Research Article The Genetic Profile from HLA and Non-HLA ...downloads.hindawi.com/journals/jdr/2015/485132.pdf · Research Article The Genetic Profile from HLA and Non-HLA Loci Allows

Research ArticleThe Genetic Profile from HLA and Non-HLA Loci AllowsIdentification of Atypical Type 2 Diabetes Patients

Matias Fabregat1 Mariana Fernandez1 Gerardo Javiel23

Graciela Vitarella3 and Adriana Mimbacas1

1Biodiversity and Genetic Department Instituto de Investigaciones Biologicas Clemente Estable 11600 Montevideo Uruguay2Teaching Care Unit Unit of Diabetes ldquoHospital Pasteurrdquo ASSE Ministry of Public Health 11600 Montevideo Uruguay3Diabetology Service of ldquoCentro de Asistencia del Sindicato Medico del Uruguayrdquo 11800 Montevideo Uruguay

Correspondence should be addressed to Adriana Mimbacas amimbacasiibceeduuy

Received 29 January 2015 Accepted 23 March 2015

Academic Editor Joseph Fomusi Ndisang

Copyright copy 2015 Matias Fabregat et alThis is an open access article distributed under the Creative CommonsAttribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

The complex diagnosis and treatment of diabetes highlight the need for markers to define how to monitor patients correctlyduring the course of their disease Different studies demonstrate the existence of patients who cannot be clearly classified We havepreviously shown that it is possible to differentiate ldquoatypical diabetic patientsrdquo based on genotyping the HLA In this work we showthat the analysis of non-HLA related to type 1 diabetes in the INS-VNTR SNP rs689 and rs3842753 improves the identification ofthese patients We genotyped 913 individuals comprising controls from the general population and ldquoclassicrdquo and ldquoatypicalrdquo diabeticpatients We compared the distribution of these loci and analyzed linkage disequilibriumThe haplotype was in LD for all the SNPsthat were evaluated Regarding their association with the disease the haplotype IAC was associated with type 1 (odds 260 182ndash372 CI 95) and ldquoatypical diabetesrdquo (odds 150 101ndash223 CI 95) whereas we did not observe an association with type 2 diabetesTherefore our results confirm that atypical diabetes is a different entity of the disease where the patient presents with a geneticbackground of T1D and a T2D phenotype findings that are likely to be relevant for patient diagnosis andmanagement in the clinic

1 Introduction

Uruguay is a little country located in South America witha population of 3286314 inhabitants according to the lastcensus [1] The population has been characterized as ofEuropean descent with a small contribution of Africandescendants and native amerindian popultion [2] Diabetesmellitus is a worldwide public health problem and Uruguayis not an exception showing a high prevalence of the disease8 and an equal percent that are likely undiagnosed despitethe small size of its population [3] Diabetes is a multi-factorial disease where genetic and environmental factorsinteract This complexity could be an important influencein the actual classification and treatment of this pathologyPreviously in an effort to link the current classification withadvances at molecular genetics we found that in severalstudies a significant proportion of diabetic patients did notpresent a correlation between genotype and phenotype [4ndash6]

Type 2 diabetes (T2D) diagnosed patients using internationalcriteria [7] presented Human Leukocyte Antigen (HLA)alleles associated with type 1 diabetes (T1D) and positiveantibodies in an intermediate value between both types thussuggesting the coexistence of both types of diabetes Severalauthors have published about this kind of diabetes [8ndash14]and these ldquoatypical patientsrdquo cannot be grouped into anyof the established groups by international guidelines Moreimportantly these atypical patients do not have an adequateresponse when undergoing treatment [15]

RecentlyMaruthur and colleagues found evidence that inT2D the pharmacogenetic interactions for some antihyper-glycemic drugs are consistent with their pharmacokineticsand pharmacodynamics showing the importance of geneticsvariants [16] In line with these observations we hypothesizedthat in ldquoatypical patientsrdquo non-HLA genes in addition to theHLA susceptibility alleles could be influencing the lack of

Hindawi Publishing CorporationJournal of Diabetes ResearchVolume 2015 Article ID 485132 6 pageshttpdxdoiorg1011552015485132

