Matching Items (74)
Description
Obesity and its underlying insulin resistance are caused by environmental and genetic factors. DNA methylation provides a mechanism by which environmental factors can regulate transcriptional activity. The overall goal of the work herein was to (1) identify alterations in DNA methylation in human skeletal muscle with obesity and its underlying

Obesity and its underlying insulin resistance are caused by environmental and genetic factors. DNA methylation provides a mechanism by which environmental factors can regulate transcriptional activity. The overall goal of the work herein was to (1) identify alterations in DNA methylation in human skeletal muscle with obesity and its underlying insulin resistance, (2) to determine if these changes in methylation can be altered through weight-loss induced by bariatric surgery, and (3) to identify DNA methylation biomarkers in whole blood that can be used as a surrogate for skeletal muscle.

Assessment of DNA methylation was performed on human skeletal muscle and blood using reduced representation bisulfite sequencing (RRBS) for high-throughput identification and pyrosequencing for site-specific confirmation. Sorbin and SH3 homology domain 3 (SORBS3) was identified in skeletal muscle to be increased in methylation (+5.0 to +24.4 %) in the promoter and 5’untranslated region (UTR) in the obese participants (n= 10) compared to lean (n=12), and this finding corresponded with a decrease in gene expression (fold change: -1.9, P=0.0001). Furthermore, SORBS3 was demonstrated in a separate cohort of morbidly obese participants (n=7) undergoing weight-loss induced by surgery, to decrease in methylation (-5.6 to -24.2%) and increase in gene expression (fold change: +1.7; P=0.05) post-surgery. Moreover, SORBS3 promoter methylation was demonstrated in vitro to inhibit transcriptional activity (P=0.000003). The methylation and transcriptional changes for SORBS3 were significantly (P≤0.05) correlated with obesity measures and fasting insulin levels. SORBS3 was not identified in the blood methylation analysis of lean (n=10) and obese (n=10) participants suggesting that it is a muscle specific marker. However, solute carrier family 19 member 1 (SLC19A1) was identified in blood and skeletal muscle to have decreased 5’UTR methylation in obese participants, and this was significantly (P≤0.05) predicted by insulin sensitivity.

These findings suggest SLC19A1 as a potential blood-based biomarker for obese, insulin resistant states. The collective findings of SORBS3 DNA methylation and gene expression present an exciting novel target in skeletal muscle for further understanding obesity and its underlying insulin resistance. Moreover, the dynamic changes to SORBS3 in response to metabolic improvements and weight-loss induced by surgery.
ContributorsDay, Samantha Elaine (Author) / Coletta, Dawn K. (Thesis advisor) / Katsanos, Christos (Committee member) / Mandarino, Lawrence J. (Committee member) / Shaibi, Gabriel Q. (Committee member) / Dinu, Valentin (Committee member) / Arizona State University (Publisher)
Created2017
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Description
Rewired biological pathways and/or rewired microRNA (miRNA)-mRNA interactions might also influence the activity of biological pathways. Here, rewired biological pathways is defined as differential (rewiring) effect of genes on the topology of biological pathways between controls and cases. Similarly, rewired miRNA-mRNA interactions are defined as the differential (rewiring) effects of

Rewired biological pathways and/or rewired microRNA (miRNA)-mRNA interactions might also influence the activity of biological pathways. Here, rewired biological pathways is defined as differential (rewiring) effect of genes on the topology of biological pathways between controls and cases. Similarly, rewired miRNA-mRNA interactions are defined as the differential (rewiring) effects of miRNAs on the topology of biological pathways between controls and cases. In the dissertation, it is discussed that how rewired biological pathways (Chapter 1) and/or rewired miRNA-mRNA interactions (Chapter 2) aberrantly influence the activity of biological pathways and their association with disease.

