Thai/Caucasian). We hypothesize that the population differences in linkage disequilibrium (LD) patterns at these loci, which disrupt linkage between causal variants and tagging SNPs, are the reason for the observed differences in the results. Risk variants for ALL may thus confer different magnitudes of increased risk in different populations for a variety of reasons, such as allele frequency and LD structure and genetic and environmental backgrounds interacting with variants. Because of the newly found SNPs such as IKZF1 rs4132601, there is currently no LD pattern in HapMap [8]. Future systematic investigation of these and other risk loci will shed fresh light on the etiology of ALL within different populations. Zhang et al. [24] assessed performance indexes (accuracy, sensitivity, and specificity) of HRM, considering Sanger sequencing as the reference test, and HRM analysis gave excellent results. SNPs in our study all have a base exchange, between A::C and A::G. Homozygotes melted in a single transition, with the order of melting correctly predicted by nearest-neighbor calculations as A/A b T/T b C/C b G/G [25]. Heterozygotes produced complex melting curves, arising from contributions of two homoduplexes and two heteroduplexes [26]. The unique melting curve traced by each heterozygote occurred from the melting temperatures (Tm) of the four duplexes. The order of melting was again according to nearest-neighbor calculations (A/T b A/C b C/T b A/G b G/T b C/G) based on the mean of the two homoduplex Tms. The six heterozygote curves merged at high temperatures, into three traces, as predicted by the highest melting homoduplex present (T/T for A/T heterozygote, C/C for A/C and C/T heterozygotes, and G/G for A/G, G/T, and C/G heterozygotes). All genotypes were distinguished by high-resolution melting analysis [27]. Theoretically, approximately 84% of human SNPs involve a base exchange between A::T and G::C base pairs, and homozygotes are easily genotyped by Tms that differ by 0.8–1.4 °C. However, in approximately 16% of SNPs, the bases only switch strands and preserve the base pair, yielding very small Tm differences between homozygotes (b0.4 °C). Although most of these cases can be genotyped by Tm, onefourth (4% of total SNPs) show nearest-neighbor symmetry, and as predicted, homozygotes cannot be resolved from each other. In these cases, adding 15% of a known homozygous genotype to unknown samples allows melting curve separation of three genotypes [27]. Reed and Wittwer [28] reported that for PCR products of 300 bp or less, all 280 heterozygous and 296 wild-type cases were correctly called without error. However, when the PCR products increased to between 400 and 1000 bp, sensitivity and specificity decreased to 96.1% and 99.4%, respectively. We designed our protocol to generate PCR products of less than 300 bp and avoided the A/T heterozygote, which has previously been associated with false-negative results [28–30]. We believe this to be the reason for our successful HRM analysis, which worked well to reveal differences in melting curve shape that correlates with genotype and the presence of SNP. Another limitation of our study includes a lack of functional information. ARID5B plays a role in defining B-cell lineage, as supported by data from homozygous knockout mice that, in addition to a growth retardation phenotype, have decreased bone marrow cellularity and reduced numbers of B-cell progenitors [6]. Furthermore, it has been reported that ARID5B polymorphisms are important determinants of treatment outcome for childhood ALL [31]. Thus, we are collecting therapeutic information on our patients and conducting a long-term follow-up study to monitor the survival status and sequelae of each patient, in order to study the pivotal role of the rs7073837 polymorphism in predicting the prognosis of ALL patients. In conclusion, we successfully applied HRM to detect SNPs rs7073837, rs10740055, and rs7089424 in the ARID5B gene and SNPs rs6964823,
rs4132601, and rs6944602 in the IKZF1 gene. SNP rs7073837 in ARID5B is associated with childhood B lineage ALL and may serve as a potential biomarker for assessing the risk of childhood B lineage ALL in Taiwanese children. Conflicts of interest statement All authors have no conflict of interest. Acknowledgments This study was supported by the Research Laboratory of Pediatrics, Children's Hospital, China Medical University, and research grants from the Department of Health, Executive Yuan, ROC (DOH102-TD-C111-005), and the China Medical University Hospital (DMR-99-132). References [1] C.H. Pui, M.V. Relling, J.R. Downing, Acute lymphoblastic leukemia, N. Engl. J. Med. 350 (2004) 1535–1548. [2] E. Papaemmanuil, F.J. Hosking, J. Vijayakrishnan, et al., Loci on 7p12.2, 10q21.2 and 14q11.2 are associated with risk of childhood acute lymphoblastic leukemia, Nat. Genet. 41 (2009) 1006–1010. [3] L.R. Trevino, W. Yang, D. 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