2 Journal of Diabetes Research

genotype-phenotype correlation and the course and develop-ment of the disease

Here we perform an in depth analysis of the presenceof other non-HLA loci related to T1D in this atypicaldiabetic population particularly focusing on the insulin gene(Insulin-Varaibale number tandem repeat SNP rs689 andrs3842753) We show that in the Uruguayan population thesevariants are in complete linkage disequilibrium [17] Thisregion is located on chromosome 11p155 in the promoterregion of the insulin gene and affects the level of transcrip-tion of INS and IGF2 genes [10 18] Mathematical modelsestimate that adding the HLA and VNTR contribution upto 60 of the total genetic component of T1D is obtained[19] VNTR polymorphisms located in the insulin promoter596 bp upstream of the insulin start codon consist of a highlypolymorphic tandem repeat sequence ACAGGGGTGTGG-GG (14 pb) whose variants are grouped into three classesof alleles according to their length [20 21] Regarding ourpopulation VNTR is in linkage disequilibrium with rs689where class I VNTR allele is associated with autoimmunityand inherited linked to the Adenine SNP allele Furthermorethe class III VNTR alleles are associated with autoimmunityprotection and inherited linked to the Timina SNP allelePopulation studies have shown that class III VNTR alleleshave a dominant protective effect and are associated witha 60ndash70 reduction in the risk of developing T1D [19ndash23]Even in the presence of autoantibodies and a high-risk HLAgenotype individuals carrying class III VNTR alleles presenta significant reduction in the probability of developing thedisease [24 25] Based on this association major studies haveused 23HphI (rs689) as an associated marker to study theVNTR [21 26 27]

Another SNP in linkage disequilibrium with the variantsdescribed above is rs3842753 a transversion at position +1140relative to the initial translation codon of the INS geneThis polymorphism is located in the 31015840UTR region of theINS mRNA and the cytosine-containing variant may causeinstability of the mRNA [28] In European and Uruguayanpopulations the cytosine-containing allele is associated withT1D and is in complete linkage disequilibriumwith theVNTRallele of class I and rs698 [17 25] Given the likely coexistenceof both types of diabetes in our population and the presenceof linkage disequilibrium as described in previous paperswe propose the in depth analysis of the genetic profile ofthese ldquoatypical patientsrdquo The analysis should include patientsthat present a phenotype characteristic of T2D with HLAsusceptibility alleles associated with T1D compared to (a) thegeneral population and (b) type 1 diabetes and type 2 diabetespatients without a HLA association

2 Materials and Methods

In this unmatched case-control study a total of 913 individu-als including diabetes patients (413) and controls (500) wereenrolled between 2004 and 2012 Recruitment of patients wasdone by the outpatient health center of Montevideo city

21 Control Samples We selected 500 unrelated individualsfrom the DNA bank of the Department of Biodiversity andGenetics IIBCE This collection is a representative sample ofMontevideorsquos general population and was randomly selectedfrom 15 different medical institutions public and privatewhen individuals assisted to their annual routine control

Due to local legislation at the time (ref 10811996) theMSP (Public Health Ministry) did not authorize collectinginformation about the clinical characteristics of patientswhen the study involved analyses of DNA samplesThereforethe only characteristic recorded for this population is the age(gt18 years old)

22 Diabetic Patient Samples 413 patients from 3rd attentionlevel at Clinics for Diabetes of Reference Health Centers ofMontevideo were analyzed For the preparation of this studywe only considered those patients receiving comprehensivecare of their diabetes following a nutritional plan andpresenting a good adherence to physical activity accordingto their functional ability within the recommendations ofthe American Diabetes Association (ADA) and ldquoAsociacionLatinoamericana de Diabetesrdquo (ALAD) [7 29] The diabetessamples were subclassified as type 1 diabetes type 2 diabetesand ldquoatypical diabetesrdquo

221 Type 1 Diabetes Patients (168) Those patients weredefined according to the ADA criteria [22] with an age ofonset lt 15 years and a body mass index lt 25 kgmts2

222 Type 2 Diabetes Patients Classical and Atypical (153 +92) The population diagnosed with T2D was divided intotwo groups based on the presence or absence of T1D HLAsusceptibility alleles described in the Uruguayan population[15 30] according to the following inclusion criteria

ldquoAtypical diabetesrdquo (92 individuals) (a) patients whohad good adherence to the treatment (b) they fulfilled theobjectives of education and nutrition plans according tointernational guidelines (c) present doubts on classificationof diabetic type andor not good therapeutic response (twoconsecutive measurements of glycated hemoglobin withinthree months not reduced in 15 [31]) (d) patients withsusceptibility HLA alleles for autoimmune disease We con-sidered DQB1 lowast 0201-0302 and DR 3-4 as susceptible ones inthe Uruguay (e) body mass index ge 25 kgmts2 [32]

