- Email: [email protected]
2B genes associated with type 2 diabetes in Lebanese Arab population
diabetes research and clinical practice 95 (2012) e37–e40
Contents available at Sciverse ScienceDirect
Diabetes Research and Clinical Practice journ al h ome pa ge : www .elsevier.co m/lo cate/diabres
Brief report
Replication study of common variants in CDKAL1 and CDKN2A/2B genes associated with type 2 diabetes in Lebanese Arab population Rita Nemr a, Ahmad W. Almawi b,*, Akram Echtay c, Mai S. Sater b, Hoda S. Daher b, Wassim Y. Almawi b a
University Medical Center Rizk Hospital, Beirut, Lebanon Department of Medical Biochemistry, Arabian Gulf University, Manama, Bahrain c Rafic Hariri University Hospital, Beirut, Lebanon b
article info
abstract
Article history:
We investigated the association of CDKAL1 (rs7754840 and rs7756992) and CDKN2A/2B
Received 30 October 2011
(rs10811661) variants with T2DM. Higher MAF of rs7754840 and rs7756992 were seen in
Accepted 1 November 2011
patients, and both were associated with T2DM under additive, dominant, and recessive
Published on line 26 November 2011
models. CDKAL1 rs7754840 and rs7756992, but not CDKN2A/2B rs10811661, are associated with T2DM in Lebanese.
Keywords:
# 2011 Elsevier Ireland Ltd. All rights reserved.
CDKAL1 CDKN2A/2B Diabetes Haplotypes Replication studies
1.
Introduction
Genome-wide association scan (GWAS) identified CDKAL1 and CDKN2A/2B as type 2 diabetes (T2DM) candidate genes [1–3]. CDKAL1 encodes a 65-kDa protein, implicated in b-cell dysfunction and T2DM predisposition [4,5]. CDKN2A and CDKN2B are CDK inhibitor genes, and their product p16INK4a inhibits CDK4, which regulates b cell replication [6]. GWAS confirmed that CDKAL1 (rs7756992 and rs7754840) [1,5], and CDKN2A/2B (rs10811661 and rs564398) [7] SNPs are T2DM susceptibility variants in select Caucasian and non-Caucasian
populations, but not others [1,8,9]. This was attributed to ethnic differences and linkage disequilibrium pattern, compounded by the contribution of non-genetic factors. This necessitates the need for replicating the association of these variants with T2DM in populations of different ethnicities. We explored the association of common CDKAL1 and CDKN2A/2B SNPs with T2DM in Lebanese. With the exception of one report demonstrating lack of association of these variants with T2DM among Moroccans [1], this is the first study to examine this association of CDKAL1 (rs7756992 and rs7754840) and CDKN2A/2B (rs10811661) common variants with T2DM among Arab population.
* Corresponding author at: Department of Medical Biochemistry, College of Medicine & Medical Sciences, Arabian Gulf University, PO Box 22979, Manama, Bahrain. Tel.: +973 39717118; fax: +973 17271090. E-mail address: [email protected] (W.Y. Almawi). 0168-8227/$ – see front matter # 2011 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.diabres.2011.11.002
e38
Characteristic
Controls (792)Patients (630)
Gender (male:female) 362:430 Age at examination (years) 58.1 6.1 Mean BMI (kg/m2) 25.7 3.8 Age at diagnosis (years) – 5.1 0.9 Glucose (mmol/L) HbA1c (%) 4.9 1.4 Total cholesterol (mmol/L) 4.6 0.9 Triglycerides (mmol/L) 1.4 0.6 a b
Pearson’s chi square test. Student’s t-test.
354:276 58.5 9.4 28.0 4.2 52.2 11.9 8.7 2.8 8.8 2.2 6.0 1.9 2.8 2.1
P 0.002a 0.457b 0.001b NA <0.001b <0.001b 0.100b 0.006b
OR (95% CI)
1.44 (1.23–1.68) 1.35 (1.15–1.59) 0.90 (0.75–1.09) 0.030 0.028 1.000
0.33 0.36 0.18
0.27 0.28 0.19
19.82 13.24 0.990
9.0 106 2.7 104 0.320
Assay ID
MAF, minor allele frequencies; HWE, Hardy–Weinberg equilibrium. Location on chromosome based on dbSNP build 125. b Minor allele defined based on frequency in controls; study subjects comprised 630 T2DM cases and 792 controls. c Observed P value.
