Skip to main content
PMC home page
Genetics and Molecular Biology logoLink to Genetics and Molecular Biology
. 2010 Dec 1;33(4):610–614. doi: 10.1590/S1415-47572010005000074

The insulin polymorphism -23Hph increases the risk for type 1 diabetes mellitus in the Romanian population

Danut Cimponeriu 1,✉, Pompilia Apostol 1, Irina Radu 1, Anne Marie Craciun 2, Cristian Serafinceanu 2, Mihai Toma 1, Cristian Panaite 2, Dan Cheta 2
PMCID: PMC3036149  PMID: 21637566

Abstract

The insulin -23Hph and IGF2 Apa polymorphisms were genotyped in Romanian patients with T1DM (n = 204), T2DM (n = 215) or obesity (n = 200) and normoponderal healthy subjects (n = 750). The genotypes of both polymorphisms were distributed in concordance with Hardy-Weinberg equilibrium in all groups. The -23Hph AA genotype increased the risk for T1DM (OR: 3.22, 95%CI: 2.09-4.98, p < 0,0001), especially in patients without macroalbuminuria (OR: 4.32, 95%CI: 2.54-7.45, p < 0,0001). No other significant association between the alleles or genotypes of insulin -23Hph and IGF2 Apa and diabetes or obesity was identified.

Keywords: Insulin -23Hph, insulin-like growth factor 2 Apa, diabetes, obesity, case-control study

Introduction

Insulin and IGF2 (11p15.5) are candidate genes for complex traits, including type I diabetes mellitus (T1DM) (Owerbach and Gabbay, 1994), type II diabetes mellitus (T2DM) (Huxtable et al., 2000) and obesity with onset especially in childhood and middle-age (O'Dell et al., 1999; Le Stunff et al., 2001; Gu et al., 2002; Roth et al., 2002; Heude et al., 2004). It is very difficult to determine the real marker(s) for susceptibility to these complex traits, because many polymorphisms from this region of chromosome 11 are in strong linkage disequilibrium with each other. As a consequence, several functional polymorphisms from the insulin – IGF2 region have been frequently implicated with diabetes and/or obesity in association or linkage based studies. One of these is a VNTR polymorphism located in the insulin promoter, 596 bp upstream of the insulin start codon. Some of its variants may adopt noncanonical conformations that can be recognized by trans regulator factors, like Pur-1/MAZ. The Insulin -23HphI and IGF2 Apa are other polymorphisms that have recently received attention (Barratt et al., 2004; Marchand and Polychronakos, 2007), because they may interfere with gene expression (Vafiadis et al., 1998; Kralovicova et al., 2006) and predisposition to some pathologic traits (O'Dell et al., 1997, 1999; Gaunt et al., 2001).

In this study we tested the possible association between two polymorphisms from the insulin – IGF2 region and T1DM, T2DM and obesity.

Subjects and Methods

Subjects

A total of 1369 unrelated Romanian Caucasians (682 men, 687 women), older than 18 years, was enrolled in the study. Patients with T1DM (n = 204), T2DM (n = 215) or obesity (n = 200) diagnosed for at least two years were selected from the N Paulescu Institute (Bucharest, Romania). T1DM patients were selected if they were younger than 20 years at the onset of the disease, required daily insulin treatment and had a BMI between 18.5-25 kg/m2. T2DM patients were included if they had had more than two fasting glycemia values above 140 mg/dL after the age of 30 years old, a BMI of 18.5-30 kg/m2 and required no treatment with insulin. Obese patients were selected based on BMI values between 30-40 kg/m2 and glycemia in a fasting state ≤ 110 mg/dL. The presence or absence of hypertension (blood pressure above 130/85 mm Hg or treatment with antihypertensive medication), smoking (more than five cigarettes per day, for at least one year) and drinking (at least 25 g of alcohol per day, for at least one year) habits were recorded for all participants.

The control subjects comprised a total of 750 individuals (381 men, 369 women) selected from visitors attending two medical clinics from Bucharest for routine checking. They were matched for age, sex, ethnicity and birth place with patients and were equally distributed into Hc1, Hc2 and Hc3 groups. All normal individuals had no relatives with DM, obesity or other genetic syndromes.

Informed consent was obtained from all subjects before enrolment. The design of the study was in accordance with internationally agreed ethical standards (Declaration of Helsinki, 1964) and approved by the N Paulescu hospital ethical committee.

