963 resultados para Genotype-environment interactions


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Pharmacogenomics is a field with origins in the study of monogenic variations in drug metabolism in the 1950s. Perhaps because of these historical underpinnings, there has been an intensive investigation of 'hepatic pharmacogenes' such as CYP450s and liver drug metabolism using pharmacogenomics approaches over the past five decades. Surprisingly, kidney pathophysiology, attendant diseases and treatment outcomes have been vastly under-studied and under-theorized despite their central importance in maintenance of health, susceptibility to disease and rational personalized therapeutics. Indeed, chronic kidney disease (CKD) represents an increasing public health burden worldwide, both in developed and developing countries. Patients with CKD suffer from high cardiovascular morbidity and mortality, which is mainly attributable to cardiovascular events before reaching end-stage renal disease. In this paper, we focus our analyses on renal function before end-stage renal disease, as seen through the lens of pharmacogenomics and human genomic variation. We herein synthesize the recent evidence linking selected Very Important Pharmacogenes (VIP) to renal function, blood pressure and salt-sensitivity in humans, and ways in which these insights might inform rational personalized therapeutics. Notably, we highlight and present the rationale for three applications that we consider as important and actionable therapeutic and preventive focus areas in renal pharmacogenomics: 1) ACE inhibitors, as a confirmed application, 2) VDR agonists, as a promising application, and 3) moderate dietary salt intake, as a suggested novel application. Additionally, we emphasize the putative contributions of gene-environment interactions, discuss the implications of these findings to treat and prevent hypertension and CKD. Finally, we conclude with a strategic agenda and vision required to accelerate advances in this under-studied field of renal pharmacogenomics with vast significance for global public health.

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Fibroblast growth factor (FGF) signaling is critical for a broad range of developmental processes. In 2003, Fibroblast growth factor receptor 1 (FGFR1) was discovered as a novel locus causing both forms of isolate GnRH Deficiency, Kallmann syndrome [KS with anosmia] and normosmic idiopathic hypogonadotropic hypogonadism [nIHH] eventually accounting for approximately 10% of gonadotropin-releasing hormone (GnRH) deficiency cases. Such cases are characterized by a broad spectrum of reproductive phenotypes from severe congenital forms of GnRH deficiency to reversal of HH. Additionally, the variable expressivity of both reproductive and non-reproductive phenotypes among patients and family members harboring the identical FGFR1 mutations has pointed to a more complex, oligogenic model for GnRH deficiency. Further, reversal of HH in patients carrying FGFR1 mutations suggests potential gene-environment interactions in human GnRH deficiency disorders.

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Balanced lethal systems are more than biological curiosities: as theory predicts, they should quickly be eliminated through the joint forces of recombination and selection. That such systems might become fixed in natural populations poses a challenge to evolutionary theory. Here we address the case of a balanced lethal system fixed in crested newts and related species, which makes 50% of offspring die early in development. All adults are heteromorphic for chromosome pair 1. The two homologues (1A and 1B) have different recessive deleterious alleles fixed on a nonrecombining segment, so that heterozygotes are viable, while homozygotes are lethal. Given such a strong segregation load, how could autosomes stop recombining? We propose a role for a sex-chromosome turnover from pair 1 (putative ancestral sex chromosome) to pair 4 (currently active sex chromosome). Accordingly, 1A and 1B represent two variants (Y(A) and Y(B)) of the Y chromosome from an ancestral male-heterogametic system. We formalize a scenario in which turnovers are driven by sex ratio selection stemming from gene-environment interactions on sex determination. Individual-based simulations show that a balanced lethal system can be fixed with significant likelihood, provided the masculinizing allele on chromosome 4 appears after the elimination of the feminizing allele on chromosome 1. Our study illustrates how strikingly maladaptive traits might evolve through natural selection.

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Path planning and control strategies applied to autonomous mobile robots should fulfil safety rules as well as achieve final goals. Trajectory planning applications should be fast and flexible to allow real time implementations as well as environment interactions. The methodology presented uses the on robot information as the meaningful data necessary to plan a narrow passage by using a corridor based on attraction potential fields that approaches the mobile robot to the final desired configuration. It employs local and dense occupancy grid perception to avoid collisions. The key goals of this research project are computational simplicity as well as the possibility of integrating this method with other methods reported by the research community. Another important aspect of this work consist in testing the proposed method by using a mobile robot with a perception system composed of a monocular camera and odometers placed on the two wheels of the differential driven motion system. Hence, visual data are used as a local horizon of perception in which trajectories without collisions are computed by satisfying final goal approaches and safety criteria

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Sleep and wakefulness are complex behaviors that are influenced by many genetic and environmental factors, which are beginning to be discovered. The contribution of genetic components to sleep disorders is also increasingly recognized as important. Point mutations in the prion protein, period 2, and the prepro-hypocretin/orexin gene have been found as the cause of a few sleep disorders but the possibility that other gene defects may contribute to the pathophysiology of major sleep disorders is worth in-depth investigations. However, single gene disorders are rare and most common disorders are complex in terms of their genetic susceptibility, environmental effects, gene-gene, and gene-environment interactions. We review here the current progress in the genetics of normal and pathological sleep.

