On the evolutionary origins of obesity: a new hypothesis

Obesity is an escalating threat of pandemic proportions, currently affecting billions of people worldwide and exerting a devastating socioeconomic influence in industrialized countries. Despite intensive efforts to curtail obesity, results have proved disappointing. Although it is well recognized that obesity is a result of gene-environment interactions and that predisposition to obesity lies predominantly in our evolutionary past, there is much debate as to the precise nature of how our evolutionary past contributed to obesity. The “thrifty genotype” hypothesis suggests that obesity in industrialized countries is a throwback to our ancestors having undergone positive selection for genes that favored energy storage as a consequence of the cyclical episodes of famine and surplus after the advent of farming 10 000 years ago. Conversely, the “drifty genotype” hypothesis contends that the prevalence of thrifty genes is not a result of positive selection for energy-storage genes but attributable to genetic drift resulting from the removal of predative selection pressures. Both theories, however, assume that selection pressures the ancestors of modern humans living in western societies faced were the same. Moreover, neither theory adequately explains the impact of globalization and changing population demographics on the genetic basis for obesity in developed countries, despite clear evidence for ethnic variation in obesity susceptibility and related metabolic disorders. In this article, we propose that the modern obesity pandemic in industrialized countries is a result of the differential exposure of the ancestors of modern humans to environmental factors that began when modern humans left Africa around 70 000 years ago and migrated through the globe, reaching the Americas around 20 000 years ago. This article serves to elucidate how an understanding of ethnic differences in genetic susceptibility to obesity and the metabolic syndrome, in the context of historic human population redistribution, could be used in the treatment of obesity in industrialized countries

Exploring the multifactorial nature of autism through computational systems biology: Calcium and the Rho GTPase RAC1 under the spotlight

Autism is a neurodevelopmental disorder characterized by impaired social interaction and communication accompanied with repetitive behavioral patterns and unusual stereotyped interests. Autism is considered a highly heterogeneous disorder with diverse putative causes and associated factors giving rise to variable ranges of symptomatology. Incidence seems to be increasing with time, while the underlying pathophysiological mechanisms remain virtually uncharacterized (or unknown). By systematic review of the literature and a systems biology approach, our aims were to examine the multifactorial nature of autism with its broad range of severity, to ascertain the predominant biological processes, cellular components, and molecular functions integral to the disorder, and finally, to elucidate the most central contributions (genetic and/or environmental) in silico. With this goal, we developed an integrative network model for gene-environment interactions (GENVI model) where calcium (Ca2+) was shown to be its most relevant node. Moreover, considering the present data from our systems biology approach together with the results from the differential gene expression analysis of cerebellar samples from autistic patients, we believe that RAC1, in particular, and the RHO family of GTPases, in general, could play a critical role in the neuropathological events associated with autism. © 2013 Springer Science+Business Media New York.

Baixas Doses de 5-fluorouracil aumentam a atividade antitumoral de células dendríticas transfectadas com RNA de células de câncer colorretal

Pós-graduação em Patologia - FMB

STATISTICAL METHODS FOR RARE AND COMMON VARIANT ASSOCIATION STUDIES

Complex human diseases are a major challenge for biological research. The goal of my research is to develop effective methods for biostatistics in order to create more opportunities for the prevention and cure of human diseases. This dissertation proposes statistical technologies that have the ability of being adapted to sequencing data in family-based designs, and that account for joint effects as well as gene-gene and gene-environment interactions in the GWA studies. The framework includes statistical methods for rare and common variant association studies. Although next-generation DNA sequencing technologies have made rare variant association studies feasible, the development of powerful statistical methods for rare variant association studies is still underway. Chapter 2 demonstrates two adaptive weighting methods for rare variant association studies based on family data for quantitative traits. The results show that both proposed methods are robust to population stratification, robust to the direction and magnitude of the effects of causal variants, and more powerful than the methods using weights suggested by Madsen and Browning [2009]. In Chapter 3, I extended the previously proposed test for Testing the effect of an Optimally Weighted combination of variants (TOW) [Sha et al., 2012] for unrelated individuals to TOW &ndash F, TOW for Family &ndash based design. Simulation results show that TOW &ndash F can control for population stratification in wide range of population structures including spatially structured populations, is robust to the directions of effect of causal variants, and is relatively robust to percentage of neutral variants. In GWA studies, this dissertation consists of a two &ndash locus joint effect analysis and a two-stage approach accounting for gene &ndash gene and gene &ndash environment interaction. Chapter 4 proposes a novel two &ndash stage approach, which is promising to identify joint effects, especially for monotonic models. The proposed approach outperforms a single &ndash marker method and a regular two &ndash stage analysis based on the two &ndash locus genotypic test. In Chapter 5, I proposed a gene &ndash based two &ndash stage approach to identify gene &ndash gene and gene &ndash environment interactions in GWA studies which can include rare variants. The two &ndash stage approach is applied to the GAW 17 dataset to identify the interaction between KDR gene and smoking status.

