A genetic risk score combining 32 SNPs is associated with body mass index and improves obesity prediction in people with major depressive disorder.

BACKGROUND: Obesity is strongly associated with major depressive disorder (MDD) and various other diseases. Genome-wide association studies have identified multiple risk loci robustly associated with body mass index (BMI). In this study, we aimed to investigate whether a genetic risk score (GRS) combining multiple BMI risk loci might have utility in prediction of obesity in patients with MDD. METHODS: Linear and logistic regression models were conducted to predict BMI and obesity, respectively, in three independent large case-control studies of major depression (Radiant, GSK-Munich, PsyCoLaus). The analyses were first performed in the whole sample and then separately in depressed cases and controls. An unweighted GRS was calculated by summation of the number of risk alleles. A weighted GRS was calculated as the sum of risk alleles at each locus multiplied by their effect sizes. Receiver operating characteristic (ROC) analysis was used to compare the discriminatory ability of predictors of obesity. RESULTS: In the discovery phase, a total of 2,521 participants (1,895 depressed patients and 626 controls) were included from the Radiant study. Both unweighted and weighted GRS were highly associated with BMI (P <0.001) but explained only a modest amount of variance. Adding 'traditional' risk factors to GRS significantly improved the predictive ability with the area under the curve (AUC) in the ROC analysis, increasing from 0.58 to 0.66 (95% CI, 0.62-0.68; χ(2) = 27.68; P <0.0001). Although there was no formal evidence of interaction between depression status and GRS, there was further improvement in AUC in the ROC analysis when depression status was added to the model (AUC = 0.71; 95% CI, 0.68-0.73; χ(2) = 28.64; P <0.0001). We further found that the GRS accounted for more variance of BMI in depressed patients than in healthy controls. Again, GRS discriminated obesity better in depressed patients compared to healthy controls. We later replicated these analyses in two independent samples (GSK-Munich and PsyCoLaus) and found similar results. CONCLUSIONS: A GRS proved to be a highly significant predictor of obesity in people with MDD but accounted for only modest amount of variance. Nevertheless, as more risk loci are identified, combining a GRS approach with information on non-genetic risk factors could become a useful strategy in identifying MDD patients at higher risk of developing obesity.

Is the adiposity-associated FTO gene variant related to all-cause mortality independent of adiposity? Meta-analysis of data from 169,551 Caucasian adults.

Previously, a single nucleotide polymorphism (SNP), rs9939609, in the FTO gene showed a much stronger association with all-cause mortality than expected from its association with body mass index (BMI), body fat mass index (FMI) and waist circumference (WC). This finding implies that the SNP has strong pleiotropic effects on adiposity and adiposity-independent pathological pathways that leads to increased mortality. To investigate this further, we conducted a meta-analysis of similar data from 34 longitudinal studies including 169,551 adult Caucasians among whom 27,100 died during follow-up. Linear regression showed that the minor allele of the FTO SNP was associated with greater BMI (n = 169,551; 0.32 kg m(-2) ; 95% CI 0.28-0.32, P < 1 × 10(-32) ), WC (n = 152,631; 0.76 cm; 0.68-0.84, P < 1 × 10(-32) ) and FMI (n = 48,192; 0.17 kg m(-2) ; 0.13-0.22, P = 1.0 × 10(-13) ). Cox proportional hazard regression analyses for mortality showed that the hazards ratio (HR) for the minor allele of the FTO SNPs was 1.02 (1.00-1.04, P = 0.097), but the apparent excess risk was eliminated after adjustment for BMI and WC (HR: 1.00; 0.98-1.03, P = 0.662) and for FMI (HR: 1.00; 0.96-1.04, P = 0.932). In conclusion, this study does not support that the FTO SNP is associated with all-cause mortality independently of the adiposity phenotypes.