223 Type 2 Diabetes (153 Individuals) Those patients werefulfilling the same requirements a and b of atypical patientsbut without diagnostic doubts responded to treatment anddo not present HLA alleles associated with autoimmunedisease

Samples frompatientswhohad other endocrine disordersor tumors were excluded

All subjects were interviewed by specialist medical doc-tors and gave a written informed consent to participate in thestudyTheprotocolwas approved by the Ethical Committee ofthe Ministry of Public Health (MSP) and the correspondingethical committee of each participating institution

Journal of Diabetes Research 3

Table 1 Clinical characteristics of diabetes patients

Variable Median plusmn SD P correctedDT1 DT2 AD DT1 versus DT2 DT1 versus AD DT2 versus AD

Age (years) 3564 plusmn 174 6505 plusmn 99 6184 plusmn 134 lt0001 lt001 005BMI (Kgm2) 2296 plusmn 37 3120 plusmn 57 3074 plusmn 57 lt001 lt001 0569HbA1c ()lowast 985 plusmn 24 828 plusmn 17 832 plusmn 19 lt001 lt001 0859Cholesterol 488 plusmn 14 553 plusmn 11 523 plusmn 12 0002 099 0065HDL 150 plusmn 05 1267 plusmn 17 122 plusmn 03 0013 0001 0041LDL 280 plusmn 10 333 plusmn 17 301 plusmn 11 0013 0207 01TG 128 plusmn 07 226 plusmn 14 221 plusmn 02 lt0001 lt0001 0838Units without bracket were expressed in IS BMI = body mass index TG = triglycerides and HbA1c ()lowast = glycated hemoglobin value at initial study

23 Molecular Analysis Highmolecular weight DNA extrac-tion was performed from peripheral blood by standardphenol chloroform protocol

The HLA typing was performed by reverse ASO tech-nique (Innogenetics Ltd Belgium UE) INS 51015840VNTRrs3842753 and HLA were processed in a previous work [45 15 17 31]

The SNP rs689 (minus23HPh1) for controls and T2D wereprocessed in a previous work [16 33] Atypical diabetespatients were genotyped by PCR-RFLP with the followingprimers forward-51015840AGCAGGTCTGTTCCAAGG-31015840 andreverse-51015840CTTGGGTGTGTAGAAGAAGC-31015840 which ampli-fies a 360 bp fragment The identification of the genotypeswas performed by digesting the DNA fragments with BsmAISequencing was used for confirmation of genotypes (Macro-gen Ltda Korea)

24 Statistical Analysis (a) Calculations of power samplesize were done with the Epi Info 343 database and thestatistics software for public health professionals and theQuanto statistical package (httpbiostatsuscedusoftware)considering the prevalence of diabetes in Uruguay (8) [3]We assumed 95 of confidential interval and power 80 inan unmatched case-control design

(b) The statistical analysis of a polymorphism was donewith the web tool for SNP analysis SNPStats (httpbioinfoiconcologianetsnpstatsstarthtm)

(c) Selection of inheritancemodel best inheritancemodewas selected according to SNPStat program The statisticfollows a chi-square distribution with degrees of freedomequal to the number of additional parameters in the morecomplex model and Akaike information criterion (AIC) andBayesian information criterion (BIC) The statistical test119875 values were calculated via an exact test The referencecategory used by program was the homozygous form

(d) Hardy-Weinberg equilibrium (HWE) for allelic andgenotype frequencies was tested by chi-square test

(e) Association between one polymorphism and diseasewe make the contingency table and then apply a chi-squaretest and the estimation of the OR (odds ratio) for eachgenotype with respect to the reference genotype (Epi Info andSNPStat)

(f) Haplotype analysis D statistic (under the assumptionof no association) and correlation coefficient between alleles

and the observed frequency were done Linkage disequilib-rium and haplotype were calculated with SNPStat programAnalysis of multiple SNPs and haplotype and analysis ofassociation between haplotypes and disease were done

3 Results

Nine hundred and thirteen DNAs were analyzed in thisstudy Five hundred correspond to samples obtained fromthe general population of Uruguay and four hundred andthirteen correspond to diabetes patients First we analyzedthe clinical characteristics of diabetes patients and performedthe comparison between the three groups defined previously(Table 1) We found a significant statistical difference whenwe compared T1D with any other subgroup in all variablesconsidered However the only difference between T2D andldquoatypical diabetesrdquo was in the level of HDL These results arein accordancewith previous reports [14] Our genetic analysisshowed that all SNPs analyzed in all groups were in Hardy-Weinberg equilibrium (HWE) The best heredity model foreach SNP analyzed was the log-additive model accordingto the AIC and BIC criteria of the SNPstat program Allelicfrequencies for all samples and association with the diseaseare shown in Tables 2(a) 2(b) and 2(c)