Genetic variations in the PI3K-AKT-mTOR pathway and bladder cancer susceptibility and clinical outcomes

Bladder cancer is the fourth most common cancer in men in the United States. There is compelling evidence supporting that genetic variations contribute to the risk and outcomes of bladder cancer. The PI3K-AKT-mTOR pathway is a major cellular pathway involved in proliferation, invasion, inflammation, tumorigenesis, and drug response. Somatic aberrations of PI3K-AKT-mTOR pathway are frequent events in several cancers including bladder cancer; however, no studies have investigated the role of germline genetic variations in this pathway in bladder cancer. In this project, we used a large case control study to evaluate the associations of a comprehensive catalogue of SNPs in this pathway with bladder cancer risk and outcomes. Three SNPs in RAPTOR were significantly associated with susceptibility: rs11653499 (OR: 1.79, 95%CI: 1.24–2.60), rs7211818 (OR: 2.13, 95%CI: 1.35–3.36), and rs7212142 (OR: 1.57, 95%CI: 1.19–2.07). Two haplotypes constructed from these 3 SNPs were also associated with bladder cancer risk. In combined analysis, a significant trend was observed for increased risk with an increase in the number of unfavorable genotypes (P for trend<0.001). Classification and regression tree analysis identified potential gene-environment interactions between RPS6KA5 rs11653499 and smoking. In superficial bladder cancer, we found that PTEN rs1234219 and rs11202600, TSC1 rs7040593, RAPTOR rs901065, and PIK3R1 rs251404 were significantly associated with recurrence in patients receiving BCG. In muscle invasive and metastatic bladder cancer, AKT2 rs3730050, PIK3R1 rs10515074, and RAPTOR rs9906827 were associated with survival. Survival tree analysis revealed potential gene-gene interactions: patients carrying the unfavorable genotypes of PTEN rs1234219 and TSC1 rs704059 exhibited a 5.24-fold (95% CI: 2.44–11.24) increased risk of recurrence. In combined analysis, with the increasing number of unfavorable genotypes, there was a significant trend of higher risk of recurrence and death (P for trend<0.001) in Cox proportional hazard regression analysis, and shorter event (recurrence and death) free survival in Kaplan-Meier estimates (P log rank<0.001). This study strongly suggests that genetic variations in PI3K-AKT-mTOR pathway play an important role in bladder cancer development. The identified SNPs, if validated in further studies, may become valuable biomarkers in assessing an individual's cancer risk, predicting prognosis and treatment response, and facilitating physicians to make individualized treatment decisions. ^

