Diet and gene interactions influence the skeletal response to polyunsaturated fatty acids.

Diets rich in omega-3s have been thought to prevent both obesity and osteoporosis. However, conflicting findings are reported, probably as a result of gene by nutritional interactions. Peroxisome proliferator-activated receptor-gamma (PPARγ) is a nuclear receptor that improves insulin sensitivity but causes weight gain and bone loss. Fish oil is a natural agonist for PPARγ and thus may exert its actions through the PPARγ pathway. We examined the role of PPARγ in body composition changes induced by a fish or safflower oil diet using two strains of C57BL/6J (B6); i.e. B6.C3H-6T (6T) congenic mice created by backcrossing a small locus on Chr 6 from C3H carrying 'gain of function' polymorphisms in the Pparγ gene onto a B6 background, and C57BL/6J mice. After 9months of feeding both diets to female mice, body weight, percent fat and leptin levels were less in mice fed the fish oil vs those fed safflower oil, independent of genotype. At the skeletal level, fish oil preserved vertebral bone mineral density (BMD) and microstructure in B6 but not in 6T mice. Moreover, fish oil consumption was associated with an increase in bone marrow adiposity and a decrease in BMD, cortical thickness, ultimate force and plastic energy in femur of the 6T but not the B6 mice. These effects paralleled an increase in adipogenic inflammatory and resorption markers in 6T but not B6. Thus, compared to safflower oil, fish oil (high ratio omega-3/-6) prevents weight gain, bone loss, and changes in trabecular microarchitecture in the spine with age. These beneficial effects are absent in mice with polymorphisms in the Pparγ gene (6T), supporting the tenet that the actions of n-3 fatty acids on bone microstructure are likely to be genotype dependent. Thus caution must be used in interpreting dietary intervention trials with skeletal endpoints in mice and in humans.

Triacylglycerol-rich lipoprotein-gene interactions in endothelial cells

Lipoproteins such as LDL (low-density lipoprotein) and oxidized LDL have potentially adverse effects on endothelial cells due to their ability to activate pro-inflammatory pathways regulated via the transcription factor NF-kappaB (nuclear factor kappaB). Triacylglycerol-rich lipoproteins (the chylomicrons, very-low-density lipoprotein and their respective remnant particles) have also been implicated in the induction of a pro-inflammatory phenotype and up-regulation of adhesion molecule expression. Although early studies supported the proposal that LPL (lipoprotein lipase)-mediated hydrolysis of TRLs (triglyceride-rich lipoproteins) at the endothelium could activate the NFkappaB pathway, more recent studies provide evidence of pro-and anti-inflammatory responses when cells are exposed to fatty acids of TRL particles. A large number of genes are up- and down-regulated when cells are exposed to TRL, with the net effect reflecting receptor- and nonreceptor-mediated pathways that are activated or inhibited depending on fatty acid type, the lipid and apolipoprotein composition of the TRL and the presence or absence of LPL. Early concepts of TRL particles as essentially pro-inflammatory stimuli to the endothelium provide an overly simplistic view of their impact on the vascular compartment.

Nutrient gene interactions in lipid metabolism

Purpose of review To summarize recent findings relating to the impact of dietary fat composition on whole body lipid metabolism, and common gene variants on the blood lipid response to dietary fat change. Recent findings In recent years a more comprehensive understanding of the impact of polyunsaturated fat (PUFA) intake on the regulation of transcription factors involved in lipogenesis and fatty acid and lipoprotein metabolism has emerged. The evidence is suggestive of a greater potency of the long chain n-3 PUFA eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), and in particular their oxidative products, relative to n-6 Pi In the area of nutrigenetics a number of common gene variants have been identified which may be important determinants of the blood lipid response to altered dietary fat composition. However, confirmation of associations in independent cohorts, and an understanding of the size effect of individual or combinations of genotypes, is often lacking. Summary Although in the future, genotyping holds the potential as a public health tool to target and personalize dietary advice, nutrigenetics is a relatively new science, and further research is needed to address the existing inconsistencies and knowledge gaps.

