Significant association of a M129V independent polymorphism in the 5\prime UTR of the PRNP gene with sporadic Creutzfeldt-Jakob disease in a large German case-control study

Background: A single nucleotide polymorphism (SNP) in the coding region of the prion protein gene (PRNP) at codon 129 has been repeatedly shown to be an associated factor to sporadic Creutzfeldt-Jakob disease (sCJD), but additional major predisposing DNA variants for sCJD are still unknown. Several previous studies focused on the characterisation of polymorphisms in PRNP and the prion-like doppel gene (PRND), generating contradictory results on relatively small sample sets. Thus, extensive studies are required for validation of the polymorphisms in PRNP and PRND.Methods: We evaluated a set of nine SNPs of PRNP and one SNP of PRND in 593 German sCJD patients and 748 German healthy controls. Genotyping was performed using MALDI-TOF mass spectrometry.Results: In addition to PRNP 129, we detected a significant association between sCJD and allele frequencies of six further PRNP SNPs. No significant association of PRND T174M with sCJD was shown. We observed strong linkage disequilibrium within eight adjacent PRNP SNPs, including PRNP 129. However, the association of sCJD with PRNP 1368 and PRNP 34296 appeared to be independent on the genotype of PRNP 129. We additionally identified the most common haplotypes of PRNP to be over-represented or under-represented in our cohort of patients with sCJD.Conclusion: Our study evaluated previous findings of the association of SNPs in the PRNP and PRND genes in the largest cohorts for association study in sCJD to date, and extends previous findings by defining for the first time the haplotypes associated with sCJD in a large population of the German CJD surveillance study

Gene-Gene Interaction between APOA5 and USF1: Two Candidate Genes for the Metabolic Syndrome

Objective: The metabolic syndrome, a major cluster of risk factors for cardiovascular diseases, shows increasing prevalence worldwide. Several studies have established associations of both apolipoprotein A5 (APOA5) gene variants and upstream stimulatory factor 1 (USF1) gene variants with blood lipid levels and metabolic syndrome. USF1 is a transcription factor for APOA5. Methods: We investigated a possible interaction between these two genes on the risk for the metabolic syndrome, using data from the German population-based KORA survey 4 (1,622 men and women aged 55-74 years). Seven APOA5 single nucleotide polymorphisms (SNPs) were analyzed in combination with six USF1 SNPs, applying logistic regression in an additive model adjusting for age and sex and the definition for metabolic syndrome from the National Cholesterol Education Program's Adult Treatment Panel III (NCEP (AIII)) including medication. Results: The overall prevalence for metabolic syndrome was 41%. Two SNP combinations showed a nominal gene-gene interaction (p values 0.024 and 0.047). The effect of one SNP was modified by the other SNP, with a lower risk for the metabolic syndrome with odds ratios (ORs) between 0.33 (95% CI = 0.13-0.83) and 0.40 (95% CI = 0.15-1.12) when the other SNP was homozygous for the minor allele. Nevertheless, none of the associations remained significant after correction for multiple testing. Conclusion: Thus, there is an indication of an interaction between APOA5 and USF1 on the risk for metabolic syndrome

Discovery of Sexual Dimorphisms in Metabolic and Genetic Biomarkers

Metabolomic profiling and the integration of whole-genome genetic association data has proven to be a powerful tool to comprehensively explore gene regulatory networks and to investigate the effects of genetic variation at the molecular level. Serum metabolite concentrations allow a direct readout of biological processes, and association of specific metabolomic signatures with complex diseases such as Alzheimer's disease and cardiovascular and metabolic disorders has been shown. There are well-known correlations between sex and the incidence, prevalence, age of onset, symptoms, and severity of a disease, as well as the reaction to drugs. However, most of the studies published so far did not consider the role of sexual dimorphism and did not analyse their data stratified by gender. This study investigated sex-specific differences of serum metabolite concentrations and their underlying genetic determination. For discovery and replication we used more than 3,300 independent individuals from KORA F3 and F4 with metabolite measurements of 131 metabolites, including amino acids, phosphatidylcholines, sphingomyelins, acylcarnitines, and C6-sugars. A linear regression approach revealed significant concentration differences between males and females for 102 out of 131 metabolites (p-values<3.8 x 10(-4); Bonferroni-corrected threshold). Sex-specific genome-wide association studies (GWAS) showed genome-wide significant differences in beta-estimates for SNPs in the CPS1 locus (carbamoyl-phosphate synthase 1, significance level: p<3.8 x 10(-10); Bonferroni-corrected threshold) for glycine. We showed that the metabolite profiles of males and females are significantly different and, furthermore, that specific genetic variants in metabolism-related genes depict sexual dimorphism. Our study provides new important insights into sex-specific differences of cell regulatory processes and underscores that studies should consider sex-specific effects in design and interpretation

