Although many genetic factors have been successfully identified for human diseases in genome-wide association studies (GWAS), genes discovered to date only account for a small proportion of overall genetic contributions to many complex traits. Association studies have difficulty in detecting the remaining true genetic variants that are either common variants with weak allelic effects, or rare variants that have strong allelic effects but are weakly associated at the population level. In this work we applied a goodness-of-fit test for detecting sets of common and rare variants associated with quantitative or binary traits by using whole genome sequencing (WGS) data. This test has been proved optimal for detecting weak and sparse signals in the literature, which fits the requirements for targeting the genetic components of missing heritability. Furthermore, this p-value-combining method allows one to incorporate different data and/or research results for meta-analysis. The method was used to simultaneously analyse the WGS and GWAS data of Genetic Analysis Workshop (GAW) 18 for detecting true genetic variants. The results show that goodness-of-fit test is comparable or better than the influential sequence kernel association test in many cases.

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Many phenotypic traits are heritable, but the exact genetic causes are difficult to determine. A common approach for disentangling the different genetic factors is to conduct a "genome-wide association study" (GWAS), where each single nucleotide variant (SNV) is tested for association with a trait of interest. Many SNVs for complex traits have been found by GWAS, but to date they explain only a fraction of heritability of complex traits. In this dissertation, we propose novel optimization-based and multiple testing procedures for variant set tests. In the second chapter, we propose a novel variant set test, convex-optimized SKAT (cSKAT), that leverages multiple SNV annotations. The test generalizes SKAT to convex combinations of SKAT statistics constructed from functional genomic annotations. We differ from previous approaches by optimizing kernel weights with a multiple kernel learning algorithm. In cSKAT, the contribution of each variant to the overall statistic is a product of annotation values and kernel weights for annotation classes. We demonstrate the utility of our biologically-informed SNV weights in a rare-variant analysis of fasting glucose in the FHS. In the third chapter, we propose a sequential testing procedure for GWAS that joins tests of single SNVs and groups of SNVs (SNV-sets) with common biological function. The proposed procedure differs from previous procedures by testing genes and sliding 4kb intergenic windows rather than chromosomes or the whole genome. We also sharpen an existing tree-based multiple testing correction by incorporating correlation between SNVs, which is present in any SNV-set containing contiguous regions (such as genes). In the fourth chapter, we present a sequential testing procedure for SNV-sets that incorporates correlation between test statistics of the SNV-sets. At each step of the procedure, the multiplicity correction is the number of remaining independent tests, making no assumption about the null distribution of tests. We provide an estimator for the number of remaining independent tests based on previous work in single-SNV GWAS and demonstrate the estimator is valid for sequential procedures. We implement the proposed method for GWAS by sequentially testing chromosomes, genes, 4kb windows, and SNVs.