Constraint-based analysis of gene interactions using restricted boolean networks and time-series data

Abstract Background A popular model for gene regulatory networks is the Boolean network model. In this paper, we propose an algorithm to perform an analysis of gene regulatory interactions using the Boolean network model and time-series data. Actually, the Boolean network is restricted in the sense that only a subset of all possible Boolean functions are considered. We explore some mathematical properties of the restricted Boolean networks in order to avoid the full search approach. The problem is modeled as a Constraint Satisfaction Problem (CSP) and CSP techniques are used to solve it. Results We applied the proposed algorithm in two data sets. First, we used an artificial dataset obtained from a model for the budding yeast cell cycle. The second data set is derived from experiments performed using HeLa cells. The results show that some interactions can be fully or, at least, partially determined under the Boolean model considered. Conclusions The algorithm proposed can be used as a first step for detection of gene/protein interactions. It is able to infer gene relationships from time-series data of gene expression, and this inference process can be aided by a priori knowledge available.

Detecting reliable gene interactions by a hierarchy of Bayesian network classifiers

The main purpose of a gene interaction network is to map the relationships of the genes that are out of sight when a genomic study is tackled. DNA microarrays allow the measure of gene expression of thousands of genes at the same time. These data constitute the numeric seed for the induction of the gene networks. In this paper, we propose a new approach to build gene networks by means of Bayesian classifiers, variable selection and bootstrap resampling. The interactions induced by the Bayesian classifiers are based both on the expression levels and on the phenotype information of the supervised variable. Feature selection and bootstrap resampling add reliability and robustness to the overall process removing the false positive findings. The consensus among all the induced models produces a hierarchy of dependences and, thus, of variables. Biologists can define the depth level of the model hierarchy so the set of interactions and genes involved can vary from a sparse to a dense set. Experimental results show how these networks perform well on classification tasks. The biological validation matches previous biological findings and opens new hypothesis for future studies

Specificity in transforming growth factor β-induced transcription of the plasminogen activator inhibitor-1 gene: Interactions of promoter DNA, transcription factor μE3, and Smad proteins

Transforming growth factor β (TGF-β) regulates a broad range of biological processes, including cell growth, development, differentiation, and immunity. TGF-β signals through its cell surface receptor serine kinases that phosphorylate Smad2 or Smad3 proteins. Because Smad3 and its partner Smad4 bind to only 4-bp Smad binding elements (SBEs) in DNA, a central question is how specificity of TGF-β-induced transcription is achieved. We show that Smad3 selectively binds to two of the three SBEs in PE2.1, a TGF-β-inducible fragment of the plasminogen activator inhibitor-1 promoter, to mediate TGF-β-induced transcription; moreover, a precise 3-bp spacer between one SBE and the E-box, a binding site for transcription factor μE3 (TFE3), is essential for TGF-β-induced transcription. Whereas an isolated Smad3 MH1 domain binds to TFE3, TGF-β receptor-mediated phosphorylation of full-length Smad3 enhances its binding to TFE3. Together, these studies elucidate an important mechanism for specificity in TGF-β-induced transcription of the plasminogen activator inhibitor-1 gene.

GPNN: Power studies and applications of a neural network method for detecting gene-gene interactions in studies of human disease

Background The identification and characterization of genes that influence the risk of common, complex multifactorial disease primarily through interactions with other genes and environmental factors remains a statistical and computational challenge in genetic epidemiology. We have previously introduced a genetic programming optimized neural network (GPNN) as a method for optimizing the architecture of a neural network to improve the identification of gene combinations associated with disease risk. The goal of this study was to evaluate the power of GPNN for identifying high-order gene-gene interactions. We were also interested in applying GPNN to a real data analysis in Parkinson's disease. Results We show that GPNN has high power to detect even relatively small genetic effects (2–3% heritability) in simulated data models involving two and three locus interactions. The limits of detection were reached under conditions with very small heritability (

GPNN: Power studies and applications of a neural network method for detecting gene-gene interactions in studies of human disease

Background: The identification and characterization of genes that influence the risk of common, complex multifactorial disease primarily through interactions with other genes and environmental factors remains a statistical and computational challenge in genetic epidemiology. We have previously introduced a genetic programming optimized neural network (GPNN) as a method for optimizing the architecture of a neural network to improve the identification of gene combinations associated with disease risk. The goal of this study was to evaluate the power of GPNN for identifying high-order gene-gene interactions. We were also interested in applying GPNN to a real data analysis in Parkinson's disease. Results: We show that GPNN has high power to detect even relatively small genetic effects (2-3% heritability) in simulated data models involving two and three locus interactions. The limits of detection were reached under conditions with very small heritability (

SNCA, MAPT, and GSK3B in Parkinson disease: a gene-gene interaction study.

