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Association of 32 type 1 diabetes risk loci in Pakistani patients
DIAB-6274; No. of Pages 6 diabetes research and clinical practice xxx (2015) xxx–xxx
Contents available at ScienceDirect
Diabetes Research and Clinical Practice journ al h ome pa ge : www .elsevier.co m/lo cate/diabres
Association of 32 type 1 diabetes risk loci in Pakistani patients Aysha Karim Kiani a,*, Peter John a,*, Attya Bhatti a, Asima Zia a, Gulbin Shahid b, Parveen Akhtar c, Xingbin Wang d, F. Yesim Demirci d, M. Ilyas Kamboh d a Department of Healthcare Biotechnology, Atta-ur-Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), Islamabad, Pakistan b Pakistan Institute of Medical Sciences (PIMS), Islamabad, Pakistan c Fauji Foundation Hospital, Rawalpindi, Pakistan d Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA
article info
abstract
Article history:
Aim: To identify risk alleles contributing towards type 1 diabetes in Pakistani patients.
Received 27 August 2014
Introduction: Type 1 diabetes (T1D) is an autoimmune disease which is caused by destruction
Received in revised form
of insulin producing b cells by immune system. Genetic predisposition as well as environ-
15 November 2014
mental factors contribute to its etiology. To date more than 40 risk loci have been identified
Accepted 3 January 2015
for T1D.
Available online xxx
Methodology: A total of 191 family-based and unrelated T1D cases and controls were
Keywords:
phisms (SNPs) previously reported in Europeans were genotyped. Genotyping was per-
recruited. DNA was extracted and 32 genome-wide significant single nucleotide polymorDiabetes
formed using TaqMan SNP genotyping assays and the data was analyzed using FamCC
Type 1 diabetes
software.
Auto-immune disease
Results: Our results showed significant association of 10 single nucleotide polymorphisms
Association studies
(SNPs) with T1D at p < 0.01, including HLA-DQA1/rs9272346, ERBB3/rs2292239, SIRPG/
Diabetes in Pakistan
rs2281808, IL2-KIAA1109/rs4505848, GLIS3/rs7020673, CD226/rs763361, PTPN2/rs478582,
Insulin dependent diabetes mellitus
IKZF1/rs10272724, BACH2/rs11755527, C6orf173/rs9388489, whereas 5 more SNPs showed their association at 0.01 < p < 0.05 in Pakistani population. Conclusion: We have replicated many of the T1D loci established among Europeans in a Pakistani population. # 2015 Elsevier Ireland Ltd. All rights reserved.
1.
Introduction
The hallmark of type 1 diabetes (T1D) is its origin due to autoimmune processes that destroy the insulin producing b cells. Beta cell destruction result in hyperglycemia, which
requires exogenous insulin for survival. Hyperglycemia causes long-term clinical problems, including renal failure, retinopathy, neuropathy and heart disease which in turn cause substantial disability and shorten lifespan [1]. Prevalence of T1D in Asian populations is very low (0.4 1.1 cases/year/100,000 individuals) as compared with
* Corresponding authors at: ASAB, National University of Sciences and Technology, Sector H-12, Islamabad, Pakistan. Tel.: +0092 3326983838; fax: +92 51 90851302. E-mail addresses: [email protected] (A.K. Kiani), [email protected] (P. John). http://dx.doi.org/10.1016/j.diabres.2015.01.022 0168-8227/# 2015 Elsevier Ireland Ltd. All rights reserved.
Please cite this article in press as: Kiani AK, et al. Association of 32 type 1 diabetes risk loci in Pakistani patients. Diabetes Res Clin Pract (2015), http://dx.doi.org/10.1016/j.diabres.2015.01.022
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Caucasian populations (more than 20 cases/year/100,000 individuals) maybe due to different frequency distribution of HLA alleles in each population. Although many autoimmune diseases affect predominantly women, rate of T1D appears to be similar in both men and women [2,3]. With the collaborated effort of WHO-DAMOND, rate of incidence of T1D in children below the age of 15 years has been registered in different parts of the world [1]. The incidence of T1D has been rising globally during the past decades, and if that trend continues, doubling of new cases of T1D in European children younger than 5 years is predicted between 2005 and 2020 [4]. Type 1 diabetes clusters in families and has a strong genetic basis as reflected by a high sibling recurrence risk ratio (lS) of 15 and a higher prevalence in monozygotic twins than in dizygotic twins [5,6]. Furthermore, siblings of T1D patients develop islet autoantibodies more frequently than their offspring or parents. Both genetic and environmental differences seem to affect the geographic distribution of T1D. Prevalence of T1D is highest in individuals of European background, intermediate in Africans and much lower in East Asians [7]. The most recently reported meta-analysis identified more than 40 T1D loci, including 18 new regions and confirming regions shared by more than one disease [7]. Candidate gene study and linkage analysis have established that HLA is the most strongly linked locus with T1D and is responsible for almost half of the relative risk for T1D [6]. Four non-HLA loci have also been identified to be associated with the risk for T1D by different candidate gene studies including INS, CTLA4, PTPN22 and IL2RA [6]. Application of genome-wide association studies (GWAS) has revealed several new genes playing role in T1D. These studies have the advantage of implementing large sample sets to increase the power to detect common variation affecting the risk. To date, most GWAS for T1D are conducted on individuals of European ancestry from the United Kingdom and North America [8,9]. Little is known about the genetic background and risk alleles of T1D in the Pakistani population. We hypothesized that there may be some sharing of susceptibility genes among different populations. Therefore, we genotyped 32 genomewide significant single-nucleotide polymorphisms (SNPs) reported in Caucasians in a Pakistani population to determine whether some of the susceptibility genes are shared between these two populations.
2.
Materials and methods
2.1.
Subjects
A total of 191 family-based and unrelated cases and controls with type 1 DM diagnosed by clinical findings and hyperglycemia and confirmed with positive antibodies against glutamic acid decarboxylase were recruited (Table 1). Family-based samples were taken from 10 different families with more than two affected individuals. All cases were clinically diagnosed and blood samples were collected with the collaboration of Pakistan Institute of Medical Sciences (PIMS) Islamabad and Fuji Foundation
Table 1 – Characteristics of Type 1 Diabetes related and unrelated samples.
Cases (n) Controls (n) Mean age (SD) Female (%)
Related individuals (n = 62)
Unrelated individuals (n = 129)
23 39 20.91 15.49 36
68 61 14.34 5.56 87
SD: standard deviation.