This dissertation proposes two PageRank-based analytical methods, Pathways of Topological Rank Analysis (PoTRA) and miR2Pathway, discussed in Chapter 1 and Chapter 2, respectively. PoTRA focuses on detecting pathways with an altered number of hub genes in corresponding pathways between two phenotypes. The basis for PoTRA is that the loss of connectivity is a common topological trait of cancer networks, as well as the prior knowledge that a normal biological network is a scale-free network whose degree distribution follows a power law where a small number of nodes are hubs and a large number of nodes are non-hubs. However, from normal to cancer, the process of the network losing connectivity might be the process of disrupting the scale-free structure of the network, namely, the number of hub genes might be altered in cancer compared to that in normal samples. Hence, it is hypothesized that if the number of hub genes is different in a pathway between normal and cancer, this pathway might be involved in cancer. MiR2Pathway focuses on quantifying the differential effects of miRNAs on the activity of a biological pathway when miRNA-mRNA connections are altered from normal to disease and rank disease risk of rewired miRNA-mediated biological pathways. This dissertation explores how rewired gene-gene interactions and rewired miRNA-mRNA interactions lead to aberrant activity of biological pathways, and rank pathways for their disease risk. The two methods proposed here can be used to complement existing genomics analysis methods to facilitate the study of biological mechanisms behind disease at the systems-level.
ContributorsLi, Chaoxing (Author) / Dinu, Valentin (Thesis advisor) / Kuang, Yang (Thesis advisor) / Liu, Li (Committee member) / Wang, Xiao (Committee member) / Arizona State University (Publisher)
Created2017
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Description
Understanding intratumor heterogeneity and their driver genes is critical to

designing personalized treatments and improving clinical outcomes of cancers. Such

investigations require accurate delineation of the subclonal composition of a tumor, which

to date can only be reliably inferred from deep-sequencing data (>300x depth). The

resulting algorithm from the work presented here, incorporates an

Understanding intratumor heterogeneity and their driver genes is critical to

designing personalized treatments and improving clinical outcomes of cancers. Such

investigations require accurate delineation of the subclonal composition of a tumor, which

to date can only be reliably inferred from deep-sequencing data (>300x depth). The

resulting algorithm from the work presented here, incorporates an adaptive error model

into statistical decomposition of mixed populations, which corrects the mean-variance

dependency of sequencing data at the subclonal level and enables accurate subclonal

discovery in tumors sequenced at standard depths (30-50x). Tested on extensive computer

simulations and real-world data, this new method, named model-based adaptive grouping

of subclones (MAGOS), consistently outperforms existing methods on minimum

sequencing depth, decomposition accuracy and computation efficiency. MAGOS supports

subclone analysis using single nucleotide variants and copy number variants from one or

more samples of an individual tumor. GUST algorithm, on the other hand is a novel method

in detecting the cancer type specific driver genes. Combination of MAGOS and GUST

results can provide insights into cancer progression. Applications of MAGOS and GUST

to whole-exome sequencing data of 33 different cancer types’ samples discovered a

significant association between subclonal diversity and their drivers and patient overall

survival.
ContributorsAhmadinejad, Navid (Author) / Liu, Li (Thesis advisor) / Maley, Carlo (Committee member) / Dinu, Valentin (Committee member) / Arizona State University (Publisher)
Created2019
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Description
ABSTRACT

Domestic dogs have assisted humans for millennia. However, the extent to which these helpful behaviors are prosocially motivated remains unclear. To assess the propensity of pet dogs to spontaneously and actively rescue distressed humans, this study tested whether sixty pet dogs would release their seemingly trapped owners from a large

ABSTRACT

Domestic dogs have assisted humans for millennia. However, the extent to which these helpful behaviors are prosocially motivated remains unclear. To assess the propensity of pet dogs to spontaneously and actively rescue distressed humans, this study tested whether sixty pet dogs would release their seemingly trapped owners from a large box. To examine the causal mechanisms that shaped this behavior, the readiness of each dog to open the box was tested in three conditions: 1) the owner sat in the box and called for help (“Distress” test), 2) an experimenter placed high-value food rewards in the box (“Food” test), and 3) the owner sat in the box and calmly read aloud (“Reading” test).

Dogs were as likely to release their distressed owner as to retrieve treats from inside the box, indicating that rescuing an owner may be a highly rewarding action for dogs. After accounting for ability, dogs released the owner more often when the owner called for help than when the owner read aloud calmly. In addition, opening latencies decreased with test number in the Distress test but not the Reading test. Thus, rescuing the owner could not be attributed solely to social facilitation, stimulus enhancement, or social contact-seeking behavior.

