PPARγ2 gene Pro12Ala and PPARα gene Leu162Val single nucleotide polymorphisms interact with dietary intake of fat in determination of plasma lipid concentrations

Background/Aims: The peroxisome proliferator-activated receptors (PPARs) are transcriptional regulators of lipid metabolism, activated by unsaturated fatty acids. We investigated independent and interactive effects of PPARγ2 gene PPARG Pro12Ala (rs1801282) andPPARαgene PPARA Leu162Val (rs1800206) genotypes with dietary intake of fatty acids on concentrations of plasma lipids in subjects of whom 47.5% had metabolic syndrome. Methods: The RISCK study is a parallel design, randomised controlled trial. Plasma lipids were quantified at baseline after a 4-week high saturated fatty acids diet and after three parallel 24-week interventions with reference (high saturated fatty acids), high monounsaturated fatty acids and low-fat diets. Single nucleotide polymorphisms were genotyped in 466 subjects. Results: At baseline, the PPARG Ala12allele was associated with increased plasma total cholesterol (n = 378; p = 0.04), LDL cholesterol (p = 0.05) and apoB (p =0.05) after adjustment for age, gender and ethnicity. At baseline, PPARA Leu162Val × PPARG Pro12Ala genotype interaction did not significantly influence plasma lipid concentrations. After dietary intervention, gene-gene interaction significantly influenced LDL cholesterol (p =0.0002) and small dense LDL as a proportion of LDL (p = 0.005) after adjustments. Conclusions: Interaction between PPARG Pro12Ala and PPARA Leu162Valgenotypes may influence plasma LDL cholesterol concentration and the proportion as small dense LDL after a high monounsaturated fatty acids diet.

In planta conditions induce genomic changes in Pseudomonas syringae pv. phaseolicola

The co-evolution of bacterial plant pathogens and their hosts is a complex and dynamic process. Plant resistance can impose stress on invading pathogens that can lead to, and select for, beneficial changes in the bacterial genome. The Pseudomonas syringae pv. phaseolicola (Pph) genomic island PPHGI-1 carries an effector gene, avrPphB (hopAR1), which triggers the hypersensitive reaction in bean plants carrying the R3 resistance gene. Interaction between avrPphB and R3 generates an antimicrobial environment within the plant, resulting in the excision of PPHGI-1 and its loss from the genome. The loss of PPHGI-1 leads to the generation of a Pph strain able to cause disease in the plant. In this study, we observed that lower bacterial densities inoculated into resistant bean (Phaseolus vulgaris) plants resulted in quicker PPHGI-1 loss from the population, and that loss of the island was strongly influenced by the type of plant resistance encountered by the bacteria. In addition, we found that a number of changes occurred in the bacterial genome during growth in the plant, whether or not PPHGI-1 was lost. We also present evidence that the circular PPHGI-1 episome is able to replicate autonomously when excised from the genome. These results shed more light onto the plasticity of the bacterial genome as it is influenced by in planta conditions.

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.

Interaction between vitamin D receptor gene polymorphisms and 25-hydroxyvitamin D concentrations on metabolic and cardiovascular disease outcomes

AIM: 25-hydroxyvitamin D (25OHD) concentrations have been shown to be associated with major clinical outcomes, with a suggestion that individual risk may vary according to common genetic differences in the vitamin D receptor (VDR) gene. Hence, we tested for the interactions between two previously studied VDR polymorphisms and 25OHD on metabolic and cardiovascular disease-related outcomes in a large population-based study. METHODS: Interactions between two previously studied VDR polymorphisms (rs7968585 and rs2239179) and 25OHD concentrations on metabolic and cardiovascular disease-related outcomes such as obesity- (body mass index, waist circumference, waist-hip ratio (WHR)), cardiovascular- (systolic and diastolic blood pressure), lipid- (high- and low-density lipoprotein, triglycerides, total cholesterol), inflammatory- (C-reactive protein, fibrinogen, insulin growth factor-1, tissue plasminogen activator) and diabetes- (glycated haemoglobin) related markers were examined in the 1958 British Birth cohort (n up to 5160). Interactions between each SNP and 25OHD concentrations were assessed using linear regression and the likelihood ratio test. RESULTS: After Bonferroni correction, none of the interactions reached statistical significance except for the interaction between the VDR SNP rs2239179 and 25OHD concentrations on waist-hip ratio (WHR) (P=0.03). For every 1nmol/L higher 25OHD concentrations, the association with WHR was stronger among those with two major alleles (-4.0%, P=6.26e-24) compared to those with either one or no major alleles (-2.3%, P≤8.201e-07, for both) of the VDR SNP rs2239179. CONCLUSION: We found no evidence for VDR polymorphisms acting as major modifiers of the association between 25OHD concentrations and cardio-metabolic risk. Interaction between VDR SNP rs2239179 and 25OHD on WHR warrants further confirmation.