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The contribution of genes, environment and gene-environment interactions to sleep disorders is increasingly recognized. Well-documented familial and twin sleep disorder studies suggest an important influence of genetic factors. However, only few sleep disorders have an established genetic basis including four rare diseases that may result from a single gene mutation: fatal familial insomnia, familial advanced sleep-phase syndrome, chronic primary insomnia, and narcolepsy with cataplexy. However, most sleep disorders are complex in terms of their genetic susceptibility together with the variable expressivity of the phenotype even within a same family. Recent linkage, genome-wide and candidate gene association studies resulted in the identification of gene mutations, gene localizations, or evidence for susceptibility genes and/or loci in several sleep disorders. Molecular techniques including mainly genome-wide linkage and association studies are further required to identify the contribution of new genes. These identified susceptibility genetic determinants will provide clues to better understand pathogenesis of sleep disorders, to assess the risk for diseases and also to find new drug targets to treat and to prevent the underlying conditions. We reviewed here the role of genetic basis in most of key sleep disorders.

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The complexity of sleep-wake regulation, in addition to the many environmental influences, includes genetic predisposing factors, which begin to be discovered. Most of the current progress in the study of sleep genetics comes from animal models (dogs, mice, and drosophila). Multiple approaches using both animal models and different genetic techniques are needed to follow the segregation and ultimately to identify 'sleep genes' and molecular bases of sleep disorders. Recent progress in molecular genetics and the development of detailed human genome map have already led to the identification of genetic factors in several complex disorders. Only a few genes are known for which a mutation causes a sleep disorder. However, single gene disorders are rare and most common disorders are complex in terms of their genetic susceptibility, environmental factors, gene-gene, and gene-environment interactions. We review here the current progress in the genetics of normal and pathological sleep and suggest a few future perspectives.

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Selection of common bean (Phaseolus vulgaris L.) cultivars with enhanced root growth would be a strategy for increasing P uptake and grain yield in tropical soils, but the strong plasticity of root traits may compromise their inclusion in breeding programs. The aim of this study was to evaluate the magnitude of the genotypic variability of root traits in common bean plants at two ontogenetic stages and two soil P levels. Twenty-four common bean genotypes, comprising the four growth habits that exist in the species and two wild genotypes, were grown in 4 kg pots at two levels of applied P (20 and 80 mg kg-1) and harvested at the stages of pod setting and early pod filling. Root area and root length were measured by digital image analysis. Significant genotype × P level and genotype × harvest interactions in analysis of variance indicate that the genotypic variation of root traits depended on soil nutrient availability and the stage at which evaluation was made. Genotypes differed for taproot mass, basal and lateral root mass, root area and root length at both P levels and growth stages; differences in specific root area and length were small. Genotypes with growth habits II (upright indeterminate) and III (prostrate indeterminate) showed better adaptation to limited P supply than genotypes of groups I (determinate) and IV (indeterminate climbing). Between the two harvests, genotypes of groups II and III increased the mass of basal and lateral roots by 40 and 50 %, respectively, whereas genotypes of groups I and IV by only 7 and 19 %. Values of the genotypic coefficient of determination, which estimates the proportion of phenotypic variance resulting from genetic effects, were higher at early pod filling than at pod setting. Correlations between shoot mass and root mass, which could indicate indirect selection of root systems via aboveground biomass, were higher at early pod filling than at pod setting. The results indicate that selection for root traits in common bean genotypes should preferentially be performed at the early pod-filling stage.

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Although gene by environment interactions may play a key role in the maintenance of genetic polymorphisms, little is known about the ecological factors involved in these interactions. We investigated whether food supply and parasites can mediate covariation between the degree of adult pheomelanin-based coloration, a heritable trait, and offspring body mass in the tawny owl (Strix aluco). We swapped clutches between nests to allocate genotypes randomly among environments. Three weeks after hatching, we challenged the immune system of 80 unrelated nestlings with either a phytohemagglutinin (PHA) or a lipopolysaccharide, surrogates of alternative parasites, and then fed them ad lib. or food-restricted them during the following 6 days in the laboratory. Whatever the immune challenge, nestlings fed ad lib. converted food more efficiently into body mass when their biological mother was dark pheomelanic. In contrast, food-restricted nestlings challenged with PHA lost less body mass when their biological mother was pale pheomelanic. Nestling tawny owls born from differently melanic mothers thus show differing reaction norms relative to food availability and parasitism. This suggests that dark and pale pheomelanic owls reflect alternative adaptations to food availability and parasites, factors known to vary in space and time.