Genome-wide meta-analysis identifies six novel loci associated with habitual coffee consumption

Coffee, a major dietary source of caffeine, is among the most widely consumed beverages in the world and has received considerable attention regarding health risks and benefits. We conducted a genome-wide (GW) meta-analysis of predominately regular-type coffee consumption (cups per day) among up to 91 462 coffee consumers of European ancestry with top single-nucleotide polymorphisms (SNPs) followed-up in ~30 062 and 7964 coffee consumers of European and African-American ancestry, respectively. Studies from both stages were combined in a trans-ethnic meta-analysis. Confirmed loci were examined for putative functional and biological relevance. Eight loci, including six novel loci, met GW significance (log10Bayes factor (BF)>5.64) with per-allele effect sizes of 0.03-0.14 cups per day. Six are located in or near genes potentially involved in pharmacokinetics (ABCG2, AHR, POR and CYP1A2) and pharmacodynamics (BDNF and SLC6A4) of caffeine. Two map to GCKR and MLXIPL genes related to metabolic traits but lacking known roles in coffee consumption. Enhancer and promoter histone marks populate the regions of many confirmed loci and several potential regulatory SNPs are highly correlated with the lead SNP of each. SNP alleles near GCKR, MLXIPL, BDNF and CYP1A2 that were associated with higher coffee consumption have previously been associated with smoking initiation, higher adiposity and fasting insulin and glucose but lower blood pressure and favorable lipid, inflammatory and liver enzyme profiles (P<5 × 10-8).Our genetic findings among European and African-American adults reinforce the role of caffeine in mediating habitual coffee consumption and may point to molecular mechanisms underlying inter-individual variability in pharmacological and health effects of coffee.

Molecular Analysis of NOTCH2 in Patients with Primary Open-Angle Glaucoma.

BACKGROUND AND PURPOSE: Transgenic mice overexpressing Notch2 in the uvea exhibit a hyperplastic ciliary body leading to increased IOP and glaucoma. The aim of this study was to investigate the possible presence of NOTCH2 variants in patients with primary open-angle glaucoma (POAG). METHODS: We screened DNA samples from 130 patients with POAG for NOTCH2 variants by denaturing high-performance liquid chromatography after PCR amplification and validated our data by direct Sanger sequencing. RESULTS: No mutations were observed in the coding regions of NOTCH2 or in the splice sites. 19 known SNPs (single nucleotide polymorphisms) were detected. An SNP located in intron 24, c.[4005+45A>G], was seen in 28.5% of the patients (37/130 patients). As this SNP is reported to have a minor allele frequency of 7% in the 1000 genomes database, it could be associated with POAG. However, we evaluated its frequency in an ethnic-matched control group of 96 subjects unaffected by POAG and observed a frequency of 29%, indicating that it was not related to POAG. CONCLUSION: NOTCH2 seemed to be a good candidate for POAG as it is expressed in the anterior segment in the human eye. However, mutational analysis did not show any causative mutation. This study also shows that proper ethnic-matched control groups are essential in association studies and that values given in databases are sometimes misleading.

Genetic Variation in the TP53 Pathway and Bladder Cancer Risk. A Comprehensive Analysis

Introduction: Germline variants in TP63 have been consistently associated with several tumors, including bladder cancer, indicating the importance of TP53 pathway in cancer genetic susceptibility. However, variants in other related genes, including TP53 rs1042522 (Arg72Pro), still present controversial results. We carried out an in depth assessment of associations between common germline variants in the TP53 pathway and bladder cancer risk. Material and Methods: We investigated 184 tagSNPs from 18 genes in 1,058 cases and 1,138 controls from the Spanish Bladder Cancer/EPICURO Study. Cases were newly-diagnosed bladder cancer patients during 1998–2001. Hospital controls were age-gender, and area matched to cases. SNPs were genotyped in blood DNA using Illumina Golden Gate and TaqMan assays. Cases were subphenotyped according to stage/grade and tumor p53 expression. We applied classical tests to assess individual SNP associations and the Least Absolute Shrinkage and Selection Operator (LASSO)-penalized logistic regression analysis to assess multiple SNPs simultaneously. Results: Based on classical analyses, SNPs in BAK1 (1), IGF1R (5), P53AIP1 (1), PMAIP1 (2), SERINPB5 (3), TP63 (3), and TP73 (1) showed significant associations at p-value#0.05. However, no evidence of association, either with overall risk or with specific disease subtypes, was observed after correction for multiple testing (p-value$0.8). LASSO selected the SNP rs6567355 in SERPINB5 with 83% of reproducibility. This SNP provided an OR = 1.21, 95%CI 1.05–1.38, p-value = 0.006, and a corrected p-value = 0.5 when controlling for over-estimation. Discussion: We found no strong evidence that common variants in the TP53 pathway are associated with bladder cancer susceptibility. Our study suggests that it is unlikely that TP53 Arg72Pro is implicated in the UCB in white Europeans. SERPINB5 and TP63 variation deserve further exploration in extended studies.