Interaction between FTO gene variants and lifestyle factors on metabolic traits in an Asian Indian population

Background Lifestyle factors such as diet and physical activity have been shown to modify the association between fat mass and obesity–associated (FTO) gene variants and metabolic traits in several populations; however, there are no gene-lifestyle interaction studies, to date, among Asian Indians living in India. In this study, we examined whether dietary factors and physical activity modified the association between two FTO single nucleotide polymorphisms (rs8050136 and rs11076023) (SNPs) and obesity traits and type 2 diabetes (T2D). Methods The study included 734 unrelated T2D and 884 normal glucose-tolerant (NGT) participants randomly selected from the urban component of the Chennai Urban Rural Epidemiology Study (CURES). Dietary intakes were assessed using a validated interviewer administered semi-quantitative food frequency questionnaire (FFQ). Physical activity was based upon the self-report. Interaction analyses were performed by including the interaction terms in the linear/logistic regression model. Results There was a significant interaction between SNP rs8050136 and carbohydrate intake (% energy) (Pinteraction = 0.04), where the ‘A’ allele carriers had 2.46 times increased risk of obesity than those with ‘CC’ genotype (P = 3.0 × 10−5) among individuals in the highest tertile of carbohydrate intake (% energy, 71 %). A significant interaction was also observed between SNP rs11076023 and dietary fibre intake (Pinteraction = 0.0008), where individuals with AA genotype who are in the 3rd tertile of dietary fibre intake had 1.62 cm lower waist circumference than those with ‘T’ allele carriers (P = 0.02). Furthermore, among those who were physically inactive, the ‘A’ allele carriers of the SNP rs8050136 had 1.89 times increased risk of obesity than those with ‘CC’ genotype (P = 4.0 × 10−5). Conclusions This is the first study to provide evidence for a gene-diet and gene-physical activity interaction on obesity and T2D in an Asian Indian population. Our findings suggest that the association between FTO SNPs and obesity might be influenced by carbohydrate and dietary fibre intake and physical inactivity. Further understanding of how FTO gene influences obesity and T2D through dietary and exercise interventions is warranted to advance the development of behavioral intervention and personalised lifestyle strategies, which could reduce the risk of metabolic diseases in this Asian Indian population.

Development and application of in vivo expression technology (IVET) for analysing microbial gene expression in complex environments

Establishing the mechanisms by which microbes interact with their environment, including eukaryotic hosts, is a major challenge that is essential for the economic utilisation of microbes and their products. Techniques for determining global gene expression profiles of microbes, such as microarray analyses, are often hampered by methodological restraints, particularly the recovery of bacterial transcripts (RNA) from complex mixtures and rapid degradation of RNA. A pioneering technology that avoids this problem is In Vivo Expression Technology (IVET). IVET is a 'promoter-trapping' methodology that can be used to capture nearly all bacterial promoters (genes) upregulated during a microbe-environment interaction. IVET is especially useful because there is virtually no limit to the type of environment used (examples to date include soil, oomycete, a host plant or animal) to select for active microbial promoters. Furthermore, IVET provides a powerful method to identify genes that are often overlooked during genomic annotation, and has proven to be a flexible technology that can provide even more information than identification of gene expression profiles. A derivative of IVET, termed resolvase-IVET (RIVET), can be used to provide spatio-temporal information about environment-specific gene expression. More recently, niche-specific genes captured during an IVET screen have been exploited to identify the regulatory mechanisms controlling their expression. Overall, IVET and its various spin-offs have proven to be a valuable and robust set of tools for analysing microbial gene expression in complex environments and providing new targets for biotechnological development.