Non-replication of an association of CTNNBL1 polymorphisms and obesity in a population of Central European ancestry

<p>Abstract</p> <p>Background</p> <p>A recent genome-wide association (GWA) study of U.S. Caucasians suggested that eight single nucleotide polymorphisms (SNPs) in <it>CTNNBL1 </it>are associated with obesity and increased fat mass. We analysed the respective SNPs in data from our previously published GWA for early onset obesity (case-control design), in GWA data from a population-based cohort of adults, and in an independent family-based obesity study. We investigated whether variants in <it>CTNNBL1 </it>(including rs6013029) and in three other genes (<it>SH3PXD2B</it>, <it>SLIT3 </it>and <it>FLJ42133</it>,) were associated with obesity.</p> <p>Methods</p> <p>The GWA studies were carried out using Affymetrix^®SNP Chips with approximately 500,000 markers each. In the families, SNP rs6013029 was genotyped using the TaqMan^®allelic discrimination assay. The German case-control GWA included 487 extremely obese children and adolescents and 442 healthy lean individuals. The adult GWA included 1,644 individuals from a German population-based study (KORA). The 775 independent German families consisted of extremely obese children and adolescents and their parents.</p> <p>Results</p> <p>We found no evidence for an association of the reported variants in <it>CTNNBL1 </it>with early onset obesity or increased BMI. Further, in our family-based study we found no evidence for over-transmission of the rs6013029 risk-allele T to obese children. Additionally, we found no evidence for an association of <it>SH3PXD2B</it>, <it>SLIT3 and FLJ42133 </it>variants in our two GWA samples.</p> <p>Conclusion</p> <p>We detected no confirmation of the recent association of variants in <it>CTNNBL1 </it>with obesity in a population of Central European ancestry.</p

An Interferon-Induced Helicase (IFIH1) Gene Polymorphism Associates With Different Rates of Progression From Autoimmunity to Type 1 Diabetes

OBJECTIVE: Genome-wide association studies have identified gene regions associated with the development of type 1 diabetes. The aim of this study was to determine whether these associations are with the development of autoimmunity and/or progression to diabetes. RESEARCH DESIGN AND METHODS: Children (n = 1,650) of parents with type 1 diabetes were prospectively followed from birth (median follow-up 10.20 years) for the development of islet autoantibodies, thyroid peroxidase antibodies, tissue transglutaminase antibodies, and diabetes. Genotyping for single-nucleotide polymorphisms of the PTPN22, ERBB3, PTPN2, KIAA0350, CD25, and IFIH1 genes was performed using the MassARRAY system with iPLEX chemistry. RESULTS: Islet autoantibodies developed in 137 children and diabetes developed in 47 children. Type 1 diabetes risk was associated with the IFIH1 rs2111485 single-nucleotide polymorphism (hazard ratio 2.08; 95% CI 1.16-3.74; P = 0.014). None of the other genes were significantly associated with diabetes development in this cohort. IFIH1 genotypes did not associate with the development of islet autoantibodies (P = 0.80) or autoantibodies against thyroid peroxidase (P = 0.55) and tissue transglutaminase (P = 0.66). Islet autoantibody-positive children with the IFIH1 rs2111485 GG genotype had a faster progression to diabetes (31% within 5 years) than children with the type 1 diabetes protective GA or AA genotypes (11% within 5 years; P = 0.006). CONCLUSIONS: The findings indicate that IFIH1 genotypes influence progression from autoimmunity to diabetes development, consistent with the notion that protective genotypes downregulate responses to environmental insults after initiation of autoimmunity