THE NATURAL AND ORTHOGONAL INTERACTION (NOIA) MODELS FOR QUANTITATIVE TRAITS (QTs) AND COMPLEX DISEASES

My dissertation focuses on developing methods for gene-gene/environment interactions and imprinting effect detections for human complex diseases and quantitative traits. It includes three sections: (1) generalizing the Natural and Orthogonal interaction (NOIA) model for the coding technique originally developed for gene-gene (GxG) interaction and also to reduced models; (2) developing a novel statistical approach that allows for modeling gene-environment (GxE) interactions influencing disease risk, and (3) developing a statistical approach for modeling genetic variants displaying parent-of-origin effects (POEs), such as imprinting. In the past decade, genetic researchers have identified a large number of causal variants for human genetic diseases and traits by single-locus analysis, and interaction has now become a hot topic in the effort to search for the complex network between multiple genes or environmental exposures contributing to the outcome. Epistasis, also known as gene-gene interaction is the departure from additive genetic effects from several genes to a trait, which means that the same alleles of one gene could display different genetic effects under different genetic backgrounds. In this study, we propose to implement the NOIA model for association studies along with interaction for human complex traits and diseases. We compare the performance of the new statistical models we developed and the usual functional model by both simulation study and real data analysis. Both simulation and real data analysis revealed higher power of the NOIA GxG interaction model for detecting both main genetic effects and interaction effects. Through application on a melanoma dataset, we confirmed the previously identified significant regions for melanoma risk at 15q13.1, 16q24.3 and 9p21.3. We also identified potential interactions with these significant regions that contribute to melanoma risk. Based on the NOIA model, we developed a novel statistical approach that allows us to model effects from a genetic factor and binary environmental exposure that are jointly influencing disease risk. Both simulation and real data analyses revealed higher power of the NOIA model for detecting both main genetic effects and interaction effects for both quantitative and binary traits. We also found that estimates of the parameters from logistic regression for binary traits are no longer statistically uncorrelated under the alternative model when there is an association. Applying our novel approach to a lung cancer dataset, we confirmed four SNPs in 5p15 and 15q25 region to be significantly associated with lung cancer risk in Caucasians population: rs2736100, rs402710, rs16969968 and rs8034191. We also validated that rs16969968 and rs8034191 in 15q25 region are significantly interacting with smoking in Caucasian population. Our approach identified the potential interactions of SNP rs2256543 in 6p21 with smoking on contributing to lung cancer risk. Genetic imprinting is the most well-known cause for parent-of-origin effect (POE) whereby a gene is differentially expressed depending on the parental origin of the same alleles. Genetic imprinting affects several human disorders, including diabetes, breast cancer, alcoholism, and obesity. This phenomenon has been shown to be important for normal embryonic development in mammals. Traditional association approaches ignore this important genetic phenomenon. In this study, we propose a NOIA framework for a single locus association study that estimates both main allelic effects and POEs. We develop statistical (Stat-POE) and functional (Func-POE) models, and demonstrate conditions for orthogonality of the Stat-POE model. We conducted simulations for both quantitative and qualitative traits to evaluate the performance of the statistical and functional models with different levels of POEs. Our results showed that the newly proposed Stat-POE model, which ensures orthogonality of variance components if Hardy-Weinberg Equilibrium (HWE) or equal minor and major allele frequencies is satisfied, had greater power for detecting the main allelic additive effect than a Func-POE model, which codes according to allelic substitutions, for both quantitative and qualitative traits. The power for detecting the POE was the same for the Stat-POE and Func-POE models under HWE for quantitative traits.

Challenges to environmental toxicology and epidemiology: where do we stand and which way do we go?

Modern toxicology investigates a wide array of both old and new health hazards. Priority setting is needed to select agents for research from the plethora of exposure circumstances. The changing societies and a growing fraction of the aged have to be taken into consideration. A precise exposure assessment is of importance for risk estimation and regulation. Toxicology contributes to the exploration of pathomechanisms to specify the exposure metrics for risk estimation. Combined effects of co-existing agents are not yet sufficiently understood. Animal experiments allow a separate administration of agents which can not be disentangled by epidemiological means, but their value is limited for low exposure levels in many of today's settings. As an experimental science, toxicology has to keep pace with the rapidly growing knowledge about the language of the genome and the changing paradigms in cancer development. During the pioneer era of assembling a working draft of the human genome, toxicogenomics has been developed. Gene and pathway complexity have to be considered when investigating gene-environment interactions. For a best conduct of studies, modem toxicology needs a close liaison with many other disciplines like epidemiology and bioinformatics. (C) 2004 Elsevier Ireland Ltd. All rights reserved.

Avaliação de polimorfismos funcionais nos genes de reparo XRCC1, APEX1, XPD e XPF em carcinomas de células escamosas orais

Base excision repair (BER) and nucleotide excision repair (NER) pathways play critical role in maintaining genome integrity. Polymorphisms in BER and NER genes which modulate the DNA repair capacity may affect the susceptibility and prognosis of oral cancer. This study was conducted with genomic DNA from 92 patients with oral squamous cell carcinomas (OSCC) and 130 controls. The cases were followed up to explore the associations between BER and NER genes polymorphisms and the risk and prognosis of OSCC. Four single-nucleotide polymorphisms (SNPs) in XRCC1 (rs25487), APEX1 (rs1130409), XPD (rs13181) and XPF (rs1799797) genes were tested by polymerase chain reaction – quantitative real time method. The GraphPad Prism version 6.0.1 statistical software was applied for statistical analysis of association. Odds ratio (OR), hazard ratio (HR), and their 95 % confidence intervals (CIs) were calculated by logistic regression. Kaplan-Meier curve and Cox proportional hazard model were used for prognostic analysis. The presence of polymorphic variants in XRCC1, APEX1, XPD and XPF genes were not associated with an increased risk of OSCC. Gene-environment interactions with smoking were not significant for any polymorphism. The presence of polymorphic variants of the XPD gene in association with alcohol consumption conferred an increased risk of 1.86 (95% CI: 0.86 – 4.01, p=0.03) for OSCC. Only APEX1 was associated with decreased specific survival (HR 3.94, 95% CI: 1.31 – 11.88, p=0.01). These results suggest an interaction between polymorphic variants of the XPF gene and alcohol consumption. Additionally APEX1 may represent a prognostic marker for OSCC.

