1,721,070 research outputs found
Genotype and phenotype relationships in neurodevelopmental disorders
Full text linkNeuroDevelopmental Disorders (NDDs) are a group of heterogeneous neuropsychiatric conditions, encompassing Developmental Delay (DD), Intellectual Disability (ID), Autism Spectrum Disorder (ASD) and Gilles de la Tourette Syndrome (GTS). NDDs often involve a life-long need of supportive services and represent a major economic and societal burden in Europe and the United States. Hitherto, no safe and effective treatment strategies are available, underpinning the urgency of deciphering their elusive aetiology.
NDDs have a strong genetic component. Accordingly, the mechanistic understanding of disease involves (1) the description of mutational landscapes, (2) the molecular and cellular of characterisation of genetic variants and (3) their integration at circuit and system levels. In this thesis, we tackled these theoretical underpinnings to provide insights into the genetics of NDDs and the onset of associated clinical abnormalities.
Firstly, aiming to shape the genetic architecture of GTS, a condition characterised by the presence of motor and vocal tics, we undertook a whole-genome CNV study of a cohort of Danish GTS cases and healthy controls. Using statistical and functional genomics approaches, we proposed novel potential candidate genes and implicated the disruption of early neurodevelopmental and late synaptic processes in the aetiology of GTS.
Secondly, to elucidate the vast phenotypic heterogeneity of NDDs, we conducted a systematic investigation of genotype and phenotype relationships in DD, ID and ASD. Taking advantage of extensive phenotypic and genetic data available for DD/ID and ASD patients, we grouped individuals based on their functional rare CNV and gene disruptions but did not to identify distinguishing clinical archetypes. Instead, we showed converging molecular perturbations underlie the onset of globally more similar clinical presentations and investigated the role of common variants in modulating their expressivity.
Lastly, we established the relevance of mouse models in the study of human disease. By applying comprehensive genomics approaches to over 1,000 mouse neuroanatomical knockouts, we implicated early neurodevelopmental and adult synaptic processes in the aetiology of ID and brain malformations. Furthermore, we showed that functionally converging genetic disturbances translate at the phenotypic level and proposed novel candidate ID genes.</p
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Identifying causative elements within structural variants associated with developmental disorders
Full text linkIt has been well established that copy number variation contributes substantially to genetic variation within human populations. However, the extent to which de novo and inherited copy number variants (CNVs) underlie human disease is not well known. In this thesis, I investigate the role of de novo and inherited CNVs in a wide range of developmental abnormalities. First, I compare disease associated and apparently benign CNVs for structural differences, with the aim of identifying distinguishing features of disease causing CNVs. I identified significant enrichments of protein-coding genes, protein-coding genes associated with disease in OMIM and miRNAs amongst disease associated disease. Conversely, inherited CNVs observed in healthy individuals show depletions of these features. Following this, I employ functional enrichment approaches to identify the copy number variable genes within these de novo CNVs that contribute to the patient’s developmental abnormalities. I predict candidate genes for 143 different developmental abnormalities, with 65% of the candidate genes not having been previously associated with disease in OMIM. Through examining the distribution of these candidate genes within the patient’s CNVs, I found evidence of extensive pleiotropy and epistasis as well as a small number of simple additive effects. Finally, I extend my analyses to examine the role of inherited CNVs as the underlying cause of human developmental disorders. I implicate inherited CNVs and their overlapping copy number variable genes in the underlying causes of 45 human developmental abnormalities. Additionally, I re-examine the patients possessing both de novo CNVs and inherited CNVs using functional enrichment analyses. I reveal significant enrichments for a greater number of human developmental abnormalities when combining both the de novo and inherited CNVs, suggesting it is de novo mutations in combination with the inherited genomic background that are responsible for many instances of human developmental abnormalities
Perturbed molecular pathways in Parkinson's disease
Full text linkParkinson's Disease (PD) is the most common movement disorder and second most common neurodegenerative disorder, affecting 1 in every 100 people over the age of 60. It is a heterogeneous disorder whose pathology and causes remain incompletely understood. Identification of genetic risk factors can provide valuable understanding of the disease process and pave the way for the development of novel treatment.