Background and purpose:  Recent evidence suggests that variation in the SNCA, MAPT, and GSK3B genes interacts in affecting risk for Parkinson disease (PD). In the current study, we attempt to validate previously published findings, evaluating gene-gene interactions between SNCA, MAPT, and GSK3B in association with PD. Methods:  Three Caucasian PD patient-control series from the United States, Ireland, and Norway (combined n = 1020 patients and 1095 controls) were genotyped for SNCA rs356219, MAPT H1/H2-discriminating SNP rs1052553, and GSK3B rs334558 and rs6438552. Results:  Our findings indicate that as previously reported, the SNCA rs356219-G allele and MAPT rs1052553 (H1 haplotype) were both associated with an increased risk of PD, whilst contrary to previous reports, GSK3B variants were not. No pair-wise interaction was observed between SNCA, MAPT, and GSK3B; the risk effects of SNCA rs356219-G and MAPT rs1052553-H1 were seen in a similar manner across genotypes of other variants, with no evidence suggesting synergistic, antagonistic, or deferential effects. Conclusions:  In the Caucasian patient-control series examined, risk for PD was influenced by variation in SNCA and MAPT but not GSK3B. Additionally, those three genes did not interact in determining disease risk.

Characterization of human gene expression changes after olive oil ingestion: an exploratory approach

Olive oil consumption is protective against risk factors for cardiovascular and cancer diseases. A nutrigenomic approach was performed to assess whether changes in gene expression could occur in human peripheral blood mononuclear cells after oli ve oil ingestion at postprandial state. Six healthy male volunteers ingested, at fasting state, 50 ml of olive oil. Prior to intervention a 1-week washout period with a controlled diet and sunflower oil as the only source of fat was followed. During the 3 days before and on the intervention day, a very low-phenolic compound diet was followed. At baseline (0 h) and at post-ingestion (6 h), total RNA was isolated and gene expression (29,082 genes) was evaluated by microarray. From microarray data, nutrient-gene interactions were observed in genes related to metabolism, cellular processes, cancer, and atherosclerosis (e.g. USP48 by 2.16; OGT by 1.68-fold change) and associated processes such as inflammation (e.g. AKAP13 by 2.30; IL-10 by 1.66-fold change) and DNA damage (e.g. DCLRE1C by 1.47; POLK by 1.44- fold change). When results obtained by microarray were verified by qRT-PCR in nine genes, full concordance was achieved only in the case of up-regulated genes. Changes were observed at a real-life dose of olive oil, as it is daily consumed in some Mediterranean areas. Our results support the hypothesis that postprandial protective changes related to olive oil consumption could be mediated through gene expression changes.

HFE gene mutations in Brazilian thalassemic patients

Hereditary hemochromatosis is a disorder of iron metabolism characterized by increased iron intake and progressive storage and is related to mutations in the HFE gene. Interactions between thalassemia and hemochromatosis may further increase iron overload. The ethnic background of the Brazilian population is heterogeneous and studies analyzing the simultaneous presence of HFE and thalassemia-related mutations have not been carried out. The aim of this study was to evaluate the prevalence of the H63D, S65C and C282Y mutations in the HFE gene among 102 individuals with alpha-thalassemia and 168 beta-thalassemia heterozygotes and to compare them with 173 control individuals without hemoglobinopathies. The allelic frequencies found in these three groups were 0.98, 2.38, and 0.29% for the C282Y mutation, 13.72, 13.70, and 9.54% for the H63D mutation, and 0, 0.60, and 0.87% for the S65C mutation, respectively. The chi-square test for multiple independent individuals indicated a significant difference among groups for the C282Y mutation, which was shown to be significant between the beta-thalassemia heterozygote and the control group by the Fisher exact test (P value = 0.009). The higher frequency of inheritance of the C282Y mutation in the HFE gene among beta-thalassemic patients may contribute to worsen the clinical picture of these individuals. In view of the characteristics of the Brazilian population, the present results emphasize the need to screen for HFE mutations in beta-thalassemia carriers.

