Due to a lack of a gold standard objective marker, the current practice for diagnosing neuropsychiatric disorders is mostly based on clinical symptoms, which may occur in the late stage of the disease. Clinical diagnosis is also subject to high variance due to between- and within-subject variability of patient symptomatology and between-clinician variability. Effectively modeling disease course and making early predictions using biomarkers and subtle clinical signs are critical and challenging both for improving diagnostic accuracy and designing preventive clinical trials for neurological disorders. Leveraging the domain knowledge that certain biological characteristics (i.e., causal genetic mutation, cognitive reserve) are part of the disease mechanism, we first propose a nonlinear model with random inflection points depending on subject-specific characteristics to jointly estimate the trajectories of the biomarkers. The model scales different biomarkers into comparable progression curves with a temporal order based on the mean inflection point. Meanwhile, it assesses how subject-specific characteristics affect the dynamic trajectory of different markers, which offers information on designing preventive therapeutics and personalized disease management strategy. We use EM algorithm for the estimation. Extensive simulation studies are conducted. The method is applied to biomarkers in neuroimaging, cognitive, and motor domains of Huntington’s disease. Under the same nonlinear random effects model framework, we propose the second model inspired by the neural mass models. Biomarkers are modeled as the average manifestation of the functioning status of neuronal ensembles. A latent liability score is shared across biomarkers to pool information. We use EM algorithm for maximum likelihood estimation, and a normal approximation is used to facilitate numerical integration. The results show that some neuroimaging biomarkers are early signs of the onset of Huntington’s disease. Finally, we develop an online tool that provides the personalized prediction of biomarker trajectory given the medical history and baseline measurements. The third model uses a dynamical system based on differential equations to model the evolution of biomarkers. The dynamical system is not only useful to characterize the temporal patterns of the biomarkers, but also informative of the interaction among the biomarkers. We propose a semiparametric dynamical system based on multi-index models. For estimation and inference, we consider a two-step procedure based on the integral equations from the proposed model. The algorithm iterates between the estimation of the link function through splines and the estimation of the index parameters, allowing for regularization to achieve sparsity. We prove the model identifiability and derive the asymptotic properties of the model parameters. A benefit of the model and the estimation approach is to pool information from multiple subjects to construct the network of biomarkers and provide inference. We demonstrate the empirical improvement over competing approaches with the simulated gene expression data from the third DREAM challenge. It is applied to the electroencephalogram (EEG) data and it reveals different effective connectivity of brain networks for patients with alcohol dependence under different cognitive tasks.

Translocator Protein 18 kDa (TSPO) is a protein that is expressed at low levels in the brain, but upon brain injury or inflammation, increases its expression in the areas of the brain specific to injury. In this way, TSPO can be used as a biomarker of brain inflammation and injury. TSPO is primarily expressed in two cell types, microglia and astrocytes, and is used as a marker of reactive gliosis in various brain pathologies. Currently, there is a paucity of knowledge on the function(s) of TSPO in glial cells. Recent studies using conditional and global TSPO knockout mice have questioned the role of TSPO in translocating cholesterol across the outer mitochondrial membrane as the first step in steroidogenesis. In the brain, microglia and astrocytes exhibit distinct spatial and temporal patterns of TSPO upregulation. These differential patterns are not well characterized across disease models and in particular, are poorly characterized in the early stages of disease, prior to behavioral and clinical disease manifestations. Importantly, these distinct patterns of TSPO upregulation may indicate different functions of TSPO in microglia and astrocytes. We examined TSPO levels in a neurodegenerative transgenic mouse model of Sandhoff disease (SD) and longitudinally compared TSPO levels to behavioral manifestations of disease and other neuropathological endpoints (neurodegeneration, reactive gliosis, ganglioside accumulation). This study confirmed TSPO upregulation prior to neurodegeneration in a brain region-dependent and disease course-dependent way. In brain regions with increased TSPO levels, there was a differential pattern of glial cell activation with astrocytes being activated earlier than microglia during the progression of disease. Immunofluorescent confocal imaging confirmed that TSPO colocalizes with both microglia and astrocyte markers, but the glial source of the TSPO response differs by brain region and age in SD mice. We next wanted to gain insight into the function of TSPO in microglia. We previously demonstrated that TSPO ligands (TSPO-L) (1-100 nM) induced intracellular ROS production which was abrogated by NADPH oxidase (NOX2) inhibitors, thereby indicating an association between TSPO and NOX2. To further elucidate the relationship between TSPO and NOX, we determined the source of ROS production resulting from microglia exposure to TSPO-L. Intracellular and extracellular ROS production was inhibited by NOX inhibitors, but not by a mitochondria permeability transition pore inhibitor, indicating that the source of ROS production is from NOX and not from mitochondria. These findings were confirmed using the mitochondria specific ROS probe MitoSOX. To further explore the TSPO-NOX2 association, we used 3 molecular approaches to examine protein-protein interactions under unstimulated or stimulated conditions (100 ng/mL lipopolysaccharide (LPS) for 18 hours) in primary microglia. 