Dogs displayed more stress behaviors in the Distress test than in the Reading test, and stress scores decreased with test number in the Reading test but not in the Distress test. This evidence of emotional contagion supports the hypothesis that rescuing the distressed owner was an empathetically-motivated prosocial behavior. Success in the Food task and previous (in-home) experience opening objects were both strong predictors of releasing the owner. Thus, prosocial behavior tests for dogs should control for physical ability and previous experience.
ContributorsVan Bourg, Joshua Lazar (Author) / Wynne, Clive D (Thesis advisor) / Gilby, Ian C (Committee member) / Aktipis, C. Athena (Committee member) / Arizona State University (Publisher)
Created2019
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Description
All biological processes like cell growth, cell differentiation, development, and aging requires a series of steps which are characterized by gene regulation. Studies have shown that gene regulation is the key to various traits and diseases. Various factors affect the gene regulation which includes genetic signals, epigenetic tracks, genetic variants,

All biological processes like cell growth, cell differentiation, development, and aging requires a series of steps which are characterized by gene regulation. Studies have shown that gene regulation is the key to various traits and diseases. Various factors affect the gene regulation which includes genetic signals, epigenetic tracks, genetic variants, etc. Deciphering and cataloging these functional genetic elements in the non-coding regions of the genome is one of the biggest challenges in precision medicine and genetic research. This thesis presents two different approaches to identifying these elements: TreeMap and DeepCORE. The first approach involves identifying putative causal genetic variants in cis-eQTL accounting for multisite effects and genetic linkage at a locus. TreeMap performs an organized search for individual and multiple causal variants using a tree guided nested machine learning method. DeepCORE on the other hand explores novel deep learning techniques that models the relationship between genetic, epigenetic and transcriptional patterns across tissues and cell lines and identifies co-operative regulatory elements that affect gene regulation. These two methods are believed to be the link for genotype-phenotype association and a necessary step to explaining various complex diseases and missing heritability.
ContributorsChandrashekar, Pramod Bharadwaj (Author) / Liu, Li (Thesis advisor) / Runger, George C. (Committee member) / Dinu, Valentin (Committee member) / Arizona State University (Publisher)
Created2020
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Description
This dissertation presents three novel algorithms with real-world applications to genomic oncology. While the methodologies presented here were all developed to overcome various challenges associated with the adoption of high throughput genomic data in clinical oncology, they can be used in other domains as well. First, a network informed feature

This dissertation presents three novel algorithms with real-world applications to genomic oncology. While the methodologies presented here were all developed to overcome various challenges associated with the adoption of high throughput genomic data in clinical oncology, they can be used in other domains as well. First, a network informed feature ranking algorithm is presented, which shows a significant increase in ability to select true predictive features from simulated data sets when compared to other state of the art graphical feature ranking methods. The methodology also shows an increased ability to predict pathological complete response to preoperative chemotherapy from genomic sequencing data of breast cancer patients utilizing domain knowledge from protein-protein interaction networks. Second, an algorithm that overcomes population biases inherent in the use of a human reference genome developed primarily from European populations is presented to classify microsatellite instability (MSI) status from next-generation-sequencing (NGS) data. The methodology significantly increases the accuracy of MSI status prediction in African and African American ancestries. Finally, a single variable model is presented to capture the bimodality inherent in genomic data stemming from heterogeneous diseases. This model shows improvements over other parametric models in the measurements of receiver-operator characteristic (ROC) curves for bimodal data. The model is used to estimate ROC curves for heterogeneous biomarkers in a dataset containing breast cancer and cancer-free specimen.
ContributorsSaul, Michelle (Author) / Dinu, Valentin (Thesis advisor) / Liu, Li (Committee member) / Wang, Junwen (Committee member) / Arizona State University (Publisher)
Created2021
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Description

Microbes in the gastrointestinal tract are under selective pressure to manipulate host eating behavior to increase their fitness, sometimes at the expense of host fitness. Microbes may do this through two potential strategies: (i) generating cravings for foods that they specialize on or foods that suppress their competitors, or (ii)

Microbes in the gastrointestinal tract are under selective pressure to manipulate host eating behavior to increase their fitness, sometimes at the expense of host fitness. Microbes may do this through two potential strategies: (i) generating cravings for foods that they specialize on or foods that suppress their competitors, or (ii) inducing dysphoria until we eat foods that enhance their fitness. We review several potential mechanisms for microbial control over eating behavior including microbial influence on reward and satiety pathways, production of toxins that alter mood, changes to receptors including taste receptors, and hijacking of the vagus nerve, the neural axis between the gut and the brain. We also review the evidence for alternative explanations for cravings and unhealthy eating behavior. Because microbiota are easily manipulatable by prebiotics, probiotics, antibiotics, fecal transplants, and dietary changes, altering our microbiota offers a tractable approach to otherwise intractable problems of obesity and unhealthy eating.