Table 1 – Clinical characteristics of the study participants.
a
Table 1 lists the characteristics of study subjects. While age and serum cholesterol were comparable between them, significant differences between patients and controls were noted in gender, BMI, and triglyceride levels. Accordingly, the
Locationa
Results
Table 2 – CDKAL1 and CDKN2B SNPs analyzed.
3.
HWE
Data were expressed as mean SD (continuous variables), or percent total (categorical variables). SNPs were tested for Hardy–Weinberg equilibrium by HPlus 2.5 (http:// cdsweb01.fhcrc.org/HPlus). The calculated power was 99.77% (rs7754840), 98.70% (rs7756992), and 54.83% (rs10811661) (http:// pngu.mgh.harvard.edu/purcell/gpc/cc2.html); the overall power (84.43%) was the average over the SNPs genotyped. CDKAL1 haplotype estimation was done by expectation maximization using HPlus 2.5.
C_29246232_10 C_2504058_20 C_31288917_10
Statistical analyses
20661000 20667945 22133844
2.3.
Cases MAFb
Genotyping was performed by allelic discrimination, using StepOne real-time PCR (Applied Biosystems, Foster City, CA). Genotype frequencies of CDKAL1 and CDKN2A/2B variants analyzed were consistent with Hardy–Weinberg equilibrium (Table 2). Their minor allele frequencies (MAF) were comparable with those in the HapMap CEU sample (www.hapmap.org).
6 6 9
SNP genotyping
rs7754840 rs7756992 rs10811661
Controls MAF
2.2.
x2
Study subjects comprised 630 consecutive unrelated T2DM patients, who were recruited from the outpatient endocrinology clinics (Table 1). T2DM diagnosis was as per WHO criteria (fasting glucose 7.0 mmol/l and/or 2-h plasma glucose 11.1 mmol/L). Patients with other diabetes types, or diagnosed with T2DM before 30 years of age, were excluded. Control subjects (n = 792) had normal glucose tolerance confirmed by fasting plasma glucose 6.0 mmol/l, or HbA1c levels < 5.4%, and no first-degree family history of diabetes. Informed consent was obtained from participants, and local ethics committees approved the study protocol.
CDKAL1 CDKAL1 CDKN2B
Subjects
Chromosome
2.1.
SNP
Subjects and methods
Gene
2.
Pc
diabetes research and clinical practice 95 (2012) e37–e40
0.019
2.0 103
rs10811661 CDKN2B
Number of subjects (frequency).
rs7756992 CDKAL1
a
OR (95% CI)
1.00 (reference) 1.86 (1.36–2.56) (G/G + G/C vs. C/C) 9.1 103 1.00 (reference) 1.57 (1.12–2.20) (A/A + A/G vs. G/G) 0.15 1.00 (reference) 1.45 (0.87–2.42) (T/T + T/C vs. C/C)
1.0 104
P OR (95% CI)
1.00 (Reference:) 1.43 (1.16–1.76) (G/G + C/C vs. G/G) 1.7 103 1.00 (reference) 1.40 (1.13–1.73) (A/G + G/G vs. A/A) 0.064 1.00 (reference) 0.81 (0.65–1.01) (T/C + C/C vs. T/T)
P
9.0 104
(reference) (1.01–1.59) (1.48–2.88) (reference) (1.05–1.64) (1.24–2.51) (reference) (0.59–0.95) (0.80–2.24) 1.00 1.26 2.06 1.00 1.31 1.76 1.00 0.75 1.34
OR (95% CI) P
1.0 104
(0.44) (0.39) (0.17) (0.47) (0.40) (0.13) (0.70) (0.25) (0.05) 279 247 104 294 254 82 442 155 33
Patients
4.