Laboratory procedures

Fasting plasma glucose, serum total cholesterol, serum triglycerides and HbA1C levels were measured using standard laboratory protocols. Genomic DNA was isolated using a commercial kit (Wizard Genomic DNA Purification Kit, Promega) from venous blood (1 mL) collected into tubes containing EDTA. Genotyping for insulin -23Hph (-23 A/T, rs689) and IGF2 Apa (820 G/A, rs680) was based on a RFLP method. The INSF 5'tccaggacaggctgcatcag3', INSR 5'agcaatgggcggttggctca3' and IGF2F 5'cttggactttgagtcaaattgg3', IGF2R 5'cctcctttggtcttactggg3' primer pairs (Sigma Genosys) were used for PCR (Corbett Research thermocycler). Amplicons (5 μL) were electrophoresed on agarose gel (2%) after digestion with 6 U of HphI or ApaI endonucleases (New England BioLabs). Two researchers who did not know the clinical data of the subjects independently scored all genotypes. Ten percent of randomly selected samples were re-genotyped as a quality control. No errors in genotyping were observed.

Statistical analysis

After checking the normality of distribution for continuous variables by means of the Shapiro-Wilk W test, comparisons of these parameters between groups were performed through Mann-Whitney U non-parametric tests. Categorical variables between groups were compared through chi-squared tests, that were also used for verifying genotype departures from Hardy-Weinberg equilibrium within each group and for comparing genotype frequencies between affected and control subjects. Odds ratio (ORs) and their corresponding 95% confidence intervals were calculated for estimating disease risks corresponding to genotypes AA from -23Hph and IGF2Apa. All statistical analyses and procedures were performed using commercial software (STATSDirect version 2.6.4).

Results

The main characteristics of the patients and controls are presented in Table 1. Patients with T2DM (52.41 ± 7.21) were older than those with T1DM (33.01 ± 6.23, p < 0.0001) or obesity (43.39 ± 11.16, p < 0.0001). The BMI and triglycerides levels were higher in T2DM and obese patients compared with Hc2 and Hc3 controls (p < 0.0001). The T2DM patients are more often smokers than control subjects (p = 0.0001). Macroalbuminuria was significantly (Yate's corrected chi2 = 4.54, p = 0.03) more frequent in T1DM (28.92%, M/F: 27/32) than in T2DM (19.53%, M/F: 19/23). The occurrence of hypertension was similar in all groups of patients (~50%).

Table 1.

Clinical and biochemical data of subjects selected for this study.

Parameters T1DM Hc1 T2DM Hc2 Ob Hc3
Number 204 250 215 250 200 250
Gender (M/F) (c) 105/99 142/108 114/101 135/115 82/118 104/146
Age (in years): Mean ± SD (range) 33.01 ± 6.23 (21-53) 33.4 ± 6.42 (21-53) 52.41 ± 7.21 (31-65) 52.58 ± 7.04 (31-65) 43.39 ± 11.16 (20-64) 44.3 ± 11.32 (20-64)
p (patients vs. Hc)mw 0.55 0.83 0.4
Current BMI (kg/m2) M ± SD (range) 23.03 ± 1.42 (18.9-24.98) 23.12 ± 1.28 (18.98-24.95) 24.78 ± 2.37 (19.35-29.98) 23.00 ± 1.4 (18.98-24.95) 34.87 ± 2.33 (30.03-39.9) 22.99 ± 1.44 (18.9-24.98)
p (patients vs. Hc)mw 0.73 < 0.0001 < 0.0001
HbA1C (%) 8.6 ± 1.8 nd 8.1 ± 2.1 nd 4.8 ± 0.4 nd
Fasting plasma glucose (mg/dL) nd 88 ± 9 110 ± 15 86 ± 11 92 ± 8 84 ± 10
Total cholesterol ± SD (mg/dL) 179.2 ± 43.3 157.3 ± 31.4 206.8 ± 39.5 138.6 ± 25.2 217.4 ± 50.2 165.1 ± 37.4
Triglycerides ± SD (mg/dL) 112.1 ± 24.84 (62-210) 109.96 ± 16.73 (61-157) 121.71 ± 20.63 (75-211) 106.6 ± 19.92 (61-196) 159.62 ± 69.7 (53-484) 109.82 ± 22.42 (65-198)
p (patients vs. Hc)mw 0.9501 < 0.0001 < 0.0001
Smokers (c) 25 31 57 p < 0.0001 21 21 26
Drinkers (c) 23 29 31 24 26 35
Open in a new tab