La dysplasie fibromusculaire artérielle (DFM) est un groupe de pathologies vasculaires non inflammatoires, et non athéromateuses de la paroi artérielle. Elle est caractérisée par la sténose, l'occlusion, l’anévrisme ou la dissection des artères de petit et moyen calibres, en particulier les artères rénales et le tronc supra-aortique. La DFM est un facteur de risque de l’hypertension et de l’accident vasculaire cérébral. Elle touche essentiellement les femmes (80% des cas) de moins de 50 ans. La prévalence en population générale est inconnue et les estimations varient de 0.4% pour les formes cliniques à 4% dans une cohorte de donneurs de reins. Une agrégation familiale a été démontrée et une composante génétique suggérée. L'objectif de mon travail de thèse était de caractériser les bases génétiques la DFM. Dans la première partie, nous avons analysé des variants génétiques rares générés par séquençage d'exomes chez 16 cas apparentés de DFM issus de 7 fratries. Aucun gène majeur n’était muté pour l’ensemble des fratries ou pour au moins 3 fratries sur 7. Cependant, nous avons pu mettre en évidence puis validé un enrichissement en variants rares à fort potentiel fonctionnel de quatre gènes candidats pour la DFM (MYLK, OBSCN, DYNC2H1, RNF213) en combinant l’approche de séquençage d’exomes et l’étude d’association gène entier de 62767 variants rares (MAF < 5%) générés par génotypage avec la puce Exome-chip chez 249 cas non apparentés de DFM et 689 témoins. Cependant, l’implication de ces gènes dans la DFM doit être confirmée dans d’autres familles, et par des études de validations fonctionnelles. Dans la seconde partie, nous avons étudié l'association avec la DFM de 25606 variants fréquents (MAF ≥ 5%) de l’Exome-chip. Les résultats majeurs obtenus ont été répliqués dans une première étude (402 cas de DFM et 2537 témoins) puis dans 3 autres études incluant 512 cas de DFM et 669 témoins. La méta-analyse de l’ensemble a permis d’associer à la DFM le polymorphisme rs9349379-A situé dans l’intron du gène PHACTR1 (OR=1,39 [1,39-1,54] ; P=7,36 ×10-10). Ce variant est aussi un facteur de risque pour la maladie coronaire, la migraine et la dissection de l’artère cervicale. Des études complémentaires conduites chez 2458 volontaires non malades ont permis de montrer que l’allèle à risque pour la DFM, rs9349379-A est associé avec une augmentation de l’épaisseur intima média (P=1,97×10-4) et du rapport de la paroi sur la lumière artérielle (P=0,002), deux paramètres décrits comme augmentés chez les cas de DFM dans des études antérieures. Ensuite, PHACTR1 a été détecté par immunohistochimie dans l’endothélium et les cellules musculaires lisses de carotides dysplasiques et non dysplasiques avec une expression augmentée de PHACTR1 pour les porteurs de l’allèle à risque de DFM dans des cultures primaires de fibroblastes humains (N=86, P=0,003). Enfin, l’invalidation de Phactr1 chez le poisson zèbre conduit à une dilatation des vaisseaux indiquant un défaut du développement vasculaire. Ce travail confirme le caractère multifactoriel et hétérogène de la DFM et ouvre de nouvelles perspectives pour évaluer l’ensemble de la variabilité génomique des patients de DFM par des approches massives de génétique épidémiologique. / Fibromuscular dysplasia (FMD) is a group of nonatherosclerotic and noninflammatory vascular diseases leading to stenosis, aneurysm, dissection and/or occlusion of medium-sized arteries, in particular the renal and extracranial cervical arteries. Clinical manifestations of FMD are hypertension, dizziness, pulsatile tinnitus, transient ischemic attack or stroke, according to the involved arterial beds. FMD occurs predominantly (80% of cases) in females under 50 years with a variable prevalence estimation from 0.4% for asymptomatic clinical relevant forms to 4% in potential renal donors. The pathogenesis of FMD is unknown and a genetic origin is suspected given its demonstrated familial aggregation. The aim of my thesis work was to characterize genetic basis of FMD. In the first part of this thesis, we analyzed whole exome sequencing data in 16 related FMD cases from seven families. No gene harbors variants that were shared by all affected members in at least three out seven families. Using combined strategy of whole exome sequencing and gene based association study of 62,767 rare variants (MAF < 5%) generated by Exome‐chip arrays in 249 unrelated FMD cases and 689 controls, we have identified and validated an enrichment of rare and putatively functional variants in four candidates genes (MYLK, OBSCN, DYNC2H1 and RNF213). This results need to be validated in other FMD families and by functional analysis. In the second part, we analyzed 25,606 common variants (MAF ≥ 5%) generated by Exome‐chip array. Top loci were replicated in first replication study (402 cases and 2,537 controls) and in 3 others studies (512 cases and 669 controls). Meta-analysis of all including 1,154 unrelated FMD cases and 3,895 controls allowed identification of association between FMD and rs9349379-A (OR=1.39 [1.39-1.54]; P=7.4×10‐10). rs9349379 is intronic to PHACTR1, a risk locus for coronary artery disease, migraine, and cervical artery dissection. The analyses of geometrical parameters of carotids from 2,458 healthy volunteers indicated higher intima media thickness (P = 1.97×10‐4) and wall to lumen ratio (P = 0.002) in rs9349379‐A carriers, suggesting indices of carotid hypertrophy as previously described in carotids of FMD patients. Immunohistochemistry detected PHACTR1 in endothelium and smooth muscle cells of FMD and normal human carotids. The expression of PHACTR1 by genotypes in primary human fibroblasts showed higher expression in rs9349379‐A carriers (N=86, P=0.003). Phactr1 knockdown in zebrafish resulted in dilated vessels indicating subtle impairment of vascular development. This work confirms the multifactorial and heterogeneous genetic architecture of the FMD and opens new opportunities to evaluate all of genomic variability of FMD patients with massive genetic epidemiology approaches.

The purpose of this research was to obtain empirical evidence regarding the knowledge and attitudes among graduate social work students. It examines the relationship between age, previous sex education, marital status and the amount of human sexuality knowledge.

