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- Member of: Theses and Dissertations
Description
Alzheimer's Disease (AD) is a progressive neurodegenerative disease accounting for 50-80% of dementia cases in the country. This disease is characterized by the deposition of extracellular plaques occurring in regions of the brain important for cognitive function. A primary component of these plaques is the amyloid-beta protein. While a natively unfolded protein, amyloid-beta can misfold and aggregate generating a variety of different species including numerous different soluble oligomeric species some of which are precursors to the neurofibrillary plaques. Various of the soluble amyloid-beta oligomeric species have been shown to be toxic to cells and their presence may correlate with progression of AD. Current treatment options target the dementia symptoms, but there is no effective cure or alternative to delay the progression of the disease once it occurs. Amyloid-beta aggregates show up many years before symptoms develop, so detection of various amyloid-beta aggregate species has great promise as an early biomarker for AD. Therefore reagents that can selectively identify key early oligomeric amyloid-beta species have value both as potential diagnostics for early detection of AD and as well as therapeutics that selectively target only the toxic amyloid-beta aggregate species. Earlier work in the lab includes development of several different single chain antibody fragments (scFvs) against different oligomeric amyloid-beta species. This includes isolation of C6 scFv against human AD brain derived oligomeric amyloid-beta (Kasturirangan et al., 2013). This thesis furthers research in this direction by improving the yields and investigating the specificity of modified C6 scFv as a diagnostic for AD. It is motivated by experiments reporting low yields of the C6 scFv. We also used the C6T scFv to characterize the variation in concentration of this particular oligomeric amyloid-beta species with age in a triple transgenic AD mouse model. We also show that C6T can be used to differentiate between post-mortem human AD, Parkinson's disease (PD) and healthy human brain samples. These results indicate that C6T has potential value as a diagnostic tool for early detection of AD.
ContributorsVenkataraman, Lalitha (Author) / Sierks, Michael (Thesis advisor) / Rege, Kaushal (Committee member) / Pauken, Christine (Committee member) / Arizona State University (Publisher)
Created2013
Description
Alzheimer's disease (AD) is the most common form of dementia leading to cognitive dysfunction and memory loss as well as emotional and behavioral disorders. It is the 6th leading cause of death in United States, and the only one among top 10 death causes that cannot be prevented, cured or slowed. An estimated 5.4 million Americans live with AD, and this number is expected to triple by year 2050 as the baby boomers age. The cost of care for AD in the US is about $200 billion each year. Unfortunately, in addition to the lack of an effective treatment or AD, there is also a lack of an effective diagnosis, particularly an early diagnosis which would enable treatment to begin before significant neuronal damage has occurred.
Increasing evidence implicates soluble oligomeric forms of beta-amyloid and tau in the onset and progression of AD. While many studies have focused on beta-amyloid, soluble oligomeric tau species may also play an important role in AD pathogenesis. Antibodies that selectively identify and target specific oligomeric tau variants would be valuable tools for both diagnostic and therapeutic applications and also to study the etiology of AD and other neurodegenerative diseases.
Recombinant human tau (rhTau) in monomeric, dimeric, trimeric and fibrillar forms were synthesized and purified to perform LDH assay on human neuroblastoma cells, so that trimeric but not monomeric or dimeric rhTau was identified as extracellularly neurotoxic to neuronal cells. A novel biopanning protocol was designed based on phage display technique and atomic force microscopy (AFM), and used to isolate single chain antibody variable domain fragments (scFvs) that selectively recognize the toxic tau oligomers. These scFvs selectively bind tau variants in brain tissue of human AD patients and AD-related tau transgenic rodent models and have potential value as early diagnostic biomarkers for AD and as potential therapeutics to selectively target toxic tau aggregates.
Increasing evidence implicates soluble oligomeric forms of beta-amyloid and tau in the onset and progression of AD. While many studies have focused on beta-amyloid, soluble oligomeric tau species may also play an important role in AD pathogenesis. Antibodies that selectively identify and target specific oligomeric tau variants would be valuable tools for both diagnostic and therapeutic applications and also to study the etiology of AD and other neurodegenerative diseases.
