ASU Scholarship Showcase

Does school participatory budgeting (SPB) increase students’ political efficacy? SPB, which is implemented in thousands of schools around the world, is a democratic process of deliberation and decision-making in which students determine how to spend a portion of the school’s budget. We examined the impact of SPB on political efficacy in one middle school in Arizona. Our participants’ (n = 28) responses on survey items designed to measure self-perceived growth in political efficacy indicated a large effect size (Cohen’s d = 1.46), suggesting that SPB is an effective approach to civic pedagogy, with promising prospects for developing students’ political efficacy.

The apolipoprotein E (APOE) e4 allele is the most prevalent genetic risk factor for Alzheimer's disease (AD). Hippocampal volumes are generally smaller in AD patients carrying the e4 allele compared to e4 noncarriers. Here we examined the effect of APOE e4 on hippocampal morphometry in a large imaging database—the Alzheimer's Disease Neuroimaging Initiative (ADNI). We automatically segmented and constructed hippocampal surfaces from the baseline MR images of 725 subjects with known APOE genotype information including 167 with AD, 354 with mild cognitive impairment (MCI), and 204 normal controls. High-order correspondences between hippocampal surfaces were enforced across subjects with a novel inverse consistent surface fluid registration method. Multivariate statistics consisting of multivariate tensor-based morphometry (mTBM) and radial distance were computed for surface deformation analysis. Using Hotelling's T2 test, we found significant morphological deformation in APOE e4 carriers relative to noncarriers in the entire cohort as well as in the nondemented (pooled MCI and control) subjects, affecting the left hippocampus more than the right, and this effect was more pronounced in e4 homozygotes than heterozygotes. Our findings are consistent with previous studies that showed e4 carriers exhibit accelerated hippocampal atrophy; we extend these findings to a novel measure of hippocampal morphometry. Hippocampal morphometry has significant potential as an imaging biomarker of early stage AD.

We develop a general framework to analyze the controllability of multiplex networks using multiple-relation networks and multiple-layer networks with interlayer couplings as two classes of prototypical systems. In the former, networks associated with different physical variables share the same set of nodes and in the latter, diffusion processes take place. We find that, for a multiple-relation network, a layer exists that dominantly determines the controllability of the whole network and, for a multiple-layer network, a small fraction of the interconnections can enhance the controllability remarkably. Our theory is generally applicable to other types of multiplex networks as well, leading to significant insights into the control of complex network systems with diverse structures and interacting patterns.

Mild Cognitive Impairment (MCI) is a transitional stage between normal aging and dementia and people with MCI are at high risk of progression to dementia. MCI is attracting increasing attention, as it offers an opportunity to target the disease process during an early symptomatic stage. Structural magnetic resonance imaging (MRI) measures have been the mainstay of Alzheimer's disease (AD) imaging research, however, ventricular morphometry analysis remains challenging because of its complicated topological structure. Here we describe a novel ventricular morphometry system based on the hyperbolic Ricci flow method and tensor-based morphometry (TBM) statistics. Unlike prior ventricular surface parameterization methods, hyperbolic conformal parameterization is angle-preserving and does not have any singularities. Our system generates a one-to-one diffeomorphic mapping between ventricular surfaces with consistent boundary matching conditions. The TBM statistics encode a great deal of surface deformation information that could be inaccessible or overlooked by other methods. We applied our system to the baseline MRI scans of a set of MCI subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI: 71 MCI converters vs. 62 MCI stable). Although the combined ventricular area and volume features did not differ between the two groups, our fine-grained surface analysis revealed significant differences in the ventricular regions close to the temporal lobe and posterior cingulate, structures that are affected early in AD. Significant correlations were also detected between ventricular morphometry, neuropsychological measures, and a previously described imaging index based on fluorodeoxyglucose positron emission tomography (FDG-PET) scans. This novel ventricular morphometry method may offer a new and more sensitive approach to study preclinical and early symptomatic stage AD.