Hospital Rawalpindi. Healthy controls without any previous T1D history were recruited from Islamabad (Table 1). The study was approved by Institutional Review Board (IRB) ASAB NUST (Pakistan) and University of Pittsburgh Institutional Review Board (USA), and all participants provided written informed consent.
2.2.
Genotyping
DNA was extracted from whole blood using either a phenol chloroform based method or using the Fermantas Whole Blood Genomic DNA Purification kit and then quantified using Quant-iTTM PicoGreen1 ds-DNA assay kit (Life Technologies, NY, USA). Genotyping was performed using TaqMan SNP genotyping assays (Life Technologies) following manufacturer’s protocol. PCR amplification was performed in 384 well plates on dualblock Gene-Amp1 PCR system 9700 (Life Technologies) and end-point readings were performed on ABI Prism 7900HT sequences detection system instrument (Life Technologies). A total of 32 SNPs were selected for genotyping based on their reported genome-wide significant P-values and frequencies in Caucasians, which is considered as closest to the Pakistani population [10] (Table 2).
2.3.
Statistical analysis
For the calculation of allele and genotype frequencies in the unrelated sample, the allele counting method was used. Similarly chi-squared (x2) goodness-of-fit test was used to check deviation from Hardy–Weinberg equilibrium. PedCheck [11] program was used to check Mendelian inconsistencies in the pedigree data of family-based samples (http:/Watson.hgen.pitt.edu). Association of the selected and already established SNPs with T1D was examined using family case control (FamCC) software Ver 1.0 [12]. FamCC is a software designed to check the association by combining the family dataset and case/ control dataset together, but can also analyze each dataset independently [12]. Briefly, the FamCC performs three sequential steps. First, principal components are generated from the genotype data. Next, multiple linear regression on the top 10 principal components is performed for both the phenotypes and markers for the unrelated individuals, respectively. Finally, the residuals of the phenotypes and the markers are calculated based on the estimated coefficients in the linear
Please cite this article in press as: Kiani AK, et al. Association of 32 type 1 diabetes risk loci in Pakistani patients. Diabetes Res Clin Pract (2015), http://dx.doi.org/10.1016/j.diabres.2015.01.022
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Table 2 – Features of 32 selected SNPs previously confirmed in Caucasions and their reported p-values. No
Chr
Position
Nearest gene
Region
Marker
Reported p-value
MAF
1 2 3 4 5 6
1p13.2 1q32.1 2q24.2 2q33.2 4p15.2 4q27
114179091 206939904 163124051 204738919 26085511 123132492
PTPN22 IL10 IFIH1 CTLA4
Exonic Intergenic Exonic Intergenic Intergenic Intronic
rs2476601 rs3024505 rs1990760 rs3087243 rs10517086 rs4505848
5.93E 80 2.09E 08 2.21E 08 1.42E 13 4.6E 10 4.70E 13
0.042 0.091 0.367 0.324 0.219 0.336
7
32604372
Intergenic
rs9272346
2.42E 134
0.463 (G)
[1,15]
8 9 10 11 12 13 14 15 16 17 18 19 20 21
6p21 (MHC) 6q15 6q22.32 7p15.2 7p12.2 9p24.2 10p15.1 10p15.1 10q23.31 11p15.5 12q13.2 12q24.12 13q32.3 14q24.1 14q32.2
90958231 126698719 26891665 50477213 4291747 6472891 6390450 90023033 2182224 56482180 111884608 100081766 69263599 101306045
Intronic Intronic Intronic Intergenic Intronic Exonic (Arg-Arg) Intergenic Intergenic Intronic Intronic Exonic (Trp-Arg) Intergenic Intergenic Intronic
rs11755527 rs9388489 rs7804356 rs10272724 rs7020673 rs11258747 rs947474 rs10509540 rs689 rs2292239 rs3184504 rs9585056 rs1465788 rs941576
5.4E 08 4.2E 13 5.3E 09 1.4E 06 5.4E 12 1.2E 07 3.65E 09 1.3E 28 3.8E 31 2.22E 25 1.77E 21 1.27E 03 1.8E 12 9.33E 05
0.377 0.439 0.172 0.216 0.401 0.132 0.200 0.236 0.335 0.334 0.218 0.247 0.290 0.413
(G) (A) (C) (C) (C) (T) (G) (C) (A) (T) (T) (C) (T) (G)
[8] [8,22] [8,22] [1,21] [1,8] [1,8,22] [1,19] [1,8,22] [1,23] [1,8] [8,22] [22] [1,8,22] [1,22]
22 23 24 25 26 27 28 29 30 31 32
15q14 16p13.13 16p11.2 16q23.1 17q12 18p11.2 18q22.2 19p13.2 19q13.32 20p13 22q12.2
79235446 11179873 28539848 75247245 38066240 12835976 67531642 10475652 47208481 1610551 30581722
Intronic Intronic Intergenic Intergenic Intronic Intronic Exonic (Ser-Gly) Exonic (Val-Phe) Intronic Intronic Intergenic
rs3825932 rs12708716 rs4788084 rs7202877 rs2290400 rs478582 rs763361 rs2304256 rs425105 rs2281808 rs5753037
7.7E 08 2.2E 16 2.6E 13 3.1E 15 5.5E 13 7.72E 04 1.38E 08 4.13E 09 2.7E 11 1.20E 11 2.6E 16
0.370 0.328 0.310 0.143 0.447 0.300 0.492 0.287 0.154 0.257 0.366
(C) (G) (T) (G) (C) (C) (C) (A) (C) (T) (T)
[1,8,19,22] [1,8,15] [1,8,22] [1,8,22] [1,8,22] [14,22] [1,8,14] [22,24] [1,8,22] [1,8,22] [1,8,22]
KIAA1109 (near IL2) HLA-DQA1 BACH2 C6orf173 SKAP2 IKZF1 GLIS3 PRKCQ DKFZp667F0711 RNLS INS (INS-IGF2) ERBB3 SH2B3 GPR183 ZFP36L1 MEG3 (near DLK1) CTSH CLEC16A IL27 CTRB2 GSDMB PTPN2 CD226 TYK2 PRKD2 SIRPG LOC729980
References (A) (A) (T) (A) (A) (G)
[22] [22] [22] [15,22] [8,22] [8]
Chr: Chromosome; MAF: Minor allele frequency.
mode in the second step, and then association between the phenotype and genotype is assessed by testing the correlations between these residuals using the following statistics: T2 S2 ¼ VarðTÞ P PN f PNc þNd T þ i¼1 Ti , and Nf is the number of where T ¼ N i¼1 T ¼ i¼1 i nuclear families; Nc and Nd are the number of unrelated controls and cases, respectively. Ti, the statistic of the ith family, is Pki gi j yi j , ki is the number of individuals defined by Ti ¼ 1=ki j¼1 of the family. For unrelated individuals, ki=1. The variance of T PN f 2 Ti T2 þ Nc þ Nd is defined by VarðTÞ ¼ N f = N f 1 i¼1 2 PNc þNd =ðNc þ Nd 1Þ i¼1 Ti T1 . T1 and T2 are the mean of Ti of unrelated and family data sets, respectively. A nominal P value of less than 0.05 was considered statistically significant.