According to the D1015840 value and the correlation coefficientbetween alleles and the observed frequency the evaluatedhaplotype was in linkage disequilibrium with all SNPs ana-lyzed The most frequent haplotype was IAC in controls anddiabetes patients (Table 3)Haplotypewith frequenciesminor1 was considered rare Regarding the association with thedisease the high protective effect (IIITA) was present in T1DThe contingency table for haplotypes associated with T1Dversus no presence of this haplotype revealed an associationin T1D and ldquoatypical diabetesrdquo but resulted in no significantassociation in T2D (Table 4)

4 Discussion

Our study allowed us to analyze the genetic profile of ldquoatypicaldiabetesrdquo comparing the phenotype of type 2 diabetes withHLA susceptibility alleles in the general population T1Dand T2D without HLA associated Based on our results wepropose that this marker can aid in the diagnosis and man-agement of patients who present difficulties in control and


Table 2 Allelic frequencies of the SNPs (a) type 1 diabetes (b) type2 diabetes and (c) atypical diabetes

(a)

VariantAllelic frequencies

OR CI 119875

correctedType 1diabetes Control

INS-VNTRI 091 072 379 251ndash574 0000III 009 028

rs689A 088 072 283 196ndash409 00000T 012 028

rs3842753A 086 072 244 172ndash347 00001C 014 028

(b)


OR CI119875



rs689A 067 072 081 060ndash107 014T 033 028

rs3842753A 068 072 084 063ndash112 026C 032 028

(c)


OR CI119875

correctedAtypicaldiabetes Control


rs689A 079 072 151 151ndash225 004T 021 028

rs3842753A 074 072 123 084ndash179 031C 024 028

OR odds ratio CI confidence intervals

follow-up In addition our analysis of the INS VNTR locusas the second marker of importance for T1D susceptibilityfurther supports the notion that patients with difficulties inall approach areas (diagnosis treatment and evolution) havea strong genetic basis

The last ADAguidelines classified diabetes in four clinicalcategories but recognized that some patients cannot be clearly

Table 3 Haplotype frequencies for all groups

INS rs689 rs3842753 Freq

Type 1 diabetes

I A C 07492III T A 02275I T A 0012

Rare lowast lowast 00113lowast

Type 2 diabetes

I A C 07035III T A 02703I T A 00199

Rare lowast lowast 00062

Atypical diabetes

I A C 07187III T A 02558I T A 00119lowastRare lowast lowast 00136

lowastMeans other haplotypes different to previous

Table 4 Haplotype association with the disease

Haplotype OR (95 CI) 119875 value

Diabetes type 1 IAC 260 (182ndash372) lt00001No IAC

Diabetes type 2 IAC 083 (062ndash110) NSNo IAC

Atypical diabetes IAC 150 (101ndash223) lt005No IAC

NS = non significant

classified as type 1 or 2 diabetes Importantly such difficultiesin classification may occur at any age and genetic studiescould improve the timely diagnosis in these kinds of patientswithout having to wait for the disease to progress

Mathematicalmodels estimate that together theHLA andINS VNTR contribution may account for near 60 of thetotal genetic basis for developing T1D [19] Therefore thesemarkers typically associated with autoimmune diabeteswhen present in T2D patients can modify the expecteddevelopment of the pathology

It has been shown that the second susceptibility locusfor autoimmune disease after HLA corresponds to a minisatellite in the insulin gene (INS-VNTR) and in Caucasianspopulations this VNTR is in linkage disequilibrium withminus23HphI SNP Previous studies estimate that 10 of thegenetic susceptibility to T1D corresponds to thismini satellite[20]