Genes involved in the metabolism of fatty acids and risk for Crohn's disease in children: a candidate gene study

Contexte - La prévalence de la maladie de Crohn (MC), une maladie inflammatoire chronique du tube digestif, chez les enfants canadiens se situe parmi les plus élevées au monde. Les interactions entre les réponses immunes innées et acquises aux microbes de l'hôte pourraient être à la base de la transition de l’inflammation physiologique à une inflammation pathologique. Le leucotriène B4 (LTB4) est un modulateur clé de l'inflammation et a été associé à la MC. Nous avons postulé que les principaux gènes impliqués dans la voie métabolique du LTB4 pourrait conférer une susceptibilité accrue à l'apparition précoce de la MC. Dans cette étude, nous avons exploré les associations potentielles entre les variantes de l'ADN des gènes ALOX5 et CYP4F2 et la survenue précoce de la MC. Nous avons également examiné si les gènes sélectionnés montraient des effets parent-d'origine, influençaient les phénotypes cliniques de la MC et s'il existait des interactions gène-gène qui modifieraient la susceptibilité à développer la MC chez l’enfant. Méthodes – Dans le cadre d’une étude de cas-parents et de cas-témoins, des cas confirmés, leurs parents et des contrôles ont été recrutés à partir de trois cliniques de gastro-entérologie à travers le Canada. Les associations entre les polymorphismes de remplacement d'un nucléotide simple (SNP) dans les gènes CYP4F2 et ALOX5 ont été examinées. Les associations allélique et génotypiques ont été examinées à partir d’une analyse du génotype conditionnel à la parenté (CPG) pour le résultats cas-parents et à l’aide de table de contingence et de régression logistique pour les données de cas-contrôles. Les interactions gène-gène ont été explorées à l'aide de méthodes de réduction multi-factorielles de dimensionnalité (MDR). Résultats – L’étude de cas-parents a été menée sur 160 trios. L’analyse CPG pour 14 tag-SNP (10 dans la CYP4F2 et 4 dans le gène ALOX5) a révélé la présence d’associations alléliques ou génotypique significatives entre 3 tag-SNP dans le gène CYP4F2 (rs1272, p = 0,04, rs3093158, p = 0.00003, et rs3093145, p = 0,02). Aucune association avec les SNPs de ALOX5 n’a pu être démontrée. L’analyse de l’haplotype de CYP4F2 a montré d'importantes associations avec la MC (test omnibus p = 0,035). Deux haplotypes (GAGTTCGTAA, p = 0,05; GGCCTCGTCG, p = 0,001) montraient des signes d'association avec la MC. Aucun effet parent-d'origine n’a été observé. Les tentatives de réplication pour trois SNPs du gene CYP4F2 dans l'étude cas-témoins comportant 225 cas de MC et 330 contrôles suggèrent l’association dans un de ceux-ci (rs3093158, valeur non-corrigée de p du test unilatéral = 0,03 ; valeur corrigée de p = 0.09). La combinaison des ces deux études a révélé des interactions significatives entre les gènes CYP4F2, ALOX et NOD2. Nous n’avons pu mettre en évidence aucune interaction gène-sexe, de même qu’aucun gène associé aux phénotypes cliniques de la MC n’a pu être identifié. Conclusions - Notre étude suggère que la CYP4F2, un membre clé de la voie métabolique LTB4 est un gène candidat potentiel pour MC. Nous avons également pu mettre en évidence que les interactions entre les gènes de l'immunité adaptative (CYP4F2 et ALOX5) et les gènes de l'immunité innée (NOD2) modifient les risques de MC chez les enfants. D'autres études sur des cohortes plus importantes sont nécessaires pour confirmer ces conclusions.