The distribution of the -23Hph and IGF2 Apa genotypes were in Hardy-Weinberg equilibrium in all groups (Table 2). The Insulin -23Hph (chi2 = 0.84, DF = 4, p = 0.93) and IGF2 Apa (chi2 = 5.78, DF = 4, p = 0.22) genotypes are similar in the control lots, Hc1, Hc2 and Hc3. We observed a different distribution of -23Hph genotypes in T1DM and Hc1 lots. The -23Hph AA genotype is significantly associated with T1DM (OR: 3.22, 95% CI: 2.09-4.98, p < 0.0001). This genotype remains also more frequent in T1DM than in controls (89.66% vs. 50.26%) if patients with macroalbuminuria and their matched controls were excluded from the analysis. In this case, the association between AA genotype and T1DM increases (OR: 4.32, 95% CI: 2.54-7.45, p < 0.0001). The disease risk remains non-significant if the T2DM patients with macroalbuminuria and their matched controls were excluded from analysis.

Table 2.

Genotypes and alleles distributions of the examined polymorphisms in each studied group.

Genotype T1DM Hc1 T2DM Hc2 Ob Hc3
-23Hph AA 158 129 118 131 107 131
-23Hph AT 40 109 89 104 85 108
-23Hph TT 6 12 8 15 8 11
A%:T% 87.25: 12.75 73.4:26.6 75.58: 24.42 73.2:26.8 74.75:25.25 74:26
HW 2.86 3.4 3.17 0.91 3.17 3.76
Chi2 32.56, p < 0.0001 1.35, p = 0.509 0.08, p = 0.9607
ORAA (95%CI) 3.22 (2.10-4.98) 1.11 (0.75-1.62) 1.05 (0.71-1.54)
IGF2 Apa GG 127 139 117 152 115 156
IGF2 Apa GA 69 102 76 85 71 79
IGF2 Apa AA 8 9 22 13 14 15
G%:A% 79.17: 20.83 76: 24 72.1:27.9 77.8:22.2 75.25:24.75 78.2:21.8
HW 0.13 3.51 3.17 0.06 0.44 1.34
Chi2 2.33, p = 0.31 4.76, p = 0.09 1.12, p = 0.57
ORAA (95%CI) 1.32 (0.89-1.96) 0.77 (0.52-1.13) 0.82 (0.55-1.21)
Open in a new tab

We did not observe any other significant associations between investigated markers and clinical and biochemical data (e.g. age of disease onset, sex).

Discussion

This is the first study to simultaneously assess the relationship between insulin – IGF2 polymorphisms and T1DM, T2DM and obesity in the Romanian population. Previous studies in other countries have shown that polymorphisms from the insulin – IGF2 region can predispose to some complex pathological traits, particularly those involving diabetes. Several functional polymorphisms or an extended haplotype may represent the genetic bases for these observations. We conducted a case-control study to investigate the relationship between the insulin -23Hph and IGF2 Apa polymorphisms and three common pathological phenotypes: T1DM, T2DM and obesity. Association studies can identify substantial genetic effects (e.g. OR > 2.0) between normal and clinical phenotypes using relatively small sample sizes (n = 200) (Dupont and Plummer, 1990). The subjects were selected from an ethnically homogenous population surrounding Bucharest to avoid spurious associations.

The variants of Insulin -23Hph (-23Hph A: 73.53%) and IGF2 Apa (IGF2 A: 77.3%) polymorphisms in our healthy controls are similar to those reported for Caucasians (Bennett and Todd, 1996).

We found a strong association between insulin -23Hph polymorphism and T1DM (ORAA = OR: 3.22, 95% CI: 2.09-4.98, p < 0.0001). This result is in agreement with previous studies based on Caucasian cohorts (Undlien et al., 1994; Krokowski et al., 1997) or families (Davies et al., 1994) which also showed the importance of markers from this region regarding diabetes susceptibility. As a common observation the results of these studies support the importance of markers in linkage disequilibrium with class I VNTR disequilibrium on the risk for T1DM.

In our study 59 patients with T1DM and 37 patients with T2DM have proteinuria. The frequency of the AA genotype in T1DM lot (81.37% vs. 50.26%) and the disease risk (ORAA: 4.32, 95% CI: 2.54-7.45) increases when patients with macroalbuminuria and their matched controls were excluded from analyses. We did not identify a similar effect in patients with T2DM. The -23Hph A allele is in almost complete linkage disequilibrium with the INS VNTR class I. It has been previously reported that the prevalence of proteinuria in insulin-requiring diabetic patients is significantly higher in homozygotes for INS VNTR class I variants than in carriers of other genotypes (Raffel et al., 1991). Additional studies are necessary to clarify these discordant results.