(0.53)a (0.37) (0.10) (0.55) (0.36) (0.09) (0.66) (0.31) (0.04)
Controls
rs7754840 CDKAL1
e39
latter were the covariates that were controlled for in subsequent analysis. Table 2 summarizes the association between CDKAL1 and CDKN2A/2B SNPs and T2DM. Significantly higher MAF of rs7754840 and rs7756992, but not rs10811661, were associated with T2DM; both CDKAL1 SNPs were in strong LD (P < 0.001; D0 = 0.811). Table 3 summarizes the association between these variants under additive, dominant and recessive models. CDKAL1 SNPs were significantly associated with T2DM under the three models. In contrast, CDKN2A/2B rs10811661 did not associate with T2DM, but showed lower magnitude of effect in the same direction under the additive model. Taking the common rs7754840/rs7756992 GA haplotype as reference (OR = 1.00), multivariate analysis confirmed the association of rs7754840C allele-containing (CG, CA) haplotypes with T2DM, thus conferring disease susceptibility. These differences remained significant for CG (Pc = 8.8 103) and CA (Pc = 1.3 103) after applying Bonferroni correction (Table 4).
421 295 76 436 287 69 519 244 29
Dominant model Additive model Genotype distribution Genotype SNP Gene
Table 3 – Effect of CDKAL1 and CDKN2B genotypes on T2DM risk under different models.
G/G G/C C/C A/A A/G G/G T/T T/C C/C
Recessive model
diabetes research and clinical practice 95 (2012) e37–e40
Discussion
CDKAL1 and CDKN2A/B were among the first set of T2DM susceptibility genes identified by GWAS [5,10,11]. Whereas most reported positive association, some studies did not identify any association. This is the first study to examine the association of CDKAL1 (rs7754840 and rs7756992) and CDKN2A/ 2B (rs10811661) SNPs with T2DM in Lebanese Arabs. As differences in genetic background stemming from ethnic origin, LD pattern, and carriage of at-risk alleles influence disease association; we included only subjects of Arab origin from the same area, thus minimizing population bias. For CDKAL1, the strongest association was for rs7754840. Heterogeneity in the association of rs7754840 with T2DM was reported for different populations, suggesting ethnically dependent and specific association. Our findings were reminiscent of those established for Israeli/Ashkenazi Jews [1], select European populations [1,3,11–13], South Indians [14], and South-East Asians [2,4,7,15,16]. On the other hand, lack of association of rs7754840 was reported for Austrians [1], Indian Sikhs [9], and Moroccan Arabs [1]. These inconsistencies are attributed to differences in genetic background, small sample size [1,9], and enrollment criteria. While the calculated OR of rs7754840 was higher than that of Europeans [1,11–13], and South-East Asians [4,7,15], risk allele frequencies were considerably lower. Our data were less compelling regarding rs7756992, which showed modest association, but remained significant after controlling for several covariates. The effect size of rs7756992 Gallele (OR = 1.35), was similar in magnitude to those reported for Europeans (OR = 1.30), Asians (OR = 1.20–1.38), and Indians (OR = 1.31). However, no association for rs7756992 with T2DM was found in Austrians [1], Moroccan Arabs [1], and Norwegians [8]. This is explained by small sample size [1], ethnic background [1,8], and differences in enrollment criteria [8]. We could not replicate the association of CDKN2A/2B rs10811661 with T2DM, previously associated with T2DM in Europeans [1,3,8,10,11], Asians [4,15–17], and Indians [18]. Our results were consistent with Israeli and Moroccan Arabs [1], and one French study [1]. This was not due to the lack of
e40
diabetes research and clinical practice 95 (2012) e37–e40
Table 4 – CDKAL1 haplotype distribution in patients and controls. Haplotypea G C G C a b c
A G G A
Controls
T2DM cases c
0.678 0.015 0.228 0.015 0.050 0.007 0.008 0.004
0.581 0.019 0.274 0.017 0.097 0.011 0.083 0.014
Pb
Pcb 4
<1.0 10 3.0 104 3.0 104 9.9 103
OR (95% CI) 4
<1.0 10 1.2 103 1.2 103 0.039
1.00 1.37 1.66 1.54
(reference) (1.16–1.63) (1.26–2.18) (1.11–2.14)
Haplotype (rs7754840/rs7756992) determined by the maximum likelihood method. Fisher’s exact test. Haplotype frequency S.