3.
Results
A total of 191 family-based and unrelated T1D case/control subjects were recruited for this study. Gender based comparison in our sample showed almost dominance of women (64%) as compared to men, although previous studies also show
male dominance in some parts of Pakistan [13]. 46% of patients developed disease during 5-10 years of age (Fig. 1). Both family based and unrelated samples were genotyped for 32 T1D susceptibility variants established in Caucasians (Table 2). In the unrelated cases/control sample, all SNPs were found to be in Hardy–Weinberg equilibrium. Similarly, the family-based samples showed Mendelian consistency. We examined the family-based data and unrelated case/control data both combined and separately (Table 3). For the combined analysis of the family-based and unrelated samples, we used FamCC software [12]. The most significantly associated SNP in our study was rs9272346 ( p = 2.83E 09) in the HLA-DQA1 region of 6p21. Two other SNPs, ERBB3/rs2292239 (12q13) and SIRPG/ rs2281808 (20p13), have also shown significant association at p < 1E 06 ( p = 1.56E 07 and 3.22E 07, respectively). Three more susceptibility loci, IL2/rs4505848 at 4q27, GLIS3/rs7020673 at 9q24.2, and CD226/rs763361 at 18q22.2, proved to be significantly associated with T1D at p < 1E 04 ( p = 2.25E 05, p = 5.29E 05, and p = 6.62E 05, respectively) in our Pakistani sample. On the seventh intron of PTPN2 (encoding T-cell protein tyrosine phosphatase) at 18p11, the rs478582 SNP was also significantly associated with T1D in our sample ( p = 1.64E 04), followed by IKF1/rs10272724 at 7p12.2
Please cite this article in press as: Kiani AK, et al. Association of 32 type 1 diabetes risk loci in Pakistani patients. Diabetes Res Clin Pract (2015), http://dx.doi.org/10.1016/j.diabres.2015.01.022
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factors for T1D as well as to identify the causal variants that can trigger T1D [4]. The objective of this study was to replicate the T1D genome-wide significant SNPs previously identified in European-derived populations in Pakistani population. We examined a total of 32 SNPs in a mixed Pakistani sample comprising family-based and sporadic cases and controls, and we performed both separate and combined analyses of our related and unrelated samples. Although our unrelated sample showed relatively higher p-values as compared to our family based sample, this was probably due to small sample size [14]. Despite our relatively small sample size, we were able to replicate the association of 15 of 32 T1D SNPs in combined analysis of our related and unrelated Pakistani individuals ( p < 0.05) (Table 3, Fig. 2). The most significantly associated T1D SNP in our study was rs9272346 residing in 50 upstream of HLA-DQA1 on chromosome 6p21 with combined p = 2.83E 09. Same SNP has also shown the most significant association with T1D in GWAS conducted by Welcome Trust Case Control Constorium WTCCC ( p = 2.42E 134) [15]. According to an estimation HLA locus provides up to 40–50% of familial clustering of T1D [16]. Overall, HLA class II genes show the strongest genetic association with T1D. The alleles of HLA-DQA1, DQB1 and DRB1 are all involved in the genetic predisposition towards T1D. However due to strong and extended LD at the HLA locus, it has been difficult to determine individual effects of HLA genes [17]. A study conducted by Awata et al. in the Japanese population exhibits closely resembling association results to our study [18]. They have investigated the association of two loci, ERBB3 at 12q13 and CLEC16A at 16p13. Their study has showed that ERBB3 had more significant association with T1D than CLEC16A ( p = 0.001 vs. p = 0.030). Although we have selected different SNPs from these particular regions, our results still showed a similar pattern of association in Pakistani population such that ERBB3 had a significant association with T1D (combined p = 1.56E 07) whereas
Fig. 1 – Trends of age of onset in T1D individuals.
( p = 8.57E 04), BACH2/rs11755527 at 6q15 ( p = 3.47E 03), and C6orf173/rs9388489 at 6q22.32 ( p = 5.05E 03). Five other SNPs included in this study showed association with T1D at 0.01 < p < 0.05; ZFP36L1/rs1465788 ( p = 1.97E 02), GSDMB/rs2290400 ( p = 2.65E 02), DKFZp667F0711/rs947474 ( p = 3.75E 02), IL27/rs4788084 ( p = 4.11E 02), CTSH/rs3825932 ( p = 4.39E 02). Additional details on these SNPs and their associations in family based and unrelated samples using separate and combined analyses are given in Table 3.
4.
Discussion
Most GWAS of T1D have been conducted in Europeans and North Americans. These studies have resulted in the identification of more than 40 T1D risk loci. Replication studies for these loci are necessary in various populations in order to understand population based differences in genetic risk
Table 3 – Replication of previously reported T1D risk loci among Pakistanis. Genes
HLA-DQA1 ERBB3 SIRPG IL2 GLIS3 CD226 PTPN2 IKZF1 BACH2 C6orf173 ZFP36L1 GSDMB DKFZp667F0711 IL27 CTSH a b
Chr
6p21 12q13.2 20p13 4q27 9p24.2 18q22.2 18p11.2 7p12.2 6q15 6q22.32 14q24.1 17q12 10p15.1 16p11.2 15q14
SNPs
rs9272346 rs2292239 rs2281808 rs4505848 rs7020673 rs763361 rs478582 rs10272724 rs11755527 rs9388489 rs1465788 rs2290400 rs947474 rs4788084 rs3825932
Minor Allele
G T T G C C C C G A T T G G T
Unrelated sample
Family sample
F_Aa
F_Ub
F_A
F_U
0.15 0.27 0.12 0.3 0.45 0.49 0.31 0.35 0.46 0.34 0.33 0.47 0.13 0.24 0.33
0.53 0.28 0.21 0.34 0.45 0.48 0.27 0.33 0.36 0.37 0.29 0.49 0.18 0.21 0.34
0.23 0.34 0.13 0.2 0.46 0.43 0.13 0.2 0.45 0.61 0.26 0.34 0.2 0.26 0.41
0.39 0.35 0.14 0.25 0.46 0.46 0.12 0.22 0.49 0.41 0.24 0.41 0.24 0.19 0.4
Unrelated sample
Family sample
Combined
p-Value
p-Value
p-Value
3.01E 01 6.63E 02 7.79E 01 9.22E 01 8.13E 01 2.85E 01 3.96E 01 8.70E 01 6.87E 01 1.88E 01 4.36E 01 9.47E 01 5.65E 01 8.24E 01 5.90E 01
2.17E 04 7.05E 04 7.88E 04 1.96E 03 1.04E 03 1.23E 02 1.20E 02 5.40E 03 1.06E 02 1.28E 04 6.90E 02 2.86E 03 5.42E 03 1.80E 02 6.04E 04
2.83E 09 1.56E 07 3.22E 07 2.25E 05 5.29E 05 6.62E 05 1.64E 04 8.57E 04 3.47E 03 5.05E 03 1.97E 02 2.65E 02 3.75E 02 4.11E 02 4.39E 02
F_A: minor allele frequency in cases. F_U: minor allele frequency in controls.