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Genetic variants influence the risk to develop certain diseases or give rise to differences in drug response. Recent progresses in cost-effective, high-throughput genome-wide techniques, such as microarrays measuring Single Nucleotide Polymorphisms (SNPs), have facilitated genotyping of large clinical and population cohorts. Combining the massive genotypic data with measurements of phenotypic traits allows for the determination of genetic differences that explain, at least in part, the phenotypic variations within a population. So far, models combining the most significant variants can only explain a small fraction of the variance, indicating the limitations of current models. In particular, researchers have only begun to address the possibility of interactions between genotypes and the environment. Elucidating the contributions of such interactions is a difficult task because of the large number of genetic as well as possible environmental factors.In this thesis, I worked on several projects within this context. My first and main project was the identification of possible SNP-environment interactions, where the phenotypes were serum lipid levels of patients from the Swiss HIV Cohort Study (SHCS) treated with antiretroviral therapy. Here the genotypes consisted of a limited set of SNPs in candidate genes relevant for lipid transport and metabolism. The environmental variables were the specific combinations of drugs given to each patient over the treatment period. My work explored bioinformatic and statistical approaches to relate patients' lipid responses to these SNPs, drugs and, importantly, their interactions. The goal of this project was to improve our understanding and to explore the possibility of predicting dyslipidemia, a well-known adverse drug reaction of antiretroviral therapy. Specifically, I quantified how much of the variance in lipid profiles could be explained by the host genetic variants, the administered drugs and SNP-drug interactions and assessed the predictive power of these features on lipid responses. Using cross-validation stratified by patients, we could not validate our hypothesis that models that select a subset of SNP-drug interactions in a principled way have better predictive power than the control models using "random" subsets. Nevertheless, all models tested containing SNP and/or drug terms, exhibited significant predictive power (as compared to a random predictor) and explained a sizable proportion of variance, in the patient stratified cross-validation context. Importantly, the model containing stepwise selected SNP terms showed higher capacity to predict triglyceride levels than a model containing randomly selected SNPs. Dyslipidemia is a complex trait for which many factors remain to be discovered, thus missing from the data, and possibly explaining the limitations of our analysis. In particular, the interactions of drugs with SNPs selected from the set of candidate genes likely have small effect sizes which we were unable to detect in a sample of the present size (<800 patients).In the second part of my thesis, I performed genome-wide association studies within the Cohorte Lausannoise (CoLaus). I have been involved in several international projects to identify SNPs that are associated with various traits, such as serum calcium, body mass index, two-hour glucose levels, as well as metabolic syndrome and its components. These phenotypes are all related to major human health issues, such as cardiovascular disease. I applied statistical methods to detect new variants associated with these phenotypes, contributing to the identification of new genetic loci that may lead to new insights into the genetic basis of these traits. This kind of research will lead to a better understanding of the mechanisms underlying these pathologies, a better evaluation of disease risk, the identification of new therapeutic leads and may ultimately lead to the realization of "personalized" medicine.

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The objective of this work was to identify by biometric analyses the most stable soybean parents, with higher oil or protein contents, cultivated at different seasons and locations of the state of Minas Gerais, Brazil. Forty-nine genotypes were evaluated in the municipalities of Viçosa, Visconde do Rio Branco, and São Gotardo, in the state of Minas Gerais, from 2009 to 2011. Protein and oil contents were analyzed by infrared spectrometry using a FT-NIR analyzer. The effects of genotype, environment, and genotype x environment interaction were significant. The BARC-8 soybean genotype is the best parent to increase protein contents in the progenies, followed by BR 8014887 and CS 3032PTA276-3-4. Selection for high oil content is more efficient when the crossings involve the Suprema, CD 01RR8384, and A7002 genotypes, which show high mean phenotypic values, wide adaptability, and greater stability to environmental variation.

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Conflicts are inherent to the human condition, as they are for all living beings. Disputes about resources or access to mating partners are among the most common causes of conflict. Conflict is herein defined as a struggle or contest between individuals or parties, and may involve a variety of aggressive behaviours. In humans, aggressiveness, violence and conflicts, including individual predisposal to conflict resolution, have traditionally been said to have deep cultural roots, but recent research in both neuroscience and genetics has shown the influence of genes on such complex behavioural traits. In this paper, recent data on the genetic aspects of these interrelated behaviours will be put together, including the effects of particular genes, the influence of stress and gender on gene regulation, and gene-environment interactions, all of which may influence biological predisposal to conflict resolution. Other genetically influenced behavioural aspects involved in conflicts and conflict resolution, such as sociability, will also be discussed. The importance of taking into account genetic and biological data to provide strategies for conflict resolution will be highlighted.