Recombinant human tau (rhTau) in monomeric, dimeric, trimeric and fibrillar forms were synthesized and purified to perform LDH assay on human neuroblastoma cells, so that trimeric but not monomeric or dimeric rhTau was identified as extracellularly neurotoxic to neuronal cells. A novel biopanning protocol was designed based on phage display technique and atomic force microscopy (AFM), and used to isolate single chain antibody variable domain fragments (scFvs) that selectively recognize the toxic tau oligomers. These scFvs selectively bind tau variants in brain tissue of human AD patients and AD-related tau transgenic rodent models and have potential value as early diagnostic biomarkers for AD and as potential therapeutics to selectively target toxic tau aggregates.
ContributorsTian, Huilai (Author) / Sierks, Michael R (Thesis advisor) / Dai, Lenore (Committee member) / Tillery, Stephen H (Committee member) / Nielsen, David R (Committee member) / Stabenfeldt, Sarah (Committee member) / Arizona State University (Publisher)
Created2014
Description
Background: Twenty-four hour urinary sucrose and fructose (24uSF) has been developed as a dietary biomarker for total sugars intake. Collection of 24-h urine is associated with high costs and heavy participant burden, while collection of spot urine samples can be easily implemented in research protocols. The aim of this thesis is to investigate the utility of uSF biomarker measured in spot urine. Methods: 15 participants age 22 to 49 years completed a 15-day feeding study in which they consumed their usual diet under controlled conditions, and recorded the time each meal was consumed. Two nonconsecutive 24-hour urines, where each urine void was collected in a separate container, were collected. Four timed voids (morning, afternoon, evening, and next day) were identified based on time of void and meal time. Urine samples were measured for sucrose, fructose and creatinine. Variability of uSF excretion was assessed by coefficient of variation (%CV) and variance ratios. Pearson correlation coefficient and multiple linear regression were used to investigate the association between uSF in each timed void and corresponding 24uSF excretion. Results: The two-day mean uSF was 50.6 mg (SD=29.5) for the 24-h urine, and ranged from 4.5 to 7.5 mg/void for the timed voids. The afternoon void uSF had the lowest within-subject variability (49.1%), and lowest within- to between-subject variance ratio (0.2). The morning and afternoon void uSF had the strongest correlation with 24-h uSF for both mg/void (r=0.80 and r=0.72) and mg/creatinine (r=0.72 and r=0.67), respectively. Finally, the afternoon void uSF along with other covariates had the strongest predictive ability of 24-h uSF excretion (mg/void) (Adjusted R2= 0.69; p=0.002), whereas the morning void had the strongest predictive ability of 24-h uSF excretion (mg/g creatinine) (adjusted R2= 0.58; p=0.008). Conclusions: The afternoon void uSF had the most favorable reproducibility estimates, strong correlation with 24uSF excretion, and explained greatest proportion of the variability in 24uSF. USF in mg/void may be better to use than uSF in mg/g creatinine as a biomarker in spot urine. These findings need to be confirmed in a larger study, and in a study population with a wide range of sugars intake.
ContributorsAverill, Annalisa (Author) / Tasevska, Natasha (Thesis advisor) / Shepard, Christina (Committee member) / Johnston, Carol (Committee member) / Arizona State University (Publisher)
Created2018
Description
Autism spectrum disorder (ASD) is a developmental neuropsychiatric condition with early childhood onset, thus most research has focused on characterizing brain function in young individuals. Little is understood about brain function differences in middle age and older adults with ASD, despite evidence of persistent and worsening cognitive symptoms. Functional Magnetic Resonance Imaging (MRI) in younger persons with ASD demonstrate that large-scale brain networks containing the prefrontal cortex are affected. A novel, threshold-selection-free graph theory metric is proposed as a more robust and sensitive method for tracking brain aging in ASD and is compared against five well-accepted graph theoretical analysis methods in older men with ASD and matched neurotypical (NT) participants. Participants were 27 men with ASD (52 +/- 8.4 years) and 21 NT men (49.7 +/- 6.5 years). Resting-state functional MRI (rs-fMRI) scans were collected for six minutes (repetition time=3s) with eyes closed. Data was preprocessed in SPM12, and Data Processing Assistant for Resting-State fMRI (DPARSF) was used to extract 116 regions-of-interest defined by the automated anatomical labeling (AAL) atlas. AAL regions were separated into six large-scale brain networks. This proposed metric is the slope of a monotonically decreasing convergence function (Integrated Persistent Feature, IPF; Slope of the IPF, SIP). Results were analyzed in SPSS using ANCOVA, with IQ as a covariate. A reduced SIP was in older men with ASD, compared to NT men, in the Default Mode Network [F(1,47)=6.48; p=0.02; 2=0.13] and Executive Network [F(1,47)=4.40; p=0.04; 2=0.09], a trend in the Fronto-Parietal Network [F(1,47)=3.36; p=0.07; 2=0.07]. There were no differences in the non-prefrontal networks (Sensory motor network, auditory network, and medial visual network). The only other graph theory metric to reach significance was network diameter in the Default Mode Network [F(1,47)=4.31; p=0.04; 2=0.09]; however, the effect size for the SIP was stronger. Modularity, Betti number, characteristic path length, and eigenvalue centrality were all non-significant. These results provide empirical evidence of decreased functional network integration in pre-frontal networks of older adults with ASD and propose a useful biomarker for tracking prognosis of aging adults with ASD to enable more informed treatment, support, and care methods for this growing population.