ContributorsAlcock, Joe (Author) / Maley, Carlo C. (Author) / Aktipis, C. Athena (Author) / College of Liberal Arts and Sciences (Contributor)
Created2014-10-01
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Description

Background: Counselor behaviors that mediate the efficacy of motivational interviewing (MI) are not well understood, especially when applied to health behavior promotion. We hypothesized that client change talk mediates the relationship between counselor variables and subsequent client behavior change.

Methods: Purposeful sampling identified individuals from a prospective randomized worksite trial using an MI

Background: Counselor behaviors that mediate the efficacy of motivational interviewing (MI) are not well understood, especially when applied to health behavior promotion. We hypothesized that client change talk mediates the relationship between counselor variables and subsequent client behavior change.

Methods: Purposeful sampling identified individuals from a prospective randomized worksite trial using an MI intervention to promote firefighters’ healthy diet and regular exercise that increased dietary intake of fruits and vegetables (n = 21) or did not increase intake of fruits and vegetables (n = 22). MI interactions were coded using the Motivational Interviewing Skill Code (MISC 2.1) to categorize counselor and firefighter verbal utterances. Both Bayesian and frequentist mediation analyses were used to investigate whether client change talk mediated the relationship between counselor skills and behavior change.

Results: Counselors’ global spirit, empathy, and direction and MI-consistent behavioral counts (e.g., reflections, open questions, affirmations, emphasize control) significantly correlated with firefighters’ total client change talk utterances (rs = 0.42, 0.40, 0.30, and 0.61, respectively), which correlated significantly with their fruit and vegetable intake increase (r = 0.33). Both Bayesian and frequentist mediation analyses demonstrated that findings were consistent with hypotheses, such that total client change talk mediated the relationship between counselor’s skills—MI-consistent behaviors [Bayesian mediated effect: αβ = .06 (.03), 95% CI = .02, .12] and MI spirit [Bayesian mediated effect: αβ = .06 (.03), 95% CI = .01, .13]—and increased fruit and vegetable consumption.

Conclusion: Motivational interviewing is a resource- and time-intensive intervention, and is currently being applied in many arenas. Previous research has identified the importance of counselor behaviors and client change talk in the treatment of substance use disorders. Our results indicate that similar mechanisms may underlie the effects of MI for dietary change. These results inform MI training and application by identifying those processes critical for MI success in health promotion domains.

ContributorsPirlott, Angela (Author) / Kisbu-Sakarya, Yasemin (Author) / DeFrancesco, Carol A. (Author) / Elliot, Diane L. (Author) / MacKinnon, David (Author) / College of Liberal Arts and Sciences (Contributor)
Created2012-06-08
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Description

Background: Obesity is a metabolic disease caused by environmental and genetic factors. However, the epigenetic mechanisms of obesity are incompletely understood. The aim of our study was to investigate the role of skeletal muscle DNA methylation in combination with transcriptomic changes in obesity.

Results: Muscle biopsies were obtained basally from lean (n = 12; BMI = 23.4 ± 0.7

Background: Obesity is a metabolic disease caused by environmental and genetic factors. However, the epigenetic mechanisms of obesity are incompletely understood. The aim of our study was to investigate the role of skeletal muscle DNA methylation in combination with transcriptomic changes in obesity.

