Peripheral blood biomarkers can inform clinical care and drug development. Establishing causality between biomarker and disease is often critical for such applications, but epidemiological studies are limited due to biases from confounding and reverse causation. Mendelian randomization analysis leverages random inheritance of genetic variants at conception to mimic properties of randomized studies and estimate unconfounded effects between biomarker and disease, or vice-versa. This thesis demonstrates the utility of Mendelian randomization as a complementary tool to elucidate observational studies, predict drug safety and repurposing opportunities, and improve diagnostic biomarkers for cardiometabolic diseases. First, we characterized the hypothesized relationship between lipoprotein(a) and atrial fibrillation. We demonstrated both observed and genetically predicted lipoprotein(a) levels were associated with higher risk of atrial fibrillation across multiple independent cohorts. Importantly, risk was partly mediated independent of atherosclerotic cardiovascular disease, a known consequence of elevated lipoprotein(a) and itself a risk factor for atrial fibrillation. Next, we explored the lifelong effects of endogenous testosterone across a comprehensive set of 461 health outcomes in 161,268 males from the UK Biobank cohort. Using Mendelian randomization analysis, we found higher testosterone had beneficial effects on body composition and bone mineral density but adverse effects on prostate cancer, androgenic alopecia, spinal stenosis, and hypertension. Finally, we applied Mendelian randomization with the intention of discovering biomarkers caused by disease, which are expected to represent markers of early disease. As a proof-of-concept, we applied this framework to identify biomarkers associated with genetic predisposition to kidney function among 238 biomarkers measured in the ORIGIN trial. We discovered reduced kidney function caused increased trefoil factor 3 and showed its addition to models with known risk factors improved discrimination of incident early-stage chronic kidney disease. Taken together, Mendelian randomization identified biomarkers that warrant further study, with promising implications for screening, prevention, and treatment of different cardiometabolic diseases. / Thesis / Doctor of Philosophy (PhD) / Biological markers associated with disease can inform novel therapeutics or diagnostics but distinguishing causation from correlation is challenging. Mendelian randomization – a technique that leverages random inheritance of genetic variation to infer causality – was used to examine the role of biomarkers in cardiometabolic diseases. First, we implicated lipoprotein(a) as a risk factor for atrial fibrillation that acts independent of atherosclerotic cardiovascular disease. Second, we comprehensively characterized the lifelong effects of testosterone on health outcomes in males, where we found evidence of both beneficial and adverse effects on disease. Finally, we discovered trefoil factor 3 as a diagnostic marker for early-stage chronic kidney disease. Altogether, this thesis demonstrated different applications of Mendelian randomization that showcase its utility as a complementary tool to reveal causal biomarkers, and served to identify biomarkers for cardiometabolic diseases that merit further studies to evaluate their potential benefit on patient care.

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No / Human aging involves a gradual decrease in cellular integrity that contributes to multiple complex disorders such as neurodegenerative disorders, cancer, diabetes, and cardiovascular diseases. Genome-wide association studies (GWAS) play a key role in discovering genetic variations that may contribute towards disease vulnerability. However, mostly disease-associated SNPs lie within non-coding part of the genome; majority of the variants are also present in linkage disequilibrium (LD) with the genome-wide significant SNPs (GWAS lead SNPs). Overall 600 SNPs were analyzed, out of which 291 returned RegulomeDB scores of 1-6. It was observed that just 4 out of those 291 SNPs show strong evidence of regulatory effects (RegulomeDB score < 3), while none of them includes any GWAS lead SNP. Nevertheless, this study demonstrates that by combining ENCODE project data along with GWAS reported information will provide important insights on the impact of a genetic variant-moving from GWAS towards understanding disease pathways. It is noteworthy that both genome-wide significant SNPs as well as the SNPs in LD must be considered for future studies; this may prove to be crucial in deciphering the potential regulatory elements involved in complex disorders and aging in particular.

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My thesis aims at identifying both genetic and environmental causes of major depressive disorder (MDD), using a large case-control study: 6,000 Chinese women with recurrent MDD and 6,000 controls. One of the major challenges for conducting genetic research on MDD is disease heterogeneity. The first question addressed is how different MDD is from highly comorbid anxiety disorders. I examine how anxiety disorders predict clinical features of depression and the degree of heterogeneity in their predictive pattern. The second question addressed is whether clinically defined MDD is a single disorder, or whether it consists of multiple subtypes. Results are then compared with and interpreted in the context of Western studies. Furthermore, latent class analysis and factor analysis results are also used in association analysis to explore more genetically homogeneous subtypes. Genetic data were derived using a novel strategy, low pass whole genome sequence analysis. Using genotypes imputed from the sequence data, I show that a cluster of single nucleotide polymorphisms (SNPs) is significantly associated with a binary disease phenotype including only cases with = 4 episodes of MDD, suggesting that recurrence might be an indication of genetic predisposition. The third issue examined is the contribution of rare variants to disease susceptibility. Again using sparse sequence data, I identified exonic sequence variants and performed gene-based analysis by comparing the number of variants between cases and controls in every gene. Furthermore I performed gene enrichment test by combining P values of SNP association tests at different minor allele frequency ranges. Overall, I did not find convincing evidence that rare variants aggregately contribute to disease susceptibility. However, the gene-based analysis resulted in an unexpected finding: cases have an excess of variants in all thirteen-protein coding mitochondrial genes, which was due to copy number differences in the mitochondrial genome. Both human phenotypic data as well as mice experimental data show that the increase in the mitochondrial copy number in cases is due to chronic stress.

