Cory B. Giles

Identification of a novel senolytic agent, navitoclax, targeting the Bcl‐2 family of anti‐apoptotic factors

Clearing senescent cells extends healthspan in mice. Using a hypothesis‐driven bioinformatics‐based approach, we recently identified pro‐survival pathways in human senescent cells that contribute to their resistance to apoptosis. This led to identification of dasatinib (D) and quercetin (Q) as senolytics, agents that target some of these pathways and induce apoptosis preferentially in senescent cells. Among other pro‐survival regulators identified was Bcl‐xl. Here, we tested whether the Bcl‐2 family inhibitors, navitoclax (N) and TW‐37 (T), are senolytic. Like D and Q, N is senolytic in some, but not all types of senescent cells: N reduced viability of senescent human umbilical vein epithelial cells (HUVECs), IMR90 human lung fibroblasts, and murine embryonic fibroblasts (MEFs), but not human primary preadipocytes, consistent with our previous finding that Bcl‐xl siRNA is senolytic in HUVECs, but not preadipocytes. In contrast, T had little senolytic activity. N targets Bcl‐2, Bcl‐xl, and Bcl‐w, while T targets Bcl‐2, Bcl‐xl, and Mcl‐1. The combination of Bcl‐2, Bcl‐xl, and Bcl‐w siRNAs was senolytic in HUVECs and IMR90 cells, while combination of Bcl‐2, Bcl‐xl, and Mcl‐1 siRNAs was not. Susceptibility to N correlated with patterns of Bcl‐2 family member proteins in different types of human senescent cells, as has been found in predicting response of cancers to N. Thus, N is senolytic and acts in a potentially predictable cell type‐restricted manner. The hypothesis‐driven, bioinformatics‐based approach we used to discover that dasatinib (D) and quercetin (Q) are senolytic can be extended to increase the repertoire of senolytic drugs, including additional cell type‐specific senolytic agents.

Aging Exacerbates Obesity-induced Cerebromicrovascular Rarefaction, Neurovascular Uncoupling, and Cognitive Decline in Mice

Epidemiological studies show that obesity has deleterious effects on the brain and cognitive function in the elderly population. However, the specific mechanisms through which aging and obesity interact to promote cognitive decline remain unclear. To test the hypothesis that aging exacerbates obesity-induced cerebromicrovascular impairment, we compared young (7 months) and aged (24 months) high-fat diet-fed obese C57BL/6 mice. We found that aging exacerbates the obesity-induced decline in microvascular density both in the hippocampus and in the cortex. The extent of hippocampal microvascular rarefaction and the extent of impairment of hippocampal-dependent cognitive function positively correlate. Aging exacerbates obesity-induced loss of pericyte coverage on cerebral microvessels and alters hippocampal angiogenic gene expression signature, which likely contributes to microvascular rarefaction. Aging also exacerbates obesity-induced oxidative stress and induction of NADPH oxidase and impairs cerebral blood flow responses to whisker stimulation. Collectively, obesity exerts deleterious cerebrovascular effects in aged mice, promoting cerebromicrovascular rarefaction and neurovascular uncoupling. The morphological and functional impairment of the cerebral microvasculature in association with increased blood-brain barrier disruption and neuroinflammation (Tucsek Z, Toth P, Sosnowsk D, et al. Obesity in aging exacerbates blood-brain barrier disruption, neuroinflammation and oxidative stress in the mouse hippocampus: effects on expression of genes involved in beta-amyloid generation and Alzheimers disease. J Gerontol Biol Med Sci. 2013. In press, PMID: 24269929) likely contribute to obesity-induced cognitive decline in aging.

Large-scale directional relationship extraction and resolution

BackgroundRelationships between entities such as genes, chemicals, metabolites, phenotypes and diseases in MEDLINE are often directional. That is, one may affect the other in a positive or negative manner. Detection of causality and direction is key in piecing pathways together and in examining possible implications of experimental results. Because of the size and growth of biomedical literature, it is increasingly important to be able to automate this process as much as possible.ResultsHere we present a method of relation extraction using dependency graph parsing with SVM classification. We tested the SVM classifier first on gold standard corpora from GENIA and find it achieved 82% precision and 94.8% recall (F-measure of 87.9) on these standardized test sets. We then applied the entire system to all available MEDLINE abstracts for two target interactions with known effects. We find that while some directional relations are extracted with low ambiguity, others are apparently contradictory, at least when considered in an isolated context. When examined, it is apparent some are dependent upon the surrounding context (e.g. whether the relationship referred to short-term or long-term effects, or whether the focus was extracellular versus intracellular).ConclusionThesaurus-based directional relation extraction can be done with reasonable accuracy, but is prone to false-positives on larger corpora due to noun modifiers. Furthermore, methods of resolving or disambiguating relationship context and contingencies are important for large-scale corpora.

