In addition to ATP generation, mitochondria are essential in various cellular processes ranging from biosynthetic pathways, apoptosis, cell cycle progression, and calcium buffering. Studies in living cells have now firmly established that mitochondria exist as a dynamic network sculpted by fission and fusion reactions, rather than separated, individual organelles. Not surprisingly, mutations in genes involved in mitochondrial dynamics and quality control lead to human diseases such as Charcot-Marie-Tooth disease type 2A, Optic atrophy, and autosomal recessive Parkinson disease. I have designed a high-throughput protocol to permit genome-wide screening for novel genes that are required for normal mitochondrial morphology. I have executed a genome-wide RNA interference screen and identified several novel genes required for mitochondrial dynamics in addition to known regulators of mitochondrial dynamics. A detailed high-throughput genome-wide screening protocol is presented. I have shown that TID1, a gene identified from the screen, has a dual-role in maintaining the integrity of mitochondrial DNA and preventing the aggregation of complex I subunits. My analysis of the mitochondrial role of TID1 supports the existence of a TID1- mediated stress response to ATP synthase inhibition. The genome screen also identified the novel gene ROMO1 as essential for normal mitochondrial morphology. I have shown that ROMO1 may have an additional role in maintaining mitochondrial spare respiratory capacity, possibly by affecting cellular substrate availability. Finally, in a collaborative effort, we have shown that homozygous mutations in the mitochondrial fusion gene MFN2 lead to multiple symmetric lipomatosis (MSL) associated with neuropathy. Mechanistically, this mutation reduces MFN2 homocomplex formation. Taken together, these results show the utility of genome-wide screening in identifying genes involved in mitochondrial quality control.

Obesity is a major risk factor for multiple common chronic diseases. The prevalence in European countries is high and a significant public health concern. This thesis aims to explore the obesity landscape in the Cooperative Health Research in South Tyrol (CHRIS) study. The first step was to characterise the obese CHRIS population, taking into account the established body mass index (BMI) classification from the World Health Organization (WHO) and looking at metabolically healthy and unhealthy obesity. We investigated the familial aggregation of these traits. We identified several families with significant familial aggregation and observed varying degrees of overlap for these traits in different families. The focus was then on implementing and applying a Genome-Wide Polygenic Score for obese participants. These scores were computed for individuals based on the presence of different genetic variants weighted according to their measured effects in genome-wide association studies (GWAS). We then paid attention to the targeted metabolomics data of the CHRIS study, to identify different serum metabolites associated with metabolically healthy/unhealthy obesity, using logistic regression and random forest methods to explore metabolic signatures to distinguish obesity into metabolically healthy and metabolically unhealthy obesity. Several biomarkers were shown to be related to obesity, many of which confirmed by existing evidence (such as BCAAs, tyrosine, and lysophosphatidylcholines).

Balancing selection refers to the maintenance of multiple phenotypic variants within a population. There are a number of proposed mechanisms explaining the origin and persistence of the evolution and genetics of polymorphisms, but they largely remain unresolved in the specific instances in which they occur. This study aims to identify the genetic basis of a polymorphism in the butterfly, Heliconius doris, which displays four distinct color patterns on the dorsal hindwings of individuals. While Mullerian mimetic theory proposes that phenotypes will converge on a common, aposematic phenotype, this is not the case in Heliconius doris. We identify an interval perfectly associated with the presence/absence of the red ray phenotype, and propose potential mechanisms and genetic architecture through which this polymorphism has been allowed to persist.

No description available.

