The French Canadian founder population : lessons and insights for genetic epidemiological research

La population canadienne-française a une histoire démographique unique faisant d’elle une population d’intérêt pour l’épidémiologie et la génétique. Cette thèse vise à mettre en valeur les caractéristiques de la population québécoise qui peuvent être utilisées afin d’améliorer la conception et l’analyse d’études d’épidémiologie génétique. Dans un premier temps, nous profitons de la présence d’information généalogique détaillée concernant les Canadiens français pour estimer leur degré d’apparentement et le comparer au degré d’apparentement génétique. L’apparentement génétique calculé à partir du partage génétique identique par ascendance est corrélé à l’apparentement généalogique, ce qui démontre l'utilité de la détection des segments identiques par ascendance pour capturer l’apparentement complexe, impliquant entre autres de la consanguinité. Les conclusions de cette première étude pourront guider l'interprétation des résultats dans d’autres populations ne disposant pas d’information généalogique. Dans un deuxième temps, afin de tirer profit pleinement du potentiel des généalogies canadienne-françaises profondes, bien conservées et quasi complètes, nous présentons le package R GENLIB, développé pour étudier de grands ensembles de données généalogiques. Nous étudions également le partage identique par ascendance à l’aide de simulations et nous mettons en évidence le fait que la structure des populations régionales peut faciliter l'identification de fondateurs importants, qui auraient pu introduire des mutations pathologiques, ce qui ouvre la porte à la prévention et au dépistage de maladies héréditaires liées à certains fondateurs. Finalement, puisque nous savons que les Canadiens français ont accumulé des segments homozygotes, à cause de la présence de consanguinité lointaine, nous estimons la consanguinité chez les individus canadiens-français et nous étudions son impact sur plusieurs traits de santé. Nous montrons comment la dépression endogamique influence des traits complexes tels que la grandeur et des traits hématologiques. Nos résultats ne sont que quelques exemples de ce que nous pouvons apprendre de la population canadienne-française. Ils nous aideront à mieux comprendre les caractéristiques des autres populations de même qu’ils pourront aider la recherche en épidémiologie génétique au sein de la population canadienne-française.

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.

Pleiotropic Analysis of Lung Cancer and Blood Triglycerides

Epidemiologically related traits may share genetic risk factors, and pleiotropic analysis could identify individual loci associated with these traits. Because of their shared epidemiological associations, we conducted pleiotropic analysis of genome-wide association studies of lung cancer (12 160 lung cancer case patients and 16 838 control subjects) and cardiovascular disease risk factors (blood lipids from 188 577 subjects, type 2 diabetes from 148 821 subjects, body mass index from 123 865 subjects, and smoking phenotypes from 74 053 subjects). We found that 6p22.1 (rs6904596, ZNF184) was associated with both lung cancer (P = 5.50x10(-6)) and blood triglycerides (P = 1.39x10(-5)). We replicated the association in 6097 lung cancer case patients and 204 657 control subjects (P = 2.40 × 10(-4)) and in 71 113 subjects with triglycerides data (P = .01). rs6904596 reached genome-wide significance in lung cancer meta-analysis (odds ratio = 1.15, 95% confidence interval = 1.10 to 1.21 ,: Pcombined = 5.20x10(-9)). The large sample size provided by the lipid GWAS data and the shared genetic risk factors between the two traits contributed to the uncovering of a hitherto unidentified genetic locus for lung cancer.

Rare coding variants in the phospholipase D3 gene confer risk for Alzheimer's disease.

Genome-wide association studies (GWAS) have identified several risk variants for late-onset Alzheimer's disease (LOAD)1, 2. These common variants have replicable but small effects on LOAD risk and generally do not have obvious functional effects. Low-frequency coding variants, not detected by GWAS, are predicted to include functional variants with larger effects on risk. To identify low-frequency coding variants with large effects on LOAD risk, we carried out whole-exome sequencing (WES) in 14 large LOAD families and follow-up analyses of the candidate variants in several large LOAD case–control data sets. A rare variant in PLD3 (phospholipase D3; Val232Met) segregated with disease status in two independent families and doubled risk for Alzheimer’s disease in seven independent case–control series with a total of more than 11,000 cases and controls of European descent. Gene-based burden analyses in 4,387 cases and controls of European descent and 302 African American cases and controls, with complete sequence data for PLD3, reveal that several variants in this gene increase risk for Alzheimer’s disease in both populations. PLD3 is highly expressed in brain regions that are vulnerable to Alzheimer’s disease pathology, including hippocampus and cortex, and is expressed at significantly lower levels in neurons from Alzheimer’s disease brains compared to control brains. Overexpression of PLD3 leads to a significant decrease in intracellular amyloid-β precursor protein (APP) and extracellular Aβ42 and Aβ40 (the 42- and 40-residue isoforms of the amyloid-β peptide), and knockdown of PLD3 leads to a significant increase in extracellular Aβ42 and Aβ40. Together, our genetic and functional data indicate that carriers of PLD3 coding variants have a twofold increased risk for LOAD and that PLD3 influences APP processing. This study provides an example of how densely affected families may help to identify rare variants with large effects on risk for disease or other complex traits.

