Estimation of genetic risk for type 1 diabetes

The most important gene loci defining risk of type 1 diabetes mellitus (T1DM) are located within the HLA gene region. HLA-DQ molecules are of primary importance but HLA-DR gene products modify the risk conferred by HLA-DQ. The risk associated with an HLA genotype is defined by the particular combination of susceptible and protective alleles. The highest risk is associated with a combination of two different risk haplotypes (7% risk to develop T1DM in Finland) whereas protective genotypes covering 69% of population have a risk of less than 0.2%). The complicated analysis of HLA genotypes is simplified by strong linkage disequilibrium between HLA-DRB1, -DQA1 and -DQB1 loci. In many cases one can deduce the alleles of other loci based on determination of the alleles in one locus. Differences between various populations in the frequency of marker alleles and in the linkages between them has to be taken into account. We have developed PCR based typing methods that utilize blood spot samples, microtiter plate format and lanthanide labeled oligonucleotide probes to define HLA-DQ and -DR alleles relevant for T1DM risk. Typing is run stepwise so that after initial HLA-DQB1 typing only those samples will be further analyzed in which -DQA1 or -DRB1 typing is informative and expected to contribute to the risk estimation. This method has been used to screen more than 50,000 newborn infants in Finland over a time period of 6 years, and it has been able to identify most children who have developed T1D during the follow-up period. The efficiency of the procedure has also been tested in Finnish and Greek populations.     

Genetic association signal near NTN4 in Tourette syndrome

Tourette syndrome (TS) is a neurodevelopmental disorder with a complex genetic etiology. Through an international collaboration, we genotyped 42 single nucleotide polymorphisms (p < 10⁻³) from the recent TS genomewide association study (GWAS) in 609 independent cases and 610 ancestry‐matched controls. Only rs2060546 on chromosome 12q22 (p = 3.3 × 10⁻⁴) remained significant after Bonferroni correction. Meta‐analysis with the original GWAS yielded the strongest association to date (p = 5.8 × 10⁻⁷). Although its functional significance is unclear, rs2060546 lies closest to NTN4, an axon guidance molecule expressed in developing striatum. Risk score analysis significantly predicted case–control status (p = 0.042), suggesting that many of these variants are true TS risk alleles. Ann Neurol 2014;76:310–315     

Exploring Genomic Structure Differences and Similarities between the Greek and European HapMap Populations: Implications for Association Studies

Studies of the genomic structure of the Greek population and Southeastern Europe are limited, despite the central position of the area as a gateway for human migrations into Europe. HapMap has provided a unique tool for the analysis of human genetic variation. Europe is represented by the CEU (Northwestern Europe) and the TSI populations (Tuscan Italians from Southern Europe), which serve as reference for the design of genetic association studies. Furthermore, genetic association findings are often transferred to unstudied populations. Although initial studies support the fact that the CEU can, in general, be used as reference for the selection of tagging SNPs in European populations, this has not been extensively studied across Europe. We set out to explore the genomic structure of the Greek population (56 individuals) and compare it to the HapMap TSI and CEU populations. We studied 1112 SNPs (27 regions, 13 chromosomes). Although the HapMap European populations are, in general, a good reference for the Greek population, regions of population differentiation do exist and results should not be light‐heartedly generalized. We conclude that, perhaps due to the individual evolutionary history of each genomic region, geographic proximity is not always a perfect guide for selecting a reference population for an unstudied population.     

Gestational diabetes mellitus and quality of life during the third trimester of pregnancy

Quality of Life Research - The primary aim of this study was to investigate the effect of gestational diabetes mellitus (GDM) on the quality of life (QoL) of pregnant women during the third...     

Mixed-model QSAR at the human mineralocorticoid receptor: Predicting binding mode and affinity of anabolic steroids

We present a computational study on the human mineralocorticoid receptor (hMR) that is based on multi-dimensional quantitative structure–activity relationships (mQSAR). Therein, we identified the binding mode of 48 steroid and non-steroid homologues by flexible docking to the crystal structure (software Yeti) and quantified it using 6D-QSAR (software Quasar). The receptor surrogate, evolved using a genetic algorithm, converged at a cross-validated r² of 0.810, and yielded a predictive r² of 0.661. The model was challenged by a series of scramble tests and by consensus scoring (software Raptor: r² = 0.844, predictive r² = 0.620). The model was then employed to predict the binding affinity of 26 anabolic steroids, demonstrating to which extent they might disrupt the endocrine system via binding to the hMR. The model for the hMR was added to the VirtualToxLab™, a technology developed by the Biographics Laboratory 3R, allows the identification of the endocrine-disrupting potential of drugs, chemicals and natural products in silico.     

Genetic screening for individuals at high risk for type 1 diabetes in the general population using HLA Class II alleles as disease markers. A comparison between three European populations with variable rates of disease incidence

BACKGROUND: To develop screening strategies for identification of individuals at increased genetic risk for type 1 diabetes in three populations with variable disease incidence rates and distinct ethnic origin. METHODS: A stepwise HLA DQB1-DQA1-DRB1-based screening approach was evaluated. Patients with childhood-onset type 1 diabetes were recruited from Finland (n = 1739), Hungary (n = 149), and Greece (n = 119). Consecutive newborns (2568 from Finland and 1047 from Greece) or healthy schoolchildren (n = 177 from Hungary) served as controls. RESULTS: The DQB1*02/0302 genotype conferred the highest disease risk in all populations. The DQB1*02/y (y not equal DQB1*0301,*0302,*0602,*0603, *0604) genotypes were more common and conferred a higher disease risk in the Greek population (OR 4.9) compared to the Finns (OR 1.2). DQB1*0302/x (x not equal DQB1*02, *0301, *0602, *0603, *0604) genotypes were, in contrast, more prevalent among Finnish cases (32.7%) as compared to Hungarians (18.1%) or Greeks (13.5%). The protective DQB1*0602 or *0603 positive genotypes were most common in the Finns, while DQB1*0301 was more common in Hungarians and Greeks. In all groups, DQA1 and DRB1*04 typing considerably increased the sensitivity of the DQB1-based screening. The different high-risk genotype combinations present in about 10% of the background population had a diagnostic sensitivity of 60% in Finland and 80% in Hungary and Greece. CONCLUSIONS: HLA DR-DQ-based screening is a feasible tool for the identification of individuals at increased genetic risk for type 1 diabetes in populations with diverse genetic background. The risk markers should, however, be individually selected for the target population since the screening efficiency of various markers is highly dependent on the ethnic group studied.