Comparison of genotyping using pooled DNA samples (allelotyping) and individual genotyping using the affymetrix genome-wide human SNP array 6.0

Background: Genome-wide association studies (GWAS) using array-based genotyping technology are widely used to identify genetic loci associated with complex diseases or other phenotypes. The costs of GWAS projects based on individual genotyping are still comparatively high and increase with the size of study populations. Genotyping using pooled DNA samples, as also being referred as to allelotyping approach, offers an alternative at affordable costs. In the

Transcriptional profiling of Helicobacter pylori Fur- and iron-regulated gene expression

Intracellular iron homeostasis is a necessity for almost all living organisms, since both iron restriction and iron overload can result in cell death. The ferric uptake regulator protein, Fur, controls iron homeostasis in most Gram-negative bacteria. In the human gastric pathogen Helicobacter pylori, Fur is thought to have acquired extra functions to compensate for the relative paucity of regulatory genes. To identify H. pylori genes regulated by iron and Fur, we used DNA array-based transcriptional profiling with RNA isolated from H. pylori 26695 wild-type and fur mutant cells grown in iron-restricted and iron-replete conditions. Sixteen genes encoding proteins involved in metal metabolism, nitrogen metabolism, motility, cell wall synthesis and cofactor synthesis displayed iron-dependent Fur-repressed expression. Conversely, 16 genes encoding proteins involved in iron storage, respiration, energy metabolism, chemotaxis, and oxygen scavenging displayed iron-induced Fur-dependent expression. Several Fur-regulated genes have been previously shown to be essential for acid resistance or gastric colonization in animal models, such as those encoding the hydrogenase and superoxide dismutase enzymes. Overall, there was a partial overlap between the sets of genes regulated by Fur and those previously identified as growth-phase, iron or acid regulated. Regulatory patterns were confirmed for five selected genes using Northern hybridization. In conclusion, H. pylori Fur is a versatile regulator involved in many pathways essential for gastric colonization. These findings further delineate the central role of Fur in regulating the unique capacity of H. pylori to colonize the human stomach

Genome-Wide Association Study with Targeted and Non-targeted NMR Metabolomics Identifies 15 Novel Loci of Urinary Human Metabolic Individuality

Genome-wide association studies with metabolic traits (mGWAS) uncovered many genetic variants that influence human metabolism. These genetically influenced metabotypes (GIMs) contribute to our metabolic individuality, our capacity to respond to environmental challenges, and our susceptibility to specific diseases. While metabolic homeostasis in blood is a well investigated topic in large mGWAS with over 150 known loci, metabolic detoxification through urinary excretion has only been addressed by few small mGWAS with only 11 associated loci so far. Here we report the largest mGWAS to date, combining targeted and non-targeted 1H NMR analysis of urine samples from 3,861 participants of the SHIP-0 cohort and 1,691 subjects of the KORA F4 cohort. We identified and replicated 22 loci with significant associations with urinary traits, 15 of which are new (HIBCH, CPS1, AGXT, XYLB, TKT, ETNPPL, SLC6A19, DMGDH, SLC36A2, GLDC, SLC6A13, ACSM3, SLC5A11, PNMT, SLC13A3). Two-thirds of the urinary loci also have a metabolite association in blood. For all but one of the 6 loci where significant associations target the same metabolite in blood and urine, the genetic effects have the same direction in both fluids. In contrast, for the SLC5A11 locus, we found increased levels of myo-inositol in urine whereas mGWAS in blood reported decreased levels for the same genetic variant. This might indicate less effective re-absorption of myo-inositol in the kidneys of carriers. In summary, our study more than doubles the number of known loci that influence urinary phenotypes. It thus allows novel insights into the relationship between blood homeostasis and its regulation through excretion. The newly discovered loci also include variants previously linked to chronic kidney disease (CPS1, SLC6A13), pulmonary hypertension (CPS1), and ischemic stroke (XYLB). By establishing connections from gene to disease via metabolic traits our results provide novel hypotheses about molecular mechanisms involved in the etiology of diseases