HNF1B variants associate with promoter methylation and regulate gene networks activated in prostate and ovarian cancer

Two independent regions within HNF1B are consistently identified in prostate and ovarian cancer genome-wide association studies (GWAS); their functional roles are unclear. We link prostate cancer (PC) risk SNPs rs11649743 and rs3760511 with elevated HNF1B gene expression and allele-specific epigenetic silencing, and outline a mechanism by which common risk variants could effect functional changes that increase disease risk: functional assays suggest that HNF1B is a pro-differentiation factor that suppresses epithelial-to-mesenchymal transition (EMT) in unmethylated, healthy tissues. This tumor-suppressor activity is lost when HNF1B is silenced by promoter methylation in the progression to PC. Epigenetic inactivation of HNF1B in ovarian cancer also associates with known risk SNPs, with a similar impact on EMT. This represents one of the first comprehensive studies into the pleiotropic role of a GWAS-associated transcription factor across distinct cancer types, and is the first to describe a conserved role for a multi-cancer genetic risk factor.

Genome-wide association study reveals greater polygenic loading for schizophrenia in cases with a family history of illness

Genome-wide association studies (GWAS) of schizophrenia have yielded more than 100 common susceptibility variants, and strongly support a substantial polygenic contribution of a large number of small allelic effects. It has been hypothesized that familial schizophrenia is largely a consequence of inherited rather than environmental factors. We investigated the extent to which familiality of schizophrenia is associated with enrichment for common risk variants detectable in a large GWAS. We analyzed single nucleotide polymorphism (SNP) data for cases reporting a family history of psychotic illness (N = 978), cases reporting no such family history (N = 4,503), and unscreened controls (N = 8,285) from the Psychiatric Genomics Consortium (PGC1) study of schizophrenia. We used a multinomial logistic regression approach with model-fitting to detect allelic effects specific to either family history subgroup. We also considered a polygenic model, in which we tested whether family history positive subjects carried more schizophrenia risk alleles than family history negative subjects, on average. Several individual SNPs attained suggestive but not genome-wide significant association with either family history subgroup. Comparison of genome-wide polygenic risk scores based on GWAS summary statistics indicated a significant enrichment for SNP effects among family history positive compared to family history negative cases (Nagelkerke's R(2 ) = 0.0021; P = 0.00331; P-value threshold <0.4). Estimates of variability in disease liability attributable to the aggregate effect of genome-wide SNPs were significantly greater for family history positive compared to family history negative cases (0.32 and 0.22, respectively; P = 0.031). We found suggestive evidence of allelic effects detectable in large GWAS of schizophrenia that might be specific to particular family history subgroups. However, consideration of a polygenic risk score indicated a significant enrichment among family history positive cases for common allelic effects. Familial illness might, therefore, represent a more heritable form of schizophrenia, as suggested by previous epidemiological studies.

Identification des gènes modifiant l’âge d’apparition du glaucome primaire à angle-ouvert dans une famille canadienne-française fondatrice.