In previous works we showed that there are patients inour population who cannot be classified as either type 1 ortype 2 diabetes according to the international guidelinesTheclinical presentation evolution and difficulty in reachingexpected therapeutic goals make them ldquoatypical patientsrdquoin relation with HLA alleles [14] Now we have gainedinsight into understanding the genetic basis of ldquoatypicaldiabetesrdquo by showing an association with genes differentfrom HLA It is noteworthy that in these patients there areno homozygous individuals for allele III of 51015840VNTR Theprotective allele III in the promoter region of INS is associated


with a greater functional reserve of 120573 cells in response toa direct hyperglycemic stimulus [34] Although we did notanalyze the functional reserve of beta cells it is striking tofind a high frequency of susceptibility allele I in ldquoatypicalpatientsrdquo and lower presence of III alleles in their genotypesThis observation could suggest an earlier beta cell failure inthese patients and therefore could be one possible explanationto understand the cellular basis of their bad treatmentresponse a possibility that should be analyzed in futureinvestigations

In conclusion our results confirm that atypical diabetesis a different entity of the disease where patients combinea genetic background of T1D with a T2D phenotype thushighlighting the importance of genetics as a new tool inclinical practice

Conflict of Interests

There are no financial competing interests

Authorsrsquo Contribution

Matias Fabregat conducted experimental procedures andvalidations data acquisition compilation analysis and inter-pretation and also was involved in retrieving conceptualinformation and draft paper preparationMariana Fernandezcontributed to draft paper preparation and performed criticalrevision to structure the content intellectually Gerardo Javielprovided substantial contributions to the concept and designof the work He was in charge of the admission protocoland monitoring of patients He was involved in retrievingmedical conceptual information and draft paper preparationperformed a critical revision to structure the content intellec-tually and gave approval for the final version to be publishedGraciela Vitarella was in charge of the admission protocoland monitoring of patients She was involved in retrievingmedical conceptual information and draft paper preparationperformed a critical revision to structure the content intellec-tually and gave approval for the final version to be publishedAdriana Mimbacas provided substantial contributions to theconcept and design of the work and controlled experimentalprocedures validations of the results and statistical analysisShe was involved in retrieving conceptual information anddraft paper preparation performed critical revision to struc-ture the content intellectually and gave approval for the finalversion to be published

Acknowledgments

The authors thank all the patients that participated in thestudy and the health personnel who contributed to thedevelopment of this study They thank Dr Jose Luis Badanofor correcting the English paper

References

[1] INE (Instituto Nacional de Estadıstica) 2011 httpwwwinegubuycensos2011indexhtml

[2] M Sans G Figueiro and P C Hidalgo ldquoA new mitochondrialC1 lineage from the prehistory of Uruguay population geno-cide ethnocide and continuityrdquo Human Biology vol 84 no 3pp 287ndash305 2012

[3] R Ferrero and T Garcia ldquoSurvey on the prevalence of diabetesinUruguayrdquoArchives of InternalMedicine vol 27 pp 1ndash12 2005

[4] AMimbacas L Garcıa P Zorrilla et al ldquoGenotype and pheno-type correlations in diabetic patients in Uruguayrdquo Genetics andMolecular Research vol 8 no 4 pp 1352ndash1358 2009

[5] A Mimbacas and G Javiel ldquoDiabetes type 1 and type 2 whatis behind a classificationrdquo in Type 1 Diabetes ComplicationsPathogenesis andAlternative Treatments C-P Liu Ed pp 287ndash304 InTech 2011

[6] AMimbacas G Vitarella J Souto et al ldquoThe phenotypemasksthe genotype a possible new expression of diabetesrdquo Journal ofPediatric Genetics vol 1 no 2 pp 131ndash134 2012

[7] AmericanDiabetes Association Position Statement ldquoStandardsof medical care in diabetesrdquo Diabetes Care vol 35 supplement1 pp S11ndashS63 2012

[8] I M Libman and D J Becker ldquoCoexistence of type 1 and type2 diabetes mellitus lsquodoublersquo diabetesrdquo Pediatric Diabetes vol 4no 2 pp 110ndash113 2003

[9] H Kolb and T Mandrup-Poulsen ldquoAn immune origin of type 2diabetesrdquo Diabetologia vol 48 no 6 pp 1038ndash1050 2005

[10] T Tuomi ldquoType 1 and type 2 diabetes what do they have incommonrdquo Diabetes vol 54 supplement 2 pp S40ndashS45 2005

[11] P Pozzilli and R Buzzetti ldquoA new expression of diabetes doublediabetesrdquo Trends in Endocrinology amp Metabolism vol 18 no 2pp 52ndash57 2007

[12] P Pozzilli C Guglielmi E Pronina and E Petraikina ldquoDoubleor hybrid diabetes associated with an increase in type 1 and type2 diabetes in children and youthsrdquo Pediatric Diabetes vol 8 no9 pp 88ndash95 2007