The genetic background (Wilkin, 2009), body mass (Kibirige et al.., 2003; Betts et al., 2005; Knerr et al., 2005), different degree of immune activation (Hathout et al.., 2001; Umpaichitra et al., 2002) and insulin resistance seem to represent some common reference points in the complex relationships between T1DM, T2DM and obesity. For this study, we carefully selected nonobese diabetic patients and nondiabetic obese patients in an attempt to reduce the effect of factors which may link these phenotypes. The Insulin -23Hph polymorphism was similarly distributed in T2DM and Hc2 lots (p > 0.05) irrespective of the degree of renal involvement. Similar results have been reported in some (e.g. Pima Indians), but not all populations (Ong et al., 1999; Lindsay et al., 2003).

We did not observe a significant association between -23Hph genotypes and obesity in middle aged patients (p > 0.05). This result is in agreement with other studies, in which IDDM2 markers were also found to not change the risk for obesity in middle-aged subjects (Sandhu et al., 2005). A similar distribution of IGF2 Apa in patients and controls was observed in our lots. Although the IGF2 polymorphisms were also not associated with BMI in middle-aged subjects in other population (Heude et al., 2007), it is speculated that an extended haplotype may better describe the relationship between obesity and response to glucose at least in older men (Rodríguez et al., 2006). In our study the results were non-significant even when the gender was taken into account (p > 0.05).

A predisposition for diabetes and obesity may be triggered by genetic and environmental determinants of growth patterns from prenatal to childhood life (Stene et al., 2001; EURODIAB Substudy 2 Study Group, 2002). We cannot entirely exclude the insulin and IGF2 genes as candidates for these complex traits because data regarding the origin of risk alleles, birth size and postnatal growth development were not available for this study. The contribution of polymorphisms from this region to predisposition for human pathology will be much better understood after testing of additional genetic (e.g. cis or trans factors, epigenetic modifications) and non-genetic (e.g. maternal factors, intracellular environment) factors.

Acknowledgments

We thank all subjects who took part in this study. This work was supported by Romanian Ministry of Education and Research (Research Project PNII Partnerships 42-161).