Le glaucome est un groupe hétérogène de maladies qui sont caractérisées par l’apoptose des cellules ganglionnaires de la rétine et la dégénérescence progressive du nerf optique. Il s’agit de la première cause de cécité irréversible, qui touche environ 60 millions de personnes dans le monde. Sa forme la plus commune est le glaucome à angle ouvert (GAO), un trouble polygénique causé principalement par une prédisposition génétique, en interaction avec d’autres facteurs de risque tels que l’âge et la pression intraoculaire élevée (PIO). Le GAO est une maladie génétique complexe, bien que certaines formes sévères sont autosomiques dominantes. Dix-sept loci ont été liés à la maladie et acceptés par la « Human Genome Organisation » (HUGO) et cinq gènes ont été identifiés à ces loci (MYOC, OPTN, WDR36, NTF4, ASB10). Récemment, des études d’association sur l’ensemble du génome ont identifié plus de 20 facteurs de risque fréquents, avec des effets relativement faibles. Depuis plus de 50 ans, notre équipe étudie 749 membres de la grande famille canadienne-française CA où la mutation MYOCK423E cause une forme autosomale dominante de GAO dont l’âge de début est fortement variable. Premièrement, il a été montré que cette variabilité de l’âge de début de l’hypertension intraoculaire possède une importante composante génétique causée par au moins un gène modificateur. Ce modificateur interagit avec la mutation primaire et altère la sévérité du glaucome chez les porteurs de MYOCK423E. Un gène modificateur candidat WDR36 a été génotypé dans 2 grandes familles CA et BV. Les porteurs de variations non-synonymes de WDR36 ainsi que de MYOCK423E de la famille CA ont montré une tendance à développer la maladie plus jeune. Un outil de forage de données a été développé pour représenter des informations connues relatives à la maladie et faciliter la priorisation des gènes candidats. Cet outil a été appliqué avec succès à la dépression bipolaire et au glaucome. La suite du projet consiste à finaliser un balayage de génome sur la famille CA et à séquencer les loci afin d’identifier les variations modificatrices du glaucome. Éventuellement, ces variations permettront d’identifier les individus dont le glaucome risque d’être plus agressif.

DATA DRIVEN APPROACHES TO IDENTIFY DETERMINANTS OF HEART DISEASES AND CANCER RESISTANCE

Cancer and cardio-vascular diseases are the leading causes of death world-wide. Caused by systemic genetic and molecular disruptions in cells, these disorders are the manifestation of profound disturbance of normal cellular homeostasis. People suffering or at high risk for these disorders need early diagnosis and personalized therapeutic intervention. Successful implementation of such clinical measures can significantly improve global health. However, development of effective therapies is hindered by the challenges in identifying genetic and molecular determinants of the onset of diseases; and in cases where therapies already exist, the main challenge is to identify molecular determinants that drive resistance to the therapies. Due to the progress in sequencing technologies, the access to a large genome-wide biological data is now extended far beyond few experimental labs to the global research community. The unprecedented availability of the data has revolutionized the capabilities of computational researchers, enabling them to collaboratively address the long standing problems from many different perspectives. Likewise, this thesis tackles the two main public health related challenges using data driven approaches. Numerous association studies have been proposed to identify genomic variants that determine disease. However, their clinical utility remains limited due to their inability to distinguish causal variants from associated variants. In the presented thesis, we first propose a simple scheme that improves association studies in supervised fashion and has shown its applicability in identifying genomic regulatory variants associated with hypertension. Next, we propose a coupled Bayesian regression approach -- eQTeL, which leverages epigenetic data to estimate regulatory and gene interaction potential, and identifies combinations of regulatory genomic variants that explain the gene expression variance. On human heart data, eQTeL not only explains a significantly greater proportion of expression variance in samples, but also predicts gene expression more accurately than other methods. We demonstrate that eQTeL accurately detects causal regulatory SNPs by simulation, particularly those with small effect sizes. Using various functional data, we show that SNPs detected by eQTeL are enriched for allele-specific protein binding and histone modifications, which potentially disrupt binding of core cardiac transcription factors and are spatially proximal to their target. eQTeL SNPs capture a substantial proportion of genetic determinants of expression variance and we estimate that 58% of these SNPs are putatively causal. The challenge of identifying molecular determinants of cancer resistance so far could only be dealt with labor intensive and costly experimental studies, and in case of experimental drugs such studies are infeasible. Here we take a fundamentally different data driven approach to understand the evolving landscape of emerging resistance. We introduce a novel class of genetic interactions termed synthetic rescues (SR) in cancer, which denotes a functional interaction between two genes where a change in the activity of one vulnerable gene (which may be a target of a cancer drug) is lethal, but subsequently altered activity of its partner rescuer gene restores cell viability. Next we describe a comprehensive computational framework --termed INCISOR-- for identifying SR underlying cancer resistance. Applying INCISOR to mine The Cancer Genome Atlas (TCGA), a large collection of cancer patient data, we identified the first pan-cancer SR networks, composed of interactions common to many cancer types. We experimentally test and validate a subset of these interactions involving the master regulator gene mTOR. We find that rescuer genes become increasingly activated as breast cancer progresses, testifying to pervasive ongoing rescue processes. We show that SRs can be utilized to successfully predict patients' survival and response to the majority of current cancer drugs, and importantly, for predicting the emergence of drug resistance from the initial tumor biopsy. Our analysis suggests a potential new strategy for enhancing the effectiveness of existing cancer therapies by targeting their rescuer genes to counteract resistance. The thesis provides statistical frameworks that can harness ever increasing high throughput genomic data to address challenges in determining the molecular underpinnings of hypertension, cardiovascular disease and cancer resistance. We discover novel molecular mechanistic insights that will advance the progress in early disease prevention and personalized therapeutics. Our analyses sheds light on the fundamental biological understanding of gene regulation and interaction, and opens up exciting avenues of translational applications in risk prediction and therapeutics.