BACKGROUND:Airway hyperresponsiveness (AHR), a primary characteristic of asthma, involves increased airway smooth muscle contractility in response to certain exposures. We sought to determine whether common genetic variants were associated with AHR severity.METHODS:A genome-wide association study (GWAS) of AHR, quantified as the natural log of the dosage of methacholine causing a 20% drop in FEV1, was performed with 994 non-Hispanic white asthmatic subjects from three drug clinical trials: CAMP, CARE, and ACRN. Genotyping was performed on Affymetrix 6.0 arrays, and imputed data based on HapMap Phase 2, was used to measure the association of SNPs with AHR using a linear regression model. Replication of primary findings was attempted in 650 white subjects from DAG, and 3,354 white subjects from LHS. Evidence that the top SNPs were eQTL of their respective genes was sought using expression data available for 419 white CAMP subjects.RESULTS:The top primary GWAS associations were in rs848788 (P-value 7.2E-07) and rs6731443 (P-value 2.5E-06), located within the ITGB5 and AGFG1 genes, respectively. The AGFG1 result replicated at a nominally significant level in one independent population (LHS P-value 0.012), and the SNP had a nominally significant unadjusted P-value (0.0067) for being an eQTL of AGFG1.CONCLUSIONS:Based on current knowledge of ITGB5 and AGFG1, our results suggest that variants within these genes may be involved in modulating AHR. Future functional studies are required to confirm that our associations represent true biologically significant findings.

Aim The aim of this study was to investigate the most commonly used approaches to measure individual genome-wide heterozygosity (IGWH) and to investigate whether IGWH can be considered as a health risk factor or a protective factor in humans. Methods This study was based on two samples from isolated communities of Croatian Adriatic islands, with a total of 1,930 adult examinees from Islands of Vis (N=986) and Korcula (N=944). Examinees were genotyped with a total of 302,662 single nucleotide polymorphisms. Heterozygosity was estimated using five commonly calculated methods. Results Correlation coefficients between different heterozygosity methods were generally in the range of 0.7-0.8. A worsening in some phenotypic traits, including cholesterol and triglycerides as well as increased odds for osteoporosis and metabolic syndrome was recorded in cases of IGWH reduction. Nevertheless, in these cases heterozygosity explained a relatively low amount of variance, generally in range of 0.4-0.6% of total trait variance. Conclusion However, these results were significant in Vis Island sample, while in the replication sample, Korcula Island, most of the associations were not significant, possibly due to the overall lower amount of inbreeding and higher heterozygosity in Korcula Island sample. The results warrant further research in order to provide more information on the extent and importance of individual genome-wide heterozygosity, which might have an important role in communities which experience consanguinity on a greater scale. Two main shortcomings of the study include possible lack of power to detect inbreeding depression and the need to replicate the results in other populations.