1) Co-immunoprecipitation (co-IP) revealed that the NOX2 subunits, gp91phox (gp91) and p22phox (p22), co-IP with TSPO supporting a protein-protein interaction. TSPO’s association with gp91 and p22 decreased with activation, but TSPO’s association with VDAC, a mitochondrial protein, remained constant. These findings suggest that microglia activation changes the dynamics of the TSPO-NOX2 interaction. 2) Confocal imaging and colocalization analysis of TSPO/gp91 or TSPO/p22 immunofluorescence confirmed that TSPO colocalizes with both NOX subunits. Under stimulated conditions, TSPO associated with gp91 and TSPO associated with p22, exhibit significantly decreased colocalization with VDAC suggesting a movement from the mitochondria to other cellular compartments. 3) Duolink Proximity Ligation Assay confirmed that TSPO interacts with p22, gp91 and VDAC. Our results suggest a novel TSPO-gp91-p22 interaction with VDAC in primary microglia that is disrupted by microglia activation and may be involved with redox homeostasis with significant implications for a new understanding of TSPO glial cell biology. In summary, the present studies have strengthened the use of TSPO as a preclinical biomarker, confirmed its specific spatiotemporal upregulation in two cell types and have provided a new potential function of TSPO in microglia that has the possibility to revolutionize the TSPO field and to inform neurotoxicity assessments and neurological disease treatments.

Precision medicine represents a shift in medicine where large datasets are gathered for massive patient groups to draw correlations between disease cohorts. An individual patient can then be compared to these large datasets to determine the best treatment strategy. While electronic health records and next generation sequencing techniques have enabled much of the early applications for precision medicine, the human genome only represents a fraction of the information present and important to a person’s health. A person’s proteome (peptides and proteins) and glycome (glycans and glycosylation patterns) contain biomarkers that indicate health and disease; however, tools to detect and analyze such biomarkers remain scarce. Thus, precision medicine databases are lacking a major source of phenotypic data due to the absence of available methods to explore these domains, despite the potential of such data to allow further stratification of patients and individualized therapeutic strategies. Available methods to detect non-nucleic acid biomarkers are currently not well suited to address the needs of precision medicine. Mass spectrometry techniques, while capable of generating high throughput data, lack standardization, require extensive preparative steps, and have many sources of errors. Immunoassays rely on antibodies which are time consuming and expensive to produce for newly discovered biomarkers. Aptamers, analogous to antibodies but composed of nucleotides and isolated through in vitro methods, have potential to identify non-nucleic acid biomarkers but methods to isolate aptamers remain labor and resource intensive and time consuming. Recently, microfluidic technology has been applied to the aptamer discovery process to reduce the aptamer development time, while consuming smaller amounts of reagents. Methods have been demonstrated that employ capillary electrophoresis, magnetic mixers, and integrated functional chambers to select aptamers. However, these methods are not yet able to fully integrate the entire aptamer discovery process on a single chip and must rely on off-chip processes to identify aptamers. In this thesis, new approaches for aptamer selection are developed that aim to integrate the entire process for aptamer discovery on a single chip. These approaches are capable of performing efficient aptamer selection and polymerase chain reaction based amplification while utilizing highly efficient bead-based reactions. The approaches use pressure driven flow, electrokinetic flow or a combination of both to transfer aptamer candidates through multiple rounds of affinity selection and PCR amplification within a single microfluidic device. As such, the approaches are capable of isolating aptamer candidates within a day while consuming <500 µg of a target molecule. The utility of the aptamer discovery approach is then demonstrated with examples in precision medicine over a broad spectrum (small molecule to protein) of molecular targets. Seeking to demonstrate the potential of the device to generate probes capable of accessing the human glycome (an emerging source of precision medicine biomarkers), aptamers are isolated against gangliosides GM1, GM3, and GD3, and a glycosylated peptide. Finally, personalized, patient specific aptamers are isolated against a multiple myeloma patient serum sample. The aptamers have high affinity only for the patient derived antibody.