Please cite this article in press as: Kiani AK, et al. Association of 32 type 1 diabetes risk loci in Pakistani patients. Diabetes Res Clin Pract (2015), http://dx.doi.org/10.1016/j.diabres.2015.01.022
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5
small sample size may cause difficulty in statistical analysis and maybe the cause of lack of replication of some already reported loci but as type 1 diabetes is a rare disorder in Pakistani population and difficult to diagnose hence expected sample size is not very large [13], although population-specific differences and/or environmental interactions could also be contributing to this observation. The results of our research suggest that more studies with larger sample sizes must be designed and conducted in Pakistani population. Functional studies are also necessary to further characterize confirmed T1D loci/genes, which in turn would reveal the pathways and early precursors or biomarkers underlying the pathogenesis of type 1 diabetes.
5.
Fig. 2 – Association of T1D SNPs in Pakistani subjects.
CLEC16A revealed only a marginal p-value ( p = 2.00E 01). The data from previous studies as well as our results, suggest that these genes or regions contribute to T1D susceptibility across different ethnic groups with ERBB3 having a stronger effect than CLEC16A. The third most significantly associated SNP rs2281808 (combined p = 3.22E 07) is located in an intronic region of SIRPG gene at 20p13. Barrett et al. reported p = 1.20E 11 in their meta-analysis for the association of this SNP with T1D [8]. Our study set from Pakistani population showed a more positive association that might be attributed to difference in our gene pool. Three more susceptibility loci, IL2/rs4505848 at 4q27, GLIS3/ rs7020673 at 9q24.2 and CD226/rs763361 at 18q22.2, showed significant association at combined p < 1E 04 ( p = 2.25E 05, p = 5.29E 05 and p = 6.62E 05, respectively) with T1D in our study sample from Pakistani population, consistent with the findings of Cooper et al. and/or Barrett et al. [8,19,20]. These findings further support that in spite of different ethnic background and geographical differences, there is still sharing of T1D susceptibility loci between populations. SNP rs478582, located in the seventh intron of PTPN2 (encoding T-cell protein tyrosine phosphatase) at 18p11, was reported to be strongly and independently associated with T1D by Todd et al. [14]. We have similarly found this SNP to be significantly associated with T1D with a combined p-value of 1.64E 04 in our sample. Three other SNPs, rs10272724/IKF1 on chromosome 7p12.2, rs11755527/BACH2 on chromosome 6q15 and rs9388489/ C6orf173 on chromosome 6q22.32, have followed the same trend of association in our study set of Pakistani population ( p < 1E 02) as reported previously by Swafford et al. or Cooper et al. and/or Barrett et al. [8,20,21]. In summary, our study has replicated several, but not all, previously reported European T1D susceptibility loci in Pakistani population, suggesting the presence of a number of shared loci between these two ethnic groups. Although
Conclusion
To our knowledge, this is the first genetic association study of T1D GWAS SNPs in a Pakistani population. Our study provides evidence of several T1D risk loci in Pakistani subjects, i.e. HLA, ERBB3, SIRPG, IL2, GLIS3, CD226, PTPN2, and suggests that a number of T1D loci are shared between Caucasians and Pakistanis. Further studies are required to correlate T1D risk alleles and haplotypes with expression of genes at RNA and protein level, which in turn would lead to the identification of causal genes in associated regions. Identification of causative variants/genes would then reveal the pathways and early precursors or biomarkers underlying the pathogenesis of type 1 diabetes.
Funding sources Funds are provided Grant No: 117-6919-bm7-003 by Higher Education Commission, Islamabad, Pakistan.
Conflict of interest statement All the authors declared that they have no competing interests.
Acknowledgements We are thankful to Higher Education Commission for supporting this study within the country and abroad. We are thankful to all the physicians for referring the patients and their supporting staff who helped with the collection of blood samples. We thank all the patients, control individual and their family members for their participation and cooperation in this study. Help and reviews provided by Samantha Rosenthal and Amnah Siddiqa are also appreciated.
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[14] Todd JA, Walker NM, Cooper JD, Smyth DJ, Downes K, Plagnol V, et al. Robust associations of four new chromosome regions from genome-wide analyses of type 1 diabetes. Nat Genet 2007;39:857–64. [15] Genome-wide association. Genome-wide association study of 14,000 cases of seven common diseases and 3000 shared controls. Nature 2007;447:661–78. [16] Al-Jenaidi FA, Wakim-Ghorayeb SF, Al-Abbasi A, Arekat MR, Irani-Hakime N, Najm P, et al. Contribution of selective HLA-DRB1/DQB1 alleles and haplotypes to the genetic susceptibility of type 1 diabetes among Lebanese and Bahraini Arabs. J Clin Endocrinol Metab 2005;90:5104–9. [17] Erlich H, Valdes AM, Noble J, Carlson JA, Varney M, Concannon P, et al. HLA DR-DQ haplotypes and genotypes and type 1 diabetes risk: analysis of the type 1 diabetes genetics consortium families. Diabetes 2008;57:1084–92. [18] Awata T, Kawasaki E, Tanaka S, Ikegami H, Maruyama T, Shimada A, et al. Association of type 1 diabetes with two Loci on 12q13 and 16p13 and the influence coexisting thyroid autoimmunity in Japanese. J Clin Endocrinol Metab 2009;94:231–5. [19] Cooper JD, Smyth DJ, Smiles AM, Plagnol V, Walker NM, Allen JE, et al. Meta-analysis of genome-wide association study data identifies additional type 1 diabetes risk loci. Nat Genet 2008;40:1399–401. [20] Cooper JD, Howson JM, Smyth D, Walker NM, Stevens H, Yang JH, et al. Confirmation of novel type 1 diabetes risk loci in families. Diabetologia 2012;55:996–1000. [21] Swafford AD, Howson JM, Davison LJ, Wallace C, Smyth DJ, Schuilenburg H, et al. An allele of IKZF1 (Ikaros) conferring susceptibility to childhood acute lymphoblastic leukemia protects against type 1 diabetes. Diabetes 2011;60:1041–4. [22] Bradfield JP, Qu HQ, Wang K, Zhang H, Sleiman PM, Kim CE, et al. A genome-wide meta-analysis of six type 1 diabetes cohorts identifies multiple associated loci. PLoS Genet 2011;7:e1002293. [23] Howson JM, Walker NM, Smyth DJ, Todd JA. Analysis of 19 genes for association with type I diabetes in the Type I Diabetes Genetics Consortium families. Genes Immun 2009;10(Suppl 1):S74–84. [24] Wallace C, Smyth DJ, Maisuria-Armer M, Walker NM, Todd JA, Clayton DG. The imprinted DLK1-MEG3 gene region on chromosome 14q32.2 alters susceptibility to type 1 diabetes. Nat Genet 2010;42:68–71.
