959 resultados para Complex human diseases
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Extracellular calcium participates in several key physiological functions, such as control of blood coagulation, bone calcification or muscle contraction. Calcium homeostasis in humans is regulated in part by genetic factors, as illustrated by rare monogenic diseases characterized by hypo or hypercalcaemia. Both serum calcium and urinary calcium excretion are heritable continuous traits in humans. Serum calcium levels are tightly regulated by two main hormonal systems, i.e. parathyroid hormone and vitamin D, which are themselves also influenced by genetic factors. Recent technological advances in molecular biology allow for the screening of the human genome at an unprecedented level of detail and using hypothesis-free approaches, such as genome-wide association studies (GWAS). GWAS identified novel loci for calcium-related phenotypes (i.e. serum calcium and 25-OH vitamin D) that shed new light on the biology of calcium in humans. The substantial overlap (i.e. CYP24A1, CASR, GATA3; CYP2R1) between genes involved in rare monogenic diseases and genes located within loci identified in GWAS suggests a genetic and phenotypic continuum between monogenic diseases of calcium homeostasis and slight disturbances of calcium homeostasis in the general population. Future studies using whole-exome and whole-genome sequencing will further advance our understanding of the genetic architecture of calcium homeostasis in humans. These findings will likely provide new insight into the complex mechanisms involved in calcium homeostasis and hopefully lead to novel preventive and therapeutic approaches. Keyword: calcium, monogenic, genome-wide association studies, genetics.
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The recent advance in high-throughput sequencing and genotyping protocols allows rapid investigation of Mendelian and complex diseases on a scale not previously been possible. In my thesis research I took advantage of these modern techniques to study retinitis pigmentosa (RP), a rare inherited disease characterized by progressive loss of photoreceptors and leading to blindness; and hypertension, a common condition affecting 30% of the adult population. Firstly, I compared the performance of different next generation sequencing (NGS) platforms in the sequencing of the RP-linked gene PRPF31. The gene contained a mutation in an intronic repetitive element, which presented difficulties for both classic sequencing methods and NGS. We showed that all NGS platforms are powerful tools to identify rare and common DNA variants, also in case of more complex sequences. Moreover, we evaluated the features of different NGS platforms that are important in re-sequencing projects. The main focus of my thesis was then to investigate the involvement of pre-mRNA splicing factors in autosomal dominant RP (adRP). I screened 5 candidate genes in a large cohort of patients by using long-range PCR as enrichment step, followed by NGS. We tested two different approaches: in one, all target PCRs from all patients were pooled and sequenced as a single DNA library; in the other, PCRs from each patient were separated within the pool by DNA barcodes. The first solution was more cost-effective, while the second one allowed obtaining faster and more accurate results, but overall they both proved to be effective strategies for gene screenings in many samples. We could in fact identify novel missense mutations in the SNRNP200 gene, encoding an essential RNA helicase for splicing catalysis. Interestingly, one of these mutations showed incomplete penetrance in one family with adRP. Thus, we started to study the possible molecular causes underlying phenotypic differences between asymptomatic and affected members of this family. For the study of hypertension, I joined a European consortium to perform genome-wide association studies (GWAS). Thanks to the use of very informative genotyping arrays and of phenotipically well-characterized cohorts, we could identify a novel susceptibility locus for hypertension in the promoter region of the endothelial nitric oxide synthase gene (NOS3). Moreover, we have proven the direct causality of the associated SNP using three different methods: 1) targeted resequencing, 2) luciferase assay, and 3) population study. - Le récent progrès dans le Séquençage à haut Débit et les protocoles de génotypage a permis une plus vaste et rapide étude des maladies mendéliennes et multifactorielles à une échelle encore jamais atteinte. Durant ma thèse de recherche, j'ai utilisé ces nouvelles techniques de séquençage afin d'étudier la retinite pigmentale (RP), une maladie héréditaire rare caractérisée par une perte progressive des photorécepteurs de l'oeil qui entraine la cécité; et l'hypertension, une maladie commune touchant 30% de la population adulte. Tout d'abord, j'ai effectué une comparaison des performances de différentes plateformes de séquençage NGS (Next Generation Sequencing) lors du séquençage de PRPF31, un gène lié à RP. Ce gène contenait une mutation dans un élément répétable intronique, qui présentait des difficultés de séquençage avec la méthode classique et les NGS. Nous avons montré que les plateformes de NGS analysées sont des outils très puissants pour identifier des variations de l'ADN rares ou communes et aussi dans le cas de séquences complexes. De plus, nous avons exploré les caractéristiques des différentes plateformes NGS qui sont importantes dans les projets de re-séquençage. L'objectif