ASU Scholarship Showcase

Background: The discovery of genetic associations is an important factor in the understanding of human illness to derive disease pathways. Identifying multiple interacting genetic mutations associated with disease remains challenging in studying the etiology of complex diseases. And although recently new single nucleotide polymorphisms (SNPs) at genes implicated in immune response, cholesterol/lipid metabolism, and cell membrane processes have been confirmed by genome-wide association studies (GWAS) to be associated with late-onset Alzheimer's disease (LOAD), a percentage of AD heritability continues to be unexplained. We try to find other genetic variants that may influence LOAD risk utilizing data mining methods.

Methods: Two different approaches were devised to select SNPs associated with LOAD in a publicly available GWAS data set consisting of three cohorts. In both approaches, single-locus analysis (logistic regression) was conducted to filter the data with a less conservative p-value than the Bonferroni threshold; this resulted in a subset of SNPs used next in multi-locus analysis (random forest (RF)). In the second approach, we took into account prior biological knowledge, and performed sample stratification and linkage disequilibrium (LD) in addition to logistic regression analysis to preselect loci to input into the RF classifier construction step.

Results: The first approach gave 199 SNPs mostly associated with genes in calcium signaling, cell adhesion, endocytosis, immune response, and synaptic function. These SNPs together with APOE and GAB2 SNPs formed a predictive subset for LOAD status with an average error of 9.8% using 10-fold cross validation (CV) in RF modeling. Nineteen variants in LD with ST5, TRPC1, ATG10, ANO3, NDUFA12, and NISCH respectively, genes linked directly or indirectly with neurobiology, were identified with the second approach. These variants were part of a model that included APOE and GAB2 SNPs to predict LOAD risk which produced a 10-fold CV average error of 17.5% in the classification modeling.

Conclusions: With the two proposed approaches, we identified a large subset of SNPs in genes mostly clustered around specific pathways/functions and a smaller set of SNPs, within or in proximity to five genes not previously reported, that may be relevant for the prediction/understanding of AD.

Background: Glioblastoma is the most aggressive primary central nervous tumor and carries a very poor prognosis. Invasion precludes effective treatment and virtually assures tumor recurrence. In the current study, we applied analytical and bioinformatics approaches to identify a set of microRNAs (miRs) from several different human glioblastoma cell lines that exhibit significant differential expression between migratory (edge) and migration-restricted (core) cell populations. The hypothesis of the study is that differential expression of miRs provides an epigenetic mechanism to drive cell migration and invasion.

Results: Our research data comprise gene expression values for a set of 805 human miRs collected from matched pairs of migratory and migration-restricted cell populations from seven different glioblastoma cell lines. We identified 62 down-regulated and 2 up-regulated miRs that exhibit significant differential expression in the migratory (edge) cell population compared to matched migration-restricted (core) cells. We then conducted target prediction and pathway enrichment analysis with these miRs to investigate potential associated gene and pathway targets. Several miRs in the list appear to directly target apoptosis related genes. The analysis identifies a set of genes that are predicted by 3 different algorithms, further emphasizing the potential validity of these miRs to promote glioblastoma.

Conclusions: The results of this study identify a set of miRs with potential for decreased expression in invasive glioblastoma cells. The verification of these miRs and their associated targeted proteins provides new insights for further investigation into therapeutic interventions. The methodological approaches employed here could be applied to the study of other diseases to provide biomedical researchers and clinicians with increased opportunities for therapeutic interventions.

Despite increasing interest in the effects of triclosan and triclocarban on human biology, current knowledge is still limited on the impact of these additives to antimicrobial personal care products on the human microbiome. A carefully designed recent study published in mSphere by Poole and colleagues [A. C. Poole et al., mSphere 1(3):e00056-15, 2016, http://dx.doi.org/10.1128/mSphere.00056-15] highlights both the power of novel methodologies for microbiome elucidation and the longstanding challenge of employing small-cohort studies to inform risk assessment for chemicals of ubiquitous use in modern society.

Thousands of chemicals have been identified as contaminants of emerging concern (CECs), but prioritizing them concerning ecological and human health risks is challenging. We explored the use of sewage treatment plants as chemical observatories to conveniently identify persistent and bioaccumulative CECs, including toxic organohalides. Nationally representative samples of sewage sludge (biosolids) were analyzed for 231 CECs, of which 123 were detected. Ten of the top 11 most abundant CECs in biosolids were found to be high-production volume chemicals, eight of which representing priority chemicals, including three flame retardants, three surfactants and two antimicrobials. A comparison of chemicals detected in nationally representative biological specimens from humans and municipal biosolids revealed 70% overlap. This observed co-occurrence of contaminants in both matrices suggests that the analysis of sewage sludge can inform human health risk assessments by providing current information on toxic exposures in human populations and associated body burdens of harmful environmental pollutants.