[13] M A Stone J Camosso-Stefinovic J Wilkinson S de Lusig-nan A T Hattersley and K Khunti ldquoIncorrect and incompletecoding and classification of diabetes a systematic reviewrdquoDiabetic Medicine vol 27 no 5 pp 491ndash497 2010

[14] S E Inzucchi RM Bergenstal J B Buse et al ldquoManagement ofhyperglycemia in type2 diabetes a patient-centered approachrdquoDiabetes Care vol 35 pp 1364ndash1379 2012

[15] M Fernandez M Fabregat G Javiel and A Mimbacas ldquoHLAallelesmay serve as a tool to discriminate atypical type 2 diabeticpatientsrdquo World Journal of Diabetes vol 5 no 5 pp 711ndash7162014

[16] N M Maruthur M O Gribble W L Bennett et al ldquoThepharmacogenetics of type 2 Diabetes a systematic reviewrdquoDiabetes Care vol 37 no 3 pp 876ndash886 2014

[17] C Gascue Analisis de polimorfismos de riesgo a la dia-betes tipo 1 en una poblacion trihıbrida Uruguay MontevideoUruguay [MS thesis] LAP LAMBERT Academic PublishingGmbH amp Company KG 2007 httpwwwboddeshopbuchhtmlampbookId=587987

[18] M I McCarthy and P Froguel ldquoGenetic approaches to themolecular understanding of type 2 diabetesrdquo American Journalof Physiology - Endocrinology and Metabolism vol 283 no 2pp E217ndashE225 2002

[19] S T Bennett and J A Todd ldquoHuman type 1 diabetes and theinsulin gene principles of mapping polygenesrdquo Annual Reviewof Genetics vol 30 pp 343ndash370 1996

[20] G I Bell M J Selby andW J Rutter ldquoThe highly polymorphicregion near the human insulin gene is composed of simple


tandemly repeating sequencesrdquo Nature vol 295 no 5844 pp31ndash35 1982

[21] D Cimponeriu P Apostol I Radu et al ldquoThe insulin polymor-phism -23Hph increases the risk for type 1 diabetes mellitus inthe Romanian populationrdquoGenetics andMolecular Biology vol33 no 4 pp 610ndash614 2010

[22] S T Bennett A M Lucassen S C L Gough et al ldquoSusceptibil-ity to human type 1 diabetes at IDDM2 is determined by tandemrepeat variation at the insulin gene minisatellite locusrdquo NatureGenetics vol 9 no 3 pp 284ndash292 1995

[23] S T Bennett A J Wilson F Cucca et al ldquoIDDM2-VNTR-encoded susceptibility to type 1 diabetes dominant protectionand parental transmission of alleles of the insulin gene-linkedminisatellite locusrdquo Journal of Autoimmunity vol 9 no 3 pp415ndash421 1996

[24] A Pugliese Z L Awdeh C A Alper R A Jackson and G SEisenbarth ldquoThe INS B allele (1428 Fok I) is associated withreduced IDDM incidence in autoantibody-positive first degreerelatives despite the presence of autoantibodies and high-riskHLA allelesrdquo Transplantation Proceedings vol 27 no 6 p 33921995

[25] AM Lucassen G R Screaton C Julier T J ElliottM Lathropand J I Bell ldquoRegulation of insulin gene expression by theIDDM associated insulin locus haplotyperdquo Human MolecularGenetics vol 4 no 4 pp 501ndash506 1995

[26] J D H Stead and A J Jeffreys ldquoAllele diversity and germlinemutation at the insulin minisatelliterdquo Human Molecular Genet-ics vol 9 no 5 pp 713ndash723 2000

[27] P Cejkova P Novota M Cerna et al ldquoHLA DRB1 DQB1and insulin promoter VNTR polymorphisms interactions andthe association with adult-onset diabetes mellitus in Czechpatientsrdquo International Journal of Immunogenetics vol 35 no2 pp 133ndash140 2008

[28] C Julier A Lucassen P Villedieu et al ldquoMultiple DNA variantassociation analysis application to the insulin gene region intype I diabetesrdquo The American Journal of Human Genetics vol55 no 6 pp 1247ndash1254 1994

[29] Asociacion Latinoamericana de Diabetes (ALAD) 2012 GuiasALAD de diagnostico control y tratamiento de la diabetes tipo2 httpalad-latinoamericaorg

[30] A Mimbacas F Perez-Bravo P C Hidalgo et al ldquoAssociationbetween diabetes type 1 andDQB1 alleles in a case-control studyconducted in Montevideo Uruguayrdquo Genetics and MolecularResearch vol 2 pp 29ndash35 2003

