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Background: Thiopurine methyltransferase (TPMT) plays a significant role in the metabolism of thiopurines, and, for patients with inflammatory bowel disease (IBD), it is useful to perform TPMT genotyping prior to azathioprine (AZA) treatment. In this study, we determined TPMT gene polymorphisms in a cohort of IBD patients in Latvia. Methods: DNA samples were obtained from 244 IBD patients, and qPCR was performed for detection of rs1800462, rs1800460, and rs1142345 single-nucleotide polymorphisms (SNPs). Three common, non-functional TPMT alleles (TPMT*2, *3B, and *3C) were identified (women, 51%; men, 49%). TPMT*2, *3A, *3B, and *3C allelic variants detected using qPCR were consistent with restriction fragment length polymorphism (RFLP) data. Results: Among patients, 78% had ulcerative colitis and 22% had Crohn's disease, with 93.9% of the former carrying a wild-type homozygous TPMT*1/*1 genotype and 6.1% carrying heterozygous genotypes. The most frequent polymorphisms were TPMT*1/*3A (5.3%: two variants: TPMT*3B and TPMT*3C), TPMT*1/*3C (0.4%), and TPMT*1/*2 (0.4%). None of the patients carried a TPMT*3B polymorphism and no patients were homozygous for any mutation. Conclusion: This is the first study to identify TPMT gene polymorphisms in adult IBD patients in Latvia. The results indicate that the frequency of common TPMT alleles is similar to that of other European populations. [ABSTRACT FROM AUTHOR]

Objective(s): High variability in clinical response to metformin is often observed in type 2 diabetes (T2D) patients, and it highlights the need for identification of genetic components affecting the efficiency of metformin therapy. Aim of this observational study is to evaluate the role of tagSNPs (tagging single nucleotide polymorphisms) from genomic regions coding for six metformin transporter genes with respect to the short-term efficiency. Design: 102 tagSNPs in 6 genes coding for metformin transporters were genotyped in the group of 102 T2D patients treated with metformin for 3 months. Methods: Most significant hits were analyzed in the group of 131 T2D patients from Slovakia. Pharmacokinetic study in 25 healthy nondiabetic volunteers was conducted to investigate the effects of identified polymorphisms. Results: In the discovery group of 102 patients, minor alleles of rs3119309, rs7757336 and rs2481030 were significantly nominally associated with metformin inefficiency (P = 1.9 × 10-6 to 8.1 × 10-6). Effects of rs2481030 and rs7757336 did not replicate in the group of 131 T2DM patients from Slovakia alone, whereas rs7757336 was significantly associated with a reduced metformin response in combined group. In pharmacokinetic study, group of individuals harboring risk alleles of rs7757336 and rs2481030 displayed significantly reduced AUC∞ of metformin in plasma. Conclusions: For the first time, we have identified an association between the lack of metformin response and SNPs rs3119309 and rs7757336 located in the 5' flanking region of the genes coding for Organic cation transporter 2 and rs2481030 located in the 5' flanking region of Organic cation transporter 3 that was supported by the results of a pharmacokinetic study on 25 healthy volunteers. [ABSTRACT FROM AUTHOR]

Background: The mechanisms by which genetic variants, such as single nucleotide polymorphisms (SNPs), identified in genome-wide association studies act to influence body mass remain unknown for most of these SNPs, which continue to puzzle the scientific community. Recent evidence points to the epigenetic and chromatin states of the genome as having important roles. Methods: We genotyped 355 healthy young individuals for 52 known obesity-associated SNPs and obtained DNA methylation levels in their blood using the Illumina 450 K BeadChip. Associations between alleles and methylation at proximal cytosine residues were tested using a linear model adjusted for age, sex, weight category, and a proxy for blood cell type counts. For replication in other tissues, we used two open-access datasets (skin fibroblasts, n = 62; four brain regions, n =121-133) and an additional dataset in subcutaneous and visceral fat (n =149). Results: We found that alleles at 28 of these obesity-associated SNPs associate with methylation levels at 107 proximal CpG sites. Out of 107 CpG sites, 38 are located in gene promoters, including genes strongly implicated in obesity (MIR148A, BDNF, PTPMT1, NR1H3, MGAT1, SCGB3A1, HOXC12, PMAIP1, PSIP1, RPS10-NUDT3, RPS10, SKOR1, MAP2K5, SIX5, AGRN, IMMP1L, ELP4, ITIH4, SEMA3G, POMC, ADCY3, SSPN, LGR4, TUFM, MIR4721, SULT1A1, SULT1A2, APOBR, CLN3, SPNS1, SH2B1, ATXN2L,a n d IL27). Interestingly, the associated SNPs are in known eQTLs for some of these genes. We also found that the 107 CpGs are enriched in enhancers in peripheral blood mononuclear cells. Finally, our results indicate that some of these associations are not blood-specific as we successfully replicated four associations in skin fibroblasts. Conclusions: Our results strongly suggest that many obesity-associated SNPs are associated with proximal gene regulation, which was reflected by association of obesity risk allele genotypes with differential DNA methylation. This study highlights the importance of DNA methylation and other chromatin marks as a way to understand the molecular basis of genetic variants associated with human diseases and traits. [ABSTRACT FROM AUTHOR]