From the Cover: Arsenite Uncouples Mitochondrial Respiration and Induces a Warburg-like Effect in Caenorhabditis elegans.

Millions of people worldwide are chronically exposed to arsenic through contaminated drinking water. Despite decades of research studying the carcinogenic potential of arsenic, the mechanisms by which arsenic causes cancer and other diseases remain poorly understood. Mitochondria appear to be an important target of arsenic toxicity. The trivalent arsenical, arsenite, can induce mitochondrial reactive oxygen species production, inhibit enzymes involved in energy metabolism, and induce aerobic glycolysis in vitro, suggesting that metabolic dysfunction may be important in arsenic-induced disease. Here, using the model organism Caenorhabditis elegans and a novel metabolic inhibition assay, we report an in vivo induction of aerobic glycolysis following arsenite exposure. Furthermore, arsenite exposure induced severe mitochondrial dysfunction, including altered pyruvate metabolism; reduced steady-state ATP levels, ATP-linked respiration and spare respiratory capacity; and increased proton leak. We also found evidence that induction of autophagy is an important protective response to arsenite exposure. Because these results demonstrate that mitochondria are an important in vivo target of arsenite toxicity, we hypothesized that deficiencies in mitochondrial electron transport chain genes, which cause mitochondrial disease in humans, would sensitize nematodes to arsenite. In agreement with this, nematodes deficient in electron transport chain complexes I, II, and III, but not ATP synthase, were sensitive to arsenite exposure, thus identifying a novel class of gene-environment interactions that warrant further investigation in the human populace.

Peroxisome Proliferator-Activated Receptor-γ Coactivator 1-α (PPARGC1A) Genetic Associations with Type 2 Diabetes in Three Ethnicities

Genetic heterogeneity, lifestyle factors, gene-gene or gene-environment interactions are the determinants of T2D which puts Hispanics and populations with African ancestry at higher risk of developing T2D. In this dissertation, the genetic associations of PPARGC1A polymorphisms with T2D and its related phenotypes (metabolic markers) in Haitian Americans (cases=110, controls=116), African Americans (cases=120, controls=124) and Cuban Americans (cases=160, controls=181) of South Florida were explored. Five single nucleotide polymorphisms of gene PPARGC1A were evaluated in each ethnicity for their disease association. In Haitian Americans, rs7656250 (OR= 0.22, pp=0.03) had significant protective association with T2D but had risk association in African Americans for rs7656250 (OR=1.02, p=0.96) and rs4235308 (OR=2.53, p=0.03). We found that in Haitian American females, both rs7656250 (OR=0.23, pp=0.03) had protective association with T2D. In African American females, rs7656250 (OR=1.14, p=0.78) had risk association whereas in males, it had significant protective effect (OR=0.37, p=0.04). However, the risk association exhibited by rs4235308 was stronger in African American females (OR=2.69, p=0.03) than males (OR=1.16, p=0.72). In Cuban Americans, only rs7656250 showed significant risk association with T2D (OR=6.87, p=0.02) which was stronger in females alone (OR=7.67, p=0.01). We also observed significant differences among correlations of PPARGC1A SNPs and T2D phenotypes. Positive correlation was observed for log Hs-CRP with rs3774907 (pp=0.03) in Cuban Americans respectively. Correlation of log A1C with rs7656250 (p=0.02) was positive in Cuban Americans while it was negative for rs3774907 in Haitian Americans (ppPPARGC1A correlations with T2D and its phenotypes among the three ethnicities studied (ii) the associations of PPARGC1A SNPs showed significant effect modification by sex. The findings suggest that variations in effects of PPARGC1A gene polymorphisms among three ethnicities and between sexes may have biomedical implications for the development of T2D as well as the phenotypes related to T2D.