ContributorsCatchings, Michael Thomas (Author) / Braden, Brittany B (Thesis advisor) / Greger, Bradley (Thesis advisor) / Schaefer, Sydney (Committee member) / Arizona State University (Publisher)
Created2019
Description
Alzheimer’s Disease (AD) and Frontotemporal Dementia (FTD) are the leading causes of early onset dementia. There are currently no ways to slow down progression, to prevent or cure AD and FTD. Both AD and FTD share a lot of the symptoms and pathology. Initial symptoms such as confusion, memory loss, mood swings and behavioral changes are common in both these dementia subtypes. Neurofibrillary tau tangles and intraneuronal aggregates of TAR DNA Binding Protein 43 (TDP-43) are also observed in both AD and FTD. Hence, FTD cases are often misdiagnosed as AD due to a lack of accurate diagnostics. Prior to the formation of tau tangles and TDP-43 aggregates, tau and TDP-43 exist as intermediate protein variants which correlate with cognitive decline and progression of these neurodegenerative diseases. Effective diagnostic and therapeutic agents would selectively recognize these toxic, disease-specific variants. Antibodies or antibody fragments such as single chain antibody variable domain fragments (scFvs), with their diverse binding capabilities, can aid in developing reagents that can selectively bind these protein variants. A combination of phage display library and Atomic Force Microscopy (AFM)-based panning was employed to identify antibody fragments against immunoprecipitated tau and immunoprecipitated TDP-43 from human postmortem AD and FTD brain tissue respectively. Five anti-TDP scFvs and five anti-tau scFvs were selected for characterization by Enzyme Linked Immunosorbent Assays (ELISAs) and Immunohistochemistry (IHC). The panel of scFvs, together, were able to identify distinct protein variants present in AD but not in FTD, and vice versa. Generating protein variant profiles for individuals, using the panel of scFvs, aids in developing targeted diagnostic and therapeutic plans, gearing towards personalized medicine.
ContributorsVenkataraman, Lalitha (Author) / Sierks, Michael R (Thesis advisor) / Dunckley, Travis (Committee member) / Oddo, Salvatore (Committee member) / Stabenfeldt, Sarah (Committee member) / Arizona State University (Publisher)
Created2018
Description
Extracellular vesicles (EVs) represent a heterogeneous population of small vesicles, consisting of a phospholipidic bilayer surrounding a soluble interior cargo. These vesicles play an important role in cellular communication by virtue of their protein, RNA, and lipid content, which can be transferred among cells. Peripheral blood is a rich source of circulating EVs. An analysis of EVs in peripheral blood could provide access to unparalleled amounts of biomarkers of great diagnostic, prognostic as well as therapeutic value. In the current study, a plasma EV enrichment method based on pluronic co-polymer was first established and characterized. Plasma EVs from breast cancer patients were then enriched, profiled and compared to non-cancer controls. Proteins signatures that contributed to the prediction of cancer samples from non-cancer controls were created by a random-forest based cross-validation approach. We found that a large portion of these signatures were related to breast cancer aggression. To verify such findings, KIAA0100, one of the features identified, was chosen for in vitro molecular and cellular studies in the breast cancer cell line MDA-MB-231. We found that KIAA0100 regulates cancer cell aggression in MDA-MB-231 in an anchorage-independent manner and is particularly associated with anoikis resistance through its interaction with HSPA1A. Lastly, plasma EVs contain not only individual proteins, but also numerous molecular complexes. In order to measure millions of proteins, isoforms, and complexes simultaneously, Adaptive Dynamic Artificial Poly-ligand Targeting (ADAPT) platform was applied. ADAPT employs an enriched library of single-stranded oligodeoxynucleotides to profile complex biological samples, thus achieving a deep coverage of system-wide, native biomolecules. Profiling of EVs from breast cancer patients was able to obtain a prediction AUC performance of 0.73 when compared biopsy-positive cancer patient to healthy controls and 0.64 compared to biopsy-negative controls and such performance was not associated with the physical breast condition indicated by BIRAD scores. Taken together, current research demonstrated the potential of profiling plasma EVs in searching for therapeutic targets as well as diagnostic signatures.