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Both small molecules and antibodies are powerful tools for research in biological mechanisms and therapeutics. The discovery of such molecules involves two opposite starting points: one being specific targets and the other being phenotypic screens. The first part of this thesis focuses on drug development starting with a specific target. The second part of this thesis focuses on identification of ferroptosis biomarkers by phenotypic screen. The specific target highlighted in the first part of this thesis is KRAS (Kirsten rat sarcoma viral oncogene homolog), the most commonly mutated
 oncogene in human pancreatic cancers, colorectal cancers, and lung cancers. The high prevalence of KRAS
mutations and its prominent role in many cancers make it a
potentially attractive drug target; however, it has been difficult
 to design small molecule inhibitors of mutant K-Ras proteins. Here, we identified a putative small molecule binding site on
K-RasG12D, which we have termed the P110 site (due to its adjacency to proline 110), using computational analyses of the protein structure. We then confirmed that one compound, named K-Ras Allosteric Ligand KAL-21404358, might bind to the P110 site of K-RasG12D using a combination of computational
 and biochemical approaches. The phenotypic screen used in the second part of this thesis focus on the process of ferroptosis, a form of regulated cell death process driven by the iron-dependent accumulation of polyunsaturated-fatty-acid-containing phospholipids (PUFA-PLs). Currently, there is no way to selectively stain ferroptotic cells in tissue sections to characterize relevant models and diseases. To circumvent this problem, we immunized mice with membranes from diffuse large B Cell lymphoma (DLBCL) cells treated with piperazine erastin (PE), and screened the generated monoclonal antibodies. The results suggested that for the first time we could detect cells undergoing ferroptosis in human tissue sections. In summary, these two projects illustrate how molecular screening and design starting from either a specific target or a phenotype screen aid in drug and biomarker development.

The physiologically important free radicals, nitrogen monoxide and superoxide, can combine to form the reactive intermediate peroxynitrite. Peroxynitrite can react with proteins and their constituent amino acids, such as tyrosine, resulting in protein peroxidation, oxidation and nitration. The nitration of proteins, assessed by the analysis of 3-nitrotyrosine, is a proposed index of pathophysiological activity of peroxynitrite. The aim of the work was to investigate the reaction products between peroxynitrite and protein, develop an assay for 3-nitrotyrosine and measure its levels in biological samples. To study the amino acid products arising from the reaction of peroxynitrite and protein, both liquid chromatography (LC) and gas chromatography (GC) combined with mass spectrometry (MS) were adopted. Approaches to 3-nitrotyrosine assay development were first, to take advantage of the intrinsic sensitivity of electron capture negative ionization GC-MS. Secondly, to avoid possible artefactual problems associated with the derivatisation step in GC-MS, an assay for 3-nitrotyrosine based on combined LC-MS-MS was developed. When a selection of peptides was exposed to peroxynitrite under physiological conditions in vitro, the hydrolysis products showed that 3-nitrotyrosine was the major product. Detectable minor products were 3,5-dinitrotyrosine and DOPA. The GC-MS assay was found to be fraught with difficulty due to artefactual formation of 3-nitrotyrosine. In order to quantify and correct for artefact formation, this complication was approached by incorporating a second isotopomer. This method, however, was confounded by large errors that reduced the overall sensitivity. Either negative or zero levels of endogenous 3-nitrotyrosine were found in tested samples after correction for artefact formation. The LC-MS-MS assay was then used to analyse 3-nitrotyrosine levels in a range of biological samples, including human plasma from healthy volunteers, synovial fluid samples from arthritis patients and tissue extracts from a mouse model of amyotropic lateral sclerosis. In contrast to published data, 3-nitrotyrosine levels were found to be below the limit of detection (1 pg/????L, 10 pg o/c) for all samples - a result somewhat consistent with the negative GC-MS data. It is suggested that the high 3-nitrotyrosine levels previously reported in the literature might reflect artefactual generation of 3-nitrotyrosine and that other approaches to assessing pathophysiological nitration should be sought in future.