Please cite this article in press as: Kiani AK, et al. Association of 32 type 1 diabetes risk loci in Pakistani patients. Diabetes Res Clin Pract (2015), http://dx.doi.org/10.1016/j.diabres.2015.01.022
Contents available at ScienceDirect
Diabetes Research and Clinical Practice journ al h ome pa ge : www .elsevier.co m/lo cate/diabres
Association of 32 type 1 diabetes risk loci in Pakistani patients Aysha Karim Kiani a,*, Peter John a,*, Attya Bhatti a, Asima Zia a, Gulbin Shahid b, Parveen Akhtar c, Xingbin Wang d, F. Yesim Demirci d, M. Ilyas Kamboh d a Department of Healthcare Biotechnology, Atta-ur-Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), Islamabad, Pakistan b Pakistan Institute of Medical Sciences (PIMS), Islamabad, Pakistan c Fauji Foundation Hospital, Rawalpindi, Pakistan d Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA
article info
abstract
Article history:
Aim: To identify risk alleles contributing towards type 1 diabetes in Pakistani patients.
Received 27 August 2014
Introduction: Type 1 diabetes (T1D) is an autoimmune disease which is caused by destruction
Received in revised form
of insulin producing b cells by immune system. Genetic predisposition as well as environ-
15 November 2014
mental factors contribute to its etiology. To date more than 40 risk loci have been identified
Accepted 3 January 2015
for T1D.
Available online xxx
Methodology: A total of 191 family-based and unrelated T1D cases and controls were
Keywords:
phisms (SNPs) previously reported in Europeans were genotyped. Genotyping was per-
recruited. DNA was extracted and 32 genome-wide significant single nucleotide polymorDiabetes
formed using TaqMan SNP genotyping assays and the data was analyzed using FamCC
Type 1 diabetes
software.
Auto-immune disease
Results: Our results showed significant association of 10 single nucleotide polymorphisms
Association studies
(SNPs) with T1D at p < 0.01, including HLA-DQA1/rs9272346, ERBB3/rs2292239, SIRPG/
Diabetes in Pakistan
rs2281808, IL2-KIAA1109/rs4505848, GLIS3/rs7020673, CD226/rs763361, PTPN2/rs478582,
Insulin dependent diabetes mellitus
IKZF1/rs10272724, BACH2/rs11755527, C6orf173/rs9388489, whereas 5 more SNPs showed their association at 0.01 < p < 0.05 in Pakistani population. Conclusion: We have replicated many of the T1D loci established among Europeans in a Pakistani population. # 2015 Elsevier Ireland Ltd. All rights reserved.
1.
Introduction
The hallmark of type 1 diabetes (T1D) is its origin due to autoimmune processes that destroy the insulin producing b cells. Beta cell destruction result in hyperglycemia, which
requires exogenous insulin for survival. Hyperglycemia causes long-term clinical problems, including renal failure, retinopathy, neuropathy and heart disease which in turn cause substantial disability and shorten lifespan [1]. Prevalence of T1D in Asian populations is very low (0.4 1.1 cases/year/100,000 individuals) as compared with
* Corresponding authors at: ASAB, National University of Sciences and Technology, Sector H-12, Islamabad, Pakistan. Tel.: +0092 3326983838; fax: +92 51 90851302. E-mail addresses: [email protected] (A.K. Kiani), [email protected] (P. John). http://dx.doi.org/10.1016/j.diabres.2015.01.022 0168-8227/# 2015 Elsevier Ireland Ltd. All rights reserved.
Please cite this article in press as: Kiani AK, et al. Association of 32 type 1 diabetes risk loci in Pakistani patients. Diabetes Res Clin Pract (2015), http://dx.doi.org/10.1016/j.diabres.2015.01.022
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Caucasian populations (more than 20 cases/year/100,000 individuals) maybe due to different frequency distribution of HLA alleles in each population. Although many autoimmune diseases affect predominantly women, rate of T1D appears to be similar in both men and women [2,3]. With the collaborated effort of WHO-DAMOND, rate of incidence of T1D in children below the age of 15 years has been registered in different parts of the world [1]. The incidence of T1D has been rising globally during the past decades, and if that trend continues, doubling of new cases of T1D in European children younger than 5 years is predicted between 2005 and 2020 [4]. Type 1 diabetes clusters in families and has a strong genetic basis as reflected by a high sibling recurrence risk ratio (lS) of 15 and a higher prevalence in monozygotic twins than in dizygotic twins [5,6]. Furthermore, siblings of T1D patients develop islet autoantibodies more frequently than their offspring or parents. Both genetic and environmental differences seem to affect the geographic distribution of T1D. Prevalence of T1D is highest in individuals of European background, intermediate in Africans and much lower in East Asians [7]. The most recently reported meta-analysis identified more than 40 T1D loci, including 18 new regions and confirming regions shared by more than one disease [7]. Candidate gene study and linkage analysis have established that HLA is the most strongly linked locus with T1D and is responsible for almost half of the relative risk for T1D [6]. Four non-HLA loci have also been identified to be associated with the risk for T1D by different candidate gene studies including INS, CTLA4, PTPN22 and IL2RA [6]. Application of genome-wide association studies (GWAS) has revealed several new genes playing role in T1D. These studies have the advantage of implementing large sample sets to increase the power to detect common variation affecting the risk. To date, most GWAS for T1D are conducted on individuals of European ancestry from the United Kingdom and North America [8,9]. Little is known about the genetic background and risk alleles of T1D in the Pakistani population. We hypothesized that there may be some sharing of susceptibility genes among different populations. Therefore, we genotyped 32 genomewide significant single-nucleotide polymorphisms (SNPs) reported in Caucasians in a Pakistani population to determine whether some of the susceptibility genes are shared between these two populations.