principal de ma thèse a été ensuite d'examiner l'effet des facteurs d'épissage de pre-ARNm dans une forme autosomale dominante de RP (adRP). Un screening de 5 gènes candidats issus d'une large cohorte de patients a été effectué en utilisant la long-range PCR comme étape d'enrichissement, suivie par séquençage avec NGS. Nous avons testé deux approches différentes : dans la première, toutes les cibles PCRs de tous les patients ont été regroupées et séquencées comme une bibliothèque d'ADN unique; dans la seconde, les PCRs de chaque patient ont été séparées par code barres d'ADN. La première solution a été la plus économique, tandis que la seconde a permis d'obtenir des résultats plus rapides et précis. Dans l'ensemble, ces deux stratégies se sont démontrées efficaces pour le screening de gènes issus de divers échantillons. Nous avons pu identifier des nouvelles mutations faux-sens dans le gène SNRNP200, une hélicase ayant une fonction essentielle dans l'épissage. Il est intéressant de noter qu'une des ces mutations montre une pénétrance incomplète dans une famille atteinte d'adRP. Ainsi, nous avons commencé une étude sur les causes moléculaires entrainant des différences phénotypiques entre membres affectés et asymptomatiques de cette famille. Lors de l'étude de l'hypertension, j'ai rejoint un consortium européen pour réaliser une étude d'association Pangénomique ou genome-wide association study Grâce à l'utilisation de tableaux de génotypage très informatifs et de cohortes extrêmement bien caractérisées au niveau phénotypique, un nouveau locus lié à l'hypertension a été identifié dans la région promotrice du gène endothélial nitric oxide sinthase (NOS3). Par ailleurs, nous avons prouvé la cause directe du SNP associé au moyen de trois méthodes différentes: i) en reséquençant la cible avec NGS, ii) avec des essais à la luciférase et iii) une étude de population.
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Background: Searching for associations between genetic variants and complex diseases has been a very active area of research for over two decades. More than 51,000 potential associations have been studied and published, a figure that keeps increasing, especially with the recent explosion of array-based Genome-Wide Association Studies. Even if the number of true associations described so far is high, many of the putative risk variants detected so far have failed to be consistently replicated and are widely considered false positives. Here, we focus on the world-wide patterns of replicability of published association studies.Results: We report three main findings. First, contrary to previous results, genes associated to complex diseases present lower degrees of genetic differentiation among human populations than average genome-wide levels. Second, also contrary to previous results, the differences in replicability of disease associated-loci between Europeans and East Asians are highly correlated with genetic differentiation between these populations. Finally, highly replicated genes present increased levels of high-frequency derived alleles in European and Asian populations when compared to African populations. Conclusions: Our findings highlight the heterogeneous nature of the genetic etiology of complex disease, confirm the importance of the recent evolutionary history of our species in current patterns of disease susceptibility and could cast doubts on the status as false positives of some associations that have failed to replicate across populations.
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Background: It is well known that the pattern of linkage disequilibrium varies between human populations, with remarkable geographical stratification. Indirect association studies routinely exploit linkage disequilibrium around genes, particularly in isolated populations where it is assumed to be higher. Here, we explore both the amount and the decay of linkage disequilibrium with physical distance along 211 gene regions, most of them related to complex diseases, across 39 HGDP-CEPH population samples, focusing particularly on the populations defined as isolates. Within each gene region and population we use r2 between all possible single nucleotide polymorphism (SNP) pairs as a measure of linkage disequilibrium and focus on the proportion of SNP pairs with r2 greater than 0.8.Results: Although the average r2 was found to be significantly different both between and within continental regions, a much higher proportion of r2 variance could be attributed to differences between continental regions (2.8% vs. 0.5%, respectively). Similarly, while the proportion of SNP pairs with r2 > 0.8 was significantly different across continents for all distance classes, it was generally much more homogenous within continents, except in the case of Africa and the Americas. The only isolated populations with consistently higher LD in all distance classes with respect to their continent are the Kalash (Central South Asia) and the Surui (America). Moreover, isolated populations showed only slightly higher proportions of SNP pairs with r2 > 0.8 per gene region than non-isolated populations in the same continent. Thus, the number of SNPs in isolated populations that need to be genotyped may be only slightly less than in non-isolates. Conclusion: The "isolated population" label by itself does not guarantee a greater genotyping efficiency in association studies, and properties other than increased linkage disequilibrium may make these populations interesting in genetic epidemiology.