Gene Set Analysis for improving genetic association studies

Introduction. Genetic epidemiology is focused on the study of the genetic causes that determine health and diseases in populations. To achieve this goal a common strategy is to explore differences in genetic variability between diseased and nondiseased individuals. Usual markers of genetic variability are single nucleotide polymorphisms (SNPs) which are changes in just one base in the genome. The usual statistical approach in genetic epidemiology study is a marginal analysis, where each SNP is analyzed separately for association with the phenotype. Motivation. It has been observed, that for common diseases the single-SNP analysis is not very powerful for detecting genetic causing variants. In this work, we consider Gene Set Analysis (GSA) as an alternative to standard marginal association approaches. GSA aims to assess the overall association of a set of genetic variants with a phenotype and has the potential to detect subtle effects of variants in a gene or a pathway that might be missed when assessed individually. Objective. We present a new optimized implementation of a pair of gene set analysis methodologies for analyze the individual evidence of SNPs in biological pathways. We perform a simulation study for exploring the power of the proposed methodologies in a set of scenarios with different number of causal SNPs under different effect sizes. In addition, we compare the results with the usual single-SNP analysis method. Moreover, we show the advantage of using the proposed gene set approaches in the context of an Alzheimer disease case-control study where we explore the Reelin signal pathway.

Novel regulatory SNPs in the promoter region of the TNFRSF18 gene in a Gabonese population

Parasites are accountable for driving diversity within immune gene families. We identified and investigated regulatory single nucleotide polymorphisms (SNPs) in the promoter regions of the tumor necrosis factor receptor superfamily member 18 (TNFRSF18) gene by direct sequencing in a group of male Gabonese individuals exposed to a wide array of parasitic diseases such as malaria, filariasis and schistosomiasis. Two new promoter variants were identified in 40 individuals. Both novel variants were heterozygous and were linked to SNP #rs3753344 (C/T), which has been described. One of the SNP variants (ss2080581728) was close to the general transcription factor site, the TATA box. We further validated these new promoter variants for their allelic gene expression using transient transfection assays. One new promoter variant with two base changes (C/T - ss2080581728/rs3753344) displayed an altered expression of the marker gene. Both novel variants remained less active at the non-induced state in comparison to the major allele. The allele frequencies observed in this study were consistent with data for other African populations. The detection and analysis of these human immune gene polymorphisms contribute to a better understanding of the interaction between host-parasite and expression of Treg activity.

Genetic association of SNPs in the FTO gene and predisposition to obesity in Malaysian Malays

The common variants in the fat mass- and obesity-associated (FTO) gene have been previously found to be associated with obesity in various adult populations. The objective of the present study was to investigate whether the single nucleotide polymorphisms (SNPs) and linkage disequilibrium (LD) blocks in various regions of the FTO gene are associated with predisposition to obesity in Malaysian Malays. Thirty-one FTO SNPs were genotyped in 587 (158 obese and 429 non-obese) Malaysian Malay subjects. Obesity traits and lipid profiles were measured and single-marker association testing, LD testing, and haplotype association analysis were performed. LD analysis of the FTO SNPs revealed the presence of 57 regions with complete LD (D’ = 1.0). In addition, we detected the association of rs17817288 with low-density lipoprotein cholesterol. The FTO gene may therefore be involved in lipid metabolism in Malaysian Malays. Two haplotype blocks were present in this region of the FTO gene, but no particular haplotype was found to be significantly associated with an increased risk of obesity in Malaysian Malays.

Association of rs12255372 in theTCF7L2 gene with type 2 diabetes mellitus: a meta-analysis

Our objective was to evaluate the association of rs12255372 in theTCF7L2 gene with type 2 diabetes mellitus (T2DM) in the world population. We carried out a survey of the literature about the effect of rs12255372 on genetic susceptibility to T2DM by consulting PubMed, the Cochrane Library, and Embase from 2006 to 2012, and then performed a meta-analysis of all the studies in order to evaluate the association between rs12255372 and T2DM. A total of 33 articles including 42 studies (with 34,076 cases and 36,192 controls) were confirmed to be eligible and were included in the final meta-analysis: 6 studies conducted on Europeans, 14 on Caucasians, 17 on Asians, 2 on Africans, and 3 on Americans. Overall, the effect size was as follows: for the variant allele T (OR = 1.387, 95%CI = 1.351-1.424), for the TT genotype (OR = 1.933, 95%CI = 1.815-2.057), for the GT genotype (OR = 1.363, 95%CI = 1.315-1.413), for the dominant model (OR = 1.425, 95%CI = 1.344-1.510), and for the recessive model (OR = 1.659, 95%CI = 1.563-1.761). In summary, by pooling all available qualified data from genetic studies on rs12255372 and T2DM, we have confirmed that rs12255372 is significantly associated with susceptibility to T2DM in the global population.