2.
Materials and methods
2.1.
Subjects
A total of 191 family-based and unrelated cases and controls with type 1 DM diagnosed by clinical findings and hyperglycemia and confirmed with positive antibodies against glutamic acid decarboxylase were recruited (Table 1). Family-based samples were taken from 10 different families with more than two affected individuals. All cases were clinically diagnosed and blood samples were collected with the collaboration of Pakistan Institute of Medical Sciences (PIMS) Islamabad and Fuji Foundation
Table 1 – Characteristics of Type 1 Diabetes related and unrelated samples.
Cases (n) Controls (n) Mean age (SD) Female (%)
Related individuals (n = 62)
Unrelated individuals (n = 129)
23 39 20.91 15.49 36
68 61 14.34 5.56 87
SD: standard deviation.
Hospital Rawalpindi. Healthy controls without any previous T1D history were recruited from Islamabad (Table 1). The study was approved by Institutional Review Board (IRB) ASAB NUST (Pakistan) and University of Pittsburgh Institutional Review Board (USA), and all participants provided written informed consent.
2.2.
Genotyping
DNA was extracted from whole blood using either a phenol chloroform based method or using the Fermantas Whole Blood Genomic DNA Purification kit and then quantified using Quant-iTTM PicoGreen1 ds-DNA assay kit (Life Technologies, NY, USA). Genotyping was performed using TaqMan SNP genotyping assays (Life Technologies) following manufacturer’s protocol. PCR amplification was performed in 384 well plates on dualblock Gene-Amp1 PCR system 9700 (Life Technologies) and end-point readings were performed on ABI Prism 7900HT sequences detection system instrument (Life Technologies). A total of 32 SNPs were selected for genotyping based on their reported genome-wide significant P-values and frequencies in Caucasians, which is considered as closest to the Pakistani population [10] (Table 2).
2.3.
Statistical analysis
For the calculation of allele and genotype frequencies in the unrelated sample, the allele counting method was used. Similarly chi-squared (x2) goodness-of-fit test was used to check deviation from Hardy–Weinberg equilibrium. PedCheck [11] program was used to check Mendelian inconsistencies in the pedigree data of family-based samples (http:/Watson.hgen.pitt.edu). Association of the selected and already established SNPs with T1D was examined using family case control (FamCC) software Ver 1.0 [12]. FamCC is a software designed to check the association by combining the family dataset and case/ control dataset together, but can also analyze each dataset independently [12]. Briefly, the FamCC performs three sequential steps. First, principal components are generated from the genotype data. Next, multiple linear regression on the top 10 principal components is performed for both the phenotypes and markers for the unrelated individuals, respectively. Finally, the residuals of the phenotypes and the markers are calculated based on the estimated coefficients in the linear
Please cite this article in press as: Kiani AK, et al. Association of 32 type 1 diabetes risk loci in Pakistani patients. Diabetes Res Clin Pract (2015), http://dx.doi.org/10.1016/j.diabres.2015.01.022
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Table 2 – Features of 32 selected SNPs previously confirmed in Caucasions and their reported p-values. No
Chr
Position
Nearest gene
Region
Marker
Reported p-value
MAF
1 2 3 4 5 6
1p13.2 1q32.1 2q24.2 2q33.2 4p15.2 4q27
114179091 206939904 163124051 204738919 26085511 123132492
PTPN22 IL10 IFIH1 CTLA4
Exonic Intergenic Exonic Intergenic Intergenic Intronic
rs2476601 rs3024505 rs1990760 rs3087243 rs10517086 rs4505848
5.93E 80 2.09E 08 2.21E 08 1.42E 13 4.6E 10 4.70E 13
0.042 0.091 0.367 0.324 0.219 0.336
7
32604372
Intergenic
rs9272346
2.42E 134
0.463 (G)
[1,15]
8 9 10 11 12 13 14 15 16 17 18 19 20 21
6p21 (MHC) 6q15 6q22.32 7p15.2 7p12.2 9p24.2 10p15.1 10p15.1 10q23.31 11p15.5 12q13.2 12q24.12 13q32.3 14q24.1 14q32.2
90958231 126698719 26891665 50477213 4291747 6472891 6390450 90023033 2182224 56482180 111884608 100081766 69263599 101306045
Intronic Intronic Intronic Intergenic Intronic Exonic (Arg-Arg) Intergenic Intergenic Intronic Intronic Exonic (Trp-Arg) Intergenic Intergenic Intronic
rs11755527 rs9388489 rs7804356 rs10272724 rs7020673 rs11258747 rs947474 rs10509540 rs689 rs2292239 rs3184504 rs9585056 rs1465788 rs941576
5.4E 08 4.2E 13 5.3E 09 1.4E 06 5.4E 12 1.2E 07 3.65E 09 1.3E 28 3.8E 31 2.22E 25 1.77E 21 1.27E 03 1.8E 12 9.33E 05
0.377 0.439 0.172 0.216 0.401 0.132 0.200 0.236 0.335 0.334 0.218 0.247 0.290 0.413
(G) (A) (C) (C) (C) (T) (G) (C) (A) (T) (T) (C) (T) (G)
[8] [8,22] [8,22] [1,21] [1,8] [1,8,22] [1,19] [1,8,22] [1,23] [1,8] [8,22] [22] [1,8,22] [1,22]
22 23 24 25 26 27 28 29 30 31 32
15q14 16p13.13 16p11.2 16q23.1 17q12 18p11.2 18q22.2 19p13.2 19q13.32 20p13 22q12.2
79235446 11179873 28539848 75247245 38066240 12835976 67531642 10475652 47208481 1610551 30581722
Intronic Intronic Intergenic Intergenic Intronic Intronic Exonic (Ser-Gly) Exonic (Val-Phe) Intronic Intronic Intergenic
rs3825932 rs12708716 rs4788084 rs7202877 rs2290400 rs478582 rs763361 rs2304256 rs425105 rs2281808 rs5753037
7.7E 08 2.2E 16 2.6E 13 3.1E 15 5.5E 13 7.72E 04 1.38E 08 4.13E 09 2.7E 11 1.20E 11 2.6E 16
0.370 0.328 0.310 0.143 0.447 0.300 0.492 0.287 0.154 0.257 0.366
(C) (G) (T) (G) (C) (C) (C) (A) (C) (T) (T)
[1,8,19,22] [1,8,15] [1,8,22] [1,8,22] [1,8,22] [14,22] [1,8,14] [22,24] [1,8,22] [1,8,22] [1,8,22]
KIAA1109 (near IL2) HLA-DQA1 BACH2 C6orf173 SKAP2 IKZF1 GLIS3 PRKCQ DKFZp667F0711 RNLS INS (INS-IGF2) ERBB3 SH2B3 GPR183 ZFP36L1 MEG3 (near DLK1) CTSH CLEC16A IL27 CTRB2 GSDMB PTPN2 CD226 TYK2 PRKD2 SIRPG LOC729980
References (A) (A) (T) (A) (A) (G)
[22] [22] [22] [15,22] [8,22] [8]
Chr: Chromosome; MAF: Minor allele frequency.