Diet and lifestyle have changed dramatically in the last few decades, leading to an increase in prevalence of obesity, defined as a body mass index >30Kg/m2, dyslipidaemias (defined as abnormal lipid profiles) and type 2 diabetes (T2D). Together, these cardiometabolic traits and diseases, have contributed to the increased burden of cardiovascular disease, the leading cause of death in Western societies. Complex traits and diseases, such as cardiometabolic traits, arise as a result of the interaction between an individual's predisposing genetic makeup and a permissive environment. Since 2007, genome-wide association studies (GWAS) have been successfully applied to complex traits leading to the discovery of thousands of trait-associated variants. Nonetheless, much is still to be understood regarding the genetic architecture of these traits, as well as their underlying biology. This thesis aims to further explore the genetic architecture of cardiometabolic traits by using complementary approaches with greater genetic and phenotype resolution, ranging from studying clinically ascertained extreme phenotypes, deep molecular profiling, or sequence level data. In chapter 2, I investigated the genetic architecture of healthy human thinness (N=1,471) and contrasted it to that of severe early onset childhood obesity (N=1,456). I demonstrated that healthy human thinness, like severe obesity, is a heritable trait, with a polygenic component. I identified a novel BMI-associated locus at PKHD1, and found evidence of association at several loci that had only been discovered using large cohorts with >40,000 individuals demonstrating the power gains in studying clinical extreme phenotypes. In chapter 3, I coupled high-resolution nuclear magnetic resonance (NMR) measurements in healthy blood donors, with next-generation sequencing to establish the role of rare coding variation in circulating metabolic biomarker biology. In gene-based analysis, I identified ACSL1, MYCN, FBXO36 and B4GALNT3 as novel gene-trait associations (P < 2.5x10-6). I also found a novel link between loss-of-function mutations in the "regulation of the pyruvate dehydrogenase (PDH) complex" pathway and intermediate-density lipoprotein (IDL), low-density lipoprotein (LDL) and circulating cholesterol measurements. In addition, I demonstrated that rare "protective" variation in lipoprotein metabolism genes was present in the lower tails of four measurements which are CVD risk factors in this healthy population, demonstrating a role for rare coding variation and the extremes of healthy phenotypes. In chapter 4, I performed a genome-wide association study of fructosamine, a measurement of total serum protein glycation which is useful to monitor rapid changes in glycaemic levels after treatment, as it reflects average glycaemia over 2-3 weeks. In contrast to HbA1c, which reflects average glucose concentration over the life-span of the erythrocyte (~3 months), fructosamine levels are not predicted to be influenced by factors affecting the erythrocyte. Surprisingly, I found that in this dataset fructosamine had low heritability (2% vs 20% for HbA1c), and was poorly correlated with HbA1c and other glycaemic traits. Despite this, I found two loci previously associated with glycaemic or albumin traits, G6PC2 and FCGRT respectively (P < 5x10-8), associated with fructosamine suggesting shared genetic influence. Altogether my results demonstrate the utility of higher resolution genotype and phenotype data in further elucidating the genetic architecture of a range of cardiometabolic traits, and the power advantages of study designs that focus on individuals at the extremes of phenotype distribution. As large cohorts and national biobanks with sequencing and deep multi-dimensional phenotyping become more prevalent, we will be moving closer to understanding the multiple aetiological mechanisms leading to CVD, and subsequently improve diagnosis and treatment of these conditions.

Glycosylation is among the most common post-translational protein modifications. Glycans are complex carbohydrates attached to the surface of many proteins, but are rarely extensively studied in a high-throughput manner. However, there is an increasing evidence of their involvement in various physiological processes and diseases. Glycosylation of Immunglobulin G was shown to be important in adaptive immunity, where it can act as a "safety switch" for different types of the immune response. Although the main enzymes of the glycosylation pathway are known, little is understood about how this template-independent process is regulated to result in a faithful synthesis of a specific glycoform. This question was previously addressed using genome-wide association studies (GWAS) and 9 loci were identified as being significantly associated with IgG N-glycosylation. Only 4 of these loci were the known glycosylation enzymes. An additional five loci were discovered by applying a newly developed multivariate GWAS method on the same dataset. Here, by performing a GWAS on 77 IgG N-glycan traits measured by ultra-performance liquid chromatography in more than 8000 samples from four European cohorts the number of genome-wide significant (p? ≤ 2.4 x 10−9) loci increased to 27, 15 of which are novel, with 6 additional loci being suggestively associated (p? ≤ 2.4 x 10−8). To assess which of the genes from the associated loci are more likely to be regulating IgG glycosylation, different gene prioritising strategies were employed. For 7 loci evidence of a non-synonymous amino acid change was found, two of which were predicted to be deleterious. Evidence of regulation through changes in gene expression levels in B-cells, the cell lineage responsible for production of IgG, was found for 4 genes, with an additional 11 genes exhibiting the same evidence with expression in peripheral blood or other immune cells. For the remaining loci the most likely candidate gene was proposed based on co-expression with genes from the enriched gene-sets or based on a physical proximity to the variant with the strongest association. To narrow down the most important loci for a functional follow-up, the omics nature of this data was used to compare glycome-wide SNP effects and suggest how newly discovered loci form a functional network that regulates the established members of the glycosylation pathway. The potential role of IgG glycosylation in various complex traits and diseases was explored by assessing the pleiotropy of the associated SNPs. The inflation of SNPs related to autoimmune, digestive and neurological diseases was observed in glycosylation SNPs. To assess whether IgG N-glycosylation is likely to share the same causal variant as the identified pleiotropic traits and diseases, regional association patterns were compared using summary data based Mendelian Randomisation analyses. This work demonstrates that an increased sample size empowered the identification of novel loci, enabling further insights into the molecular mechanisms underlying protein glycosylation and its relationship with complex human diseases. It also shows that such analyses of omic traits can assist in creating a functional network of the identified loci, prioritising the most important genes and allowing a more focused approach to future experimental functional follow-up.