Results: Muscle biopsies were obtained basally from lean (n = 12; BMI = 23.4 ± 0.7 kg/m[superscript 2]) and obese (n = 10; BMI = 32.9 ± 0.7 kg/m[superscript 2]) participants in combination with euglycemic-hyperinsulinemic clamps to assess insulin sensitivity. We performed reduced representation bisulfite sequencing (RRBS) next-generation methylation and microarray analyses on DNA and RNA isolated from vastus lateralis muscle biopsies. There were 13,130 differentially methylated cytosines (DMC; uncorrected P < 0.05) that were altered in the promoter and untranslated (5' and 3'UTR) regions in the obese versus lean analysis. Microarray analysis revealed 99 probes that were significantly (corrected P < 0.05) altered. Of these, 12 genes (encompassing 22 methylation sites) demonstrated a negative relationship between gene expression and DNA methylation. Specifically, sorbin and SH3 domain containing 3 (SORBS3) which codes for the adapter protein vinexin was significantly decreased in gene expression (fold change −1.9) and had nine DMCs that were significantly increased in methylation in obesity (methylation differences ranged from 5.0 to 24.4 %). Moreover, differentially methylated region (DMR) analysis identified a region in the 5'UTR (Chr.8:22,423,530–22,423,569) of SORBS3 that was increased in methylation by 11.2 % in the obese group. The negative relationship observed between DNA methylation and gene expression for SORBS3 was validated by a site-specific sequencing approach, pyrosequencing, and qRT-PCR. Additionally, we performed transcription factor binding analysis and identified a number of transcription factors whose binding to the differentially methylated sites or region may contribute to obesity.

Conclusions: These results demonstrate that obesity alters the epigenome through DNA methylation and highlights novel transcriptomic changes in SORBS3 in skeletal muscle.

ContributorsDay, Samantha (Author) / Coletta, Rich (Author) / Kim, Joon Young (Author) / Campbell, Latoya (Author) / Benjamin, Tonya R. (Author) / Roust, Lori R. (Author) / De Filippis, Elena A. (Author) / Dinu, Valentin (Author) / Shaibi, Gabriel (Author) / Mandarino, Lawrence J. (Author) / Coletta, Dawn (Author) / College of Liberal Arts and Sciences (Contributor)
Created2016-07-18
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Description

We have previously hypothesized a biological pathway of activity-dependent synaptic plasticity proteins that addresses the dual genetic and environmental contributions to schizophrenia. Accordingly, variations in the immediate early gene EGR3, and its target ARC, should influence schizophrenia susceptibility. We used a pooled Next-Generation Sequencing approach to identify variants across these

We have previously hypothesized a biological pathway of activity-dependent synaptic plasticity proteins that addresses the dual genetic and environmental contributions to schizophrenia. Accordingly, variations in the immediate early gene EGR3, and its target ARC, should influence schizophrenia susceptibility. We used a pooled Next-Generation Sequencing approach to identify variants across these genes in U.S. populations of European (EU) and African (AA) descent. Three EGR3 and one ARC SNP were selected and genotyped for validation, and three SNPs were tested for association in a replication cohort. In the EU group of 386 schizophrenia cases and 150 controls EGR3 SNP rs1877670 and ARC SNP rs35900184 showed significant associations (p = 0.0078 and p = 0.0275, respectively). In the AA group of 185 cases and 50 controls, only the ARC SNP revealed significant association (p = 0.0448). The ARC SNP did not show association in the Han Chinese (CH) population. However, combining the EU, AA, and CH groups revealed a highly significant association of ARC SNP rs35900184 (p = 2.353 x 10-7; OR [95% CI] = 1.54 [1.310–1.820]). These findings support previously reported associations between EGR3 and schizophrenia. Moreover, this is the first report associating an ARC SNP with schizophrenia and supports recent large-scale GWAS findings implicating the ARC complex in schizophrenia risk. These results support the need for further investigation of the proposed pathway of environmentally responsive, synaptic plasticity-related, schizophrenia genes.

ContributorsHuentelman, Matthew J. (Author) / Muppana, Leela (Author) / Courneveaux, Jason J. (Author) / Dinu, Valentin (Author) / Pruzin, Jeremy J. (Author) / Reiman, Rebecca (Author) / Borish, Cassie N. (Author) / De Both, Matt (Author) / Ahmed, Amber (Author) / Todorov, Alexandre (Author) / Cloninger, C. Robert (Author) / Zhang, Rui (Author) / Ma, Jie (Author) / Gallitano, Amelia L. (Author) / College of Health Solutions (Contributor)
Created2015-10-16