Browsing by Author "Arnold, Paul Daniel"

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    Examining the Relationship Between Obsessive-Compulsive Symptoms, Genetic Risk and Cortical Thickness in Youth
    (2019-09-04) Corrigan, Kimberly; Arnold, Paul Daniel; MacMaster, Frank P.; Harris, Ashley D.; Dimitropoulos, Gina
    Obsessive-compulsive disorder (OCD) is a disabling neuropsychiatric disorder that affects approximately 1-3% of the population worldwide. One-third to one-half of individuals with OCD have symptom onset before 15 years of age. The heterogeneous clinical expression of OCD has rendered inconsistent findings from structural imaging studies with small sample sizes. Large scale structural imaging studies are needed to better understand the complicated neurobiology of OCD in child and adolescent population. To assess brain structure, magnetic resonance imaging (MRI) was used. FreeSurfer (Version 6.0) recon-all pathway was used to determine cortical thickness. The cingulate cortex, orbitofrontal cortex and insular cortex were selected as regions of interest. A candidate gene analysis of PTPRD SNP rs7856850 was performed using Illumina Multi-Ethnic Global microarray. Obsessive-compulsive symptom severity was determined using the Child Behaviour Checklist Obsessive-Compulsive Scale (CBCL-OCS). A significant relationship was found between the current CBCL-OCS score and the right posterior cingulate. Increase in symptom severity on the current CBCL-OCS predicted an increase in cortical thickness of the right posterior cingulate. Rs7856850 genotype did not significantly modify the relationship between symptom severity and right posterior cingulate thickness. This a unique large scale pediatric imaging study investigating the association between obsessive-compulsive symptoms and cortical thickness with an additional exploration of a PTPRD SNP variant. The results support the concept that the posterior cingulate is involved in the pathophysiology of OCD. The candidate gene analysis was inconclusive but hopefully, this study will encourage more research in the neurobiology of youth OCD.
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    Novel stabilized models to characterize gene-gene interactions by utilizing transcriptome data
    (2022-09-28) Kossinna, Thalagala Kossinnage Pathum Subhashana; Long, Quan; Zhang, Qingrun; Arnold, Paul Daniel; De Leon, Alexander
    Machine learning models employed in genetics often grapple with issues related to the "curse of dimensionality". Furthermore, due to the inherent noisy nature of most -omics data, most methods suffer from the problem of "stability": i.e., even slight perturbations of the original data may result in wholly different outcomes. This becomes particularly true when dealing with interactions as the number of potential interactions are usually astronomical. In this thesis, we present two novel methods: 1) Stabilized COre gene and Pathway Election (SCOPE) and 2) Interaction Bridged Association Study (IBAS) that uses two differing approaches in analyzing biological interactions. SCOPE employs a stabilized form of the LASSO that is better able to handle highly correlated expression data and a co-expression network analysis that identifies "core" genes that may be of interest as well as the underlying biological pathways or mechanisms by which they interact. Stabilizing these results across six cancers of The Cancer Genome Atlas uncovered hallmark cancer pathways as well as a novel potential therapeutic target of kidney cancer, CD63. IBAS utilizes a "data-bridge" composed of dimensionality reduced pathway level interactions of the transcriptome to identify genes associated with a phenotype of interest using the Sequence Kernel Association Test (SKAT), in a disentangled form of the Transcriptome Wide Association Study. Application to the Wellcome Trust Case Control Consortium reveals novel gene candidates with literature reviews highlighting their potential for further study. In conclusion, we have developed two novel methodologies in analyzing complex interaction patterns in -omics data using stabilized machine learning methods, paving the way to further understand the biological interactions underlying complex disease.
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    Predictors of Response to Repetitive Transcranial Magnetic Stimulation Treatment in Adolescent Major Depressive Disorder
    (2018-04-27) McLellan, Quinn Kenneth; MacMaster, Frank P.; Arnold, Paul Daniel; Bulloch, Andrew G. M.
    Adolescent major depressive disorder has limited treatment options and response is unpredictable. Repetitive transcranial magnetic stimulation (rTMS) is a novel treatment option while pre-treatment cortical thickness may be an objective biomarker predictive of response. Twenty-three youth (12-21 years; 11 female) with treatment-resistant depression (TRD) underwent 3 weeks of high-frequency rTMS. Baseline left rostral middle frontal gyrus (lRMF) thickness was compared between eventual responders, non-responders and age-matched controls (n=16; 10 female). Symptom-specific treatment response, defined as ≥50% symptom reduction, was evaluated. Demographic and symptom profile differences were explored. Interventional rTMS alleviated both anxious and depressive symptoms. lRMF was thinner in responders than non-responders, and age negatively correlated with lRMF thickness in controls but not TRD subjects. Exploration of demographic and symptom variables showed responders on the depressive measure had greater frequency of past suicide attempts and higher atypical symptom cluster score while social phobia was associated with non-responsiveness.