Genetic analysis of the ELOVL6 gene polymorphism associated with type 2 diabetes mellitus

Recent animal studies have indicated that overexpression of the elongation of long-chain fatty acids family member 6 (Elovl6) gene can cause insulin resistance and β-cell dysfunction. These are the major factors involved in the development of type 2 diabetes mellitus (T2DM). To identify the relationship between single nucleotide polymorphisms (SNP) ofELOVL6 and T2DM pathogenesis, we conducted a case-control study of 610 Han Chinese individuals (328 newly diagnosed T2DM and 282 healthy subjects). Insulin resistance and islet first-phase secretion function were evaluated by assessment of insulin resistance in a homeostasis model (HOMA-IR) and an arginine stimulation test. Three SNPs of the ELOVL6 gene were genotyped with polymerase chain reaction-restriction fragment length polymorphism, with DNA sequencing used to confirm the results. Only genotypes TT and CT of the ELOVL6 SNP rs12504538 were detected in the samples. Genotype CC was not observed. The T2DM group had a higher frequency of the C allele and the CT genotype than the control group. Subjects with the CT genotype had higher HOMA-IR values than those with the TT genotype. In addition, no statistical significance was observed between the genotype and allele frequencies of the control and T2DM groups for SNPs rs17041272 and rs6824447. The study indicated that the ELOVL6 gene polymorphism rs12504538 is associated with an increased risk of T2DM, because it causes an increase in insulin resistance.

Single-nucleotide polymorphism analysis of GH, GHR, and IGF-1 genes in minipigs

Tibetan (TB) and Bama (BM) miniature pigs are two popular pig breeds that are used as experimental animals in China due to their small body size. Here, we analyzed single-nucleotide polymorphisms (SNPs) in gene fragments that are closely related to growth traits [growth hormone (GH), growth hormone receptor (GHR), and insulin-like growth factor (IGF)-1)] in these pig breeds and a large white (LW) control pig breed. On the basis of the analysis of 100 BMs, 108 TBs, and 50 LWs, the polymorphic distribution levels of GH, GHR, and IGF-1 were significantly different among these three pig breeds. According to correlation analyses between SNPs and five growth traits - body weight (BW), body length (BL), withers height (WH), chest circumference (CC), and abdomen circumference (AC) - three SNP loci in BMs and four SNP loci in TBs significantly affected growth traits. Three SNP sites in BMs and four SNP sites in TBs significantly affected growth traits. SNPs located in the GH gene fragment significantly affected BL and CC at locus 12 and BL at locus 45 in BMs, and also BW, WH, CC, and AC at locus 45 and WH and CC at locus 93 in TBs. One SNP at locus 85 in the BM GHR gene fragment significantly affected all growth traits. All indices were significantly reduced with a mixture of alleles at locus 85. These results provide more information regarding the genetic background of these minipig species and indicate useful selection markers for pig breeding programs.

Genetic Analysis of Taste in Homo Sapiens

There are many known taste receptors specific to each taste attribute. This thesis examines the relationship between single nucleotide polymorphisms (SNPs) and copy number variations (CNVs) in known taste and taste pathway receptors TAS2R38, Gustin, and TRPM5 and for PROP (6-n-propylthiouracil) taster status (PTS), thermal taster status (TTS), and orosensory sensation intensity ratings. PTS is a proxy for general taste responsiveness, and the ability to taste PROP classifies individuals into three phenotypes: super (PST), medium (PMT), and non-tasters (PNT). Another taste phenotype, also serving as a proxy for general taste responsiveness, is TTS, classifying individuals as thermal tasters (TTs) or thermal non-tasters (TnTs). DNA extractions from buccal cells obtained from 60 individuals were performed and analysis of TAS2R38, Gustin, and TRPM5 variations were conducted through Polymerase Chain Reaction (PCR), sequencing for SNPs, and upQMPSF for CNV analysis of TRPM5. Among the SNPs and CNVs studied, only TAS2R38 was found to be significantly associated with PTS and intensity ratings for sweet, bitter, and sour taste as well as astringency. However, not all PROP phenotypic differences can be explained by the variations at these three SNP sites in TAS2R38, suggesting the involvement of additional genes. No association was found between TTS and TAS2R38 or Gustin, confirming that PTS and TTS are not genetically associated. The examined TRPM5 SNPs and CNVs did not correlate with TTS. Therefore, further research is necessary into other factors contributing to PTS and TTS.