Firstly, eQTLs were identified that affected the expression of functionally related PD-linked gene pairs and were within PD associated genomic regions. This was achieved by integrating multiple data sources into a network tailored to PD, then interrogating this in tandem with genome-wide association study and eQTL data. Four eQTLs were identified, two affecting LRRK2. The genotype conferring greatest additive increase in LRRK2 expression was significantly over-represented among two independent case populations but not among controls.
Secondly, Copy Number Variants were classified by their functional annotations to identify common molecular pathways on which PD-linked variation converged. Seven pathways were enriched among PD patients, two of which remained so after independently significant variation within PARK2 was removed. However this was not replicated in an independent cohort.
Thirdly genome-wide association studies were carried out first comparing PD case and control and second comparing phenotypic subtypes among PD cases. Enrichment analysis identified two pathways significantly associated with disease onset and implicated a subset of one with a specific phenotypic subgroup.
Finally, continuous phenotypic variation was analysed. Phenotypic axes were identified each representing multiple co-varying phenotypes. Genome-wide genetic analyses of these identified 10 genomic regions significantly affecting the severity of specific measured phenotypes.
This work implicates genetic variation in mediating both PD onset and phenotypic progression and yields insight into the common molecular pathways that may be involved. A novel method of quantifying patient phenotype was also developed that should facilitate future analysis.</p
Probabilistic modelling of genomic trajectories
Full text linkThe recent advancement of whole-transcriptome gene expression quantification technology - particularly at the single-cell level - has created a wealth of biological data. An increasingly popular unsupervised analysis is to find one dimensional manifolds or trajectories through such data that track the development of some biological process. Such methods may be necessary due to the lack of explicit time series measurements or due to asynchronicity of the biological process at a given time.
This thesis aims to recast trajectory inference from high-dimensional "omics" data as a statistical latent variable problem. We begin by examining sources of uncertainty in current approaches and examine the consequences of propagating such uncertainty to downstream analyses. We also introduce a model of switch-like differentiation along trajectories. Next, we consider inferring such trajectories through parametric nonlinear factor analysis models and demonstrate that incorporating information about gene behaviour as informative Bayesian priors improves inference. We then consider the case of bifurcations in data and demonstrate the extent to which they may be modelled using a hierarchical mixture of factor analysers. Finally, we propose a novel type of latent variable model that performs inference of such trajectories in the presence of heterogeneous genetic and environmental backgrounds. We apply this to both single-cell and population-level cancer datasets and propose a nonparametric extension similar to Gaussian Process Latent Variable Models.</p
Clustering genes by function to understand disease phenotypes
Full text linkDevelopmental disorders including: autism, intellectual disability, and congenital abnormalities are present in 3-8% of live births and display a huge amount of phenotypic and genetic heterogeneity. Traditionally, geneticists have identified individual monogenic diseases among these patients but a majority of patients fail to receive a clinical diagnosis. However, the genomes of these patients frequently harbour large copynumber variants (CNVs) but their interpretation remains challenging. Using pathway analysis I found significant functional associations for 329 individual phenotypes and show that 39% of these could explain the patients’ multiple co-morbid phenotypes; and multiple associated genes clustered within individual CNVs. I showed there was significantly more such clustering than expected by chance. In addition, the presence of a multiple functionally-related genes is a significant predictor of CNV pathogenicity beyond the presence of known disease genes and size of the CNV. This clustering of functionally-related genes was part of a broader pattern of functional clusters across the human genome. These genome-wide functional clusters showed tissuespecific expression and some evidence of chromatin-domain level regulation. Furthermore, many genome-wide functional clusters were enriched in segmental duplications making them prone to CNV-causing mutations and were frequently seen disrupted in healthy individuals. However, the majority of the time a pathogenic CNV affected the entire functional cluster, where as benign CNVs tended to affect only one or two genes. I also showed that patients with CNVs affecting the same functional cluster are significantly more phenotypically similar to each other than expected even if their CNVs do not affect any of the same genes. Lastly, I considered one of the major limitations in pathway analysis, namely ascertainment biases in functional information due to the prioritization of genes linked to human disease, and show how the modular nature of gene-networks can be used to identify and prioritize understudied genes