ELTD1, a potential new biomarker for gliomas

BACKGROUND Glioblastoma multiforme (GBM), a high-grade glioma, is characterized by being diffuse, invasive, and highly angiogenic and has a very poor prognosis. Identification of new biomarkers could help in the further diagnosis of GBM. OBJECTIVE To identify ELTD1 (epidermal growth factor, latrophilin, and 7 transmembrane domain-containing protein 1 on chromosome 1) as a putative glioma-associated marker via a bioinformatic method. METHODS We used advanced data mining and a novel bioinformatics method to predict ELTD1 as a potential novel biomarker that is associated with gliomas. Validation was done with immunohistochemistry, which was used to detect levels of ELTD1 in human high-grade gliomas and rat F98 glioma tumors. In vivo levels of ELTD1 in rat F98 gliomas were assessed using molecular magnetic resonance imaging. RESULTS ELTD1 was found to be significantly higher (P = .03) in high-grade gliomas (50 patients) compared with low-grade gliomas (21 patients) and compared well with traditional immunohistochemistry markers including vascular endothelial growth factor, glucose transporter 1, carbonic anhydrase IX, and hypoxia-inducible factor 1α. ELTD1 gene expression indicates an association with grade, survival across grade, and an increase in the mesenchymal subtype. Significantly high (P < .001) in vivo levels of ELTD1 were additionally found in F98 tumors compared with normal brain tissue. CONCLUSION Results of this study strongly suggests that associative analysis was able to accurately identify ELTD1 as a putative glioma-associated biomarker. The detection of ELTD1 was also validated in both rodent and human gliomas and may serve as an additional biomarker for gliomas in preclinical and clinical diagnosis of gliomas.

Aging exacerbates hypertension-induced cerebral microhemorrhages in mice: role of resveratrol treatment in vasoprotection

Recent studies demonstrate that aging exacerbates hypertension‐induced cognitive decline, but the specific age‐related mechanisms remain elusive. Cerebral microhemorrhages (CMHs) are associated with rupture of small intracerebral vessels and are thought to progressively impair neuronal function. To determine whether aging exacerbates hypertension‐induced CMHs young (3 months) and aged (24 months) mice were treated with angiotensin II plus L‐NAME. We found that the same level of hypertension leads to significantly earlier onset and increased incidence of CMHs in aged mice than in young mice, as shown by neurological examination, gait analysis, and histological assessment of CMHs in serial brain sections. Hypertension‐induced cerebrovascular oxidative stress and redox‐sensitive activation of matrix metalloproteinases (MMPs) were increased in aging. Treatment of aged mice with resveratrol significantly attenuated hypertension‐induced oxidative stress, inhibited vascular MMP activation, significantly delayed the onset, and reduced the incidence of CMHs. Collectively, aging promotes CMHs in mice likely by exacerbating hypertension‐induced oxidative stress and MMP activation. Therapeutic strategies that reduce microvascular oxidative stress and MMP activation may be useful for the prevention of CMHs, protecting neurocognitive function in high‐risk elderly patients.

Caloric restriction confers persistent anti-oxidative, pro-angiogenic, and anti-inflammatory effects and promotes anti-aging miRNA expression profile in cerebromicrovascular endothelial cells of aged rats

In rodents, moderate caloric restriction (CR) without malnutrition exerts significant cerebrovascular protective effects, improving cortical microvascular density and endothelium-dependent vasodilation, but the underlying cellular mechanisms remain elusive. To elucidate the persisting effects of CR on cerebromicrovascular endothelial cells (CMVECs), primary CMVECs were isolated from young (3 mo old) and aged (24 mo old) ad libitum-fed and aged CR F344xBN rats. We found an age-related increase in cellular and mitochondrial oxidative stress, which is prevented by CR. Expression and transcriptional activity of Nrf2 are both significantly reduced in aged CMVECs, whereas CR prevents age-related Nrf2 dysfunction. Expression of miR-144 was upregulated in aged CMVECs, and overexpression of miR-144 significantly decreased expression of Nrf2 in cells derived from both young animals and aged CR rats. Overexpression of a miR-144 antagomir in aged CMVECs significantly decreases expression of miR-144 and upregulates Nrf2. We found that CR prevents age-related impairment of angiogenic processes, including cell proliferation, adhesion to collagen, and formation of capillary-like structures and inhibits apoptosis in CMVECs. CR also exerts significant anti-inflammatory effects, preventing age-related increases in the transcriptional activity of NF-κB and age-associated pro-inflammatory shift in the endothelial secretome. Characterization of CR-induced changes in miRNA expression suggests that they likely affect several critical functions in endothelial cell homeostasis. The predicted regulatory effects of CR-related differentially expressed miRNAs in aged CMVECs are consistent with the anti-aging endothelial effects of CR observed in vivo. Collectively, we find that CR confers persisting anti-oxidative, pro-angiogenic, and anti-inflammatory cellular effects, preserving a youthful phenotype in rat cerebromicrovascular endothelial cells, suggesting that through these effects CR may improve cerebrovascular function and prevent vascular cognitive impairment.

