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The Genetic Profile from HLA and Non-HLA Loci Allows Identification of Atypical Type 2 Diabetes Patients.

ABSTRACT: The complex diagnosis and treatment of diabetes highlight the need for markers to define how to monitor patients correctly during the course of their disease. Different studies demonstrate the existence of patients who cannot be clearly classified. We have previously shown that it is possible to differentiate "atypical diabetic patients" based on genotyping the HLA. In this work we show that the analysis of non-HLA related to type 1 diabetes in the INS-VNTR, SNP rs689, and rs3842753 improves the identification of these patients. We genotyped 913 individuals comprising controls from the general population and "classic" and "atypical" diabetic patients. We compared the distribution of these loci and analyzed linkage disequilibrium. The haplotype was in LD for all the SNPs that were evaluated. Regarding their association with the disease, the haplotype IAC was associated with type 1 (odds 2.60, 1.82-3.72, CI 95%) and "atypical diabetes" (odds 1.50, 1.01-2.23, CI 95%), whereas we did not observe an association with type 2 diabetes. Therefore, our results confirm that atypical diabetes is a different entity of the disease where the patient presents with a genetic background of T1D and a T2D phenotype, findings that are likely to be relevant for patient diagnosis and management in the clinic.

SUBMITTER: Fabregat M

PROVIDER: S-EPMC4530254 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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The Genetic Profile from HLA and Non-HLA Loci Allows Identification of Atypical Type 2 Diabetes Patients.

Fabregat Matias M Fernandez Mariana M Javiel Gerardo G Vitarella Graciela G Mimbacas Adriana A

Journal of diabetes research 20150727

The complex diagnosis and treatment of diabetes highlight the need for markers to define how to monitor patients correctly during the course of their disease. Different studies demonstrate the existence of patients who cannot be clearly classified. We have previously shown that it is possible to differentiate "atypical diabetic patients" based on genotyping the HLA. In this work we show that the analysis of non-HLA related to type 1 diabetes in the INS-VNTR, SNP rs689, and rs3842753 improves the ...[more]

PMID: 26273670

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Project description:BackgroundIn adulthood, autoimmune diabetes can present as non-insulin-requiring diabetes, termed as 'latent autoimmune diabetes in adults' (LADA). In this study, we investigated established type 1 diabetes (T1D) and type 2 diabetes (T2D) genetic loci in a large cohort of LADA cases to assess where LADA is situated relative to these two well-characterized, classic forms of diabetes.MethodsWe tested the association of T1D and T2D GWAS-implicated loci in 978 LADA cases and 1057 non-diabetic controls of European ancestry using a linear mixed model. We then compared the associations of T1D and T2D loci between LADA and T1D and T2D cases, respectively. We quantified the difference in genetic risk between each given disease at each locus, and also calculated genetic risk scores to quantify how genetic liability to T1D and T2D distinguished LADA cases from controls.ResultsOverall, our results showed that LADA is genetically more similar to T1D, with the exception of an association at the T2D HNF1A locus. Several T1D loci were associated with LADA, including the major histocompatibility complex region, as well as at PTPN22, SH2B3, and INS. Contrary to previous studies, the key T2D risk allele at TCF7L2 (rs7903146-T) had a significantly lower frequency in LADA cases, suggesting that this locus does not play a role in LADA etiology. When constrained on antibody status, the similarity between LADA and T1D became more apparent; however, the HNF1A and TCF7L2 observations persisted.ConclusionLADA is genetically closer to T1D than T2D, although the genetic load of T1D risk alleles is less than childhood-onset T1D, particularly at the major histocompatibility complex region, potentially accounting for the later disease onset. Our results show that the genetic spectrum of T1D extends into adult-onset diabetes, where it can clinically masquerade as T2D. Furthermore, T2D genetic risk plays a small role in LADA, with a degree of evidence for the HNF1A locus, highlighting the potential for genetic risk scores to contribute towards defining diabetes subtypes.

Project description:Traditional linkage analysis and genome-wide association studies have identified HLA and a number of non-HLA genes as genetic factors for islet autoimmunity (IA) and type 1 diabetes (T1D). However, the relative risk associated with previously identified non-HLA genes is usually very small as measured in cases/controls from mixed populations. Genetic associations for IA and T1D may be more accurately assessed in prospective cohorts. In this study, 5806 subjects from the TEDDY (The Environmental Determinants of Diabetes in the Young) study, an international prospective cohort study, were genotyped for 176,586 SNPs on the ImmunoChip. Cox proportional hazards analyses were performed to discover the SNPs associated with the risk for IA, T1D, or both. Three regions were associated with the risk of developing any persistent confirmed islet autoantibody: one known region near SH2B3 (HR = 1.35, p = 3.58 × 10-7) with Bonferroni-corrected significance and another known region near PTPN22 (HR = 1.46, p = 2.17 × 10-6) and one novel region near PPIL2 (HR = 2.47, p = 9.64 × 10-7) with suggestive evidence (p < 10-5). Two known regions (PTPN22: p = 2.25 × 10-6, INS; p = 1.32 × 10-7) and one novel region (PXK/PDHB: p = 8.99 × 10-6) were associated with the risk for multiple islet autoantibodies. First appearing islet autoantibodies differ with respect to association. Two regions (INS: p = 5.67 × 10-6 and TTC34/PRDM16: 6.45 × 10-6) were associated if the fist appearing autoantibody was IAA and one region (RBFOX1: p = 8.02 × 10-6) was associated if the first appearing autoantibody was GADA. The analysis of T1D identified one region already known to be associated with T1D (INS: p = 3.13 × 10-7) and three novel regions (RNASET2, PLEKHA1, and PPIL2; 5.42 × 10-6 > p > 2.31 × 10-6). These results suggest that a number of low frequency variants influence the risk of developing IA and/or T1D and these variants can be identified by large prospective cohort studies using a survival analysis approach.

Dataset Information

The Genetic Profile from HLA and Non-HLA Loci Allows Identification of Atypical Type 2 Diabetes Patients.

Publications

The Genetic Profile from HLA and Non-HLA Loci Allows Identification of Atypical Type 2 Diabetes Patients.

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