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Clinical Chemistry 53: 1585-1592, 2007. First published July 18, 2007; 10.1373/clinchem.2007.088146
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(Clinical Chemistry. 2007;53:1585-1592.)
© 2007 American Association for Clinical Chemistry, Inc.

Molecular Diagnostics and Genetics

Polymorphisms within the Protein Tyrosine Phosphatase 1B (PTPN1) Gene Promoter: Functional Characterization and Association with Type 2 Diabetes and Related Metabolic Traits

Reza Meshkani1,2, Mohammad Taghikhani3, Hussam Al-Kateb4, Bagher Larijani5, Shohreh Khatami6, Gus Konstantinos Sidiropoulos2, Robert Alexander Hegele7 and Khosrow Adeli2,a

1 Department of Biochemistry, Faculty of Medicine, Tehran University of Medical Sciences, Tehran, I.R. Iran.
2 Division of Clinical Biochemistry, Department of Pediatric Laboratory Medicine, Hospital for Sick Children, University of Toronto, Ontario, Canada.
3 Department of Clinical Biochemistry, Faculty of Medical Sciences, Tarbiat Modarres University, Tehran, I.R. Iran.
4 Program in Genetics and Genomic Biology, Hospital for Sick Children, University of Toronto, Ontario, Canada.
5 Endocrinology and Metabolism Research Centre, Shariati Hospital, Tehran University of Medical Sciences, Tehran, I.R. Iran.
6 Department of Biochemistry, Institute Pasteur of Iran, Tehran, I.R. Iran.
7 Robarts Research Institute and University of Western Ontario, London, Ontario, Canada.

aAddress correspondence to this author at: Division of Clinical Biochemistry, DPLM, Hospital for Sick Children, University of Toronto, Toronto, Ontario, M5G 1X8 Canada. Fax 416-813-6257; e-mail khosrow.adeli{at}sickkids.ca.


   Abstract
Top
 Abstract
Introduction
 Patients and Methods
 Results
 Discussion
 References
 
Background: Protein tyrosine phosphatase 1B (PTPN1) dephosphorylates insulin receptors and attenuates insulin signaling. Polymorphisms in the coding sequence of PTPN1 have been variably associated with type 2 diabetes (T2D). We hypothesized that variations within the PTPN1 promoter might contribute to the development of T2D and related metabolic traits.

Methods: We screened 2.0 kb of PTPN1 promoter in 174 T2D patients and 412 controls using PCR and denaturing HPLC. Association analysis was performed between diabetes and related traits and single-nucleotide polymorphism genotypes. We functionally tested 2 variants (–1023C>A and –51delA) by measuring their influence on luciferase activity in HepG2 cells and performing the electrophoretic mobility shift assay (EMSA).

Results: One common (–1023C>A) and 6 rare (–51delA, –451A>G, –467T>C, –1045G>A, –1286-3bp-del, and –1291-9bp-del) variants were identified in the PTPN1 promoter. The –1023(C) allele had significant association with T2D that disappeared after we adjusted for established diabetes risk factors. The alleles of –1023C>A and –51delA variants did not show significant effects on the biochemical markers after adjustment for established diabetes risk factors in the nondiabetic and diabetic groups separately. The –51delA variant decreased luciferase gene expression in HepG2 cells by 2-fold. EMSA revealed a weaker binding of –51delA to specific protein family proteins compared with the A allele. The –1023C>A variant had no influence in either experiment.

Conclusions: The PTPN1 promoter variants –1023C>A and –51delA (which appears to be functional) were not associated with T2D or related traits in this study but must be investigated in a larger population to reveal any potential metabolic association.


   Introduction
Top
 Abstract
 Introduction
Patients and Methods
 Results
 Discussion
 References
 
Type 2 diabetes (T2D) 1 is a heterogeneous disorder that results from a combination of environmental and genetic factors (1), which contribute to its pathogenesis by influencing ß-cell function and tissue insulin sensitivity (2)(3)(4). Insulin resistance (IR) is the core defect in T2D (5). The molecular mechanisms underlying IR are poorly understood but appear to include defects in the signal transduction pathway downstream of the insulin receptor (6). Protein tyrosine kinases and protein tyrosine phosphatases are important regulators of insulin signal transduction. Recently, much attention has been directed toward protein tyrosine phosphatase, nonreceptor type 1 (PTPN1), 2 which negatively regulates the phosphorylation of insulin receptor and insulin receptor substrates (7)(8).