Fat Mass and Obesity-Associated Gene (FTO) in Eating Disorders: Evidence for Association of the rs9939609 Obesity Risk Allele with Bulimia nervosa and Anorexia nervosa

Objective: The common single nucleotide polymorphism (SNP) rs9939609 in the fat mass and obesity-associated gene (FTO) is associated with obesity. As genetic variants associated with weight regulation might also be implicated in the etiology of eating disorders, we evaluated whether SNP rs9939609 is associated with bulimia nervosa (BN) and anorexia nervosa (AN). Methods: Association of rs9939609 with BN and AN was assessed in 689 patients with AN, 477 patients with BN, 984 healthy non-population-based controls, and 3,951 population-based controls (KORA-S4). Based on the familial and premorbid occurrence of obesity in patients with BN, we hypothesized an association of the obesity risk A-allele with BN. Results: In accordance with our hypothesis, we observed evidence for association of the rs9939609 A-allele with BN when compared to the non-population-based controls (unadjusted odds ratio (OR) = 1.142, one-sided 95% confidence interval (CI) 1.001-infinity; one-sided p = 0.049) and a trend in the population-based controls (OR = 1.124, one-sided 95% CI 0.932-infinity; one-sided p = 0.056). Interestingly, compared to both control groups, we further detected a nominal association of the rs9939609 A-allele to AN (OR = 1.181, 95% CI 1.027-1.359, two-sided p = 0.020 or OR = 1.673, 95% CI 1.101-2.541, two-sided p = 0.015,). Conclusion: Our data suggest that the obesity-predisposing FTO allele might be relevant in both AN and BN. Copyright (C) 2012 S. Karger GmbH, Freibur

Effects of smoking and smoking cessation on human serum metabolite profile: results from the KORA cohort study

Background: Metabolomics helps to identify links between environmental exposures and intermediate biomarkers of disturbed pathways. We previously reported variations in phosphatidylcholines in male smokers compared with non-smokers in a cross-sectional pilot study with a small sample size, but knowledge of the reversibility of smoking effects on metabolite profiles is limited. Here, we extend our metabolomics study with a large prospective study including female smokers and quitters. Methods: Using targeted metabolomics approach, we quantified 140 metabolite concentrations for 1,241 fasting serum samples in the population-based Cooperative Health Research in the Region of Augsburg (KORA) human cohort at two time points: baseline survey conducted between 1999 and 2001 and follow-up after seven years. Metabolite profiles were compared among groups of current smokers, former smokers and never smokers, and were further assessed for their reversibility after smoking cessation. Changes in metabolite concentrations from baseline to the follow-up were investigated in a longitudinal analysis comparing current smokers, never smokers and smoking quitters, who were current smokers at baseline but former smokers by the time of follow-up. In addition, we constructed protein-metabolite networks with smoking-related genes and metabolites. Results: We identified 21 smoking-related metabolites in the baseline investigation (18 in men and six in women, with three overlaps) enriched in amino acid and lipid pathways, which were significantly different between current smokers and never smokers. Moreover, 19 out of the 21 metabolites were found to be reversible in former smokers. In the follow-up study, 13 reversible metabolites in men were measured, of which 10 were confirmed to be reversible in male quitters. Protein-metabolite networks are proposed to explain the consistent reversibility of smoking effects on metabolites. Conclusions: We showed that smoking-related changes in human serum metabolites are reversible after smoking cessation, consistent with the known cardiovascular risk reduction. The metabolites identified may serve as potential biomarkers to evaluate the status of smoking cessation and characterize smoking-related diseases

Haplotype Reconstruction Error as a Classical Misclassification Problem: Introducing Sensitivity and Specificity as Error Measures