power, but to differences in ethnic/racial backgrounds. Interestingly, both negative [1] and positive [8,10,11] associations were documented in European. Large sample sizes are needed to replicate the association of rs10811661 with T2DM. The 2-locus haplotype analysis identified rs7754840 C-allelecontaining haplotypes (CG, CA) to be associated with increased T2DM risk. As the risk imparted by CA haplotype (OR = 1.67; 95% CI = 1.25–2.24) was higher than that of double positive CG haplotype (OR = 1.39; 95% CI = 1.08–1.54), this prompts the speculation of epistatic interaction between these SNPs. We replicate association of CDKAL1 rs7754840 and rs7756992, but not CDKN2A/2B rs10811661 variants with T2DM. Given their association with populations of diverse racial backgrounds, this confirms that both CDKAL1 variants are T2DM-susceptibility genes in Lebanese. As lifestyle influences T2DM risk, the contribution of these variants on quantitative traits needs to be addressed.
Conflict of interest The authors declare that they have no conflict of interest.
references
[1] Cauchi S, Meyre D, Durand E, Proenc¸a C, Marre M, Hadjadj S, et al. Post genome-wide association studies of novel genes associated with type 2 diabetes show gene-gene interaction and high predictive value. PLoS One 2008;3:e2031. [2] Bao XY, Peng B, Yang MS. Replication study of novel risk variants in six genes with type 2 diabetes and related quantitative traits in the Han Chinese lean individuals. Mol Biol Rep 2011. doi: 10.1007/s11033-011-0995-8. [3] Cauchi S, Proenc¸a C, Choquet H, Gaget S, De Graeve F, Marre M, et al. Analysis of novel risk loci for type 2 diabetes in a general French population: the D.E.S.I.R. study. J Mol Med (Berl) 2008;86:341–8. [4] Cho YM, Kim TH, Lim S, Choi SH, Shin HD, Lee HK, et al. Type 2 diabetes-associated genetic variants discovered in the recent genome-wide association studies are related to gestational diabetes mellitus in the Korean population. Diabetologia 2009;52:253–61. [5] Dehwah MA, Wang M, Huang QY. CDKAL1 and type 2 diabetes: a global meta-analysis. Genet Mol Res 2010;9:1109–20. [6] Marzo N, Mora C, Fabregat ME, Martı´n J, Usac EF, Franco C, et al. Pancreatic islets from cyclin-dependent kinase 4/R24C (Cdk4) knockin mice have significantly increased beta cell mass and are physiologically functional, indicating that Cdk4 is a potential target for pancreatic beta cell mass regeneration in type 1 diabetes. Diabetologia 2004;47:686–94.