Predicting functional gene links from phylogenetic-statistical analyses of whole genomes

An important element of the developing field of proteomics is to understand protein-protein interactions and other functional links amongst genes. Across-species correlation methods for detecting functional links work on the premise that functionally linked proteins will tend to show a common pattern of presence and absence across a range of genomes. We describe a maximum likelihood statistical model for predicting functional gene linkages. The method detects independent instances of the correlated gain or loss of pairs of proteins on phylogenetic trees, reducing the high rates of false positives observed in conventional across-species methods that do not explicitly incorporate a phylogeny. We show, in a dataset of 10,551 protein pairs, that the phylogenetic method improves by up to 35% on across-species analyses at identifying known functionally linked proteins. The method shows that protein pairs with at least two to three correlated events of gain or loss are almost certainly functionally linked. Contingent evolution, in which one gene's presence or absence depends upon the presence of another, can also be detected phylogenetically, and may identify genes whose functional significance depends upon its interaction with other genes. Incorporating phylogenetic information improves the prediction of functional linkages. The improvement derives from having a lower rate of false positives and from detecting trends that across-species analyses miss. Phylogenetic methods can easily be incorporated into the screening of large-scale bioinformatics datasets to identify sets of protein links and to characterise gene networks.

DNA interaction and phosphotransfer of the C-4-dicarboxylate-responsive DcuS-DcuR two-component regulatory system from Escherichia coli

The DcuS-DcuR system of Escherichia coli is a two-component sensor-regulator that controls gene expression in response to external C-4-dicarboxylates and citrate. The DcuS protein is particularly interesting since it contains two PAS domains, namely a periplasmic C-4-dicarboxylate-sensing PAS domain (PASp) and a cytosolic PAS domain (PASc) of uncertain function. For a study of the role of the PASc domain, three different fragments of DcuS were overproduced and examined: they were PASc-kinase, PASc, and kinase. The two kinase-domain-containing fragments were autophosphorylated by [gamma-P-32]ATP. The rate was not affected by fumarate or succinate, supporting the role of the PASp domain in C-4-dicarboxylate sensing. Both of the phosphorylated DcuS constructs were able to rapidly pass their phosphoryl groups to DcuR, and after phosphorylation, DcuR dephosphorylated rapidly. No prosthetic group or significant quantity of metal was found associated with either of the PASc-containing proteins. The DNA-binding specificity of DcuR was studied by use of the pure protein. It was found to be converted from a monomer to a dimer upon acetylphosphate treatment, and native polyacrylamide gel electrophoresis suggested that it can oligomerize. DcuR specifically bound to the promoters of the three known DcuSR-regulated genes (dctA, dcuB, and frdA), with apparent K(D)s of 6 to 32 muM for untreated DcuR and less than or equal to1 to 2 muM for the acetylphosphate-treated form. The binding sites were located by DNase I footprinting, allowing a putative DcuR-binding motif [tandemly repeated (T/A)(A/T)(T/C)(A/T)AA sequences] to be identified. The DcuR-binding sites of the dcuB, dctA, and frdA genes were located 27, 94, and 86 bp, respectively, upstream of the corresponding +1 sites, and a new promoter was identified for dcuB that responds to DcuR.

ACC2 gene polymorphisms, metabolic syndrome, and gene-nutrient interactions with dietary fat.

Acetyl-CoA carboxylase β (ACC2) plays a key role in fatty acid synthesis and oxidation pathways. Disturbance of these pathways is associated with impaired insulin responsiveness and metabolic syndrome (MetS). Gene-nutrient interactions may affect MetS risk. This study determined the relationship between ACC2 polymorphisms (rs2075263, rs2268387, rs2284685, rs2284689, rs2300453, rs3742023, rs3742026, rs4766587, and rs6606697) and MetS risk, and whether dietary fatty acids modulate this in the LIPGENE-SU.VI.MAX study of MetS cases and matched controls (n = 1754). Minor A allele carriers of rs4766587 had increased MetS risk (OR 1.29 [CI 1.08, 1.58], P = 0.0064) compared with the GG homozygotes, which may in part be explained by their increased body mass index (BMI), abdominal obesity, and impaired insulin sensitivity (P < 0.05). MetS risk was modulated by dietary fat intake (P = 0.04 for gene-nutrient interaction), where risk conferred by the A allele was exacerbated among individuals with a high-fat intake (>35% energy) (OR 1.62 [CI 1.05, 2.50], P = 0.027), particularly a high intake (>5.5% energy) of n-6 polyunsaturated fat (PUFA) (OR 1.82 [CI 1.14, 2.94], P = 0.01; P = 0.05 for gene-nutrient interaction). Saturated and monounsaturated fat intake did not modulate MetS risk. Importantly, we replicated some of these findings in an independent cohort. In conclusion, the ACC2 rs4766587 polymorphism influences MetS risk, which was modulated by dietary fat, suggesting novel gene-nutrient interactions.