Genetic analysis of the flowering date and number of petals in rose

International audience

Influências genéticas nas características da carcaça e carne em bovinos

Tese de Doutoramento em Ciências Veterinárias - Especialidade de Produção Animal

Functional characterisation of putative Cis-Regulatory Risk Loci for breast cancer

Dissertação de Mestrado, Qualidade em Análises - Erasmus Mundus, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2015

Functional characterization by genetic complementation of aroB-Encoded dehydroquinate synthase from Mycobactetium tuberculosis H37Rv and its heterologous expression and purification

The recent recrudescence of Mycobacterium tuberculosis infection and the emergence of multidrug-resistant strains have created an urgent need for new therapeutics against tuberculosis. The enzymes of the shikimate pathway are attractive drug targets because this route is absent in mammals and, in M. tuberculosis, it is essential for pathogen viability. This pathway leads to the biosynthesis of aromatic compounds, including aromatic amino acids, and it is found in plants, fungi, bacteria, and apicomplexan parasites. The aroB-encoded enzyme dehydroquinate synthase is the second enzyme of this pathway, and it catalyzes the cyclization of 3-deoxy-D-arabino-heptulosonate-7-phosphate in 3-dehydroquinate. Here we describe the PCR amplification and cloning of the aroB gene and the overexpression and purification of its product, dehydroquinate synthase, to homogeneity. In order to probe where the recombinant dehydroquinate synthase was active, genetic complementation studies were performed. The Escherichia coli AB2847 mutant was used to demonstrate that the plasmid construction was able to repair the mutants, allowing them to grow in minimal medium devoid of aromatic compound supplementation. In addition, homogeneous recombinant M. tuberculosis dehydroquinate synthase was active in the absence of other enzymes, showing that it is homomeric. These results will support the structural studies with M. tuberculosis dehydroquinate synthase that are essential for the rational design of antimycobacterial agents.

Genomic structure and marker-derived gene networks for growth and meat quality traits of brazilian nelore beef cattle.

Nelore is the major beef cattle breed in Brazil with more than 130 million heads. Genome-wide association studies (GWAS) are often used to associate markers and genomic regions to growth and meat quality traits that can be used to assist selection programs. An alternative methodology to traditional GWAS that involves the construction of gene network interactions, derived from results of several GWAS is the AWM (Association Weight Matrices)/PCIT (Partial Correlation and Information Theory). With the aim of evaluating the genetic architecture of Brazilian Nelore cattle, we used high-density SNP genotyping data (~770,000 SNP) from 780 Nelore animals comprising 34 half-sibling families derived from highly disseminated and unrelated sires from across Brazil. The AWM/PCIT methodology was employed to evaluate the genes that participate in a series of eight phenotypes related to growth and meat quality obtained from this Nelore sample.

A DRD2 and ANKK1 haplotype is associated with nicotine dependence

To test the importance of the dopamine D2 receptor (DRD2) region in nicotine dependence, 150 smokers and 228 controls were genotyped for the DRD2 C957T, -141delC and ANKK1 TaqIA polymorphisms (rs6277, rs1799732 and rs1800497, respectively). The -141delC SNP did not show any association but both the C957T and TaqIA SNPs showed association at the allele, genotype, haplotype and combined genotype levels. The 957C/TaqI A1 haplotype was more than 3.5 times as likely to be associated with nicotine dependence compared with the 957T/TaqI A1 haplotype (P = 0.003). Analysis of the combined genotypes of both SNPs revealed that individuals who were homozygous for the 957C-allele (CC) and had either one or two copies of the TaqI A1-allele were 3.3 times as likely to have nicotine dependence compared to all other genotype combinations (P = 0.0003) and that these genotypes accounted for approximately 13% of the susceptibility to nicotine addiction in our population. Our findings suggest that the DRD2 C957T polymorphism and the ANKK1 TaqIA polymorphism are key contributors to the genetic susceptibility to nicotine dependence.