[7] Tabara Y, Osawa H, Kawamoto R, Onuma H, Shimizu I, Miki T, et al. Replication study of candidate genes associated with type 2 diabetes based on genome-wide screening. Diabetes 2009;58:493–8. [8] Hertel JK, Johansson S, Raeder H, Midthjell K, Lyssenko V, Groop L, et al. Genetic analysis of recently identified type 2 diabetes loci in 1,638 unselected patients with type 2 diabetes and 1,858 control participants from a Norwegian population-based cohort (the HUNT study). Diabetologia 2008;51:971–7. [9] Sanghera DK, Ortega L, Han S, Singh J, Ralhan SK, Wander GS, et al. Impact of nine common type 2 diabetes risk polymorphisms in Asian Indian Sikhs: PPARG2 (Pro12Ala), IGF2BP2, TCF7L2 and FTO variants confer a significant risk. BMC Med Genet 2008;9:59. [10] Duesing K, Fatemifar G, Charpentier G, Marre M, Tichet J, Hercberg S, et al. Strong association of common variants in the CDKN2A/CDKN2B region with type 2 diabetes in French Europids. Diabetologia 2008;51:821–6. [11] Saxena R, Voight BF, Lyssenko V, Burtt NP, de Bakker PI, Chen H, et al. Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels. Science 2007;316:1331–6. [12] Chistiakov DA, Potapov VA, Smetanina SA, Bel‘chikova LN, Suplotova LA, Nosikov VV. The carriage of risk variants of CDKAL1 impairs beta-cell function in both diabetic and non-diabetic patients and reduces response to nonsulfonylurea and sulfonylurea agonists of the pancreatic KATP channel. Acta Diabetol 2011;48:227–35. [13] Stanca´kova´ A, Pihlajama¨ki J, Kuusisto J, Stefan N, Fritsche A, Ha¨ring H, et al. Single-nucleotide polymorphism rs7754840 of CDKAL1 is associated with impaired insulin secretion in nondiabetic offspring of type 2 diabetic subjects and in a large sample of men with normal glucose tolerance. J Clin Endocrinol Metab 2008; 93:1924–30. [14] Chidambaram M, Radha V, Mohan V. Replication of recently described type 2 diabetes gene variants in a South Indian population. Metabolism 2010;59:1760–6. [15] Horikawa Y, Miyake K, Yasuda K, Enya M, Hirota Y, Yamagata K, et al. Replication of genome-wide association studies of type 2 diabetes susceptibility in Japan. J Clin Endocrinol Metab 2008;93:3136–41. [16] Lee YH, Kang ES, Kim SH, Han SJ, Kim CH, Kim HJ, et al. Association between polymorphisms in SLC30A8, HHEX, CDKN2A/B, IGF2BP2, FTO, WFS1, CDKAL1, KCNQ1 and type 2 diabetes in the Korean population. J Hum Genet 2008;53:991–8. [17] Xu M, Bi Y, Xu Y, Yu B, Huang Y, Gu L, et al. Combined effects of 19 common variations on type 2 diabetes in Chinese: results from two community-based studies. PLoS One 2010;5:e14022. [18] Chauhan G, Spurgeon CJ, Tabassum R, Bhaskar S, Kulkarni SR, Mahajan A, et al. Impact of common variants of PPARG, KCNJ11, TCF7L2, SLC30A8, HHEX, CDKN2A, IGF2BP2, and CDKAL1 on the risk of type 2 diabetes in 5,164 Indians. Diabetes 2010;59:2068–74.
Contents available at Sciverse ScienceDirect
Diabetes Research and Clinical Practice journ al h ome pa ge : www .elsevier.co m/lo cate/diabres
Brief report
Replication study of common variants in CDKAL1 and CDKN2A/2B genes associated with type 2 diabetes in Lebanese Arab population Rita Nemr a, Ahmad W. Almawi b,*, Akram Echtay c, Mai S. Sater b, Hoda S. Daher b, Wassim Y. Almawi b a
University Medical Center Rizk Hospital, Beirut, Lebanon Department of Medical Biochemistry, Arabian Gulf University, Manama, Bahrain c Rafic Hariri University Hospital, Beirut, Lebanon b
article info
abstract
Article history:
We investigated the association of CDKAL1 (rs7754840 and rs7756992) and CDKN2A/2B
Received 30 October 2011
(rs10811661) variants with T2DM. Higher MAF of rs7754840 and rs7756992 were seen in
Accepted 1 November 2011
patients, and both were associated with T2DM under additive, dominant, and recessive
Published on line 26 November 2011
models. CDKAL1 rs7754840 and rs7756992, but not CDKN2A/2B rs10811661, are associated with T2DM in Lebanese.
Keywords:
# 2011 Elsevier Ireland Ltd. All rights reserved.
CDKAL1 CDKN2A/2B Diabetes Haplotypes Replication studies
1.