BACKGROUND: Statistically reconstructing haplotypes from single nucleotide polymorphism (SNP) genotypes, can lead to falsely classified haplotypes. This can be an issue when interpreting haplotype association results or when selecting subjects with certain haplotypes for subsequent functional studies. It was our aim to quantify haplotype reconstruction error and to provide tools for it. METHODS AND RESULTS: By numerous simulation scenarios, we systematically investigated several error measures, including discrepancy, error rate, and R(2), and introduced the sensitivity and specificity to this context. We exemplified several measures in the KORA study, a large population-based study from Southern Germany. We find that the specificity is slightly reduced only for common haplotypes, while the sensitivity was decreased for some, but not all rare haplotypes. The overall error rate was generally increasing with increasing number of loci, increasing minor allele frequency of SNPs, decreasing correlation between the alleles and increasing ambiguity. CONCLUSIONS: We conclude that, with the analytical approach presented here, haplotype-specific error measures can be computed to gain insight into the haplotype uncertainty. This method provides the information, if a specific risk haplotype can be expected to be reconstructed with rather no or high misclassification and thus on the magnitude of expected bias in association estimates. We also illustrate that sensitivity and specificity separate two dimensions of the haplotype reconstruction error, which completely describe the misclassification matrix and thus provide the prerequisite for methods accounting for misclassification

Association between variations in the TLR4 gene and incident type 2 diabetes is modified by the ratio of total cholesterol to HDL-cholesterol

<p>Abstract</p> <p>Background</p> <p>Toll-like receptor 4 (TLR4), the signaling receptor for lipopolysaccharides, is an important member of the innate immunity system. Since several studies have suggested that type 2 diabetes might be associated with changes in the innate immune response, we sought to investigate the association between genetic variants in the <it>TLR4 </it>gene and incident type 2 diabetes.</p> <p>Methods</p> <p>A case-cohort study was conducted in initially healthy, middle-aged subjects from the MONICA/KORA Augsburg studies including 498 individuals with incident type 2 diabetes and 1,569 non-cases. Seven SNPs were systematically selected in the <it>TLR4 </it>gene and haplotypes were reconstructed.</p> <p>Results</p> <p>The effect of <it>TLR4 </it>SNPs on incident type 2 diabetes was modified by the ratio of total cholesterol to high-density lipoprotein cholesterol (TC/HDL-C). In men, four out of seven <it>TLR4 </it>variants showed significant interaction with TC/HDL-C after correction for multiple testing (p < 0.01). The influence of the minor alleles of those variants on the incidence of type 2 diabetes was observed particularly for male patients with high values of TC/HDL-C. Consistent with these findings, haplotype-based analyses also revealed that the effect of two haplotypes on incident type 2 diabetes was modified by TC/HDL-C in men (p < 10^-3). However, none of the investigated variants or haplotypes was associated with type 2 diabetes in main effect models without assessment of effect modifications.</p> <p>Conclusion</p> <p>We conclude that minor alleles of several <it>TLR4 </it>variants, although not directly associated with type 2 diabetes might increase the risk for type 2 diabetes in subjects with high TC/HDL-C. Additionally, our results confirm previous studies reporting sex-related dissimilarities in the development of type 2 diabetes.</p

Potential Impact and Study Considerations of Metabolomics in Cardiovascular Health and Disease: A Scientific Statement From the American Heart Association.

Through the measure of thousands of small-molecule metabolites in diverse biological systems, metabolomics now offers the potential for new insights into the factors that contribute to complex human diseases such as cardiovascular disease. Targeted metabolomics methods have already identified new molecular markers and metabolomic signatures of cardiovascular disease risk (including branched-chain amino acids, select unsaturated lipid species, and trimethylamine-N-oxide), thus in effect linking diverse exposures such as those from dietary intake and the microbiota with cardiometabolic traits. As technologies for metabolomics continue to evolve, the depth and breadth of small-molecule metabolite profiling in complex systems continue to advance rapidly, along with prospects for ongoing discovery. Current challenges facing the field of metabolomics include scaling throughput and technical capacity for metabolomics approaches, bioinformatic and chemoinformatic tools for handling large-scale metabolomics data, methods for elucidating the biochemical structure and function of novel metabolites, and strategies for determining the true clinical relevance of metabolites observed in association with cardiovascular disease outcomes. Progress made in addressing these challenges will allow metabolomics the potential to substantially affect diagnostics and therapeutics in cardiovascular medicine