The heritability of high-density lipoprotein cholesterol (HDL-C) level is estimated at approximately 50%. Recent genome-wide association studies have identified genes involved in regulation of high-density lipoprotein cholesterol (HDL-C) levels. The precise genetic profile determining heritability of HDL-C however are far from complete and there is substantial room for further characterization of genetic profiles influencing blood lipid levels. Here we report an association study comparing the distribution of 139 SNPs from more than 30 genes between groups that represent extreme ends of HDL-C distribution. We genotyped 704 individuals that were selected from Genome Database of Latvian Population. 10 SNPs from CETP gene showed convincing association with low HDL-C levels (rs1800775, rs3764261, rs173539, rs9939224, rs711752, rs708272, rs7203984, rs7205804, rs11076175 and rs9929488) while 34 SNPs from 10 genes were nominally associated (p<0.05) with HDL-C levels. We have also identified haplotypes from CETP with distinct effects on determination of HDL-C levels. Our conclusion: So far the SNPs in CETP gene are identified as the most common genetic factor influencing HDL-C levels in the representative sample from Latvian population. [ABSTRACT FROM AUTHOR]

Several studies examined the fine-scale structure of human genetic variation in Europe. However, the European sets analyzed represent mainly northern, western, central, and southern Europe. Here, we report an analysis of approximately 166,000 single nucleotide polymorphisms in populations from eastern (northeastern) Europe: four Russian populations from European Russia, and three populations from the northernmost Finno-Ugric ethnicities (Veps and two contrast groups of Komi people). These were compared with several reference European samples, including Finns, Estonians, Latvians, Poles, Czechs, Germans, and Italians. The results obtained demonstrated genetic heterogeneity of populations living in the region studied. Russians from the central part of European Russia (Tver, Murom, and Kursk) exhibited similarities with populations from central–eastern Europe, and were distant from Russian sample from the northern Russia (Mezen district, Archangelsk region). Komi samples, especially Izhemski Komi, were significantly different from all other populations studied. These can be considered as a second pole of genetic diversity in northern Europe (in addition to the pole, occupied by Finns), as they had a distinct ancestry component. Russians from Mezen and the Finnic-speaking Veps were positioned between the two poles, but differed from each other in the proportions of Komi and Finnic ancestries. In general, our data provides a more complete genetic map of Europe accounting for the diversity in its most eastern (northeastern) populations. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study was to characterize the genetic variance of somatostatin receptor 5 (SSTR5) and investigate the possible correlation of such variants with acromegaly risk and different disease characteristics. Design and methods: The SSTR5 gene coding region and 2000 bp upstream region was sequenced in 48 patients with acromegaly and 96 control subjects. Further, three single nucleotide polymorphisms (SNPs) were analyzed in the same group of acromegaly patients and in an additional group of 475 age- and sex-matched controls. Results: In total, 19 SNPs were identified in the SSTR5 gene locus by direct sequencing. Three SNPs (rs34037914, rs169068, and rs642249) were significantly associated with the presence of acromegaly using the initial controls. The allele frequencies were significantly (P<0.01) different between the acromegaly patients and the additional large control group. rs34037914 and rs642249 remained significantly associated with acromegaly after Bonferroni correction and permutation tests (odds ratio (OR)Z3.38; 95% confidence interval (CI), 1.78-6.42; PZ0.00016 and ORZ2.41; 95% CI, 1.41-4.13; PZ0.0014 respectively). Haplotype reconstruction revealed two possible risk haplotypes determined by rs34037914 (633T) and rs642249 (1044A) alleles. Both haplotypes were found in significantly higher frequency in acromegaly patients compared with controls (P<0.001). In addition, the 663T allele was significantly associated with a younger age of acromegaly diagnosis (unstandardized regression coefficient β= -10.4; P=0.002), increased body mass index (&beta=4.1; P=0.004), higher number of adenoma resection (P<0.001) and lack of observable tumor shrinkage after somatostatin analog treatment (P=0.014). Conclusions: Our results demonstrate a previously undetected strong association of two SSTR5 SNPs with acromegaly. The data also suggest a possible involvement of SSTR5 variants in decreased suppression of GH production and increased tumor proliferation. [ABSTRACT FROM AUTHOR]

The article presents a study on HFE-related hemochromatosis (HH) which is an autosomal recessive, multisystemic disease caused by regulated uptake and accumulation of iron. Topics discussed include causes of HH due to mutations in HFE gene C282Y, use of TaqMan (single nucleotide polymorphism) SNP for carrying genotyping on polymerase chain reaction (PCR) system, and aim of the study to provide frequency of HH risk mutation for Ukraine and Belarus population.

Abstract: The glyoxalase system and its main enzyme, glyoxalase 1 (GLO1), protect cells from advanced glycation end products (AGEs), such as methylglyoxal (MG) and other reactive dicarbonyls, the formation of which is increased in diabetes patients as a result of excessive glycolysis. MG is partly responsible for harmful protein alterations in living cells, notably in neurons, leading to their dysfunction, and recent studies have shown a negative correlation between GLO1 expression and tissue damage. Neuronal dysfunction is a common diabetes complication due to elevated blood sugar levels, leading to high levels of AGEs. The aim of our study was to determine whether single nucleotide polymorphisms (SNPs) in the GLO1 gene influence activity of the enzyme. In total, 125 healthy controls, 101 type 1 diabetes, and 100 type 2 diabetes patients were genotyped for three common SNPs, rs2736654 (A111E), rs1130534 (G124G), and rs1049346 (5′-UTR), in GLO1. GLO1 activity was determined in whole blood lysates for all participants of the study. Our results showed a significant association between the minor alleles rs1130534 and rs1049346 and decreased enzyme activity (P =0.001 and P =2.61×10−5, respectively). Increased allelic counts of the risk alleles were strongly associated with decreased GLO1 activity (standardised β =−0.24, P =2.15×10−5), indicating independent actions of these variants on GLO1 activity, as supported by the haplotype analysis. We showed for the first time an association between genetic variants with GLO1 enzyme activity in humans. SNPs in GLO1 can be used to predict enzyme activity and detoxifying capabilities, but further studies are needed to link these SNPs with common complications in diabetes. [Copyright &y& Elsevier]