Helicobacter pylori colonization and obesity - A Mendelian randomization study

Obesity is associated with substantial morbidity, costs, and decreased life expectancy, and continues to rise worldwide. While etiological understanding is needed for prevention, epidemiological studies indicated that colonization with Helicobacter pylori (H. pylori) may affect body mass index (BMI), but with inconsistent results. Here, we examine the relationship between H. pylori colonization and BMI/obesity. Cross-sectional analyses were performed in two independent population-based cohorts of elderly from the Netherlands and Germany (n = 13,044). Genetic risk scores were conducted based on genetic loci associated with either H. pylori colonization or BMI/obesity. We performed a bi-directional Mendelian randomization. Meta-analysis of cross-sectional data revealed no association between anti-H. pylori IgG titer and BMI, nor of H. pylori positivity and BMI. Anti-H. pylori IgG titer was negatively associated with obesity (OR 0.99972; 95% CI 0.99946-0.99997, p = 0.03) and with obesity classes (Beta -6.91 •10-5; 95% CI -1.38•10-4, -5.49•10-7, p = 0.048), but the magnitude of these effects was limited. Mendelian randomization showed no causal relation between H. pylori genetic risk score and BMI/obesity, nor between BMI or obesity genetic risk scores and H. pylori positivity. This study provides no evidence for a clinically relevant association between H. pylori and BMI/obesity

Genome-wide association study identifies the SERPINB gene cluster as a susceptibility locus for food allergy

Genetic factors and mechanisms underlying food allergy are largely unknown. Due to heterogeneity of symptoms a reliable diagnosis is often difficult to make. Here, we report a genome-wide association study on food allergy diagnosed by oral food challenge in 497 cases and 2387 controls. We identify five loci at genome-wide significance, the clade B serpin (SERPINB) gene cluster at 18q21.3, the cytokine gene cluster at 5q31.1, the filaggrin gene, the C11orf30/LRRC32 locus, and the human leukocyte antigen (HLA) region. Stratifying the results for the causative food demonstrates that association of the HLA locus is peanut allergy-specific whereas the other four loci increase the risk for any food allergy. Variants in the SERPINB gene cluster are associated with SERPINB10 expression in leukocytes. Moreover, SERPINB genes are highly expressed in the esophagus. All identified loci are involved in immunological regulation or epithelial barrier function, emphasizing the role of both mechanisms in food allergy

Novel multiple sclerosis susceptibility loci implicated in epigenetic regulation

We conducted a genome-wide association study (GWAS) on multiple sclerosis (MS) susceptibility in German cohorts with 4888 cases and 10,395 controls. In addition to associations within the major histocompatibility complex (MHC) region, 15 non-MHC loci reached genome-wide significance. Four of these loci are novel MS susceptibility loci. They map to the genes L3MBTL3, MAZ, ERG, and SHMT1. The lead variant at SHMT1 was replicated in an independent Sardinian cohort. Products of the genes L3MBTL3, MAZ, and ERG play important roles in immune cell regulation. SHMT1 encodes a serine hydroxymethyltransferase catalyzing the transfer of a carbon unit to the folate cycle. This reaction is required for regulation of methylation homeostasis, which is important for establishment and maintenance of epigenetic signatures. Our GWAS approach in a defined population with limited genetic substructure detected associations not found in larger, more heterogeneous cohorts, thus providing new clues regarding MS pathogenesis

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors

A SULT2A1 genetic variant identified by GWAS as associated with low serum DHEAS does not impact on the actual DHEA/DHEAS ratio