mode in the second step, and then association between the phenotype and genotype is assessed by testing the correlations between these residuals using the following statistics: T2 S2 ¼ VarðTÞ P PN f PNc þNd T þ i¼1 Ti , and Nf is the number of where T ¼ N i¼1 T ¼ i¼1 i nuclear families; Nc and Nd are the number of unrelated controls and cases, respectively. Ti, the statistic of the ith family, is Pki gi j yi j , ki is the number of individuals defined by Ti ¼ 1=ki j¼1 of the family. For unrelated individuals, ki=1. The variance of T PN f 2 Ti T2 þ Nc þ Nd is defined by VarðTÞ ¼ N f = N f 1 i¼1 2 PNc þNd =ðNc þ Nd 1Þ i¼1 Ti T1 . T1 and T2 are the mean of Ti of unrelated and family data sets, respectively. A nominal P value of less than 0.05 was considered statistically significant.
3.
Results
A total of 191 family-based and unrelated T1D case/control subjects were recruited for this study. Gender based comparison in our sample showed almost dominance of women (64%) as compared to men, although previous studies also show
male dominance in some parts of Pakistan [13]. 46% of patients developed disease during 5-10 years of age (Fig. 1). Both family based and unrelated samples were genotyped for 32 T1D susceptibility variants established in Caucasians (Table 2). In the unrelated cases/control sample, all SNPs were found to be in Hardy–Weinberg equilibrium. Similarly, the family-based samples showed Mendelian consistency. We examined the family-based data and unrelated case/control data both combined and separately (Table 3). For the combined analysis of the family-based and unrelated samples, we used FamCC software [12]. The most significantly associated SNP in our study was rs9272346 ( p = 2.83E 09) in the HLA-DQA1 region of 6p21. Two other SNPs, ERBB3/rs2292239 (12q13) and SIRPG/ rs2281808 (20p13), have also shown significant association at p < 1E 06 ( p = 1.56E 07 and 3.22E 07, respectively). Three more susceptibility loci, IL2/rs4505848 at 4q27, GLIS3/rs7020673 at 9q24.2, and CD226/rs763361 at 18q22.2, proved to be significantly associated with T1D at p < 1E 04 ( p = 2.25E 05, p = 5.29E 05, and p = 6.62E 05, respectively) in our Pakistani sample. On the seventh intron of PTPN2 (encoding T-cell protein tyrosine phosphatase) at 18p11, the rs478582 SNP was also significantly associated with T1D in our sample ( p = 1.64E 04), followed by IKF1/rs10272724 at 7p12.2
Please cite this article in press as: Kiani AK, et al. Association of 32 type 1 diabetes risk loci in Pakistani patients. Diabetes Res Clin Pract (2015), http://dx.doi.org/10.1016/j.diabres.2015.01.022
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factors for T1D as well as to identify the causal variants that can trigger T1D [4]. The objective of this study was to replicate the T1D genome-wide significant SNPs previously identified in European-derived populations in Pakistani population. We examined a total of 32 SNPs in a mixed Pakistani sample comprising family-based and sporadic cases and controls, and we performed both separate and combined analyses of our related and unrelated samples. Although our unrelated sample showed relatively higher p-values as compared to our family based sample, this was probably due to small sample size [14]. Despite our relatively small sample size, we were able to replicate the association of 15 of 32 T1D SNPs in combined analysis of our related and unrelated Pakistani individuals ( p < 0.05) (Table 3, Fig. 2). The most significantly associated T1D SNP in our study was rs9272346 residing in 50 upstream of HLA-DQA1 on chromosome 6p21 with combined p = 2.83E 09. Same SNP has also shown the most significant association with T1D in GWAS conducted by Welcome Trust Case Control Constorium WTCCC ( p = 2.42E 134) [15]. According to an estimation HLA locus provides up to 40–50% of familial clustering of T1D [16]. Overall, HLA class II genes show the strongest genetic association with T1D. The alleles of HLA-DQA1, DQB1 and DRB1 are all involved in the genetic predisposition towards T1D. However due to strong and extended LD at the HLA locus, it has been difficult to determine individual effects of HLA genes [17]. A study conducted by Awata et al. in the Japanese population exhibits closely resembling association results to our study [18]. They have investigated the association of two loci, ERBB3 at 12q13 and CLEC16A at 16p13. Their study has showed that ERBB3 had more significant association with T1D than CLEC16A ( p = 0.001 vs. p = 0.030). Although we have selected different SNPs from these particular regions, our results still showed a similar pattern of association in Pakistani population such that ERBB3 had a significant association with T1D (combined p = 1.56E 07) whereas
Fig. 1 – Trends of age of onset in T1D individuals.
( p = 8.57E 04), BACH2/rs11755527 at 6q15 ( p = 3.47E 03), and C6orf173/rs9388489 at 6q22.32 ( p = 5.05E 03). Five other SNPs included in this study showed association with T1D at 0.01 < p < 0.05; ZFP36L1/rs1465788 ( p = 1.97E 02), GSDMB/rs2290400 ( p = 2.65E 02), DKFZp667F0711/rs947474 ( p = 3.75E 02), IL27/rs4788084 ( p = 4.11E 02), CTSH/rs3825932 ( p = 4.39E 02). Additional details on these SNPs and their associations in family based and unrelated samples using separate and combined analyses are given in Table 3.
4.