Data from a Croatian isolate population are analysed in a genome-wide association study (GWAS) for a variety of disease-related quantitative traits. A novel genomewide approach to analysing pedigree-based association data called GRAMMAR is utilised. One of the significant findings, for uric acid, is followed up in greater detail, and is replicated in another isolate population, from Orkney. The associated SNPs are located in the SLC2A9 gene, coding for a known glucose transporter, which leads to identification of SLC2A9 as a urate transporter too (Vitart et al., 2008). These SNPs are later implicated in affecting gout, a disease known to be linked with high serum uric acid levels, in an independent study (Dehghan et al., 2008). Subsequently, investigation into different ways in which to use SNP data to identify quantitative trait loci (QTL) for genome-wide association (GWA) studies is performed. Several multi-marker approaches are compared to single SNP analysis using simulated phenotypes and real genotype data, and results show that for rare variants haplotype analysis is the most effective method of detection. Finally, the multi-marker methods are compared with single SNP analysis on the real uric acid data. Interpretation of real data results was complicated due to low sample size, since only founder and unrelated individuals may be used for population-based haplotype analysis, nonetheless, results of the prior analyses of simulated data indicate that multi-marker methods, in particular haplotypes, may greatly facilitate detection of QTL with low minor allele frequency in GWA studies.

Stress contributes to the development of major depressive disorder (MDD) and post-traumatic stress disorder (PTSD), and an intermediary factor between stress and psychiatric disorders may be epigenetics. Studies have shown altered DNA methylation (DNAm) in animal models of and humans with stress exposure and in individuals with PTSD and MDD. The availability of genome-wide experimental platforms has given us new tools to investigate DNAm, and in this dissertation these techniques have been used to further our current understanding of the epigenetics of stress. We performed a genome-wide investigation in mice exposed to chronic stress that exhibit depressive- and anxious-like behaviors, examining DNAm changes within the dentate gyrus, a sub-region of the hippocampus that contributes to the stress response. Using the Methyl-Seq method, an intergenic region of chromosome X was shown to be differentially methylated with chronic stress, and this finding replicated in two additional cohorts of mice. In postmortem brain tissue of humans with MDD, an increase in DNAm within this intergenic region was also found. Animal models do not fully capture the complexity of stress and psychiatric disorders in humans, but comparable studies in humans are limited by the difficulty of obtaining brain tissues. Instead, these studies have used peripheral tissues to examine DNAm changes related to stress and psychiatric disorders. To address the usefulness of these peripheral tissues, we employed the Illumina 450K and EPIC arrays to establish a resource that compares DNAm of the brain to that of blood, buccal, and saliva tissues. Glucocorticoids (GCs) play an essential role in the stress response, and their dysregulation is seen in individuals with MDD and PTSD. To determine the role of GCs in stress-mediated epigenetic changes, buccal samples were obtained before and after individuals were given GCs in the context of oral surgery, and DNAm was analyzed using the Illumina EPIC array. Five CpGs were altered following this exposure, to a genome-wide significant degree. Further analysis revealed FDR-significant CpG changes to be in genes involved in steroid hormone biosynthesis and in genes differentially expressed with GC exposure. Collectively, these results exemplify the complexity of DNAm changes associated with the stress response and provide potential avenues for elucidating their impact on psychiatric disorders.