Introduction
Genome-wide association scan (GWAS) identified CDKAL1 and CDKN2A/2B as type 2 diabetes (T2DM) candidate genes [1–3]. CDKAL1 encodes a 65-kDa protein, implicated in b-cell dysfunction and T2DM predisposition [4,5]. CDKN2A and CDKN2B are CDK inhibitor genes, and their product p16INK4a inhibits CDK4, which regulates b cell replication [6]. GWAS confirmed that CDKAL1 (rs7756992 and rs7754840) [1,5], and CDKN2A/2B (rs10811661 and rs564398) [7] SNPs are T2DM susceptibility variants in select Caucasian and non-Caucasian
populations, but not others [1,8,9]. This was attributed to ethnic differences and linkage disequilibrium pattern, compounded by the contribution of non-genetic factors. This necessitates the need for replicating the association of these variants with T2DM in populations of different ethnicities. We explored the association of common CDKAL1 and CDKN2A/2B SNPs with T2DM in Lebanese. With the exception of one report demonstrating lack of association of these variants with T2DM among Moroccans [1], this is the first study to examine this association of CDKAL1 (rs7756992 and rs7754840) and CDKN2A/2B (rs10811661) common variants with T2DM among Arab population.
* Corresponding author at: Department of Medical Biochemistry, College of Medicine & Medical Sciences, Arabian Gulf University, PO Box 22979, Manama, Bahrain. Tel.: +973 39717118; fax: +973 17271090. E-mail address: [email protected] (W.Y. Almawi). 0168-8227/$ – see front matter # 2011 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.diabres.2011.11.002
e38
Characteristic
Controls (792)Patients (630)
Gender (male:female) 362:430 Age at examination (years) 58.1 6.1 Mean BMI (kg/m2) 25.7 3.8 Age at diagnosis (years) – 5.1 0.9 Glucose (mmol/L) HbA1c (%) 4.9 1.4 Total cholesterol (mmol/L) 4.6 0.9 Triglycerides (mmol/L) 1.4 0.6 a b
Pearson’s chi square test. Student’s t-test.
354:276 58.5 9.4 28.0 4.2 52.2 11.9 8.7 2.8 8.8 2.2 6.0 1.9 2.8 2.1
P 0.002a 0.457b 0.001b NA <0.001b <0.001b 0.100b 0.006b
OR (95% CI)
1.44 (1.23–1.68) 1.35 (1.15–1.59) 0.90 (0.75–1.09) 0.030 0.028 1.000
0.33 0.36 0.18
0.27 0.28 0.19
19.82 13.24 0.990
9.0 106 2.7 104 0.320
Assay ID
MAF, minor allele frequencies; HWE, Hardy–Weinberg equilibrium. Location on chromosome based on dbSNP build 125. b Minor allele defined based on frequency in controls; study subjects comprised 630 T2DM cases and 792 controls. c Observed P value.
Table 1 – Clinical characteristics of the study participants.
a
Table 1 lists the characteristics of study subjects. While age and serum cholesterol were comparable between them, significant differences between patients and controls were noted in gender, BMI, and triglyceride levels. Accordingly, the
Locationa
Results
Table 2 – CDKAL1 and CDKN2B SNPs analyzed.
3.
HWE
Data were expressed as mean SD (continuous variables), or percent total (categorical variables). SNPs were tested for Hardy–Weinberg equilibrium by HPlus 2.5 (http:// cdsweb01.fhcrc.org/HPlus). The calculated power was 99.77% (rs7754840), 98.70% (rs7756992), and 54.83% (rs10811661) (http:// pngu.mgh.harvard.edu/purcell/gpc/cc2.html); the overall power (84.43%) was the average over the SNPs genotyped. CDKAL1 haplotype estimation was done by expectation maximization using HPlus 2.5.
C_29246232_10 C_2504058_20 C_31288917_10
Statistical analyses
20661000 20667945 22133844
2.3.