Several studies investigated the association of PTPN1 single-nucleotide polymorphisms (SNPs) with traits related to T2D. Mok et al. (9) reported an association between an SNP in exon 8 and impaired glucose tolerance and T2D in Canadian aboriginal individuals. Similarly, Echwald et al. (10) observed an association of a coding SNP (P387L) with T2D in Danes. Di Paola et al. (11) identified a nucleotide insertion in the 3' untranslated region (UTR) that was associated with IR in obese individuals. Bento et al. (12) and Palmer et al. (13) investigated common variants in PTPN1 and found association with T2D and IR. Olivier et al. (14) observed a strong association between common haplotypes and hypertension, and also between individual SNPs and lipids and obesity, in Japanese and Chinese individuals. Florez et al. (15) studied 42 SNPs spanning 112 kb and selected partly from the HapMap Phase I database and partly from those previously studied but found no association between selected tag SNPs or haplotypes and T2D or diabetic phenotypes.

Human studies have demonstrated that PTPN1 expression increases in obese individuals and those with T2D (16)(17). The effect of genetic variations on gene expression is one of the most likely mechanisms by which such variations can contribute to complex diseases such as T2D; obviously, gene promoter regions are the best targets to look for variations that affect gene expression and contribute to traits in health and disease. Few efforts have been made to identify variants within the PTPN1 promoter region and investigate their relationships with T2D and its related traits. In the present study, we hypothesized that variants in the PTPN1 promoter region not previously studied, identified, or well captured by variants available on HapMap Project Phase I (18) or in Phase II (release 19) at the r2 = 0.8 cutoff might affect T2D and related traits.


   Patients and Methods
Top
 Abstract
 Introduction
 Patients and Methods
Results
 Discussion
 References
 
study participants
We initially recruited 639 unrelated Iranian individuals ages 23 to 79 years. After excluding 43 individuals with abnormal glucose tolerance based on the WHO 1997 criteria (19) and 12 diabetic patients who were being treated with insulin, we performed genetic association analysis on 412 nondiabetic and 174 diabetic individuals. Written informed consent was obtained from all participants before enrollment in the study.

A detailed description of the study population has been published (20). Screening included standardized questionnaires on personal data and clinical measurements such as age, sex, obesity, drug consumption during the past month, and medical or family history of diabetes. All those who were not taking diabetes medication underwent a 2-h oral glucose tolerance test (OGTT) after an overnight fast. Criteria for control selection was fasting glucose <6.1 mmol/L and 2-h plasma glucose <7.8 mmol/L after OGTT. Diabetes was defined as fasting glucose ≥7.0 mmol/L, 2-h glucose ≥11/1 mmol/L after OGTT, or use of hypoglycemic medication.

laboratory measurements
Blood samples were taken at 0 and 120 min. We measured glucose, total cholesterol, triglycerides, and HDL cholesterol using enzymatic methods on the Technicon® analyzer RATM 1000 (Technicon Instruments). We measured serum concentrations of insulin by RIA (BioSource Europe).

classification criteria
IR was assessed from glucose and insulin concentrations by use of the homeostasis model assessment of IR (HOMA-IR) equation (21). Hypertension was defined as systolic blood pressure ≥85 mmHg, diastolic blood pressure ≥130 mmHg, or use of antihypertensive medication; parental history of diabetes was based on self-reported diabetes in one or both parents (22).

variation detection
We screened variations by PCR and denaturing HPLC and confirmed them by direct sequencing. We used 8 sets of primers to amplify overlapping regions of the PTPN1 promoter from chromosome 20:48 558 283 to 48 560 496, corresponding to –2044 to +169 of the transcription start site. Primer sequences and PCR conditions are listed in Table 1 . We performed initial screening on genomic DNA of 100 patients with T2D and 100 nondiabetic individuals (400 chromosomes in total) by denaturing HPLC using a Transgenomic WAVE HT DNA Fragment Analysis System (Transgenomic, Inc.). We confirmed all variants identified by denaturing HPLC by sequencing in both directions.