The genetic basis of psychological traits in infancy: Implications for understanding the causes of developmental psychopathology

This chapter reviews genetic studies that have aimed to identify genes influencing psychological traits in infancy (from birth to age 12 months), and considers how this research informs us about the causes of developmental psychopathology. Specifically, this chapter systematically reviews findings from studies that associated common genetic variants with individual variation in infants’ attention, temperament and behaviour, and attachment disorganisation. DRD4 and 5-HTTLPR genes were the most frequently studied candidate genes. Possibly the most coherent set of results relates to the L-DRD4 genotype, which is significantly associated with infant attention, temperament, and attachment style. Research in infant genetics has been strengthened by a careful focus on uniform age ranges within studies, by several longitudinal studies, and by exploration of gene-environment interactions between genes and maternal characteristics. However there is also considerable inconsistency in results in this field and possible reasons for this are discussed. The chapter outlines the main genetic methods that have been used and what new genetic approaches such as polygenic risk scoring could offer infant genetics. Recent findings suggest that some traits during infancy predict individual differences in developmental psychopathology in childhood. It is argued that infant genetic research has considerable potential for the identification of populations at risk for psychopathology in later life, and this remains an area open for future research.

Drinking water disinfection by-products, genetic polymorphisms, and birth outcomes in a european mother-child cohort study

International audience

Revisión sistemática utilidad de asa y calcio con o sin vitamina d en la prevención de cáncer colorrectal y la recurrencia de pólipos adenomatosos en paciente con riesgo de padecer esta patología

Introducción: El cáncer colorrectal es una patología con alto impacto en la salud pública, debido a su prevalencia, incidencia, severidad, costo e impacto en la salud mental y física del individuo y la familia. Ensayos clínicos realizados en pacientes con antecedente de infarto al miocardio que consumían ácido acetil salicílico (asa), calcio con y sin vitamina D, mostraron asociación entre el consumo de estos medicamentos y disminución en la incidencia en cáncer colorrectal y pólipos adenomatosos. Objetivo: Evaluar la literatura sobre el uso de asa, calcio con y sin vitamina D con relación a su impacto en la prevención del cáncer colorrectal y pólipos adenomatosos. Métodos: Se realizó revisión sistemática buscando ensayos clínicos realizados en pacientes con factores de riesgo para cáncer colorrectal y pólipos adenomatosos que usaron asa, calcio con y sin vitamina D fueron incluidos. Resultados: se escogieron 105 para la revisión sistemática. Conclusiones: Es necesario desarrollar más estudios que lleven a evaluar el efecto protector de la aspirina, calcio y vitamina D. En los artículos revisados la aspirina a dosis de 81 a 325 mg día se correlaciona con reducción de riesgo de aparición de CRC aunque la dosis ideal, el tiempo de inicio y la duración de la ingesta continua no son claros. Hacen falta estudios que comparen poblaciones con ingesta de asa a diferentes dosis.

Estudio molecular en dos hermanas afectadas por ictiosis congénita autosómica recesiva : descripción de una nueva mutación causal en TGM1

Se describe la variante homocigota c.320-2A>G de TGM1 en dos hermanas con ictiosis congénita autosómica recesiva. El clonaje de los transcritos generados por esta variante permitió identificar tres mecanismos moleculares de splicing alternativos.

Gene by environment QTL mapping through multiple trait analyses in blood pressure salt-sensitivity: identification of a novel QTL in rat chromosome 5

Background The genetic mechanisms underlying interindividual blood pressure variation reflect the complex interplay of both genetic and environmental variables. The current standard statistical methods for detecting genes involved in the regulation mechanisms of complex traits are based on univariate analysis. Few studies have focused on the search for and understanding of quantitative trait loci responsible for gene × environmental interactions or multiple trait analysis. Composite interval mapping has been extended to multiple traits and may be an interesting approach to such a problem. Methods We used multiple-trait analysis for quantitative trait locus mapping of loci having different effects on systolic blood pressure with NaCl exposure. Animals studied were 188 rats, the progenies of an F2 rat intercross between the hypertensive and normotensive strain, genotyped in 179 polymorphic markers across the rat genome. To accommodate the correlational structure from measurements taken in the same animals, we applied univariate and multivariate strategies for analyzing the data. Results We detected a new quantitative train locus on a region close to marker R589 in chromosome 5 of the rat genome, not previously identified through serial analysis of individual traits. In addition, we were able to justify analytically the parametric restrictions in terms of regression coefficients responsible for the gain in precision with the adopted analytical approach. Conclusion Future work should focus on fine mapping and the identification of the causative variant responsible for this quantitative trait locus signal. The multivariable strategy might be valuable in the study of genetic determinants of interindividual variation of antihypertensive drug effectiveness.