Sequentially testing for a gene-drug interaction in a genomewide analysis

Assaying a large number of genetic markers from patients in clinical trials is now possible in order to tailor drugs with respect to efficacy. The statistical methodology for analysing such massive data sets is challenging. The most popular type of statistical analysis is to use a univariate test for each genetic marker, once all the data from a clinical study have been collected. This paper presents a sequential method for conducting an omnibus test for detecting gene-drug interactions across the genome, thus allowing informed decisions at the earliest opportunity and overcoming the multiple testing problems from conducting many univariate tests. We first propose an omnibus test for a fixed sample size. This test is based on combining F-statistics that test for an interaction between treatment and the individual single nucleotide polymorphism (SNP). As SNPs tend to be correlated, we use permutations to calculate a global p-value. We extend our omnibus test to the sequential case. In order to control the type I error rate, we propose a sequential method that uses permutations to obtain the stopping boundaries. The results of a simulation study show that the sequential permutation method is more powerful than alternative sequential methods that control the type I error rate, such as the inverse-normal method. The proposed method is flexible as we do not need to assume a mode of inheritance and can also adjust for confounding factors. An application to real clinical data illustrates that the method is computationally feasible for a large number of SNPs. Copyright (c) 2007 John Wiley & Sons, Ltd.

Analysis of 16S rDNA sequences from pathogenic Leptospira serovars and use of single nucleotide polymorphisms for rapid speciation by D-HPLC

Leptospira have a worldwide distribution and include important zoonotic pathogens yet diagnosis and differentiation still tend to rely on traditional bacteriological and serological approaches. In this study a 1.3 kb fragment of the rrs gene (16S rDNA) was sequenced from a panel of 22 control strains, representing serovars within the pathogenic species Leptospira interrogans, Leptospira borgpetersenii, and Leptospira kirschneri, to identify single nucleotide polymorphisms (SNPs). These were identified in the 5' variable region of the 16S sequence and a 181 bp PCR fragment encompassing this region was used for speciation by Denaturing High Performance Liquid Chromatography (D-HPLC). This method was applied to eleven additional species, representing pathogenic, non-pathogenic and intermediate species and was demonstrated to rapidly differentiate all but 2 of the non-pathogenic Leptospira species. The method was applied successfully to infected tissues from field samples proving its value for diagnosing leptospiral infections found in animals in the UK. Crown Copyright (C) 2010 Published by Elsevier Ltd. All rights reserved.

High Resolution Melt (HRM) analysis is an efficient tool to genotype EMS mutants in complex crop genomes

Background: Targeted Induced Loci Lesions IN Genomes (TILLING) is increasingly being used to generate and identify mutations in target genes of crop genomes. TILLING populations of several thousand lines have been generated in a number of crop species including Brassica rapa. Genetic analysis of mutants identified by TILLING requires an efficient, high-throughput and cost effective genotyping method to track the mutations through numerous generations. High resolution melt (HRM) analysis has been used in a number of systems to identify single nucleotide polymorphisms (SNPs) and insertion/deletions (IN/DELs) enabling the genotyping of different types of samples. HRM is ideally suited to high-throughput genotyping of multiple TILLING mutants in complex crop genomes. To date it has been used to identify mutants and genotype single mutations. The aim of this study was to determine if HRM can facilitate downstream analysis of multiple mutant lines identified by TILLING in order to characterise allelic series of EMS induced mutations in target genes across a number of generations in complex crop genomes. Results: We demonstrate that HRM can be used to genotype allelic series of mutations in two genes, BraA.CAX1a and BraA.MET1.a in Brassica rapa. We analysed 12 mutations in BraA.CAX1.a and five in BraA.MET1.a over two generations including a back-cross to the wild-type. Using a commercially available HRM kit and the Lightscanner™ system we were able to detect mutations in heterozygous and homozygous states for both genes. Conclusions: Using HRM genotyping on TILLING derived mutants, it is possible to generate an allelic series of mutations within multiple target genes rapidly. Lines suitable for phenotypic analysis can be isolated approximately 8-9 months (3 generations) from receiving M3 seed of Brassica rapa from the RevGenUK TILLING service.