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  		Table 1. Nucleotide sequence of DNA primers used for PCR amplification of 8 fragments of the PTPN1promoter.

genotyping
We performed genotyping with either PCR-RFLP or denaturing HPLC. Genotyping of the –467T>C variant was carried out by PCR amplification of a 269-bp segment using the following primers: forward, 5'-TTC ATT CCT GCA GCA CCC AAG-3', and reverse, 5'-GTT GAG TCA CAG AGT GAG TGG-3'. The rare variant creates a restriction site (RS) for the AvaI enzyme, which cuts the PCR amplicon into 163 and 106 bp for a homozygous variant and 269, 163, and 106 bp for a heterozygote. For genotyping –1023C>A SNP, genomic DNA was PCR-amplified using the following primers: forward, 5'-TAG CAG AAA CCG AGT TTC ACC-3', and reverse, 5'-CCT GGG TAA CAG AAT CAG ACC-3'. The SNP creates an RS for BclI, which cuts the 312-bp PCR amplicon into 249- and 63-bp fragments for variant homozygote. The –1045G>A was genotyped with mismatch PCR-RFLP. Briefly, the PTPN1 promoter was amplified using a forward primer (5'-TCT GTT GAG ACC CTA ATG CCA GAA-3') and a mutagenic reverse primer (5'-GGA TCA CCT GAG GTC AAG AGgC-3'). For the latter, a T>G substitution was engineered at the penultimate primer base (shown above in lowercase). The presence of G at the variant position then created an artificial RS for BsuRI within the amplicon. The expected products after the digestion of the 268-bp amplicon with BsuRI were 268 bp for a wild-type homozygote; 245 and 23 bp for a variant homozygote; and 268, 245, and 23 bp for a heterozygote. Denaturing HPLC was used to genotype the –51delA, –451A>G, 3-bp insertion-deletion, and 9-bp insertion-deletion variants. To identify the homozygotes for these polymorphisms, aliquots of a known wild-type sample were pooled with the unknown DNA samples before the reannealing step to enable heteroduplex formation before injection into denaturing HPLC.

genotyping of the –1023c>a in hapmap samples
The –1023C>A was genotyped in 90 HapMap Centre d’Étude du Polymorphisme Humain samples. We added the genotypes to those of HapMap samples (Phase II, release 19, 2005) for all markers in a 200-kb interval encompassing the PTPN1 gene. We used Haploview software (23) to produce the linkage disequilibrium (LD) structure.

cell culture
We obtained HepG2 cells from ATCC and cultured at 37 °C under 5% CO2 in DMEM (Gibco-BRL) supplemented with 10% fetal calf serum and 100 000 units/L penicillin/streptomycin.

transfection and luciferase reporter assay
We prepared 4 constructs from human genomic DNA obtained from participants with the –1023C>A and –51delA genotypes. The oligonucleotides spanned the DNA sequence from –1100 (from the transcription start site) to +169 bp for –1023C>A and from –545 to +169 bp for –51delA. We introduced the HindIII and XhoI sites at the ends of the PCR products that were cloned into the PGL3-Basic vector (Promega) after subcloning to the pcR2.1 TOPO. The sequences of the primers used are listed in Table 1 in the Data Supplement that accompanies the online version of this article at http://www.clinchem.org/content/vol53/issue9. We transiently transfected HepG2 cells with 1-µg constructs using Fugene6. Ten hours after transfection, we treated the cells with 5.5 or 22.5 mmol/L glucose and 100 nmol/L insulin. Forty-eight hours posttransfection, we carried out the luciferase assay using the Dual-Luciferase Reporter Assay System (Promega). To control transfection efficiency, we mixed 0.25 µg pRL-TK plasmid (Renilla luciferase under control of TK promoter; Promega) with experimental DNA. We performed parallel transfections with positive control vector (SV40-PGL3) and negative control vector (PGL3 with no insert). Firefly luciferase activity was normalized for Renilla luciferase activity. We repeated each transfection 6 times in triplicate, and data were averaged.