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Abstract The object of game theory lies in the analysis of situations where different social actors have conflicting requirements and where their individual decisions will all influence the global outcome. In this framework, several games have been invented to capture the essence of various dilemmas encountered in many common important socio-economic situations. Even though these games often succeed in helping us understand human or animal behavior in interactive settings, some experiments have shown that people tend to cooperate with each other in situations for which classical game theory strongly recommends them to do the exact opposite. Several mechanisms have been invoked to try to explain the emergence of this unexpected cooperative attitude. Among them, repeated interaction, reputation, and belonging to a recognizable group have often been mentioned. However, the work of Nowak and May (1992) showed that the simple fact of arranging the players according to a spatial structure and only allowing them to interact with their immediate neighbors is sufficient to sustain a certain amount of cooperation even when the game is played anonymously and without repetition. Nowak and May's study and much of the following work was based on regular structures such as two-dimensional grids. Axelrod et al. (2002) showed that by randomizing the choice of neighbors, i.e. by actually giving up a strictly local geographical structure, cooperation can still emerge, provided that the interaction patterns remain stable in time. This is a first step towards a social network structure. However, following pioneering work by sociologists in the sixties such as that of Milgram (1967), in the last few years it has become apparent that many social and biological interaction networks, and even some technological networks, have particular, and partly unexpected, properties that set them apart from regular or random graphs. Among other things, they usually display broad degree distributions, and show small-world topological structure. Roughly speaking, a small-world graph is a network where any individual is relatively close, in terms of social ties, to any other individual, a property also found in random graphs but not in regular lattices. However, in contrast with random graphs, small-world networks also have a certain amount of local structure, as measured, for instance, by a quantity called the clustering coefficient. In the same vein, many real conflicting situations in economy and sociology are not well described neither by a fixed geographical position of the individuals in a regular lattice, nor by a random graph. Furthermore, it is a known fact that network structure can highly influence dynamical phenomena such as the way diseases spread across a population and ideas or information get transmitted. Therefore, in the last decade, research attention has naturally shifted from random and regular graphs towards better models of social interaction structures. The primary goal of this work is to discover whether or not the underlying graph structure of real social networks could give explanations as to why one finds higher levels of cooperation in populations of human beings or animals than what is prescribed by classical game theory. To meet this objective, I start by thoroughly studying a real scientific coauthorship network and showing how it differs from biological or technological networks using divers statistical measurements. Furthermore, I extract and describe its community structure taking into account the intensity of a collaboration. Finally, I investigate the temporal evolution of the network, from its inception to its state at the time of the study in 2006, suggesting also an effective view of it as opposed to a historical one. Thereafter, I combine evolutionary game theory with several network models along with the studied coauthorship network in order to highlight which specific network properties foster cooperation and shed some light on the various mechanisms responsible for the maintenance of this same cooperation. I point out the fact that, to resist defection, cooperators take advantage, whenever possible, of the degree-heterogeneity of social networks and their underlying community structure. Finally, I show that cooperation level and stability depend not only on the game played, but also on the evolutionary dynamic rules used and the individual payoff calculations. Synopsis Le but de la théorie des jeux réside dans l'analyse de situations dans lesquelles différents acteurs sociaux, avec des objectifs souvent conflictuels, doivent individuellement prendre des décisions qui influenceront toutes le résultat global. Dans ce cadre, plusieurs jeux ont été inventés afin de saisir l'essence de divers dilemmes rencontrés dans d'importantes situations socio-économiques. Bien que ces jeux nous permettent souvent de comprendre le comportement d'êtres humains ou d'animaux en interactions, des expériences ont montré que les individus ont parfois tendance à coopérer dans des situations pour lesquelles la théorie classique des jeux prescrit de faire le contraire. Plusieurs mécanismes ont été invoqués pour tenter d'expliquer l'émergence de ce comportement coopératif inattendu. Parmi ceux-ci, la répétition des interactions, la réputation ou encore l'appartenance à des groupes reconnaissables ont souvent été mentionnés. Toutefois, les travaux de Nowak et May (1992) ont montré que le simple fait de