MicroRNAs (miRNAs) are short non-coding RNAs that regulate gene output at the post-transcriptional level by targeting degenerate elements primarily in 3′untranslated regions (3′UTRs) of mRNAs. Individual miRNAs can regulate networks of hundreds of genes, yet for the majority of miRNAs few, if any, targets are known. Misexpression of miRNAs is also a major contributor to cancer progression, thus there is a critical need to validate miRNA targets in high-throughput to understand miRNAs' contribution to tumorigenesis. Here we introduce a novel high-throughput assay to detect miRNA targets in 3′UTRs, called Luminescent Identification of Functional Elements in 3′UTRs (3′LIFE). We demonstrate the feasibility of 3′LIFE using a data set of 275 human 3′UTRs and two cancer-relevant miRNAs, let-7c and miR-10b, and compare our results to alternative methods to detect miRNA targets throughout the genome. We identify a large number of novel gene targets for these miRNAs, with only 32% of hits being bioinformatically predicted and 27% directed by non-canonical interactions. Functional analysis of target genes reveals consistent roles for each miRNA as either a tumor suppressor (let-7c) or oncogenic miRNA (miR-10b), and preferentially target multiple genes within regulatory networks, suggesting 3′LIFE is a rapid and sensitive method to detect miRNA targets in high-throughput.

Background: Lizards are evolutionarily the most closely related vertebrates to humans that can lose and regrow an entire appendage. Regeneration in lizards involves differential expression of hundreds of genes that regulate wound healing, musculoskeletal development, hormonal response, and embryonic morphogenesis. While microRNAs are able to regulate large groups of genes, their role in lizard regeneration has not been investigated.

Results: MicroRNA sequencing of green anole lizard (Anolis carolinensis) regenerating tail and associated tissues revealed 350 putative novel and 196 known microRNA precursors. Eleven microRNAs were differentially expressed between the regenerating tail tip and base during maximum outgrowth (25 days post autotomy), including miR-133a, miR-133b, and miR-206, which have been reported to regulate regeneration and stem cell proliferation in other model systems. Three putative novel differentially expressed microRNAs were identified in the regenerating tail tip.

Conclusions: Differentially expressed microRNAs were identified in the regenerating lizard tail, including known regulators of stem cell proliferation. The identification of 3 putative novel microRNAs suggests that regulatory networks, either conserved in vertebrates and previously uncharacterized or specific to lizards, are involved in regeneration. These findings suggest that differential regulation of microRNAs may play a role in coordinating the timing and expression of hundreds of genes involved in regeneration.

Background: Tissue-specific RNA plasticity broadly impacts the development, tissue identity and adaptability of all organisms, but changes in composition, expression levels and its impact on gene regulation in different somatic tissues are largely unknown. Here we developed a new method, polyA-tagging and sequencing (PAT-Seq) to isolate high-quality tissue-specific mRNA from Caenorhabditis elegans intestine, pharynx and body muscle tissues and study changes in their tissue-specific transcriptomes and 3’UTRomes.

Results: We have identified thousands of novel genes and isoforms differentially expressed between these three tissues. The intestine transcriptome is expansive, expressing over 30% of C. elegans mRNAs, while muscle transcriptomes are smaller but contain characteristic unique gene signatures. Active promoter regions in all three tissues reveal both known and novel enriched tissue-specific elements, along with putative transcription factors, suggesting novel tissue-specific modes of transcription initiation. We have precisely mapped approximately 20,000 tissue-specific polyadenylation sites and discovered that about 30% of transcripts in somatic cells use alternative polyadenylation in a tissue-specific manner, with their 3’UTR isoforms significantly enriched with microRNA targets.

Conclusions: For the first time, PAT-Seq allowed us to directly study tissue specific gene expression changes in an in vivo setting and compare these changes between three somatic tissues from the same organism at single-base resolution within the same experiment. We pinpoint precise tissue-specific transcriptome rearrangements and for the first time link tissue-specific alternative polyadenylation to miRNA regulation, suggesting novel and unexplored tissue-specific post-transcriptional regulatory networks in somatic cells.