electrophoretic mobility shift assays
Synthesized wild-type and mutated oligonucleotides were 3'-end labeled with biotin-11-dUTP using the Biotin 3'-end DNA labeling reagent set (Pierce). The sequences of the used upper strands of the oligonucleotides are listed in Table 2 in the online Data Supplement. We performed electrophoretic mobility shift assays (EMSAs) by use of the LightShift Chemiluminescent EMSA reagent set (Pierce) on nuclear extract of HepG2 cells. For competition experiments, we added unlabeled wild-type, mutant, sterol regulatory element–binding protein (SREBP), Sp, and Egr1-consensus oligonucleotides in a 100-fold molar excess before the addition of the biotinylated probes.

statistical analysis
We performed statistical analysis by use of SAS (SAS Institute) and considered a 2-sided value of P <0.05 to be statistically significant. Baseline quantitative results are expressed as mean (SD). Concentrations of triglycerides, insulin, and HOMA-IR were log transformed. To determine the predictors of diabetes risk in this data set, we performed stepwise logistic regression analyses. We calculated odds ratios (ORs) and 95% CIs for diabetes from the regression model estimates conditioned on clinical covariates. Binary covariates included sex, hypertension, parental history of diabetes, and smoking. Continuous covariates included age, body mass index, waist circumference, HDL cholesterol, triglycerides, and HOMA-IR. Except for age, we included all continuous covariates in the model per interquartile range increase to allow easier interpretation of their relative effect size. We used an additive model for the –1023C>A variant and included it in the models. We estimated allele frequencies by gene counting. We used analysis of covariance to determine associations of –1023C>A and –51delA variants with diabetes-related traits after adjusting for age and sex. We used the {chi}2 test to evaluate deviation from Hardy–Weinberg equilibrium and to compare categorical variables. We assessed LD between SNPs using D' (24) and r2. We performed power calculations by use of the program by Purcell et al. (25), available at http://statgen.iop.kcl.ac.uk/gpc.


   Results
Top
 Abstract
 Introduction
 Patients and Methods
 Results
Discussion
 References
 
baseline characteristics of study samples
We included 586 Iranian individuals in the analyses of genetic association. All studied biomarkers significantly differed between the diabetic and the control groups (Table 2 ).


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  		Table 2. General characteristics of the study population.1

genomic dna screening of the ptpn1 promoter
Primary analysis of 2.0 kb of the PTPN1 promoter in 200 individuals revealed 7 variants: a deletion of A nucleotide at position –51 (–51delA), 4 SNPs (–451A>G, –467T>C, –1023-C>A, and –1045G>A), a 3-bp insertion-deletion (–1286 to –1288), and a 9-bp insertion-deletion (–1291 to –1299; Table 3 ). At the time of the present study, only –1023C>A had been submitted to the public SNP database (http://www.ncbi.nlm.nih.gov/SNP), corresponding to dbSNP entry rs6126029. Allele and genotype frequencies of each variant, as well as genomic position, are shown in Table 3 . None of the genotype frequencies significantly deviated from Hardy–Weinberg equilibrium. The frequency of the A allele of –1023C>A SNP significantly differed between the T2D and nondiabetic individuals (P = 0.020), whereas the difference in the genotype frequency between the 2 groups approached borderline significance (P = 0.069; Table 3 ). None of the other markers was significantly associated with T2D.


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  		Table 3. Descriptive information of the identified variants in the PTPN1 promoter and their genotype and allelic comparisons between the control (412) and diabetic (174) participants.

To verify the association observed between the –1023C>A variant and T2D, we performed stepwise logistic regression analysis, which included the genotypes of –1023C>A variant, assuming an additive model along with established risk factors for T2D (Table 4 ). Age, parental history of diabetes, HOMA-IR, smoking, and hypertension were the only significant predictors of T2D, suggesting that the –1023C>A genotype is not an independent risk factor for T2D in this population.


