Computational analysis of the genetic and environmental contributions to disease-related human phenotypes: From predicting adverse lipid response of HIV patients receiving antiretroviral therapy to genome-wide association studies of cardiovascular and lipid related disorders

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.

Comparative population genetic structure in a plant-pollinator/seed predator system.

Comparative analyses of spatial genetic structure of populations of plants and the insects they interact with provide an indication of how gene flow, natural selection and genetic drift may jointly influence the distribution of genetic variation and potential for local co-adaptation for interacting species. Here, we analysed the spatial scale of genetic structure within and among nine populations of an interacting species pair, the white campion Silene latifolia and the moth Hadena bicruris, along a latitudinal gradient across Northern/Central Europe. This dioecious, short-lived perennial plant inhabits patchy, often disturbed environments. The moth H. bicruris acts both as its pollinator and specialist seed predator that reproduces by laying eggs in S. latifolia flowers. We used nine microsatellite markers for S. latifolia and eight newly developed markers for H. bicruris. We found high levels of inbreeding in most populations of both plant and pollinator/seed predator. Among populations, significant genetic structure was observed for S. latifolia but not for its pollinator/seed predator, suggesting that despite migration among populations of H. bicruris, pollen is not, or only rarely, carried over between populations, thus maintaining genetic structure among plant populations. There was a weak positive correlation between genetic distances of S. latifolia and H. bicruris. These results indicate that while significant structure of S. latifolia populations creates the potential for differentiation at traits relevant for the interaction with the pollinator/seed predator, substantial gene flow in H. bicruris may counteract this process in at least some populations.

Genetic transformation of sweet oranges with the D4E1 gene driven by the AtPP2 promoter

The objective of this work was to produce transgenic 'Pêra' and 'Valência' sweet orange plants using the D4E1 gene driven by the Arabidopsis thaliana phloem protein (AtPP2) promoter and to quantify transgene expression in different transformation events. Genetic transformation experiments were carried out with epicotyl segments co‑cultivated with Agrobacterium tumefaciens. Six plants from 'Pêra' sweet orange and seven plants from 'Valência' sweet orange were confirmed as different transgenic events by means of the polymerase chain reaction (PCR) and the Southern blot techniques. Transgene expression was quantified using real‑time quantitative PCR. D4E1 gene expression levels vary from 5 up to 50 times among different transformation events.

Genetic diversity of irrigated barley based on molecular and quantitative data and on malting quality

The objective of this work was to quantify the genetic diversity of elite genotypes of irrigated barley in the Brazilian savanna. Thirty elite barley genotypes from Embrapa Cerrados' collection were evaluated using 160 RAPD markers, 12 agronomic traits related to yield components, and 10 malting quality parameters. The genetic dissimilarity matrices based on molecular markers, quantitative traits, and malting quality characters were calculated and a cluster analysis was performed using the unweighted pair-group method with arithmetic mean (UPGMA) as grouping criterion. High genetic diversity among accessions were observed. The estimated genetic dissimilarities were weakly correlated, showing the complementarity of the different character groups. Selection indices and graphical dispersion analysis allowed the selection of promising genotypes and the indication of suitable crosses for maximizing the heterotic effects in breeding programs for irrigated barley in the Brazilian savanna.

Genetic studies of body mass index yield new insights for obesity biology

Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P < 5 × 10(-8)), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for ∼2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.

Genetic variability of marine shrimp in the Brazilian industry

The objective of this work was to estimate the genetic variability level and distribution in Brazilian broodstocks of marine shrimp (Litopenaeus vannamei). Nine of the country's largest hatcheries were evaluated using codominant and highly polymorphic microsatellite markers. The results obtained from genotyping of ten microsatellite loci are indicative of genetic variability that is compatible with that found in wild populations of L. vannamei in Mexico and Central America. A possible explanation is the highly diversified and relatively recent origin of the available broodstocks. Bayesian analysis detected a signal for five founding populations. The distribution of genetic distances partially reflects geographical location, and this information will be useful for the creation of new broodstocks. Therefore, L. vannamei genetic variability among nine of the largest national hatcheries can be considered high.

APOBEC3G genetic variants and their influence on the progression to AIDS.

The cytosine deaminase APOBEC3G, in the absence of the human immunodeficiency virus type 1 (HIV-1) accessory gene HIV-1 viral infectivity factor (vif), inhibits viral replication by introducing G-->A hypermutation in the newly synthesized HIV-1 DNA negative strand. We tested the hypothesis that genetic variants of APOBEC3G may modify HIV-1 transmission and disease progression. Single nucleotide polymorphisms were identified in the promoter region (three), introns (two), and exons (two). Genotypes were determined for 3,073 study participants enrolled in six HIV-AIDS prospective cohorts. One codon-changing variant, H186R in exon 4, was polymorphic in African Americans (AA) (f = 37%) and rare in European Americans (f < 3%) or Europeans (f = 5%). For AA, the variant allele 186R was strongly associated with decline in CD4 T cells (CD4 slope on square root scale: -1.86, P = 0.009), The 186R allele was also associated with accelerated progression to AIDS-defining conditions in AA. The in vitro antiviral activity of the 186R enzyme was not inferior to that of the common H186 variant. These studies suggest that there may be a modifying role of variants of APOBEC3G on HIV-1 disease progression that warrants further investigation.