Background: 3′untranslated regions (3′UTRs) are poorly understood portions of eukaryotic mRNAs essential for post-transcriptional gene regulation. Sequence elements in 3′UTRs can be target sites for regulatory molecules such as RNA binding proteins and microRNAs (miRNAs), and these interactions can exert significant control on gene networks. However, many such interactions remain uncharacterized due to a lack of high-throughput (HT) tools to study 3′UTR biology. HT cloning efforts such as the human ORFeome exemplify the potential benefits of genomic repositories for studying human disease, especially in relation to the discovery of biomarkers and targets for therapeutic agents. Currently there are no publicly available human 3′UTR libraries. To address this we have prepared the first version of the human 3′UTRome (h3′UTRome v1) library. The h3′UTRome is produced to a single high quality standard using the same recombinational cloning technology used for the human ORFeome, enabling universal operating methods and high throughput experimentation. The library is thoroughly sequenced and annotated with simple online access to information, and made publicly available through gene repositories at low cost to all scientists with minimal restriction.

Results: The first release of the h3′UTRome library comprises 1,461 human 3′UTRs cloned into Gateway® entry vectors, ready for downstream analyses. It contains 3′UTRs for 985 transcription factors, 156 kinases, 171 RNA binding proteins, and 186 other genes involved in gene regulation and in disease. We demonstrate the feasibility of the h3′UTRome library by screening a panel of 87 3′UTRs for targeting by two miRNAs: let-7c, which is implicated in tumorigenesis, and miR-221, which is implicated in atherosclerosis and heart disease. The panel is enriched with genes involved in the RAS signaling pathway, putative novel targets for the two miRNAs, as well as genes implicated in tumorigenesis and heart disease.

Conclusions: The h3′UTRome v1 library is a modular resource that can be utilized for high-throughput screens to identify regulatory interactions between trans-acting factors and 3′UTRs, Importantly, the library can be customized based on the specifications of the researcher, allowing the systematic study of human 3′UTR biology.

The apolipoprotein E (APOE) e4 genotype is a powerful risk factor for late-onset Alzheimer’s disease (AD). In the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort, we previously reported significant baseline structural differences in APOE e4 carriers relative to non-carriers, involving the left hippocampus more than the right—a difference more pronounced in e4 homozygotes than heterozygotes. We now examine the longitudinal effects of APOE genotype on hippocampal morphometry at 6-, 12- and 24-months, in the ADNI cohort. We employed a new automated surface registration system based on conformal geometry and tensor-based morphometry. Among different hippocampal surfaces, we computed high-order correspondences, using a novel inverse-consistent surface-based fluid registration method and multivariate statistics consisting of multivariate tensor-based morphometry (mTBM) and radial distance. At each time point, using Hotelling’s T² test, we found significant morphological deformation in APOE e4 carriers relative to non-carriers in the full cohort as well as in the non-demented (pooled MCI and control) subjects at each follow-up interval. In the complete ADNI cohort, we found greater atrophy of the left hippocampus than the right, and this asymmetry was more pronounced in e4 homozygotes than heterozygotes. These findings, combined with our earlier investigations, demonstrate an e4 dose effect on accelerated hippocampal atrophy, and support the enrichment of prevention trial cohorts with e4 carriers.

Alzheimer’s disease (AD) involves a gradual breakdown of brain connectivity, and network analyses offer a promising new approach to track and understand disease progression. Even so, our ability to detect degenerative changes in brain networks depends on the methods used. Here we compared several tractography and feature extraction methods to see which ones gave best diagnostic classification for 202 people with AD, mild cognitive impairment or normal cognition, scanned with 41-gradient diffusion-weighted magnetic resonance imaging as part of the Alzheimer’s Disease Neuroimaging Initiative (ADNI) project. We computed brain networks based on whole brain tractography with nine different methods – four of them tensor-based deterministic (FACT, RK2, SL, and TL), two orientation distribution function (ODF)-based deterministic (FACT, RK2), two ODF-based probabilistic approaches (Hough and PICo), and one “ball-and-stick” approach (Probtrackx). Brain networks derived from different tractography algorithms did not differ in terms of classification performance on ADNI, but performing principal components analysis on networks helped classification in some cases. Small differences may still be detectable in a truly vast cohort, but these experiments help assess the relative advantages of different tractography algorithms, and different post-processing choices, when used for classification.