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Varhaislapsuuden virusinfektioiden, lehmänmaitopohjaisen äidinmaitovastikeen ja geneettisen alttiuden merkitys diabetekseen liittyvän autoimmuniteetin kehittymisessä Tyypin 1 diabetes on autoimmuunisairaus, joka syntyy haiman insuliinia tuottavien beta-solujen tuhouduttua elimistön oman immuunipuolustusjärjestelmän hyökkäyksen seurauksena. Sekä perimän että ympäristötekijöiden arvellaan vaikuttavan tautiprosessiin, mutta taudin tarkkaa syntymekanismia ei tunneta. Tutkimuksen tarkoituksena oli selvittää varhaislapsuuden ympäristötekijöiden vaikutusta beta-soluautoimmuniteetin syntyyn, erityispaino tutkimuksessa oli ympäristötekijöiden yhteisvaikutuksessa sekä geneettisten riskitekijöiden ja ympäristötekijöiden vuorovaikutuksessa. Varhaislapsuudessa sairastettu sytomegalovirus- tai enterovirusinfektio ei lisännyt beta-soluautoimmuniteetin riskiä lapsilla, joilla on geneettisesti kohonnut riski sairastua tyypin 1 diabetekseen. Ennen puolen vuoden ikää sairastettu rotavirusinfektio lisäsi hieman tyypin 1 diabetekseen liittyvän autoimmuniteetin riskiä. Tarkemmassa analyysissa varhaislapsuuden enterovirusinfektio osoittautui kuitenkin autovasta-aineiden muodostumisen riskitekijäksi niiden lasten joukossa, jotka olivat saaneet lehmänmaitopohjaista äidinmaidon vastiketta ensimmäisten elinkuukausien aikana. Tämä löydös viittaa enterovirusinfektion ja lehmänmaitopohjaisen vastikkeen yhteisvaikutukseen tyypin 1 diabetekseen liittyvän autoimmuniteetin synnyssä. Löydösten mukaan PTPN22 geenin C1858T polymorfismi vaikuttaa CD4+ T solujen aktivaatioon ja proliferaatiovasteeseen, 1858T alleeliin liittyy alentunut T-soluresepto-rivälitteinen aktivaatio. 1858T alleelin kantajuuteen liittyy lisäksi lisääntynyt autovasta-aineiden ja kliinisen diabeteksen ilmaantuvuus. Tämä yhteys rajoittui yksilöihin, jotka olivat altistuneet lehmänmaitopohjaiselle vastikkeelle ennen kuuden kuukauden ikää. Tulosten mukaan sekä ympäristötekijöiden väliset yhteisvaikutukset että perimä vaikuttavat yksittäisen ympäristötekijän merkitykseen tyypin 1 diabetekseen liittyvän autoimmuniteetin synnyssä. Nämä yhteisvaikutukset ympäristötekijöiden kesken ja perimän ja ympäristötekijöiden välillä selittävät aiemmin julkaistujen tulosten ristiriittaisuutta tutkimuksissa, joissa on analysoitu vain yhden ympäristötekijän vaikutusta diabeteksen ilmaantuvuuteen.

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Genomics is expanding the horizons of epidemiology, providing a new dimension for classical epidemiological studies and inspiring the development of large-scale multicenter studies with the statistical power necessary for the assessment of gene-gene and gene-environment interactions in cancer etiology and prognosis. This paper describes the methodology of the Clinical Genome of Cancer Project in São Paulo, Brazil (CGCP), which includes patients with nine types of tumors and controls. Three major epidemiological designs were used to reach specific objectives: cross-sectional studies to examine gene expression, case-control studies to evaluate etiological factors, and follow-up studies to analyze genetic profiles in prognosis. The clinical groups included patients' data in the electronic database through the Internet. Two approaches were used for data quality control: continuous data evaluation and data entry consistency. A total of 1749 cases and 1509 controls were entered into the CGCP database from the first trimester of 2002 to the end of 2004. Continuous evaluation showed that, for all tumors taken together, only 0.5% of the general form fields still included potential inconsistencies by the end of 2004. Regarding data entry consistency, the highest percentage of errors (11.8%) was observed for the follow-up form, followed by 6.7% for the clinical form, 4.0% for the general form, and only 1.1% for the pathology form. Good data quality is required for their transformation into useful information for clinical application and for preventive measures. The use of the Internet for communication among researchers and for data entry is perhaps the most innovative feature of the CGCP. The monitoring of patients' data guaranteed their quality.