disposer les joueurs selon une structure spatiale en leur permettant d'interagir uniquement avec leurs voisins directs est suffisant pour maintenir un certain niveau de coopération même si le jeu est joué de manière anonyme et sans répétitions. L'étude de Nowak et May, ainsi qu'un nombre substantiel de travaux qui ont suivi, étaient basés sur des structures régulières telles que des grilles à deux dimensions. Axelrod et al. (2002) ont montré qu'en randomisant le choix des voisins, i.e. en abandonnant une localisation géographique stricte, la coopération peut malgré tout émerger, pour autant que les schémas d'interactions restent stables au cours du temps. Ceci est un premier pas en direction d'une structure de réseau social. Toutefois, suite aux travaux précurseurs de sociologues des années soixante, tels que ceux de Milgram (1967), il est devenu clair ces dernières années qu'une grande partie des réseaux d'interactions sociaux et biologiques, et même quelques réseaux technologiques, possèdent des propriétés particulières, et partiellement inattendues, qui les distinguent de graphes réguliers ou aléatoires. Entre autres, ils affichent en général une distribution du degré relativement large ainsi qu'une structure de "petit-monde". Grossièrement parlant, un graphe "petit-monde" est un réseau où tout individu se trouve relativement près de tout autre individu en termes de distance sociale, une propriété également présente dans les graphes aléatoires mais absente des grilles régulières. Par contre, les réseaux "petit-monde" ont, contrairement aux graphes aléatoires, une certaine structure de localité, mesurée par exemple par une quantité appelée le "coefficient de clustering". Dans le même esprit, plusieurs situations réelles de conflit en économie et sociologie ne sont pas bien décrites ni par des positions géographiquement fixes des individus en grilles régulières, ni par des graphes aléatoires. De plus, il est bien connu que la structure même d'un réseau peut passablement influencer des phénomènes dynamiques tels que la manière qu'a une maladie de se répandre à travers une population, ou encore la façon dont des idées ou une information s'y propagent. Ainsi, durant cette dernière décennie, l'attention de la recherche s'est tout naturellement déplacée des graphes aléatoires et réguliers vers de meilleurs modèles de structure d'interactions sociales. L'objectif principal de ce travail est de découvrir si la structure sous-jacente de graphe de vrais réseaux sociaux peut fournir des explications quant aux raisons pour lesquelles on trouve, chez certains groupes d'êtres humains ou d'animaux, des niveaux de coopération supérieurs à ce qui est prescrit par la théorie classique des jeux. Dans l'optique d'atteindre ce but, je commence par étudier un véritable réseau de collaborations scientifiques et, en utilisant diverses mesures statistiques, je mets en évidence la manière dont il diffère de réseaux biologiques ou technologiques. De plus, j'extrais et je décris sa structure de communautés en tenant compte de l'intensité d'une collaboration. Finalement, j'examine l'évolution temporelle du réseau depuis son origine jusqu'à son état en 2006, date à laquelle l'étude a été effectuée, en suggérant également une vue effective du réseau par opposition à une vue historique. Par la suite, je combine la théorie évolutionnaire des jeux avec des réseaux comprenant plusieurs modèles et le réseau de collaboration susmentionné, afin de déterminer les propriétés structurelles utiles à la promotion de la coopération et les mécanismes responsables du maintien de celle-ci. Je mets en évidence le fait que, pour ne pas succomber à la défection, les coopérateurs exploitent dans la mesure du possible l'hétérogénéité des réseaux sociaux en termes de degré ainsi que la structure de communautés sous-jacente de ces mêmes réseaux. Finalement, je montre que le niveau de coopération et sa stabilité dépendent non seulement du jeu joué, mais aussi des règles de la dynamique évolutionnaire utilisées et du calcul du bénéfice d'un individu.
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Glial fibrillary acidic protein, GFAP, is a major intermediate filament protein of glial cells and major cytoskeletal structure in astrocytes. The entorhinal cortex has a key role in memory function and is one of the first brain areas to reveal hallmark structures of Alzheimer's disease and therefore provides an ideal tissue to investigate incipient neurodegenerative changes. Here we have analyzed age- and disease-related occurrence and composition of GFAP in the human entorhinal cortex by using one- and two-dimensional electrophoresis, Western blots and immunocytochemistry combined with confocal microscopy. A novel monoclonal antibody, GF-02, was characterized that mainly reacted with intact GFAP molecules and indicated that more acidic and soluble GFAP forms were also more susceptible to degradation. GFAP and vimentin increased with aging and in Alzheimer's disease (AD). Two-dimensional electrophoresis and Western blots revealed a complex GFAP pattern, both in aging and AD with different modification and degradation forms. Immunohistochemistry indicated that reactive astrocytes mainly accumulated in relation to neurofibrillary tangles and senile plaques in deeper entorhinal cortex layers. GFAP may be used as an additional but not exclusive diagnostic tool in the evaluation of neurodegenerative diseases because its levels change with age and respond to senile plaque and tangle formation.