NOS3 gene polymorphisms are associated with risk markers of cardiovascular disease, and interact with omega-3 polyunsaturated fatty acids

Objective Omega-3 polyunsaturated fatty acids (n-3 PUFA) may protect against the development of cardiovascular disease (CVD). Genotype at key genes such as nitric oxide synthase (NOS3) may determine responsiveness to fatty acids. Gene–nutrient interactions may be important in modulating the development of CVD, particularly in high-risk individuals with the metabolic syndrome (MetS). Methods Biomarkers of CVD risk, plasma fatty acid composition, and NOS3 single nucleotide polymorphism (SNP) genotype (rs11771443, rs1800783, rs1800779, rs1799983, rs3918227, and rs743507) were determined in 450 individuals with the MetS from the LIPGENE dietary intervention cohort. The effect of dietary fat modification for 12 weeks on metabolic indices of the MetS was determined to understand potential NOS3 gene–nutrient interactions. Results Several markers of inflammation and dyslipidaemia were significantly different between the genotype groups. A significant gene–nutrient interaction was observed between the NOS3 rs1799983 SNP and plasma n-3 PUFA status on plasma triacylglycerol (TAG) concentrations. Minor allele carriers (AC + AA) showed an inverse association with significantly higher plasma TAG concentrations in those with low plasma n-3 PUFA status and vice versa but the major allele homozygotes (CC) did not. Following n-3 PUFA supplementation, plasma TAG concentrations of minor allele carriers of rs1799983 were considerably more responsive to changes in plasma n-3 PUFA, than major allele homozygotes. Conclusions Carriers of the minor allele at rs1799983 in NOS3 have plasma TAG concentrations which are more responsive to n-3 PUFA. This suggests that these individuals might show greater beneficial effects of n-3 PUFA consumption to reduce plasma TAG concentrations.

Pleiotropic effects of TCF7L2 gene variants and its modulation in the metabolic syndrome: from the LIPGENE study

Aims/hypothesis: Variants of the TCF7L2 gene predict the development of type 2 diabetes mellitus (T2DM). We investigated the associations between gene variants of TCF7L2 and clinical features of the metabolic syndrome (MetS) (an entity often preceeding T2DM), and their interaction with non-genetic factors, including plasma saturated fatty acids (SFA) concentration and insulin resistance (IR). Methods: Fasting lipid profiles, insulin sensitivity, insulin secretion, anthropometrics, blood pressure and 10 gene variations of the TCF7L2 gene were determined in 450 subjects with MetS. Results: Several single nucleotide polymorphisms (SNP) showed phenotypic associations independent of SFA or IR. Carriers of the rare T allele of rs7903146, and of three other SNPs in linkage disequilibrium with rs7903146, had lower blood pressure and insulin secretion. High IR and the presence of the T-allele of rs7903146 acted synergistically to define those with reduced insulin secretion. Carriers of the minor allele of rs290481 exhibited an altered lipid profile, with increased plasma levels of apolipoprotein B, non-esterified fatty acids, cholesterol and apolipoprotein B in triglyceride rich lipoproteins, and LDL cholesterol. Carriers of the minor allele of rs11196224 that had higher plasma SFA levels showed elevated procoagulant/proinflammatory biomarkers, impaired insulin secretion and increased IR, whereas carriers of the minor allele of rs17685538 with high plasma SFA levels exhibited higher blood pressure. Conclusions/interpretation: SNP in the TCF7L2 gene are associated with differences in insulin secretion, blood pressure, blood lipids and coagulation in MetS patients, and may be modulated by SFA in plasma or IR.