Software components provide essential means to structure and organize software effectively. However, frequently, required component abstractions are not available in a programming language or system, or are not adequately combinable with each other. Invasive software composition (ISC) is a general approach to software composition that unifies component-like abstractions such as templates, aspects and macros. ISC is based on fragment composition, and composes programs and other software artifacts at the level of syntax trees. Therefore, a unifying fragment component model is related to the context-free grammar of a language to identify extension and variation points in syntax trees as well as valid component types. By doing so, fragment components can be composed by transformations at respective extension and variation points so that always valid composition results regarding the underlying context-free grammar are yielded. However, given a language’s context-free grammar, the composition result may still be incorrect. Context-sensitive constraints such as type constraints may be violated so that the program cannot be compiled and/or interpreted correctly. While a compiler can detect such errors after composition, it is difficult to relate them back to the original transformation step in the composition system, especially in the case of complex compositions with several hundreds of such steps. To tackle this problem, this thesis proposes well-formed ISC—an extension to ISC that uses reference attribute grammars (RAGs) to specify fragment component models and fragment contracts to guard compositions with context-sensitive constraints. Additionally, well-formed ISC provides composition strategies as a means to configure composition algorithms and handle interferences between composition steps. Developing ISC systems for complex languages such as programming languages is a complex undertaking. Composition-system developers need to supply or develop adequate language and parser specifications that can be processed by an ISC composition engine. Moreover, the specifications may need to be extended with rules for the intended composition abstractions. Current approaches to ISC require complete grammars to be able to compose fragments in the respective languages. Hence, the specifications need to be developed exhaustively before any component model can be supplied. To tackle this problem, this thesis introduces scalable ISC—a variant of ISC that uses island component models as a means to define component models for partially specified languages while still the whole language is supported. Additionally, a scalable workflow for agile composition-system development is proposed which supports a development of ISC systems in small increments using modular extensions. All theoretical concepts introduced in this thesis are implemented in the Skeletons and Application Templates framework SkAT. It supports “classic”, well-formed and scalable ISC by leveraging RAGs as its main specification and implementation language. Moreover, several composition systems based on SkAT are discussed, e.g., a well-formed composition system for Java and a C preprocessor-like macro language. In turn, those composition systems are used as composers in several example applications such as a library of parallel algorithmic skeletons.

Software components provide essential means to structure and organize software effectively. However, frequently, required component abstractions are not available in a programming language or system, or are not adequately combinable with each other. Invasive software composition (ISC) is a general approach to software composition that unifies component-like abstractions such as templates, aspects and macros. ISC is based on fragment composition, and composes programs and other software artifacts at the level of syntax trees. Therefore, a unifying fragment component model is related to the context-free grammar of a language to identify extension and variation points in syntax trees as well as valid component types. By doing so, fragment components can be composed by transformations at respective extension and variation points so that always valid composition results regarding the underlying context-free grammar are yielded. However, given a language’s context-free grammar, the composition result may still be incorrect. Context-sensitive constraints such as type constraints may be violated so that the program cannot be compiled and/or interpreted correctly. While a compiler can detect such errors after composition, it is difficult to relate them back to the original transformation step in the composition system, especially in the case of complex compositions with several hundreds of such steps. To tackle this problem, this thesis proposes well-formed ISC—an extension to ISC that uses reference attribute grammars (RAGs) to specify fragment component models and fragment contracts to guard compositions with context-sensitive constraints. Additionally, well-formed ISC provides composition strategies as a means to configure composition algorithms and handle interferences between composition steps. Developing ISC systems for complex languages such as programming languages is a complex undertaking. Composition-system developers need to supply or develop adequate language and parser specifications that can be processed by an ISC composition engine. Moreover, the specifications may need to be extended with rules for the intended composition abstractions. Current approaches to ISC require complete grammars to be able to compose fragments in the respective languages. Hence, the specifications need to be developed exhaustively before any component model can be supplied. To tackle this problem, this thesis introduces scalable ISC—a variant of ISC that uses island component models as a means to define component models for partially specified languages while still the whole language is supported. Additionally, a scalable workflow for agile composition-system development is proposed which supports a development of ISC systems in small increments using modular extensions. All theoretical concepts introduced in this thesis are implemented in the Skeletons and Application Templates framework SkAT. It supports “classic”, well-formed and scalable ISC by leveraging RAGs as its main specification and implementation language. Moreover, several composition systems based on SkAT are discussed, e.g., a well-formed composition system for Java and a C preprocessor-like macro language. In turn, those composition systems are used as composers in several example applications such as a library of parallel algorithmic skeletons.