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Prominin-1 (CD133) is physiologically expressed at the apical membranes of secretory (serous and mucous) and duct cells of major salivary glands. We investigated its expression in various human salivary gland lesions using two distinct anti-prominin-1 monoclonal antibodies (80B258 and AC133) applied on paraffin-embedded sections and characterized its occurrence in saliva. The 80B258 epitope was extensively expressed in adenoid cystic carcinoma, in lesser extent in acinic cell carcinoma and pleomorphic adenoma, and rarely in mucoepidermoid carcinoma. The 80B258 immunoreactivity was predominately detected at the apical membrane of tumor cells showing acinar or intercalated duct cell differentiation, which lined duct- or cyst-like structures, and in luminal secretions. It was observed on the whole cell membrane in non-luminal structures present in the vicinity of thin-walled blood vessels and hemorrhagic areas in adenoid cystic carcinoma. Of note, AC133 labeled only a subset of 80B258-positive structures. In peritumoral salivary gland tissues as well as in obstructive sialadenitis, an up-regulation of prominin-1 (both 80B258 and AC133 immunoreactivities) was observed in intercalated duct cells. In most tissues, prominin-1 was partially co-expressed with two cancer markers: carcinoembryonic antigen (CEA) and mucin-1 (MUC1). Differential centrifugation of saliva followed by immunoblotting indicated that all three markers were released in association with small membrane vesicles. Immuno-isolated prominin-1-positive vesicles contained CEA and MUC1, but also exosome-related proteins CD63, flotillin-1, flotillin-2 and the adaptor protein syntenin-1. The latter protein was shown to interact with prominin-1 as demonstrated by its co-immunoisolation. A fraction of saliva-associated prominin-1 appeared to be ubiquitinated. Collectively, our findings bring new insights into the biochemistry and trafficking of prominin-1 as well as its immunohistochemical profile in certain types of salivary gland tumors and inflammatory diseases.
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Genome-wide association studies (GWAS) have identified many risk loci for complex diseases, but effect sizes are typically small and information on the underlying biological processes is often lacking. Associations with metabolic traits as functional intermediates can overcome these problems and potentially inform individualized therapy. Here we report a comprehensive analysis of genotype-dependent metabolic phenotypes using a GWAS with non-targeted metabolomics. We identified 37 genetic loci associated with blood metabolite concentrations, of which 25 show effect sizes that are unusually high for GWAS and account for 10-60% differences in metabolite levels per allele copy. Our associations provide new functional insights for many disease-related associations that have been reported in previous studies, including those for cardiovascular and kidney disorders, type 2 diabetes, cancer, gout, venous thromboembolism and Crohn's disease. The study advances our knowledge of the genetic basis of metabolic individuality in humans and generates many new hypotheses for biomedical and pharmaceutical research.
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Abstract : The human body is composed of a huge number of cells acting together in a concerted manner. The current understanding is that proteins perform most of the necessary activities in keeping a cell alive. The DNA, on the other hand, stores the information on how to produce the different proteins in the genome. Regulating gene transcription is the first important step that can thus affect the life of a cell, modify its functions and its responses to the environment. Regulation is a complex operation that involves specialized proteins, the transcription factors. Transcription factors (TFs) can bind to DNA and activate the processes leading to the expression of genes into new proteins. Errors in this process may lead to diseases. In particular, some transcription factors have been associated with a lethal pathological state, commonly known as cancer, associated with uncontrolled cellular proliferation, invasiveness of healthy tissues and abnormal responses to stimuli. Understanding cancer-related regulatory programs is a difficult task, often involving several TFs interacting together and influencing each other's activity. This Thesis presents new computational methodologies to study gene regulation. In addition we present applications of our methods to the understanding of cancer-related regulatory programs. The understanding of transcriptional regulation is a major challenge. We address this difficult question combining computational approaches with large collections of heterogeneous experimental data. In detail, we design signal processing tools to recover transcription factors binding sites on the DNA from genome-wide surveys like chromatin immunoprecipitation assays on tiling arrays (ChIP-chip). We then use the localization about the binding of TFs to explain expression levels of regulated genes. In this way we identify a regulatory synergy between two TFs, the oncogene C-MYC and SP1. C-MYC and SP1 bind preferentially at promoters and when SP1 binds next to C-NIYC on the DNA, the nearby gene is strongly expressed. The association between the two TFs at promoters is reflected by the binding sites conservation across mammals, by the permissive underlying chromatin states 'it represents an important control mechanism involved in cellular proliferation, thereby involved in cancer. Secondly, we identify the characteristics of TF estrogen receptor alpha (hERa) target genes and we study the influence of hERa in regulating transcription. hERa, upon hormone estrogen signaling, binds to DNA to regulate transcription of its targets in concert with its co-factors. To overcome the scarce experimental data about the binding sites of other TFs that may interact with hERa, we conduct in silico analysis of the sequences underlying the ChIP sites using the collection of position weight matrices (PWMs) of hERa partners, TFs FOXA1 and SP1. We combine ChIP-chip and ChIP-paired-end-diTags (ChIP-pet) data about hERa binding on DNA with the sequence information to explain gene expression levels in a large collection of cancer tissue samples and also on studies about the response of cells to estrogen. We confirm that hERa binding sites are distributed anywhere on the genome. However, we distinguish between binding sites near promoters and binding sites along the transcripts. The first group shows weak binding of hERa and high occurrence of SP1 motifs, in particular near estrogen responsive genes. The second group shows strong binding of hERa and significant correlation between the number of binding sites along a gene and the strength of gene induction in presence of estrogen. Some binding sites of the second group also show presence of FOXA1, but the role of this TF still needs to be investigated. Different mechanisms have been proposed to explain hERa-mediated induction of gene expression. Our work supports the model of hERa activating gene expression from distal binding sites by interacting with promoter bound TFs, like SP1. hERa has been associated with survival rates of breast cancer patients, though explanatory models are still incomplete: this result is important to better understand how hERa can control gene expression. Thirdly, we address the difficult question of regulatory network inference. We tackle this problem analyzing time-series of biological measurements such as quantification of mRNA levels or protein concentrations. Our approach uses the well-established penalized linear regression models where we impose sparseness on the connectivity of the regulatory network. We extend this method enforcing the coherence of the regulatory dependencies: a TF must coherently behave as an activator, or a repressor on all its targets. This requirement is implemented as constraints on the signs of the regressed coefficients in the penalized linear regression model. Our approach is better at reconstructing meaningful biological networks than previous methods based on penalized regression. The method is tested on the DREAM2 challenge of reconstructing a five-genes/TFs regulatory network obtaining the best performance in the "undirected signed excitatory" category. Thus, these bioinformatics methods, which are reliable, interpretable and fast enough to cover large biological dataset, have enabled us to better understand gene regulation in humans.
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Résumé large public La protéomique clinique est une discipline qui vise l'étude des protéines dans un but diagnostique ou thérapeutique. Nous avons utilisé cette approche pour étudier les lymphocytes T «tueurs » ou cytotoxiques qui font partie des globules blancs du système sanguin et agissent dans la lutte contre les infections et les tumeurs. Ces cellules sont impliquées dans l'immunothérapie cellulaire qui se fonde sur la capacité naturelle des ces lymphocytes à repérer les cellules tumorales et à les détruire. L'introduction du gène de la télomérase dans les lymphocytes T résulte en une prolongation de leur longévité, ce qui en ferait des candidats intéressants pour l'immunothérapie cellulaire. Il subsiste cependant des doutes quant aux conséquences de l'utilisation de ces lymphocytes «immortalisés ». Pour répondre à cette question, nous avons comparé le profile protéique de lymphocytes T cytotoxiques «jeunes » et vieux » avec celui des lymphocytes «immortalisés ». Nous avons trouvé que ces derniers présentent une double face et partagent à la fois les caractéristiques de la jeunesse et de la vieillesse. Dans une seconde étude de protéomique clinique, nous nous sommes penchés sur les lymphocytes B «immortalisés » cette fois-ci non pas avec la télomérase, mais avec le virus d'Epstein-Barr. Ces derniers sont utilisés comme modèle dans l'étude de la leucodystrophie, une maladie