Induction of the ferritin gene (ftnA) of Escherichia coli by Fe2+–Fur is mediated by reversal of H-NS silencing and is RyhB independent

FtnA is the major iron-storage protein of Escherichia coli accounting for < or = 50% of total cellular iron. The FtnA gene (ftnA) is induced by iron in an Fe(2+)-Fur-dependent fashion. This effect is reportedly mediated by RyhB, the Fe(2+)-Fur-repressed, small, regulatory RNA. However, results presented here show that ftnA iron induction is independent of RyhB and instead involves direct interaction of Fe(2+)-Fur with an 'extended' Fur binding site (containing five tandem Fur boxes) located upstream (-83) of the ftnA promoter. In addition, H-NS acts as a direct repressor of ftnA transcription by binding at multiple sites (I-VI) within, and upstream of, the ftnA promoter. Fur directly competes with H-NS binding at upstream sites (II-IV) and consequently displaces H-NS from the ftnA promoter (sites V-VI) which in turn leads to derepression of ftnA transcription. It is proposed that H-NS binding within the ftnA promoter is facilitated by H-NS occupation of the upstream sites through H-NS oligomerization-induced DNA looping. Consequently, Fur displacement of H-NS from the upstream sites prevents cooperative H-NS binding at the downstream sites within the promoter, thus allowing access to RNA polymerase. This direct activation of ftnA transcription by Fe(2+)-Fur through H-NS antisilencing represents a new mechanism for iron-induced gene expression.

Single nucleotide polymorphisms at the ADIPOQ gene locus interact with age and dietary intake of fat to determine serum adiponectin in subjects at risk of the metabolic syndrome

Background: Adiponectin gene expression is modulated by peroxisome proliferator–activated receptor γ, which is a transcription factor activated by unsaturated fatty acids. Objective: We investigated the effect of the interaction between variants at the ADIPOQ gene locus, age, sex, body mass index (BMI), ethnicity, and the replacement of dietary saturated fatty acids (SFAs) with monounsaturated fatty acids (MUFAs) or carbohydrates on serum adiponectin concentrations. Design: The RISCK (Reading, Imperial, Surrey, Cambridge, and Kings) study is a parallel-design, randomized controlled trial. Serum adiponectin concentrations were measured after a 4-wk high-SFA (HS) diet and a 24-wk intervention with reference (HS), high-MUFA (HM), and low-fat (LF) diets. Single nucleotide polymorphisms at the ADIPOQ locus −11391 G/A (rs17300539), −10066 G/A (rs182052), −7734 A/C (rs16861209), and +276 G/T (rs1501299) were genotyped in 448 participants. Results: In white Europeans, +276 T was associated with higher serum adiponectin concentrations (n = 340; P = 0.006) and −10066 A was associated with lower serum adiponectin concentrations (n = 360; P = 0.03), after adjustment for age, BMI, and sex. After the HM diet, −10066 G/G subjects showed a 3.8% increase (95% CI: −0.1%, 7.7%) and G/A+A/A subjects a 2.6% decrease (95% CI: −5.6%, 0.4%) in serum adiponectin (P = 0.006 for difference after adjustment for the change in BMI, age, and sex). In −10066 G/G homozygotes, serum adiponectin increased with age after the HM diet and decreased after the LF diet. Conclusion: In white −10066 G/G homozygotes, an HM diet may help to increase adiponectin concentrations with advancing age. This trial was registered at clinicaltrials.gov as ISRCTN29111298.

Interaction of PPARG Pro12Ala with dietary fat influences plasma lipids in subjects at cardiometabolic risk

The PPARγ2 gene SNP Pro12Ala has shown variable association with metabolic syndrome traits in healthy subjects. We investigated the effect of interaction between genotype and the ratio of polyunsaturated:saturated (P:S) fatty acid intake on plasma lipids in 367 White subjects aged 30-70 y at increased cardiometabolic risk, in the RISCK study. Interaction was determined after habitual diet at recruitment, at baseline after a 4-week high-SFA (HS) diet and after 24-week reference (HS), high-MUFA (HM) and low-fat (LF) diets. At recruitment, there were no significant associations between genotype and plasma lipids, however, P:S x genotype interaction influenced plasma total cholesterol (TC) (P=0.02), LDL-cholesterol (LDL-C) (P=0.002) and triglyceride (TG) (P=0.02) concentrations. At P:S ratio ≤0.33, mean TC and LDL-C concentrations in Ala12 allele carriers were significantly higher than in non-carriers (respectively P=0.003; P=0.0001). Significant trends in reduction of plasma TC (P=0.02) and TG (P=0.002) concentrations occurred with increasing P:S (respectively ≤0.33 to >0.65 and 0.34 to >0.65) in Ala12 allele carriers. There were no significant differences between carriers and non-carriers after the 4-week HS diet or 24-week interventions. Plasma TC and TG concentrations in PPARG Ala12 allele carriers decrease as P:S increases, but are not dependent on a reduction in SFA intake.