Le Syndrome d’Impatiences Musculaires de l’Éveil (SIME) est une maladie neurologique caractérisée par un besoin urgent de bouger les jambes. C’est également l’une des causes les plus fréquentes d’insomnie. C’est une maladie très répandue, avec une prévalence de presque 15 % dans la population générale. Les maladies multifactorielles comme le SIME sont souvent le résultat de l’évolution d’une composante génétique et d’une composante environnementale. Dans le cadre du SIME, les études d’association génomique ont permis l’identification de 4 variants à effet modéré ou faible. Cependant, ces quatre variants n’expliquent qu’une faible partie de la composante génétique de la maladie, ce qui confirme que plusieurs nouveaux variants sont encore à identifier. Le rôle des déséquilibres génomiques (Copy Number Variations ou CNVs) dans le mécanisme génétique du SIME est à ce jour inconnu. Cependant, les CNVs se sont récemment positionnés comme une source d’intérêt majeur de variation génétique potentiellement responsable des phénotypes. En collaboration avec une équipe de Munich, nous avons réalisé deux études CNVs à échelle génomique (biopuces à SNP et hybridation génomique comparée (CGH)) sur des patients SIME d’ascendance germanique. À l’aide d’une étude cas-contrôle, nous avons pu identifier des régions avec une occurrence de CNVs différentes pour les patients SIME, comparés à différents groupes contrôles. L’une de ces régions est particulièrement intéressante, car elle est concordante à la fois avec des précédentes études familiales ainsi qu’avec les récentes études d’associations génomiques. / Restless Legs syndrome (RLS) is a neurological disorder characterized by the urge to move one’s limbs. It is also one of the most frequent causes of insomnia. The prevalence of RLS is estimated to be around 15% in the general population. Complexes disorders like RLS are often the result of the evolution of genetic and environmental components. For RLS, recent Genome Wide Association Study (GWAS) have identified four variants with mild to moderate effects. However, those four variants explain only a small part of the disease heritability and thus, we expect that many new variants are still to be found. The impact of Copy-Number Variation (CNV) in the genetic mechanism of RLS is still unknown. However, many studies have recently position the CNVs as a significant source of genetic variation potentially responsible of phenotypes. In collaboration with a team from Munich, we conducted two genome-wide CNVs studies (Genome Wide SNP chips and Comparative Genomic Hybridization (CGH)) on RLS patients from Germany. Using cases-controls studies, we identified regions with a different occurrence of CNVs for RLS patients, compared to different groups of controls. One of these regions is particularly interesting, as it has already been identified by both linkage and association studies.

La malformation de Chiari type 1 (MCI) est une anomalie congénitale de la jonction cranio-cérébrale fréquente avec une incidence de 1:1280. MCI est caractérisée par la descente des amygdales cérébelleuses à travers le foramen magnum et est souvent associée à la syringomyélie. Les causes de cette maladie semblent être multifactorielles incluant des facteurs génétiques. La MCI est similaire à une malformation fréquente chez la race des Griffon Bruxellois (GB) connue sous le nom de Malformation Chiari-like (MCL). Le modèle canin offre l’avantage d’une forte homogénéité génétique réduisant ainsi la complexité de la maladie et facilitant l’identification d’un locus causatif. Une étude d’association du génome entier sur une cohorte de 56 GB suivie d’une cartographie fine sur une cohorte de 217 GB a identifié un locus fortement associé à la MCL sur le chromosome 2 (22 SNPs, valeur P= 7 x 10-8) avec un haplotype de 1.9 Mb plus fréquent chez les non affectés. Une seconde étude d’association du génome entier sur une cohorte de 113 GB a permis d’identifier un 2 ème locus fortement associé à la MCL sur le chromosome 13 (25 SNPs , valeur P= 3 x 10 -7) avec un haplotype de 4 Mb surreprésenté chez les non affectés. Ces régions candidates constituent la première étape vers l’identification de gènes causatifs pour la MCL. Notre étude offre un point d’entrée vers une meilleure compréhension des mécanismes moléculaires sous-tendant la pathogénèse de la MCI humaine. / Chiari I malformation (CMI) represents a common congenital abnormality of the craniocerebral junction with an estimated incidence of 1 in 1280. CMI is characterized by a descent of the cerebellar tonsils into the foramen magnum, often in association with syringomyelia. The developmental defect in CMI is thought to be the result of an underdeveloped occipital bone and small posterior fossa. The etiology of CMI is thought to be multifactorial involving genetic factors. CMI in humans is similar to a condition in the dog called Chiari-like malformation (CM) that is particularly common in the Griffon Bruxellois (GB) breeds. A genome wide association study on a 56 GB cohort followed by a fine mapping in a 217 GB cohort have identified a locus on chromosome 2 that was strongly associated with CM (22 SNPs, P value= 7 x 10-8). Haploview analysis of this locus identified a haplotype of 1.9 Mb that was more frequent in non-affected dogs. A second genome wide association study in a 113 GB cohort lead to the identification of another locus on chromosome 13 that was strongly associated with CM (25 SNPs , P value= 3 x 10-7). Analysis of this region identified a 4Mb haplotype that was more frequent in non-affected dogs. Our study constitutes the first essential step towards identification of the causative genes in CM. Our study provides an entry point for better understanding of the molecular genetic mechanisms underlying the pathogenesis of human CMI.