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  		Table 4. Stepwise logistic regression analysis of diabetes predictors.1

power calculation
Considering the minor allele frequency (MAF) of the –1023C>A and –51delA variants and 0.8 D' with the risk allele, and the ORs of 1.5 and 15% for frequency of the disease allele, our case-control provides 37% and 11% power, respectively, to detect associations between –1023C>A and –51delA variants and T2D.

association analysis of ptpn1 promoter gene variants with biochemical and clinical phenotypes
We used a general linear model analysis to assess the relationship of genotypes of –1023C>A and –51delA with biochemical and clinical features in the diabetic and control groups separately. Covariates included age, sex, body mass index, and use of antihypertensive or lipid-lowering medication. No significant differences (P <0.05) in anthropometric or biochemical features were observed between the wild-type and heterozygous individuals at –51delA and –1023-C>A variants in the T2D group or controls (data not shown).

Pairwise D' statistics were calculated for the identified PTPN1 promoter variants (see Table 3 in the online Data Supplement). The –451A>G variant is in complete LD with –467T>C (r2 = 1.00). All other variants had low LD between each other.

To investigate whether –1023C>A SNP was captured well by the previously studied SNPs, this variant was genotyped in the same 30 trio Centre d’Étude du Polymorphisme Humain samples that have been genotyped in the HapMap project (Phase II, release 19). The MAF of –1023C>A in HapMap samples was 6.7%. With Phase II release 19 of HapMap and examination of a 200-kb interval, –1023C>A could be tagged by itself only if an r2 cutoff of 0.8 was used. The highest r2 between –1023C>A and other markers was 0.75 with rs6126033 (see Table 4 in the online Data Supplement).

effect of the –1023c>a and –51DELA polymorphisms on promoter activity
We used Genomatix to perform a bioinformatics search for potential binding sites for transcription factors at the sites of –1023C>A and –51delA variations (http://www.genomatix.de/products/GEMSLauncher/GEMSLauncher2.html). The search identified potential binding sites for C2H2 zinc finger proteins, such as the specificity protein (SP) family and Egr1 at –51delA and SREBP at –1023C>A. To validate these sites experimentally, we assessed the effect of the 2 variants on PTPN1 promoter activity by the luciferase reporter assay. As shown in Fig. 1 , there was no difference in luciferase activity between the 2 alleles of the –1023C>A variant in the absence or presence of 5.5 or 22.5 mmol/L glucose and 100 nmol/L insulin. Constructs containing –51delA genotype showed 2-fold lower PTPN1 promoter activity compared with the wild-type construct in the absence or presence of 5.5 or 22.5 mmol/L glucose and 100 nmol/L insulin (P <0.001; Fig. 1 ).


Figure 1
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  		Figure 1. Luciferase reporter expression of the –1023C>A and –51delA polymorphisms in HepG2 cells.

HepG2 cells were transfected with the pGL3 basic vector containing each promoter allele (left panel, –1023C and –1023A; right panel, –51A and –51delA) under different conditions (A, negative control; B, positive control; C, no glucose; D, 5.5 mmol/L glucose; E, 22.5 mmol/L glucose; F, 100 nmol/L insulin). The amount of firefly luciferase activity was normalized for transfection efficiency by cotransfection with a Renilla luciferase control plasmid. The results are expressed as mean ± SD of the mean of the 6 independent experiments done in triplicate wells for each condition. Statistical analysis was performed by the standard t-test. (All P values were >0.05 in the left panel and <0.001 in the right panel.)

determination of the binding of nuclear proteins by emsa
We performed EMSA to further verify the potential binding sites for transcription factors at –1023C>A and –51delA variations. As shown in Fig. 1 in the online Data Supplement, 2 complexes, A and B, were retarded when the –1023C/A DNA fragments were used as probes. In unlabeled probe competition assays, excess of oligonucleotide A or C and SREBP consensus sequence eliminated the binding of complex B. The result suggests that a similar specific DNA-protein complex was formed with both –1023C and –1023A. We also performed EMSA on nuclear extracts of HepG2 and labeled –51A, –51delA, Sp, and Egr1 probes. The results indicated that there are 3 complexes that specifically bind to the labeled probes. The 2 upper complexes correspond to the Sp consensus sequence, whereas the lower complex corresponds to the Egr1 consensus sequence (Fig. 2 ). Competition assay with unlabeled probes disrupted the binding of all labeled probes with nuclear proteins. As shown in Fig. 2A , the affinity of SP family proteins to the A allele was visibly higher than that to the delA (Fig. 2 , lane 7 vs lane 2).