ContributorsZhong, Zhenyu (Author) / Spetzler, David (Thesis advisor) / Yan, Hao (Thesis advisor) / Lake, Douglas (Committee member) / Mangone, Marco (Committee member) / Arizona State University (Publisher)
Created2018
Description
Valley Fever (VF), is a potentially lethal fungal pneumonia caused by Coccidioides spp., which is estimated to cause ~15-30% of all community-acquired pneumonias in the highly endemic Greater Phoenix and Tucson areas of Arizona. However, an accurate antigen-based diagnostic is still lacking. In order to identify protein and glycan antigen biomarkers of infection, I used a combination of genomics, proteomics and glycomics analyses to provide evidence of genus-specific proteins and glycosylations. The next goal was to determine if Coccidioides-specific glycans were present in biological samples from VF patients. Urine collected from 77 humans and 63 dogs were enriched for glycans and evaluated by mass spectrometry for Coccidioides-specific glycans and evaluated against a panel of normal donor urines, urines from patients infected with other fungi, and fungal cultures from closely related pneumonia-causing fungi. A combination of 6 glycan biomarkers was 100% sensitive and 100% specific in the diagnosis of human VF subjects, while only 3 glycan biomarkers were needed for 100% sensitivity and 100 specificity in the diagnosis of dog VF subject. Additionally, a blinded trial of 23 human urine samples was correctly able to classify urine samples with 93.3% sensitivity and 100% specificity. The results of this research provides evidence that Coccidioides genus-specific glycosylations have potential as antigens in diagnostic assays.
ContributorsMitchell, Natalie M (Author) / Lake, Douglas F (Thesis advisor) / Bean, Heather D (Committee member) / Grys, Thomas E (Committee member) / Magee, Dewey M (Committee member) / Arizona State University (Publisher)
Created2019
Description
Physical activity, sedentary behaviors, and sleep are often associated with cardiometabolic biomarkers commonly found in metabolic syndrome. These relationships are well studied, and yet there are still questions on how each activity may affect cardiometabolic biomarkers. The objective of this study was to examine data from the BeWell24 studies to evaluate the relationship between objectively measured physical activity and sedentary behaviors and cardiometabolic biomarkers in middle age adults, while also determining if sleep quality and duration mediates this relationship. A group of inactive participants (N = 29, age = 52.1 ± 8.1 years, 38% female) with increased risk for cardiometabolic disease were recruited to participate in BeWell24, a trial testing the impact of a lifestyle-based, multicomponent smartphone application targeting sleep, sedentary, and more active behaviors. During baseline, interim (4 weeks), and posttest visits (8 weeks), biomarker measurements were collected for weight (kg), waist circumference (cm), glucose (mg/dl), insulin (uU/ml), lipids (mg/dl), diastolic and systolic blood pressures (mm Hg), and C reactive protein (mg/L). Participants wore validated wrist and thigh sensors for one week intervals at each time point to measure sedentary behavior, physical activity, and sleep outcomes. Long bouts of sitting time (>30 min) significantly affected triglycerides (beta = .15 (±.07), p<.03); however, no significant mediation effects for sleep quality or duration were present. No other direct effects were observed between physical activity measurements and cardiometabolic biomarkers. The findings of this study suggest that reductions in long bouts of sitting time may support reductions in triglycerides, yet these effects were not mediated by sleep-related improvements.