Mucoviscidose: illustration de la complexité du dépistage génétique. [The example of cystic fibrosis to highlight the complexity of genetic screening].

Différentes organisations et différents pays aboutissent souvent à des conclusions différentes quant à la pertinence d'introduire un test de dépistage génétique dans la population générale. Cet article décrit la complexité du dépistage basé sur des tests génétiques. Utilisant l'exemple de la mucoviscidose - pour laquelle un groupe de travail national est en train d'évaluer la pertinence d'un dépistage génétique - les auteurs relèvent les situaions où les recommandations de dépistage sont parfois basées sur l'émergence de nouvelles technologies (par exemple, test génétique) et d'opinion publique plutôt que sur la base d'évidences. Ils présentent également les enjeux éthiques et économiques du dépistage génétique de la mucoviscidose. [Abstract] Various institutions and countries often reach different conclusions about the utility of introducing a newborn screening test in the general population. This paper highlights the complexity of population screening including genetic tests. Using the example of cystic fibrosis genetic screening, for which a Swiss Working Group for Cystic Fibrosis is currently evaluating the pertinence, we outline that screening recommendations are often based more on expert opinion and emerging new technologies rather than on evidence. We also present some ethical and economic issues related to cystic fibrosis genetic screening.

Prospective study of insulin-like growth factor-I, insulin-like growth factor-binding protein 3, genetic variants in the IGF1 and IGFBP3 genes and risk of coronary artery disease.

Although experimental studies have suggested that insulin-like growth factor I (IGF-I) and its binding protein IGFBP-3 might have a role in the aetiology of coronary artery disease (CAD), the relevance of circulating IGFs and their binding proteins in the development of CAD in human populations is unclear. We conducted a nested case-control study, with a mean follow-up of six years, within the EPIC-Norfolk cohort to assess the association between circulating levels of IGF-I and IGFBP-3 and risk of CAD in up to 1,013 cases and 2,055 controls matched for age, sex and study enrolment date. After adjustment for cardiovascular risk factors, we found no association between circulating levels of IGF-I or IGFBP-3 and risk of CAD (odds ratio: 0.98 (95% Cl 0.90-1.06) per 1 SD increase in circulating IGF-I; odds ratio: 1.02 (95% Cl 0.94-1.12) for IGFBP-3). We examined associations between tagging single nucleotide polymorphisms (tSNPs) at the IGF1 and IGFBP3 loci and circulating IGF-I and IGFBP-3 levels in up to 1,133 cases and 2,223 controls and identified three tSNPs (rs1520220, rs3730204, rs2132571) that showed independent association with either circulating IGF-I or IGFBP-3 levels. In an assessment of 31 SNPs spanning the IGF1 or IGFBP3 loci, none were associated with risk of CAD in a meta-analysis that included EPIC-Norfolk and eight additional studies comprising up to 9,319 cases and 19,964 controls. Our results indicate that IGF-I and IGFBP-3 are unlikely to be importantly involved in the aetiology of CAD in human populations.

C4 Photosynthesis evolved in grasses via parallel adaptive genetic changes.

Phenotypic convergence is a widespread and well-recognized evolutionary phenomenon. However, the responsible molecular mechanisms remain often unknown mainly because the genes involved are not identified. A well-known example of physiological convergence is the C4 photosynthetic pathway, which evolved independently more than 45 times [1]. Here, we address the question of the molecular bases of the C4 convergent phenotypes in grasses (Poaceae) by reconstructing the evolutionary history of genes encoding a C4 key enzyme, the phosphoenolpyruvate carboxylase (PEPC). PEPC genes belong to a multigene family encoding distinct isoforms of which only one is involved in C4 photosynthesis [2]. By using phylogenetic analyses, we showed that grass C4 PEPCs appeared at least eight times independently from the same non-C4 PEPC. Twenty-one amino acids evolved under positive selection and converged to similar or identical amino acids in most of the grass C4 PEPC lineages. This is the first record of such a high level of molecular convergent evolution, illustrating the repeatability of evolution. These amino acids were responsible for a strong phylogenetic bias grouping all C4 PEPCs together. The C4-specific amino acids detected must be essential for C4 PEPC enzymatic characteristics, and their identification opens new avenues for the engineering of the C4 pathway in crops.