The Florence Statement on Triclosan and Triclocarban documents a consensus of more than 200 scientists and medical professionals on the hazards of and lack of demonstrated benefit from common uses of triclosan and triclocarban. These chemicals may be used in thousands of personal care and consumer products as well as in building materials. Based on extensive peer-reviewed research, this statement concludes that triclosan and triclocarban are environmentally persistent endocrine disruptors that bioaccumulate in and are toxic to aquatic and other organisms. Evidence of other hazards to humans and ecosystems from triclosan and triclocarban is presented along with recommendations intended to prevent future harm from triclosan, triclocarban, and antimicrobial substances with similar properties and effects. Because antimicrobials can have unintended adverse health and environmental impacts, they should only be used when they provide an evidence-based health benefit. Greater transparency is needed in product formulations, and before an antimicrobial is incorporated into a product, the long-term health and ecological impacts should be evaluated.

Aquaculture production has nearly tripled in the last two decades, bringing with it a significant increase in the use of antibiotics. Using liquid chromatography/tandem mass spectrometry (LC–MS/MS), the presence of 47 antibiotics was investigated in U.S. purchased shrimp, salmon, catfish, trout, tilapia, and swai originating from 11 different countries. All samples (n = 27) complied with U.S. FDA regulations and five antibiotics were detected above the limits of detection: oxytetracycline (in wild shrimp, 7.7 ng/g of fresh weight; farmed tilapia, 2.7; farmed salmon, 8.6; farmed trout with spinal deformities, 3.9), 4-epioxytetracycline (farmed salmon, 4.1), sulfadimethoxine (farmed shrimp, 0.3), ormetoprim (farmed salmon, 0.5), and virginiamycin (farmed salmon marketed as antibiotic-free, 5.2). A literature review showed that sub-regulatory levels of antibiotics, as found here, can promote resistance development; publications linking aquaculture to this have increased more than 8-fold from 1991 to 2013. Although this study was limited in size and employed sample pooling, it represents the largest reconnaissance of antibiotics in U.S. seafood to date, providing data on previously unmonitored antibiotics and on farmed trout with spinal deformities. Results indicate low levels of antibiotic residues and general compliance with U.S. regulations. The potential for development of microbial drug resistance was identified as a key concern and research priority.

The land, water, and energy requirements of hydroponics were compared to those of conventional agriculture by example of lettuce production in Yuma, Arizona, USA. Data were obtained from crop budgets and governmental agricultural statistics, and contrasted with theoretical data for hydroponic lettuce production derived by using engineering equations populated with literature values. Yields of lettuce per greenhouse unit (815 m(2)) of 41 +/- 6.1 kg/m(2)/y had water and energy demands of 20 +/- 3.8 L/kg/y and 90,000 +/- 11,000 kJ/kg/y (+/- standard deviation), respectively. In comparison, conventional production yielded 3.9 +/- 0.21 kg/m(2)/y of produce, with water and energy demands of 250 +/- 25 L/kg/y and 1100 +/- 75 kJ/kg/y, respectively. Hydroponics offered 11 +/- 1.7 times higher yields but required 82 +/- 11 times more energy compared to conventionally produced lettuce. To the authors' knowledge, this is the first quantitative comparison of conventional and hydroponic produce production by example of lettuce grown in the southwestern United States. It identified energy availability as a major factor in assessing the sustainability of hydroponics, and it points to water-scarce settings offering an abundance of renewable energy (e.g., from solar, geothermal, or wind power) as particularly attractive regions for hydroponic agriculture.

Traditionally, hazardous chemicals have been regulated in the U.S. on a one-by-one basis, an approach that is slow, expensive and can be inefficient, as illustrated by a decades-long succession of replacing one type of organohalogen flame retardants (OHFRs) with another one, without addressing the root cause of toxicity and associated public health threats posed. The present article expounds on the need for efficient monitoring strategies and pragmatic steps in reducing environmental pollution and adverse human health impacts. A promising approach is to combine specific bioassays with state-of-the-art chemical screening to identify chemicals and chemical mixtures sharing specific modes of action (MOAs) and pathways of toxicity (PoTs). This approach could be used to identify and regulate hazardous chemicals as classes or compound families, featuring similar biological end-points, such as endocrine disruption and mutagenicity. Opportunities and potential obstacles of implementing this approach are discussed.