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Functional genomics analyses of neuropsychiatric and neurodevelopmental disorders
No full textRecent large-scale genome-wide studies for many human disorders have identified associations with numerous genetic variants. The biological interpretation of these variants presents a major challenge. In particular, the identification of biological pathways underlying the association could provide crucial insights into the disease aetiologies. In this thesis, I used functional genomics approaches to increase our understanding of neuropsychiatric and neurodevelopmental disorders. Firstly, in an integrative analysis of autism spectrum disorder (ASD), I looked into the role of genes targeted by Fragile-X Mental Retardation Protein ("FMRP targets"). I found evidence that FMRP targets contribute to ASD via two distinct aetiologies: (1) ultra-rare and highly penetrant single disruptions of embryonically upregulated FMRP targets ("single-hit aetiology") or (2) the combination of multiple less penetrant disruptions of synaptic FMRP targets ("multiple-hit aetiology"). In particular, I developed a pathway-association test sensitive to multiple-hit aetiologies. Secondly, I carried out an integrative analysis of bipolar disorder, following up a previously identified association with long-term potentiation. The association was not consistent across independent SNP and CNV datasets. Thirdly, I addressed the difficulty in identifying functional relationships between genes by integrating different datasets into a gene functional-linkage network tuned to the nervous system ("NsNet"). NsNet identified functional links between the genes disrupted by de novo loss-of-function mutations in ASD and, separately, in schizophrenia probands more sensitively than a general functional-linkage network. Fourthly, I considered the challenge of interpreting the phenotypic impact of gene disruptions, focusing on the identification of haploinsufficient genes. I constructed a gene haploinsufficiency score based on genome-wide datasets. Compared to existing approaches, the new score performed better in identifying less-studied haploinsufficient genes. This work both extends the methodology to detect the contribution of genetic variation to neuropsychiatric disorders and also yields insights into the variant genes and the pathways that underlie them. Firstly, in an integrative analysis of autism spectrum disorder (ASD), I looked into the role of genes targeted by Fragile-X Mental Retardation Protein ("FMRP targets"). I found evidence that FMRP targets contribute to ASD via two distinct aetiologies: (1) ultra-rare and highly penetrant single disruptions of embryonically upregulated FMRP targets ("single-hit aetiology") or (2) the combination of multiple less penetrant disruptions of synaptic FMRP targets ("multiple-hit aetiology"). In particular, I developed a pathway-association test sensitive to multiple-hit aetiologies. Secondly, I carried out an integrative analysis of bipolar disorder, following up a previously identified association with long-term potentiation. The association was not consistent across independent SNP and CNV datasets. Thirdly, I addressed the difficulty in identifying functional relationships between genes by integrating different datasets into a gene functional-linkage network tuned to the nervous system ("NsNet"). NsNet identified functional links between the genes disrupted by de novo loss-of-function mutations in ASD and, separately, in schizophrenia probands more sensitively than a general functional-linkage network. Fourthly, I considered the challenge of interpreting the phenotypic impact of gene disruptions, focusing on the identification of haploinsufficient genes. I constructed a gene haploinsufficiency score based on genome-wide datasets. Compared to existing approaches, the new score performed better in identifying less-studied haploinsufficient genes. This work both extends the methodology to detect the contribution of genetic variation to neuropsychiatric disorders and also yields insights into the variant genes and the pathways that underlie them
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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