[31] D M Nathan J B Buse M B Davidson et al ldquoMedicalmanagement of hyperglycemia in type 2 diabetes a consensusalgorithm for the initiation and adjustment of therapyrdquoDiabetesCare vol 32 no 1 pp 193ndash203 2009

[32] World Health Organization ldquoBMI classificationrdquo httpwwwwhointghoncdrisk factorsbmi texten

[33] P Zorrilla Polimorfismos asociados a Diabetes Mellitus Tipo1 en el gen PTPN22 en la poblacion de Montevideo EditorialAcademica Espanola 2011 httpswwweae-publishingcomcatalogsearch

[34] W Fendler K Wyka A Cieslik-Heinrich E Polakowska JJastrzebska and W Młynarski ldquoThe 51015840VNTR proinsulin gene(INS) polymorphism and the functional reserve of 120573 cells inthe intravenous glucose tolerance testrdquo Pediatric EndocrinologyDiabetes and Metabolism vol 17 no 1 pp 5ndash9 2011

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Evidence-Based Complementary and Alternative Medicine

Volume 2014Hindawi Publishing Corporationhttpwwwhindawicom


genotype-phenotype correlation and the course and develop-ment of the disease

Here we perform an in depth analysis of the presenceof other non-HLA loci related to T1D in this atypicaldiabetic population particularly focusing on the insulin gene(Insulin-Varaibale number tandem repeat SNP rs689 andrs3842753) We show that in the Uruguayan population thesevariants are in complete linkage disequilibrium [17] Thisregion is located on chromosome 11p155 in the promoterregion of the insulin gene and affects the level of transcrip-tion of INS and IGF2 genes [10 18] Mathematical modelsestimate that adding the HLA and VNTR contribution upto 60 of the total genetic component of T1D is obtained[19] VNTR polymorphisms located in the insulin promoter596 bp upstream of the insulin start codon consist of a highlypolymorphic tandem repeat sequence ACAGGGGTGTGG-GG (14 pb) whose variants are grouped into three classesof alleles according to their length [20 21] Regarding ourpopulation VNTR is in linkage disequilibrium with rs689where class I VNTR allele is associated with autoimmunityand inherited linked to the Adenine SNP allele Furthermorethe class III VNTR alleles are associated with autoimmunityprotection and inherited linked to the Timina SNP allelePopulation studies have shown that class III VNTR alleleshave a dominant protective effect and are associated witha 60ndash70 reduction in the risk of developing T1D [19ndash23]Even in the presence of autoantibodies and a high-risk HLAgenotype individuals carrying class III VNTR alleles presenta significant reduction in the probability of developing thedisease [24 25] Based on this association major studies haveused 23HphI (rs689) as an associated marker to study theVNTR [21 26 27]

Another SNP in linkage disequilibrium with the variantsdescribed above is rs3842753 a transversion at position +1140relative to the initial translation codon of the INS geneThis polymorphism is located in the 31015840UTR region of theINS mRNA and the cytosine-containing variant may causeinstability of the mRNA [28] In European and Uruguayanpopulations the cytosine-containing allele is associated withT1D and is in complete linkage disequilibriumwith theVNTRallele of class I and rs698 [17 25] Given the likely coexistenceof both types of diabetes in our population and the presenceof linkage disequilibrium as described in previous paperswe propose the in depth analysis of the genetic profile ofthese ldquoatypical patientsrdquo The analysis should include patientsthat present a phenotype characteristic of T2D with HLAsusceptibility alleles associated with T1D compared to (a) thegeneral population and (b) type 1 diabetes and type 2 diabetespatients without a HLA association

2 Materials and Methods

In this unmatched case-control study a total of 913 individu-als including diabetes patients (413) and controls (500) wereenrolled between 2004 and 2012 Recruitment of patients wasdone by the outpatient health center of Montevideo city

21 Control Samples We selected 500 unrelated individualsfrom the DNA bank of the Department of Biodiversity andGenetics IIBCE This collection is a representative sample ofMontevideorsquos general population and was randomly selectedfrom 15 different medical institutions public and privatewhen individuals assisted to their annual routine control

Due to local legislation at the time (ref 10811996) theMSP (Public Health Ministry) did not authorize collectinginformation about the clinical characteristics of patientswhen the study involved analyses of DNA samplesThereforethe only characteristic recorded for this population is the age(gt18 years old)