ContributorsLanich, Boyd (Author) / Buman, Matthew (Thesis advisor) / Ainsworth, Barbara (Committee member) / Huberty, Jennifer (Committee member) / Arizona State University (Publisher)
Created2017
Description
Cardiovascular disease is affecting millions of people worldwide and is the leading cause of death in the United States. This disease is closely related to the abnormal creatinine levels in blood. For this reason, there is a need for a low-cost point-of-care device that could measure the creatinine level in blood with the goal of managing and preventing cardiovascular disease. This project introduces a Molecular Reactive Lateral Flow Assay (MoReLFA) device that is aimed toward creatinine detection based on an optimized chemical reaction of creatinine and alkaline picrate. The device consists of different membranes that accommodate 50 microliters of fluid sample and carry out a colorimetric reaction, in which deposited-colored region is analyzed for Red, Green, and Blue (RGB) components via an image processing software. The color intensity from the RGB outputs was then studied and compared with a gold standard spectrophotometry-based technique. The results show that the MoReLFA sensor could successfully detect creatinine levels in standard solutions. The plot of the sensor color intensity against the absorbance from spectrophotometry shows a good correlation between the two methods (R2 = 0.96). Furthermore, the paper introduces the development of a RGB reader box that is portable and for easy assessment of RGB values. The color intensity from the box shows an increasing trend with increasing creatinine concentrations; and the coefficient of determination of this relationship is 0.85.
ContributorsNguyen, Ngan Anh (Author) / Raupp, Gregory (Thesis advisor) / Forzani, Erica (Thesis advisor) / Mora, Sabrina Jimena (Committee member) / Arizona State University (Publisher)
Created2022
Description
Breast cancer is the most common cancer and currently the second leading cause of death among women in the United States. Patients’ five-year relative survival rate decreases from 99% to 25% when breast cancer is diagnosed late. Immune checkpoint blockage has shown to be a promising therapy to improve patients’ outcome in many other cancers. However, due to the lack of early diagnosis, the treatment is normally given in the later stages. An early diagnosis system for breast cancer could potentially revolutionize current treatment strategies, improve patients’ outcomes and even eradicate the disease. The current breast cancer diagnostic methods cannot meet this demand. A simple, effective, noninvasive and inexpensive early diagnostic technology is needed. Immunosignature technology leverages the power of the immune system to find cancer early. Antibodies targeting tumor antigens in the blood are probed on a high-throughput random peptide array and generate a specific binding pattern called the immunosignature.
In this dissertation, I propose a scenario for using immunosignature technology to detect breast cancer early and to implement an early treatment strategy by using the PD-L1 immune checkpoint inhibitor. I develop a methodology to describe the early diagnosis and treatment of breast cancer in a FVB/N neuN breast cancer mouse model. By comparing FVB/N neuN transgenic mice and age-matched wild type controls, I have found and validated specific immunosignatures at multiple time points before tumors are palpable. Immunosignatures change along with tumor development. Using a late-stage immunosignature to predict early samples, or vice versa, cannot achieve high prediction performance. By using the immunosignature of early breast cancer, I show that at the time of diagnosis, early treatment with the checkpoint blockade, anti-PD-L1, inhibits tumor growth in FVB/N neuN transgenic mouse model. The mRNA analysis of the PD-L1 level in mice mammary glands suggests that it is more effective to have treatment early.
Novel discoveries are changing understanding of breast cancer and improving strategies in clinical treatment. Researchers and healthcare professionals are actively working in the early diagnosis and early treatment fields. This dissertation provides a step along the road for better diagnosis and treatment of breast cancer.
In this dissertation, I propose a scenario for using immunosignature technology to detect breast cancer early and to implement an early treatment strategy by using the PD-L1 immune checkpoint inhibitor. I develop a methodology to describe the early diagnosis and treatment of breast cancer in a FVB/N neuN breast cancer mouse model. By comparing FVB/N neuN transgenic mice and age-matched wild type controls, I have found and validated specific immunosignatures at multiple time points before tumors are palpable. Immunosignatures change along with tumor development. Using a late-stage immunosignature to predict early samples, or vice versa, cannot achieve high prediction performance. By using the immunosignature of early breast cancer, I show that at the time of diagnosis, early treatment with the checkpoint blockade, anti-PD-L1, inhibits tumor growth in FVB/N neuN transgenic mouse model. The mRNA analysis of the PD-L1 level in mice mammary glands suggests that it is more effective to have treatment early.
Novel discoveries are changing understanding of breast cancer and improving strategies in clinical treatment. Researchers and healthcare professionals are actively working in the early diagnosis and early treatment fields. This dissertation provides a step along the road for better diagnosis and treatment of breast cancer.
ContributorsDuan, Hu (Author) / Johnston, Stephen Albert (Thesis advisor) / Hartwell, Leland Harrison (Committee member) / Dinu, Valentin (Committee member) / Chang, Yung (Committee member) / Arizona State University (Publisher)
Created2015