génétique rare qui affecte le cerveau. Notre but est d'identifier des marqueurs biologiques potentiels qui pourraient aider le diagnostic et le traitement de cette maladie neurodégénérative. Nous avons pour ce faire comparé les profiles protéiques des lymphocytes B «immortalisés » provenant d'individus sains et malades. Malheureusement, notre analyse n'a pas révélé de différences notoires entre ces deux classes de lymphocytes. Ceci nous permet toutefois de conclure que la maladie n'affecte pas la synthèse des protéines de manière prépondérante dans ces cellules sanguines. En résumé, le travail présenté dans cette thèse montre à la fois le potentiel et les limites de l'analyse des protéines lymphocytaires, dans différentes situations biologiques. Résumé La protéomique clinique ouvre la porte vers de multiples horizons relatifs au traitement de diverses maladies. Ce domaine particulier alliant la protéomique à la médecine, implique l'intervention de la biologie moléculaire et cellulaire. Dans notre étude, nous nous sommes d'abord intéressés aux lymphocytes T CD8+ cytotoxiques dans le contexte de l'immunothérapie adoptive. Le fondement de cette thérapie repose sur la capacité naturelle de ces lymphocytes à reconnaître les cellules tumorales et à les détruire chez les patients atteints de cancer. L'introduction du gène de la transcriptase réverse de la télomérase (hTERT) dans les lymphocytes T humains permet de rallonger leur durée de vie, sans toutefois induire d'altérations liées à la transformation. Cependant, des incertitudes subsistent quant à la ressemblance physiologique et biochimique entre ces cellules surexprirnant la télomérase et les cellules normales. Afin de répondre à cette question, nous avons comparé l'expression des protéines de lymphocytes humains T CD8+ «jeunes » et «vieux »avec celle de lymphocytes transduits avec hTERT. Nous avons trouvé que les lymphocytes T surexprimant la télomérase ont un profile protéique intermédiaire, avec certaines expressions protéiques similaires aux jeunes cellules T et d'autres se rapprochant des cellules vieilles. Dans la seconde partie de notre étude, nous nous sommes intéressés aux lymphocytes B transformés avec le virus d'Epstein-Barr provenant de patients atteints d'une maladie génétique rare du cerveau, la leucodystrophie. Dans cette maladie, des mutations dans le facteur de transcription eIF2B, impliqué dans la synthèse protéique, ont été trouvées. Afin d'analyser les conséquences de ces mutations et de trouver des biomarqueurs spécifiques à cette maladie, nous avons effectué une analyse protéomique des lymphoblastes provenant de malades et d'individus sains. Nous avons trouvé que les mutations dans le complexe ubiquitaire eIF2B n'affectent pas de manière significative l'expression des protéines des lymphoblastes mutés. En conclusion, notre travail illustre le potentiel et les limitations des technologies protéomiques utilisées pour disséquer l'implication des protéines dans différentes situations biologiques. Summary Clinical proteomics opens the door to multiple applications related to the treatment of diseases. This particular field is at the crossroad of proteomics and medicine and involves tools from cellular and molecular biology. We focused first our investigations on cytotoxic T cells in the context of adoptive immunotherapy, which is an interesting and evolving field. The basis of this therapy relies on the natural capacity of cytotoxic CD8+ T lymphocytes in recognizing tumor cells and destroying them in cancer patients. As their number is reduced, the idea would be to use transformed T lymphocytes with extended life span. Overexpression of telomerase into human T lymphocytes results in the extension of their replicative life span, but it still remains unclear whether these cells are physiologically indistinguishable from normal ones. To address this question, we compared the proteome of young and aged CD8+ T lymphocytes with that of T cells transduced with hTERT and found that the latter cells displayed an intermediate protein pattern, sharing similar protein expression with young, but also with aged T cells. We were then interested in studying Epstein-Barr virus transformed B lymphocytes in the context of a rare human brain genetic disorder called leukodystrophy. In this disease, mutations in the ubiquitous factor eIF2B involved in protein synthesis and its regulation have been reported. In order to analyze the functional consequences of the mutations and to find out specific biomarkers of eIF2B-related disorders, proteomic and peptidomic studies were carried out on lymphoblasts from eIF2Bmutated patients versus healthy patients. Following two-dimensional gel electrophoresis and mass fingerprints, mutations in the eIF2B complex did not appear to significantly affect the proteome of the mutated lymphoblasts extracts. To conclude, our work emphasizes the potentials and the limitations of the proteomic technologies used to analyze the role of lymphocyte proteins in different biological situations.
