Zugl.: Tübingen, Universiẗat, Diss., 2009.

A Dissertation submitted to the Faculty of Medicine in part fulfilment of the requirements for the Degree of Master of Medicine in Psychiatry at the University of the Witwatersrand. / The motivation for undertaking this study stems from the confusion that reigns in the literature regarding the relationship between personality, personality traits and dysthymic disorder. A large body of theorists ancl researchers still claim a definite association between dysthymia and personality. Their views arose to an extent from the concept of dysthymia as it developed through the past few decades. Dysthymia grew out of the concept of depressive neurosis which had a stronger basis in personality pathology. other terms like neurotic depression and depressive reaction preceded depressive neurosis. with the advent of DSM-III and DSM-III-R, dysthymia was moved from the neuroses to the mood disorders category. The DSM-IV Mood Disorders Work Group has also reinforced the classification of dysthymia with mood disorders. The Work Group has embarked on research to determine the symptomatology that should be used for the diagnosis of dysthymia. It is proposed that cognitive, functional and vegetative symptoms be included in DSM-IV to further entrench dysthymia as an affective disorder and extricate it from the personality disorders. / Andrew Chakane 2018

For complex traits, population genetic studies ask: to what extent do genetic variation and environmental variation influence, determine and predict phenotypic variation? More specifically, researchers ask two questions. First, how much of the phenotypic variation is genetic in origin? Second, if the genetic component of a trait has been ascertained, then by what mechanisms do the causal variants contribute to the genetic variation that impacts on the phenotype? Previous studies have indicated a polygenic structure for many complex traits, which means that the genetic variation in those traits is the result of the cumulative effect from hundreds or even thousands of genetic variants. To further decipher the polygenic genetic architecture of a complex trait, genetic studies aim to identify the number, the location in the genome, and the distribution of the effect sizes of causal variants, as well as their individual and interacting effects. Linkage analysis and genome-wide association studies (GWAS), either based on single variants or sets of variants categorized by functional annotations, can be applied to map the potentially causal variants in the genome. The identification of disease-associated loci, however, is only the starting point in identifying causal variants. Causal variants are usually difficult to distinguish from the large number of variants in linkage disequilibrium (LD) within the associated loci, and may be in incomplete LD with genotyped variants. Computational prediction integrated with multi-level ‘Omic’ data will help the prioritization of candidate causal variants, which then become important targets for experimental validation (Chapter 1). Major depressive disorder (MDD) is a complex trait, contributes the second most important burden to global disease. Both genetic and environmental components have been suggested for this disorder in previous studies, although a clear partitioning of the contribution of each component and the identification of major contributing components is yet to be achieved. In efforts to map causal genetic variants, genome-wide association studies of MDD have identified few significant associations so far. The polygenic architecture combined with the widespread clinical and genetic heterogeneity of MDD between populations may impede the identification of causal variants (Chapter 2). In this thesis, I will present three studies; the first study estimated the proportions of the phenotypic variation that are genetic or familial environmental in origin in two depression definitions(chapter 3), followed by two studies where distinct (non- GWAS) methods were used to identify candidate causal genetic variants for MDD (chapter 4,5). In detail, in chapter 3, a variance component analysis was applied to GS:SFHS (Generation Scotland: Scottish Family Health Study) to investigate the relative genetic and environmental contributions to diagnosed major depressive disorder (MDD) and self-declared depression (SDD). Models for MDD and SDD that simultaneously included genetic and environmental effects suggested that narrow-sense heritability could be inflated by the environments shared by nuclear family members. The most parsimonious models selected for both MDD and SDD included SNP and pedigree-associated genetic effects and the effect of the common environment of couples. In chapter 4, I integrated pathway analysis and multi-level regional heritability analyses in a pipeline designed to identify MDD-associated pathways. The pipeline was applied to two independent GWAS studies (GS:SFHS and PGC1-MDD). The NETRIN1 signalling pathway showed the most consistent association with MDD across the two samples. Polygenic risk scores (PRSs) from this pathway showed predictive accuracy better than whole-genome PRSs when using AUC statistics, logistic regression and the linear mixed model. In chapter 5, genome-wide Haplotype-block-based regional heritability mapping (HRHM) was applied to identify haplotype blocks significantly contributing to MDD. A haplotype block across a 24kb region within the TOX2 gene reached genotype-wide significance in GS:SFHS. Single-SNP and haplotype based association tests were used to localize the association signal within the region identified by HRHM, and demonstrated that five out of nine genotyped SNPs and two haplotypes were significantly associated with MDD. The results were replicated in the UK-Ireland group in PGC2-MDD. The brain expression of TOX2 and brain-specific LncRNA RP1-269M15.3 were also significantly regulated by MDD-associated SNPs within the identified haplotype block. The three studies highlight the value of the application of multiple population genetics and bioinformatics methods to multiple family-based and population-based cohorts in identification of risk factors for MDD.

Thesis (Ph. D.)--University of Texas at Austin, 2001. / Vita. Includes bibliographical references. Available also from UMI/Dissertation Abstracts International.

Thesis (Ph. D.)--University of Texas at Austin, 2002. / Vita. Includes bibliographical references. Available also from UMI Company.

abstract / Psychiatry / Master / Master of Philosophy

Not available / text

Not available / text

One approach to the clinical problem of defining the neural substrates of human depressive disorders is to model discrete aspects of affective psychopathology in animals. Two major methodological problems have hindered the development of valid animals models of depression. First, individual responses to the manipulations commonly used to model depression are highly variable. Second, reliable and valid measures of hedonic state remain elusive. This thesis describes experimental work which addresses these methodological concerns. Selective breeding based on individual responses to cholinergic challenge has resulted in a putative genetic model of depression, the <I>Flinders Sensitive Line hypercholinergic rat</I> (FSL). An examination of the affective status of the FSL described in this thesis confirms that selective breeding can generate interesting behavioural and neurochemical phenomena, but does not support the FSL's validity as a model of anhedonia. Problems of measurement of hedonic responsivity are considered both in the description of a novel dependent measure derived from an operant food reward paradigm; and also in an evaluation of the reliability and validity of standard measurement techniques employed with the '<I>chronic unpredictable mild stress model</I>' (CMS) of anhedonia. Initial validating studies suggest that the food reward paradigm may represent a useful method for assessment of affective state. Manipulation of environmental stimuli to induce CMS led to a partial replication of the target behavioural phenomena. However, the effects were not independent of metabolic consequences that seriously confound the interpretation of experiments employing this procedure. It is concluded that future advances in the development of valid models of depression will require a shift of emphasis towards combined manipulations of genetic predisposition and of specific critical environmental stimuli.

Diss. Univ. Zürich, 2003. / Online-Datei+Arbeitsbericht (17 Bl.)+die einzelnen Seiten der Homepage in ausgedruckter Form.