Figure 2
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  		Figure 2. EMSA with HepG2 nuclear extract using –51delA and –51A oligonucleotides.

EMSA was performed using –51A, –51delA, Sp, and Egr1 probes. Each binding reaction contained 3 µg HepG2 nuclear extract and labeled –51delA (lanes 2–6), –51A (lanes 7–11), Sp (lanes 12 and 13), and Egr1 (lanes 14 and 15) oligonucleotides. Excess unlabeled –51delA (lanes 3 and 8), –51A (lanes 4 and 9), Sp (lanes 5, 10, and 13), and Egr1 (lanes 6, 11, and 15) oligonucleotides were included in the binding reactions as competitor. Lane 1 is negative control. –51A/delA oligonucleotides form 3 main gel retardation complexes corresponding to Sp and Egr1 family proteins. The affinity of SP family proteins to the A allele was significantly higher than that to the delA (lane 7 compared with lane 2).


   Discussion
Top
 Abstract
 Introduction
 Patients and Methods
 Results
 Discussion
References
 
PTPN1 is a negative regulator of the insulin signaling pathway (16). The importance of PTPN1 for several crucial metabolic pathways has been illustrated in mice deficient for this phosphatase (26). These observations suggest that PTPN1 plays a role in attenuating insulin signal transduction. Variations in the PTPN1 promoter might affect gene regulation and could therefore be associated with T2D (7). Several studies have investigated the association of variants in the PTPN1 gene with T2D (9)(10)(11)(12)(13)(14)(15)(27)(28)(29)(30)(31), but none has included sequence analysis of the PTPN1 promoter region. Our study is the first to do so, and because we analyzed 400 chromosomes, we were able to identify variants even with low allele frequency.

Both common and rare variants are expected to contribute to common diseases, as illustrated by the finding in the PCSK9 gene of a spectrum of alleles with a wide range of allele frequencies (0.2%–34%) associated with LDL cholesterol and magnitude of phenotypic effects (approximately 3% increase to 49% reduction in LDL cholesterol) (32).

Identifying SNPs in the promoter region of the PTPN1 gene and testing their relations to T2D and its related traits is particularly important, because this region seems to be an SNP-poor area in the HapMap Project (Phase II, release 19), for which the first available SNP (rs6020563) is >7 kb upstream exon 1 in PTPN1 gene. PCR–denaturing HPLC analysis of 2.0 kb spanning the PTPN1 promoter region identified 7 polymorphisms, which were then investigated in our entire sample. In the dbSNP genome build 36.2, 7 SNPs were observed to map to the scanned area (see Table 5 in the online Data Supplement). None of these SNPs were detected in our scan. However, the sample size used to identify most of these SNPs was only 2, and the variation status for these SNPs is not verified, which casts doubts about their presence. Of the variants identified in our scan, only the –1023A allele seemed to be associated with a protective effect against T2D at P <0.05, but this association disappeared after adjusting for established T2D risk factors. An r2 = 0.8 cutoff was suggested to be able to capture both haplotype- and clade-specific patterns of variation (33). The highest r2 of –1023C>A with SNPs contained in a 200-kb interval harboring PTPN1 in HapMap Phase II, release 19, 2005, was with rs6126033 (intron 1, position = chromosome 20:48 579 516). Two more variants (rs11698821 in intron 3 and rs2230604, a synonymous variant in exon 8) that were added to the Phase II, HapMap release 22, 2007, have the same r2 as the –1023C>A variant. Florez et al. (15) studied rs2230604 but found no association with T2D. To our knowledge, no study has investigated rs6126033 or rs11698821 in T2D. None of these variants seems to have functional importance.