22 Diabetic Patient Samples 413 patients from 3rd attentionlevel at Clinics for Diabetes of Reference Health Centers ofMontevideo were analyzed For the preparation of this studywe only considered those patients receiving comprehensivecare of their diabetes following a nutritional plan andpresenting a good adherence to physical activity accordingto their functional ability within the recommendations ofthe American Diabetes Association (ADA) and ldquoAsociacionLatinoamericana de Diabetesrdquo (ALAD) [7 29] The diabetessamples were subclassified as type 1 diabetes type 2 diabetesand ldquoatypical diabetesrdquo

221 Type 1 Diabetes Patients (168) Those patients weredefined according to the ADA criteria [22] with an age ofonset lt 15 years and a body mass index lt 25 kgmts2

222 Type 2 Diabetes Patients Classical and Atypical (153 +92) The population diagnosed with T2D was divided intotwo groups based on the presence or absence of T1D HLAsusceptibility alleles described in the Uruguayan population[15 30] according to the following inclusion criteria

ldquoAtypical diabetesrdquo (92 individuals) (a) patients whohad good adherence to the treatment (b) they fulfilled theobjectives of education and nutrition plans according tointernational guidelines (c) present doubts on classificationof diabetic type andor not good therapeutic response (twoconsecutive measurements of glycated hemoglobin withinthree months not reduced in 15 [31]) (d) patients withsusceptibility HLA alleles for autoimmune disease We con-sidered DQB1 lowast 0201-0302 and DR 3-4 as susceptible ones inthe Uruguay (e) body mass index ge 25 kgmts2 [32]

223 Type 2 Diabetes (153 Individuals) Those patients werefulfilling the same requirements a and b of atypical patientsbut without diagnostic doubts responded to treatment anddo not present HLA alleles associated with autoimmunedisease

Samples frompatientswhohad other endocrine disordersor tumors were excluded

All subjects were interviewed by specialist medical doc-tors and gave a written informed consent to participate in thestudyTheprotocolwas approved by the Ethical Committee ofthe Ministry of Public Health (MSP) and the correspondingethical committee of each participating institution















3 Results



4 Discussion




(a)


OR CI 119875



rs689A 088 072 283 196ndash409 00000T 012 028

rs3842753A 086 072 244 172ndash347 00001C 014 028

(b)


OR CI119875



rs689A 067 072 081 060ndash107 014T 033 028

rs3842753A 068 072 084 063ndash112 026C 032 028

(c)


OR CI119875



rs689A 079 072 151 151ndash225 004T 021 028

rs3842753A 074 072 123 084ndash179 031C 024 028






Type 1 diabetes

I A C 07492III T A 02275I T A 0012


Type 2 diabetes

I A C 07035III T A 02703I T A 00199


Atypical diabetes




















Acknowledgments


References










































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of






























3 Results



4 Discussion




(a)


OR CI 119875



rs689A 088 072 283 196ndash409 00000T 012 028

rs3842753A 086 072 244 172ndash347 00001C 014 028

(b)


OR CI119875



rs689A 067 072 081 060ndash107 014T 033 028

rs3842753A 068 072 084 063ndash112 026C 032 028

(c)


OR CI119875



rs689A 079 072 151 151ndash225 004T 021 028

rs3842753A 074 072 123 084ndash179 031C 024 028






Type 1 diabetes

I A C 07492III T A 02275I T A 0012


Type 2 diabetes

I A C 07035III T A 02703I T A 00199


Atypical diabetes




















Acknowledgments


References










































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of


















(a)


OR CI 119875



rs689A 088 072 283 196ndash409 00000T 012 028

rs3842753A 086 072 244 172ndash347 00001C 014 028

(b)


OR CI119875



rs689A 067 072 081 060ndash107 014T 033 028

rs3842753A 068 072 084 063ndash112 026C 032 028

(c)


OR CI119875



rs689A 079 072 151 151ndash225 004T 021 028

rs3842753A 074 072 123 084ndash179 031C 024 028






Type 1 diabetes

I A C 07492III T A 02275I T A 0012


Type 2 diabetes

I A C 07035III T A 02703I T A 00199


Atypical diabetes




















Acknowledgments


References










































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of























Acknowledgments


References










































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of





































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of





















of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of
















Research Article The Genetic Profile from HLA and Non-HLA ...downloads.hindawi.com/journals/jdr/2015/485132.pdf · Research Article The Genetic Profile from HLA and Non-HLA Loci Allows

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