Footnotes

Associate Editor: Peter L. Pearson

References

  1. Barratt B.J., Payne F., Lowe C.E., Hermann R., Healy B.C., Harold D., Concannon P., Gharani N., McCarthy M.I., Olavesen M.G., et al. Remapping the insulin gene/IDDM2 locus in type 1 diabetes. Diabetes. 2004;53:1884–1889. doi: 10.2337/diabetes.53.7.1884. [DOI] [PubMed] [Google Scholar]
  2. Bennett S.T., Todd J.A. Human type 1 diabetes and the insulin gene: Principles of mapping polygenes. Annu Rev Genet. 1996;30:343–370. doi: 10.1146/annurev.genet.30.1.343. [DOI] [PubMed] [Google Scholar]
  3. Betts P., Mulligan J., Ward P., Smith B., Wilkin T. Increasing body weight predicts the earlier onset of insulin-dependant diabetes in childhood: Testing the `accelerator hypothesis' (2) Diabet Med. 2005;22:144–151. doi: 10.1111/j.1464-5491.2004.01368.x. [DOI] [PubMed] [Google Scholar]
  4. Davies J.L., Kawaguchi Y., Bennett S.T., Copeman J.B., Cordell H.J., Pritchard L.E., Reed P.W., Gough S.C., Jenkins S.C., Palmer S.M., et al. A genome-wide search for human type 1 diabetes susceptibility genes. Nature. 1994;371:130–136. doi: 10.1038/371130a0. [DOI] [PubMed] [Google Scholar]
  5. Dupont W.D., Plummer W.D., Jr Power and sample size calculations: A review and computer program. Control Clin Trials. 1990;11:116–128. doi: 10.1016/0197-2456(90)90005-m. [DOI] [PubMed] [Google Scholar]
  6. EURODIAB Substudy 2 Study Group Rapid early growth is associated with increased risk of childhood type 1 diabetes in various European populations. Diabetes Care. 2002;25:1755–1760. doi: 10.2337/diacare.25.10.1755. [DOI] [PubMed] [Google Scholar]
  7. Gaunt T.R., Cooper J.A., Miller G.J., Day I.N., O'Dell S.D. Positive associations between single nucleotide polymorphisms in the IGF2 gene region and body mass index in adult males. Hum Mol Genet. 2001;10:1491–1501. doi: 10.1093/hmg/10.14.1491. [DOI] [PubMed] [Google Scholar]
  8. Gu D., O'Dell S.D., Chen X.H., Miller G.J., Day I.N. Evidence of multiple causal sites affecting weight in the IGF2-INS-TH region of human chromosome 11. Hum Genet. 2002;110:173–181. doi: 10.1007/s00439-001-0663-5. [DOI] [PubMed] [Google Scholar]
  9. Hathout E.H., Thomas W., El-Shahawy M., Nahab F., Mace J.W. Diabetic autoimmune markers in children and adolescents with type 2 diabetes. Pediatrics. 2001;107:e102. doi: 10.1542/peds.107.6.e102. [DOI] [PubMed] [Google Scholar]
  10. Heude B., Dubois S., Charles M.A., Deweirder M., Dina C., Borys J.M., Ducimetiere P., Froguel P. VNTR polymorphism of the insulin gene and childhood overweight in a general population. Obes Res. 2004;12:499–504. doi: 10.1038/oby.2004.56. [DOI] [PubMed] [Google Scholar]
  11. Heude B., Ong K.K., Luben R., Wareham N.J., Sandhu M.S. Study of association between common variation in the insulin-like growth factor 2 gene and indices of obesity and body size in middle-aged men and women. J Clin Endocrinol Metab. 2007;92:2734–2738. doi: 10.1210/jc.2006-1948. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Huxtable S.J., Saker P.J., Haddad L., Walker M., Frayling T.M., Levy J.C., Hitman G.A., O'Rahilly S., Hattersley A.T., McCarthy M.I. Analysis of parent-offspring trios provides evidence for linkage and association between the insulin gene and type 2 diabetes mediated exclusively through paternally transmitted class III variable number tandem repeat alleles. Diabetes. 2000;49:126–130. doi: 10.2337/diabetes.49.1.126. [DOI] [PubMed] [Google Scholar]
  13. Kibirige M., Metcalf B., Renuka R., Wilkin T.J. Testing the accelerator hypothesis: The relationship between body mass and age at diagnosis of type 1 diabetes. Diabetes Care. 2003;26:2865–2870. doi: 10.2337/diacare.26.10.2865. [DOI] [PubMed] [Google Scholar]
  14. Knerr I., Wolf J., Reinehr T., Stachow R., Grabert M., Schober E., Rascher W., Holl R.W. The `accelerator hypothesis': Relationship between weight, height, body mass index and age at diagnosis in a large cohort of 9,248 German and Austrian children with type 1 diabetes mellitus. Diabetologia. 2005;48:2501–2504. doi: 10.1007/s00125-005-0033-2. [DOI] [PubMed] [Google Scholar]
  15. Královicová J., Gaunt T.R., Rodriguez S., Wood P.J., Day I.N., Vorechovsky I. Variants in the human insulin gene that affect pre-mRNA splicing: Is -23HphI a functional single nucleotide polymorphism at IDDM2? Diabetes. 2006;55:260–264. doi: 10.2337/diabetes.55.01.06.db05-0773. [DOI] [PubMed] [Google Scholar]