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In vertebrates, the RAD51 protein is required for genetic recombination, DNA repair, and cellular proliferation. Five paralogs of RAD51, known as RAD51B, RAD51C, RAD51D, XRCC2, and XRCC3, have been identified and also shown to be required for recombination and genome stability. At the present time, however, very little is known about their biochemical properties or precise biological functions. As a first step toward understanding the roles of the RAD51 paralogs in recombination, the human RAD51C and XRCC3 proteins were overexpressed and purified from baculovirus-infected insect cells. The two proteins copurify as a complex, a property that reflects their endogenous association observed in HeLa cells. Purified RAD51C--XRCC3 complex binds single-stranded, but not duplex DNA, to form protein--DNA networks that have been visualized by electron microscopy.
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Copy number variation (CNV) has recently gained considerable interest as a source of genetic variation likely to play a role in phenotypic diversity and evolution. Much effort has been put into the identification and mapping of regions that vary in copy number among seemingly normal individuals in humans and a number of model organisms, using bioinformatics or hybridization-based methods. These have allowed uncovering associations between copy number changes and complex diseases in whole-genome association studies, as well as identify new genomic disorders. At the genome-wide scale, however, the functional impact of CNV remains poorly studied. Here we review the current catalogs of CNVs, their association with diseases and how they link genotype and phenotype. We describe initial evidence which revealed that genes in CNV regions are expressed at lower and more variable levels than genes mapping elsewhere, and also that CNV not only affects the expression of genes varying in copy number, but also have a global influence on the transcriptome. Further studies are warranted for complete cataloguing and fine mapping of CNVs, as well as to elucidate the different mechanisms by which they influence gene expression.
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BACKGROUND: Active screening by mobile teams is considered the best method for detecting human African trypanosomiasis (HAT) caused by Trypanosoma brucei gambiense but the current funding context in many post-conflict countries limits this approach. As an alternative, non-specialist health care workers (HCWs) in peripheral health facilities could be trained to identify potential cases who need testing based on their symptoms. We explored the predictive value of syndromic referral algorithms to identify symptomatic cases of HAT among a treatment-seeking population in Nimule, South Sudan. METHODOLOGY/PRINCIPAL FINDINGS: Symptom data from 462 patients (27 cases) presenting for a HAT test via passive screening over a 7 month period were collected to construct and evaluate over 14,000 four item syndromic algorithms considered simple enough to be used by peripheral HCWs. For comparison, algorithms developed in other settings were also tested on our data, and a panel of expert HAT clinicians were asked to make referral decisions based on the symptom dataset. The best performing algorithms consisted of three core symptoms (sleep problems, neurological problems and weight loss), with or without a history of oedema, cervical adenopathy or proximity to livestock. They had a sensitivity of 88.9-92.6%, a negative predictive value of up to 98.8% and a positive predictive value in this context of 8.4-8.7%. In terms of sensitivity, these out-performed more complex algorithms identified in other studies, as well as the expert panel. The best-performing algorithm is predicted to identify about 9/10 treatment-seeking HAT cases, though only 1/10 patients referred would test positive. CONCLUSIONS/SIGNIFICANCE: In the absence of regular active screening, improving referrals of HAT patients through other means is essential. Systematic use of syndromic algorithms by peripheral HCWs has the potential to increase case detection and would increase their participation in HAT programmes. The algorithms proposed here, though promising, should be validated elsewhere.
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Una revisión sistemática de la organización compleja de los dominios cognitivos humanos y su heredabilidad. Antecedentes: se ha propuesto que la estructura de la cognición humana respondería a un sistema jerárquico, donde las secuencias propias a una acción se organizarían desde sub-unidades de análisis hasta funciones de nivel superior relativamente complejas. Esta estructura organizacional estaría reflejada en las representaciones neurales que subyacen al comportamiento humano, así como también en sus sustratos genéticos. El objetivo del presente estudio fue explorar la posible organización jerárquica de las influencias genéticas subyacentes a los dominios cognitivos humanos. Método: se revisaron treinta y cuatro estudios de la heredabilidad de la cognición en muestras de la población general, que incluyeron medidas de inteligencia, habilidades verbales y manipulativas, memoria, memoria de trabajo y velocidad de procesamiento. Resultados: diversos dominios cognitivos mostraron distintas proporciones de influencias genéticas, con las mayores estimaciones de heredabilidad halladas para las funciones cognitivas de nivel superior y las menores estimaciones para las funciones de orden medio o inferior. Conclusiones: tomando como referencia los conocimientos actuales acerca del neurodesarrollo humano, las contribuciones genéticas de las habilidades cognitivas parecen organizarse paralelamente al crecimiento ontogénico del cerebro. Se discuten estos resultados en relación a la interacción entre el control genético de las funciones cognitivas y sus influencias ambientales.