Cases MAFb
Genotyping was performed by allelic discrimination, using StepOne real-time PCR (Applied Biosystems, Foster City, CA). Genotype frequencies of CDKAL1 and CDKN2A/2B variants analyzed were consistent with Hardy–Weinberg equilibrium (Table 2). Their minor allele frequencies (MAF) were comparable with those in the HapMap CEU sample (www.hapmap.org).
6 6 9
SNP genotyping
rs7754840 rs7756992 rs10811661
Controls MAF
2.2.
x2
Study subjects comprised 630 consecutive unrelated T2DM patients, who were recruited from the outpatient endocrinology clinics (Table 1). T2DM diagnosis was as per WHO criteria (fasting glucose 7.0 mmol/l and/or 2-h plasma glucose 11.1 mmol/L). Patients with other diabetes types, or diagnosed with T2DM before 30 years of age, were excluded. Control subjects (n = 792) had normal glucose tolerance confirmed by fasting plasma glucose 6.0 mmol/l, or HbA1c levels < 5.4%, and no first-degree family history of diabetes. Informed consent was obtained from participants, and local ethics committees approved the study protocol.
CDKAL1 CDKAL1 CDKN2B
Subjects
Chromosome
2.1.
SNP
Subjects and methods
Gene
2.
Pc
diabetes research and clinical practice 95 (2012) e37–e40
0.019
2.0 103
rs10811661 CDKN2B
Number of subjects (frequency).
rs7756992 CDKAL1
a
OR (95% CI)
1.00 (reference) 1.86 (1.36–2.56) (G/G + G/C vs. C/C) 9.1 103 1.00 (reference) 1.57 (1.12–2.20) (A/A + A/G vs. G/G) 0.15 1.00 (reference) 1.45 (0.87–2.42) (T/T + T/C vs. C/C)
1.0 104
P OR (95% CI)
1.00 (Reference:) 1.43 (1.16–1.76) (G/G + C/C vs. G/G) 1.7 103 1.00 (reference) 1.40 (1.13–1.73) (A/G + G/G vs. A/A) 0.064 1.00 (reference) 0.81 (0.65–1.01) (T/C + C/C vs. T/T)
P
9.0 104
(reference) (1.01–1.59) (1.48–2.88) (reference) (1.05–1.64) (1.24–2.51) (reference) (0.59–0.95) (0.80–2.24) 1.00 1.26 2.06 1.00 1.31 1.76 1.00 0.75 1.34
OR (95% CI) P
1.0 104
(0.44) (0.39) (0.17) (0.47) (0.40) (0.13) (0.70) (0.25) (0.05) 279 247 104 294 254 82 442 155 33
Patients
4.
(0.53)a (0.37) (0.10) (0.55) (0.36) (0.09) (0.66) (0.31) (0.04)
Controls
rs7754840 CDKAL1
e39
latter were the covariates that were controlled for in subsequent analysis. Table 2 summarizes the association between CDKAL1 and CDKN2A/2B SNPs and T2DM. Significantly higher MAF of rs7754840 and rs7756992, but not rs10811661, were associated with T2DM; both CDKAL1 SNPs were in strong LD (P < 0.001; D0 = 0.811). Table 3 summarizes the association between these variants under additive, dominant and recessive models. CDKAL1 SNPs were significantly associated with T2DM under the three models. In contrast, CDKN2A/2B rs10811661 did not associate with T2DM, but showed lower magnitude of effect in the same direction under the additive model. Taking the common rs7754840/rs7756992 GA haplotype as reference (OR = 1.00), multivariate analysis confirmed the association of rs7754840C allele-containing (CG, CA) haplotypes with T2DM, thus conferring disease susceptibility. These differences remained significant for CG (Pc = 8.8 103) and CA (Pc = 1.3 103) after applying Bonferroni correction (Table 4).
421 295 76 436 287 69 519 244 29
Dominant model Additive model Genotype distribution Genotype SNP Gene
Table 3 – Effect of CDKAL1 and CDKN2B genotypes on T2DM risk under different models.