  16. Krokowski M., Machejko P., Bodalski J., Hryncewicz M. Insulin gene region on chromosome 11p15.5 is associated with insulin-dependent diabetes mellitus in a Polish population. Mon Sci Monit. 1997;3:451–455. [Google Scholar]
  17. Le Stunff C., Fallin D., Bougnères P. Paternal transmission of the very common class I INS VNTR alleles predisposes to childhood obesity. Nat Genet. 2001;29:96–99. doi: 10.1038/ng707. [DOI] [PubMed] [Google Scholar]
  18. Lindsay R.S., Hanson R.L., Wiedrich C., Knowler W.C., Bennett P.H., Baier L.J. The insulin gene variable number tandem repeat class I/III polymorphism is in linkage disequilibrium with birth weight but not Type 2 diabetes in the Pima population. Diabetes. 2003;52:187–193. doi: 10.2337/diabetes.52.1.187. [DOI] [PubMed] [Google Scholar]
  19. Marchand L., Polychronakos C. Evaluation of polymorphic splicing in the mechanism of the association of the insulin gene with diabetes. Diabetes. 2007;56:709–713. doi: 10.2337/db06-0402. [DOI] [PubMed] [Google Scholar]
  20. O'Dell S.D., Miller G.J., Cooper J.A., Hindmarsh P.C., Pringle P.J., Ford H., Humphries S.E., Day I.N. Apal polymorphism in insulin-like growth factor II (IGF2) gene and weight in middle-aged males. Int J Obes Relat Metab Disord. 1997;21:822–825. doi: 10.1038/sj.ijo.0800483. [DOI] [PubMed] [Google Scholar]
  21. O'Dell S.D., Bujac S.R., Miller G.J., Day I.N. Associations of IGF2 ApaI RFLP and INS VNTR class I allele size with obesity. Eur J Hum Genet. 1999;7:821–827. doi: 10.1038/sj.ejhg.5200381. [DOI] [PubMed] [Google Scholar]
  22. Ong K.K., Phillips D.I., Fall C., Poulton J., Bennett S.T., Golding J., Todd J.A., Dunger D.B. The insulin gene VNTR, type 2 diabetes and birth weight. Nat Genet. 1999;21:262–263. doi: 10.1038/6775. [DOI] [PubMed] [Google Scholar]
  23. Owerbach D., Gabbay K.H. Linkage of the VNTR/insulin-gene and type I diabetes mellitus: Increased gene sharing in affected sibling pairs. Am J Hum Genet. 1994;54:909–912. [PMC free article] [PubMed] [Google Scholar]
  24. Raffel L.J., Vadheim C.M., Roth M.P., Klein R., Moss S.E., Rotter J.I. The 5' insulin gene polymorphism and the genetics of vascular complications in type 1 (insulin-dependent) diabetes mellitus. Diabetologia. 1991;34:680–683. doi: 10.1007/BF00400999. [DOI] [PubMed] [Google Scholar]
  25. Rodríguez S., Gaunt T.R., Dennison E., Chen X.H., Syddall H.E., Phillips D.I., Cooper C., Day I.N. Replication of IGF2-INS-TH*5 haplotype effect on obesity in older men and study of related phenotypes. Eur J Hum Genet. 2006;14:109–116. doi: 10.1038/sj.ejhg.5201505. [DOI] [PubMed] [Google Scholar]
  26. Roth S.M., Schrager M.A., Metter E.J., Riechman S.E., Fleg J.L., Hurley B.F., Ferrell R.E. IGF2 genotype and obesity in men and women across the adult age span. Int J Obes Relat Metab Disord. 2002;26:585–587. doi: 10.1038/sj.ijo.0801927. [DOI] [PubMed] [Google Scholar]
  27. Sandhu M.S., Heude B., Young E.H., Luben R., Luan J., Khaw K.T., Todd J., Wareham N.J. INS VNTR class genotype and indexes of body size and obesity: Population-based studies of 7,999 middle-aged men and women. Diabetes. 2005;54:2812–2815. doi: 10.2337/diabetes.54.9.2812. [DOI] [PubMed] [Google Scholar]
  28. Stene L.C., Magnus P., Lie R.T., Søvik O., Joner G. Birth weight and childhood onset type 1 diabetes: Population based cohort study. BMJ. 2001;322:889–892. doi: 10.1136/bmj.322.7291.889. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Umpaichitra V., Banerji M.A., Castells S. Autoantibodies in children with type 2 diabetes mellitus. J Pediatr Endocrinol Metab (Suppl) 2002;15:525–530. [PubMed] [Google Scholar]
  30. Undlien D.E., Hamaguchi K., Kimura A., Tuomilehto-Wolf E., Swai A.B., McLarty D.G., Tuomilehto J., Thorsby E., Rønningen K.S. IDDM susceptibility associated with polymorphisms in the insulin gene region. A study of blacks, Caucasians and orientals. Diabetologia. 1994;37:745–749. doi: 10.1007/BF00404330. [DOI] [PubMed] [Google Scholar]
  31. Vafiadis P., Grabs R., Goodyer C.G., Colle E., Polychronakos C. A functional analysis of the role of IGF2 in IDDM2-encoded susceptibility to type 1 diabetes. Diabetes. 1998;47:831–836. doi: 10.2337/diabetes.47.5.831. [DOI] [PubMed] [Google Scholar]
  32. Wilkin T.J. The accelerator hypothesis: A review of the evidence for insulin resistance as the basis for type I as well as type II diabetes. Int J Obes (Lond) 2009;33:716–726. doi: 10.1038/ijo.2009.97. [DOI] [PubMed] [Google Scholar]

Articles from Genetics and Molecular Biology are provided here courtesy of Sociedade Brasileira de Genética

RESOURCES