Discussion
Most GWAS of T1D have been conducted in Europeans and North Americans. These studies have resulted in the identification of more than 40 T1D risk loci. Replication studies for these loci are necessary in various populations in order to understand population based differences in genetic risk
Table 3 – Replication of previously reported T1D risk loci among Pakistanis. Genes
HLA-DQA1 ERBB3 SIRPG IL2 GLIS3 CD226 PTPN2 IKZF1 BACH2 C6orf173 ZFP36L1 GSDMB DKFZp667F0711 IL27 CTSH a b
Chr
6p21 12q13.2 20p13 4q27 9p24.2 18q22.2 18p11.2 7p12.2 6q15 6q22.32 14q24.1 17q12 10p15.1 16p11.2 15q14
SNPs
rs9272346 rs2292239 rs2281808 rs4505848 rs7020673 rs763361 rs478582 rs10272724 rs11755527 rs9388489 rs1465788 rs2290400 rs947474 rs4788084 rs3825932
Minor Allele
G T T G C C C C G A T T G G T
Unrelated sample
Family sample
F_Aa
F_Ub
F_A
F_U
0.15 0.27 0.12 0.3 0.45 0.49 0.31 0.35 0.46 0.34 0.33 0.47 0.13 0.24 0.33
0.53 0.28 0.21 0.34 0.45 0.48 0.27 0.33 0.36 0.37 0.29 0.49 0.18 0.21 0.34
0.23 0.34 0.13 0.2 0.46 0.43 0.13 0.2 0.45 0.61 0.26 0.34 0.2 0.26 0.41
0.39 0.35 0.14 0.25 0.46 0.46 0.12 0.22 0.49 0.41 0.24 0.41 0.24 0.19 0.4
Unrelated sample
Family sample
Combined
p-Value
p-Value
p-Value
3.01E 01 6.63E 02 7.79E 01 9.22E 01 8.13E 01 2.85E 01 3.96E 01 8.70E 01 6.87E 01 1.88E 01 4.36E 01 9.47E 01 5.65E 01 8.24E 01 5.90E 01
2.17E 04 7.05E 04 7.88E 04 1.96E 03 1.04E 03 1.23E 02 1.20E 02 5.40E 03 1.06E 02 1.28E 04 6.90E 02 2.86E 03 5.42E 03 1.80E 02 6.04E 04
2.83E 09 1.56E 07 3.22E 07 2.25E 05 5.29E 05 6.62E 05 1.64E 04 8.57E 04 3.47E 03 5.05E 03 1.97E 02 2.65E 02 3.75E 02 4.11E 02 4.39E 02
F_A: minor allele frequency in cases. F_U: minor allele frequency in controls.
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5
small sample size may cause difficulty in statistical analysis and maybe the cause of lack of replication of some already reported loci but as type 1 diabetes is a rare disorder in Pakistani population and difficult to diagnose hence expected sample size is not very large [13], although population-specific differences and/or environmental interactions could also be contributing to this observation. The results of our research suggest that more studies with larger sample sizes must be designed and conducted in Pakistani population. Functional studies are also necessary to further characterize confirmed T1D loci/genes, which in turn would reveal the pathways and early precursors or biomarkers underlying the pathogenesis of type 1 diabetes.
5.
Fig. 2 – Association of T1D SNPs in Pakistani subjects.
CLEC16A revealed only a marginal p-value ( p = 2.00E 01). The data from previous studies as well as our results, suggest that these genes or regions contribute to T1D susceptibility across different ethnic groups with ERBB3 having a stronger effect than CLEC16A. The third most significantly associated SNP rs2281808 (combined p = 3.22E 07) is located in an intronic region of SIRPG gene at 20p13. Barrett et al. reported p = 1.20E 11 in their meta-analysis for the association of this SNP with T1D [8]. Our study set from Pakistani population showed a more positive association that might be attributed to difference in our gene pool. Three more susceptibility loci, IL2/rs4505848 at 4q27, GLIS3/ rs7020673 at 9q24.2 and CD226/rs763361 at 18q22.2, showed significant association at combined p < 1E 04 ( p = 2.25E 05, p = 5.29E 05 and p = 6.62E 05, respectively) with T1D in our study sample from Pakistani population, consistent with the findings of Cooper et al. and/or Barrett et al. [8,19,20]. These findings further support that in spite of different ethnic background and geographical differences, there is still sharing of T1D susceptibility loci between populations. SNP rs478582, located in the seventh intron of PTPN2 (encoding T-cell protein tyrosine phosphatase) at 18p11, was reported to be strongly and independently associated with T1D by Todd et al. [14]. We have similarly found this SNP to be significantly associated with T1D with a combined p-value of 1.64E 04 in our sample. Three other SNPs, rs10272724/IKF1 on chromosome 7p12.2, rs11755527/BACH2 on chromosome 6q15 and rs9388489/ C6orf173 on chromosome 6q22.32, have followed the same trend of association in our study set of Pakistani population ( p < 1E 02) as reported previously by Swafford et al. or Cooper et al. and/or Barrett et al. [8,20,21]. In summary, our study has replicated several, but not all, previously reported European T1D susceptibility loci in Pakistani population, suggesting the presence of a number of shared loci between these two ethnic groups. Although
Conclusion
To our knowledge, this is the first genetic association study of T1D GWAS SNPs in a Pakistani population. Our study provides evidence of several T1D risk loci in Pakistani subjects, i.e. HLA, ERBB3, SIRPG, IL2, GLIS3, CD226, PTPN2, and suggests that a number of T1D loci are shared between Caucasians and Pakistanis. Further studies are required to correlate T1D risk alleles and haplotypes with expression of genes at RNA and protein level, which in turn would lead to the identification of causal genes in associated regions. Identification of causative variants/genes would then reveal the pathways and early precursors or biomarkers underlying the pathogenesis of type 1 diabetes.
Funding sources Funds are provided Grant No: 117-6919-bm7-003 by Higher Education Commission, Islamabad, Pakistan.
Conflict of interest statement All the authors declared that they have no competing interests.
Acknowledgements We are thankful to Higher Education Commission for supporting this study within the country and abroad. We are thankful to all the physicians for referring the patients and their supporting staff who helped with the collection of blood samples. We thank all the patients, control individual and their family members for their participation and cooperation in this study. Help and reviews provided by Samantha Rosenthal and Amnah Siddiqa are also appreciated.
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Please cite this article in press as: Kiani AK, et al. Association of 32 type 1 diabetes risk loci in Pakistani patients. Diabetes Res Clin Pract (2015), http://dx.doi.org/10.1016/j.diabres.2015.01.022
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Please cite this article in press as: Kiani AK, et al. Association of 32 type 1 diabetes risk loci in Pakistani patients. Diabetes Res Clin Pract (2015), http://dx.doi.org/10.1016/j.diabres.2015.01.022