G/G G/C C/C A/A A/G G/G T/T T/C C/C
Recessive model
diabetes research and clinical practice 95 (2012) e37–e40
Discussion
CDKAL1 and CDKN2A/B were among the first set of T2DM susceptibility genes identified by GWAS [5,10,11]. Whereas most reported positive association, some studies did not identify any association. This is the first study to examine the association of CDKAL1 (rs7754840 and rs7756992) and CDKN2A/ 2B (rs10811661) SNPs with T2DM in Lebanese Arabs. As differences in genetic background stemming from ethnic origin, LD pattern, and carriage of at-risk alleles influence disease association; we included only subjects of Arab origin from the same area, thus minimizing population bias. For CDKAL1, the strongest association was for rs7754840. Heterogeneity in the association of rs7754840 with T2DM was reported for different populations, suggesting ethnically dependent and specific association. Our findings were reminiscent of those established for Israeli/Ashkenazi Jews [1], select European populations [1,3,11–13], South Indians [14], and South-East Asians [2,4,7,15,16]. On the other hand, lack of association of rs7754840 was reported for Austrians [1], Indian Sikhs [9], and Moroccan Arabs [1]. These inconsistencies are attributed to differences in genetic background, small sample size [1,9], and enrollment criteria. While the calculated OR of rs7754840 was higher than that of Europeans [1,11–13], and South-East Asians [4,7,15], risk allele frequencies were considerably lower. Our data were less compelling regarding rs7756992, which showed modest association, but remained significant after controlling for several covariates. The effect size of rs7756992 Gallele (OR = 1.35), was similar in magnitude to those reported for Europeans (OR = 1.30), Asians (OR = 1.20–1.38), and Indians (OR = 1.31). However, no association for rs7756992 with T2DM was found in Austrians [1], Moroccan Arabs [1], and Norwegians [8]. This is explained by small sample size [1], ethnic background [1,8], and differences in enrollment criteria [8]. We could not replicate the association of CDKN2A/2B rs10811661 with T2DM, previously associated with T2DM in Europeans [1,3,8,10,11], Asians [4,15–17], and Indians [18]. Our results were consistent with Israeli and Moroccan Arabs [1], and one French study [1]. This was not due to the lack of
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diabetes research and clinical practice 95 (2012) e37–e40
Table 4 – CDKAL1 haplotype distribution in patients and controls. Haplotypea G C G C a b c
A G G A
Controls
T2DM cases c
0.678 0.015 0.228 0.015 0.050 0.007 0.008 0.004
0.581 0.019 0.274 0.017 0.097 0.011 0.083 0.014
Pb
Pcb 4
<1.0 10 3.0 104 3.0 104 9.9 103
OR (95% CI) 4
<1.0 10 1.2 103 1.2 103 0.039
1.00 1.37 1.66 1.54
(reference) (1.16–1.63) (1.26–2.18) (1.11–2.14)
Haplotype (rs7754840/rs7756992) determined by the maximum likelihood method. Fisher’s exact test. Haplotype frequency S.
power, but to differences in ethnic/racial backgrounds. Interestingly, both negative [1] and positive [8,10,11] associations were documented in European. Large sample sizes are needed to replicate the association of rs10811661 with T2DM. The 2-locus haplotype analysis identified rs7754840 C-allelecontaining haplotypes (CG, CA) to be associated with increased T2DM risk. As the risk imparted by CA haplotype (OR = 1.67; 95% CI = 1.25–2.24) was higher than that of double positive CG haplotype (OR = 1.39; 95% CI = 1.08–1.54), this prompts the speculation of epistatic interaction between these SNPs. We replicate association of CDKAL1 rs7754840 and rs7756992, but not CDKN2A/2B rs10811661 variants with T2DM. Given their association with populations of diverse racial backgrounds, this confirms that both CDKAL1 variants are T2DM-susceptibility genes in Lebanese. As lifestyle influences T2DM risk, the contribution of these variants on quantitative traits needs to be addressed.
Conflict of interest The authors declare that they have no conflict of interest.
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