Given the low MAF of the –1023C>A and –51Adel variants, we would have only 37% and 11% power, respectively, to detect association with T2D. Assuming ORs of the risk allele of 1.5 or 2.0 with 10% frequency and an 8% prevalence of T2D, we would need 2163 and 733 cases to detect association with the –51del variant, and 426 and 146 cases to detect association with the –1023 variant with 80% power at the ≤0.05 level. Table 6 in the online Data Supplement includes the number of samples needed to have 80% power to detect association with the –1023C>A and –51delA variants at different ORs.

Our reporter assay studies showed no differences between –1023 C and A alleles on PTPN1 promoter activity in HepG2 cells. EMSA experiments suggest binding of the oligonucleotide that contains the –1023 variant alleles to SREBP in HepG2 cell nuclear extract. However, oligos that contain A or C alleles of this variant equally bind to SREBP. These observations suggest that the –1023C>A variant has no functional role in T2D by modulating PTPN1 gene expression. In contrast, the –51delA genotype lowered the transcriptional activity in transient transfection experiments by 2-fold in comparison to the wild-type allele. This finding was confirmed by EMSA, in which –51A-containing oligonucleotide markedly bound more SP proteins than –51Adel (Fig. 2Up , lane 7 vs lane 2), implying a lower affinity of –51delA allele to binding SPs.

Several studies reported association between variants in the PTPN1 and T2D or related traits in Hispanics (20)(21)(22)(23)(24)(25)(26), African Americans (34), or white twins(14). However, Florez et al. (15) studied 42 SNPs in 7883 individuals and disclosed no association between individual SNPs and haplotypes with T2D. Because no variants in the promoter region of PTPN1 were available at the time when those studies were conducted, such SNPs could not be included upon selecting tag SNPs (Florez et al. (15)); therefore, this method may have resulted in missing some variants that could or could not be associated with T2D.

We could not detect any influence of the –1023C>A and –51delA variants on diabetes-related traits in the study groups. In fact, we observed a trend toward association between glucose and HOMA-IR levels and –51delA (P = 0.09 and 0.10, respectively; data not shown). The reason that we observed an effect of the –51delA SNP on reporter gene expression but not on T2D-related traits might be a tissue-specific effect.

In conclusion, our study in a sample of Iranian T2D cases and controls identified several SNPs, of which the –1023C>A SNP was the most frequent, but with no effect on PTPN1 expression or association with T2D and related metabolic traits after adjustment for established T2D risk factors. In addition, the rare –51delA variant significantly reduced the transcription of the luciferase reporter gene as well as the affinity to binding SP family proteins in HepG2 cells but had no significant physiological effect on T2D-related traits at P <0.05 in our sample. Ruling in or out a possible role of these 2 variants in T2D and related traits requires investigating them in a larger population.


   Acknowledgments
 
Grant/funding support: This work was financially supported by a grant from the Pasteur Institute of Iran (to M.T. and B.L.) and by an operating grant from the Heart and Stroke Foundation of Ontario (to K.A.).

Financial disclosures: None declared.

Acknowledgments: We greatly appreciate the assistance provided by staff of the Department of Biochemistry, Pasteur Institute of Iran; the Endocrinology and Metabolism Research Center of Shariati Hospital, Tehran University of Medical Sciences; Dr. Babak Shababa of the University of Toronto; and Dr. Peter Ray and Liping Han, Division of Molecular Genetics, the Hospital for Sick Children, University of Toronto. We also thank all volunteers for their participation in the study.


   Footnotes
 
1 Nonstandard abbreviations: T2D, type 2 diabetes; IR, insulin resistance; SNP, single-nucleotide polymorphism; OGTT, oral glucose tolerance test; HOMA-IR, homeostasis model assessment of IR; RS, restriction site; LD, linkage disequilibrium; EMSA, electrophoretic mobility shift assay; SREBP, sterol regulatory element–binding protein; OR, odds ratio; MAF, minor allele frequency; SP, specificity protein.

2 Human genes: PTPN1, protein tyrosine phosphatase, nonreceptor type 1; PCSK9, proprotein convertase subtilisin/kexin type 9.


   References
Top
 Abstract
 Introduction
 Patients and Methods
 Results
 Discussion
 References
 

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