DHEA is the major precursor of human sex steroid synthesis and is inactivated via sulfonation to DHEAS. A previous genome-wide association study related the single nucleotide polymorphism (SNP) rs2637125, located near the coding region of DHEA sulfotransferase, SULT2A1, to serum DHEAS concentrations. However, the functional relevance of this SNP with regard to DHEA sulfonation is unknown. Using data from 3300 participants of the population-based cohort Study of Health in Pomerania, we identified 43 individuals being homozygote for the minor allele of the SNP rs2637125 (AA) and selected two sex- and age-matched individuals with AG and GG genotype (n=172) respectively. Steroid analysis including measurement of serum DHEA and DHEAS was carried out by liquid chromatography/mass spectrometry, employing steroid oxime analysis for enhancing the sensitivity of DHEA detection. We applied quantile regression models to compare median hormone levels across SULT2A1 genotypes. Median comparisons by SULT2A1 genotype (AA vs AG and GG genotypes respectively) showed no differences in the considered hormones including DHEAS, DHEA, androstenedione, as well as cortisol and cortisone concentrations. SULT2A1 genotype also had no effect on the DHEA/DHEAS ratio. Sex-stratified analyses, as well as alternative use of the SULT2A1 SNP rs182420, yielded similar negative results. Genetic variants of SULT2A1 do not appear to have an effect on individual DHEA and DHEAS concentrations or the DHEA/DHEAS ratio as a marker of DHEA sulfonation capacity

Common Variants at 10 Genomic Loci Influence Hemoglobin A(1C) Levels via Glycemic and Nonglycemic Pathways

OBJECTIVE-Glycated hemoglobin (HbA(1c)), used to monitor and diagnose diabetes, is influenced by average glycemia over a 2- to 3-month period. Genetic factors affecting expression, turnover, and abnormal glycation of hemoglobin could also be associated with increased levels of HbA(1c). We aimed to identify such genetic factors and investigate the extent to which they influence diabetes classification based on HbA(1c) levels.RESEARCH DESIGN AND METHODS-We studied associations with HbA(1c) in up to 46,368 nondiabetic adults of European descent from 23 genome-wide association studies (GWAS) and 8 cohorts with de novo genotyped single nucleotide polymorphisms (SNPs). We combined studies using inverse-variance meta-analysis and tested mediation by glycemia using conditional analyses. We estimated the global effect of HbA(1c) loci using a multilocus risk score, and used net reclassification to estimate genetic effects on diabetes screening.RESULTS-Ten loci reached genome-wide significant association with HbA(1c), including six new loci near FN3K (lead SNP/P value, rs1046896/P = 1.6 x 10(-26)), HFE (rs1800562/P = 2.6 x 10(-20)), TMPRSS6 (rs855791/P = 2.7 x 10(-14)), ANK1 (rs4737009/P = 6.1 x 10(-12)), SPTA1 (rs2779116/P = 2.8 x 10(-9)) and ATP11A/TUBGCP3 (rs7998202/P = 5.2 x 10(-9)), and four known HbA(1c) loci: HK1 (rs16926246/P = 3.1 x 10(-54)), MTNR1B (rs1387153/P = 4.0 X 10(-11)), GCK (rs1799884/P = 1.5 x 10(-20)) and G6PC2/ABCB11 (rs552976/P = 8.2 x 10(-18)). We show that associations with HbA(1c) are partly a function of hyperglycemia associated with 3 of the 10 loci (GCK, G6PC2 and MTNR1B). The seven nonglycemic loci accounted for a 0.19 (%HbA(1c)) difference between the extreme 10% tails of the risk score, and would reclassify similar to 2% of a general white population screened for diabetes with HbA(1c).CONCLUSIONS-GWAS identified 10 genetic loci reproducibly associated with HbA(1c). Six are novel and seven map to loci where rarer variants cause hereditary anemias and iron storage disorders. Common variants at these loci likely influence HbA(1c) levels via erythrocyte biology, and confer a small but detectable reclassification of diabetes diagnosis by HbA(1c) Diabetes 59: 3229-3239, 201