My thesis research has examined the fatty acid composition of serum triacylglycerol, phospholipid and cholesterol ester in 2793 participants who took part in the 1997 National Nutrition Survey - a national population-based survey of New Zealand adolescents and adults aged or [greater than or equal to]̲15 y. Differences in serum fatty acids by sex, age, ethnicity, body mass index and smoking - independent of dietary fat intake - were determined. Serum fatty acids were used as biomarkers of saturated and polyunsaturated fat intake to predict population serum total cholesterol concentrations. The association between n-3 long-chain polyunsaturated fatty acids in serum phospholipid and mental and physical wellbeing, as assessed by the short form-36, was determined. Serum fatty acids have been used as biological markers of fat intake and to predict the risk of disease. The fatty acid composition of serum triacylglycerol, phospholipid and cholesterol ester is subject to alteration by dietary fat but overall, is largely controlled by metabolic enzymes. Non-dietary variables - sex, age, body mass index or cigarette smoking - may influence the activity of these enzymes, which will subsequently alter the fatty acid composition but the extent to which these affect serum fatty acid composition in the general population is poorly understood. Our results showed that the proportion of docosahexaenoic acid in serum phospholipid and cholesterol ester was significantly greater in women by 0.15 and 0.02 mol%, respectively in comparison to men whereas, the proportion of eicosapentaenoic acid was significantly greater in men by 0.08 and 0.1 mol%, respectively, after adjusting for age, ethnicity, body mass index and smoking. A number of differences in the proportion of palmitoleic acid in serum triacylglycerol, phospholipid and cholesterol ester were detected; palmitoleic acid increased across the age categories in women (15-24, 25-44, 45-64 65+ y), was higher in women compared to men, New Zealand Europeans compared to New Zealand Maori and Pacific People, those with a body mass index or [greater than or equal to] 30 kg/m� compared to those with a body mass index < 25 kg/m� and in current smokers in comparison to non-smokers. In women, there was an inverse trend in the proportion of linoleic acid in serum phospholipid and cholesterol ester across the age categories. The proportion of linoleic acid in serum triacylglycerol, phospholipid and cholesterol ester was lower in smokers by 2.19, 1.04 and 0.75 mol%, respectively in comparison to non-smokers. None of these differences could be explained by a difference in dietary fat intake. Consequently, sex appears to affect the metabolism of n-3 long-chain polyunsaturated fatty acids independent of dietary fat intake and metabolic differences associated with age, body mass index and smoking may be at play for a number of other serum fatty acids notably, palmitoleic and linoleic acids. Evidence for a role of dietary fat as a predictor of serum cholesterol concentrations in the general population is conflicting. On one hand, results from cholesterol-lowering dietary intervention trials show unequivocally that decreasing saturated fat intake produces a meaningful reduction in serum cholesterol concentrations. On the other hand, the results of large observational studies show little association between saturated fat intake and cholesterol concentrations. The lack of association in the latter studies may result from errors in dietary assessment and therefore, using serum fatty acids as biomarkers of fat intake may overcome the limitations associated with typical dietary assessment techniques. Participants were divided into quintiles of increasing proportion of serum fatty acids. Each one SD increase in the myristic acid composition of serum cholesterol ester, triacylglycerol and phospholipid was associated with an increase in cholesterol of 0.19, 0.10 and 0.13 mmol/L, respectively after adjusting for confounding variables. The difference in cholesterol concentrations between those categorised into the highest and lowest quintiles of serum cholesterol ester myristate was 0.48 mmol/L. A one SD increase in the linoleic acid composition of serum cholesterol ester, triacylglycerol and phospholipid corresponded to a decrease in cholesterol of 0.07, 0.05 and 0.07 mmol/L, respectively. The difference in cholesterol concentrations between the 1st and 5th quintiles of serum cholesterol linoleate was 0.18 mmol/L. Intake of saturated and polyunsaturated fats, as measured using serum fatty acids, are important determinants of cholesterol concentrations in New Zealanders. It has been hypothesised that a lower intake of n-3 long-chain polyunsaturated fatty acids, largely of marine origin, is implicated in the aetiology of depressive disorder. Results from the majority of observational studies have shown that depressed participants have a lower proportion of eicosapentaenoic or docosahexaenoic acid in phospholipids compared to controls but evidence for an improvement in depressive symptoms after supplementation with n-3 long-chain polyunsaturated fatty acids is conflicting. There is little known about the role that n-3 long-chain polyunsaturated fatty acids may have as predictors of mental wellbeing in the general population. Participants were categorised into quintiles of increasing n-3 long-chain polyunsaturated fatty acids in serum phospholipid. There was no significant trend in self-reported mental wellbeing - the mental component score - across the quintiles of eicosapentaenoic, docosapentaenoic and docosahexaenoic acids or the sum of these three fatty acids after adjusting for confounding variables. There was a significant trend in the mental component score across the quintiles of the ratio of eicosapentaenoic/arachidonic acid; the difference between the highest and the lowest quintile was 6.6 points. There were significant positive trends in self-reported physical health - the physical component score - across the quintiles of eicosapentaenoic and docosapentaenoic acids as well as the ratio of eicosapentaenoic/arachidonic acid ratio; the difference between the 1st and 5th quintiles were 8.6, 6.0 and 8.9 points, respectively. Overall, there appears to be little association between the n-3 long-chain polyunsaturated fatty acid composition of serum phospholipid and self-reported mental health in a population of low fish consumers; however, the proportion of n-3 long-chain polyunsaturated fatty acids may be an important predictor of physical wellbeing in New Zealanders.

Graduation date: 1995