Experimental validation of 5 in-silico predicted glioma biomarkers

BACKGROUND Glioblastoma multiforme (GBM) is a high-grade glioma with poor prognosis. Identification of new biomarkers specific to GBM could help in disease diagnosis. We have developed and validated a bioinformatics method to predict proteins likely to be suitable as glioma biomarkers via a global microarray meta-analysis to identify uncharacterized genes consistently coexpressed with known glioma-associated genes. METHODS A novel bioinformatics method was implemented called global microarray meta-analysis, using approximately 16,000 microarray experiments to identify uncharacterized genes consistently coexpressed with known glioma-associated genes. These novel biomarkers were validated as proteins highly expressed in human gliomas varying in tumor grades using immunohistochemistry. Glioma gene databases were used to assess delineation of expression of these markers in varying glioma grades and subtypes of GBM. RESULTS We have identified 5 potential biomarkers-spondin1, Plexin-B2, SLIT3, fibulin-1, and LINGO1-that were validated as proteins highly expressed on the surface of human gliomas using immunohistochemistry. Expression of spondin1, Plexin-B2, and SLIT3 was significantly higher (P < .01) in high-grade gliomas than in low-grade gliomas. These biomarkers were significant discriminators in grade IV gliomas compared with either grade III or II tumors and also distinguished between GBM subclasses. CONCLUSIONS This study strongly suggests that this type of bioinformatics approach has high translational potential to rapidly discern which poorly characterized proteins may be of clinical relevance.

GenomeRunner: Automating genome exploration

MOTIVATION One of the challenges in interpreting high-throughput genomic studies such as a genome-wide associations, microarray or ChIP-seq is their open-ended nature-once a set of experimentally identified regions is identified as statistically significant, at least two questions arise: (i) besides P-value, do any of these significant regions stand out in terms of biological implications? (ii) Does the set of significant regions, as a whole, have anything in common genome wide? These issues are difficult to address because of the growing number of annotated genomic features (e.g. single nucleotide polymorphisms, transcription factor binding sites, methylation peaks, etc.), and it is difficult to know a priori which features would be most fruitful to analyze. Our goal is to provide partial automation of this process to begin examining associations between experimental features and annotated genomic regions in a hypothesis-free, data-driven manner. RESULTS We created GenomeRunner-a tool for automating annotation and enrichment of genomic features of interest (FOI) with annotated genomic features (GFs), in different organisms. Besides simple association of FOIs with known GFs GenomeRunner tests whether the enriched FOIs, as a group, are statistically associated with a large and growing set of genomic features. AVAILABILITY GenomeRunner setup files and source code are freely available at http://sourceforge.net/projects/genomerunner. CONTACT mikhail-dozmorov@omrf.org; Jonathan-Wren@omrf.org; jdwren@gmail.com SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

Predicting gene ontology from a global meta-analysis of 1-color microarray experiments

BackgroundGlobal meta-analysis (GMA) of microarray data to identify genes with highly similar co-expression profiles is emerging as an accurate method to predict gene function and phenotype, even in the absence of published data on the gene(s) being analyzed. With a third of human genes still uncharacterized, this approach is a promising way to direct experiments and rapidly understand the biological roles of genes. To predict function for genes of interest, GMA relies on a guilt-by-association approach to identify sets of genes with known functions that are consistently co-expressed with it across different experimental conditions, suggesting coordinated regulation for a specific biological purpose. Our goal here is to define how sample, dataset size and ranking parameters affect prediction performance.Results13,000 human 1-color microarrays were downloaded from GEO for GMA analysis. Prediction performance was benchmarked by calculating the distance within the Gene Ontology (GO) tree between predicted function and annotated function for sets of 100 randomly selected genes. We find the number of new predicted functions rises as more datasets are added, but begins to saturate at a sample size of approximately 2,000 experiments. For the gene set used to predict function, we find precision to be higher with smaller set sizes, yet with correspondingly poor recall and, as set size is increased, recall and F-measure also tend to increase but at the cost of precision.ConclusionsOf the 20,813 genes expressed in 50 or more experiments, at least one predicted GO category was found for 72.5% of them. Of the 5,720 genes without GO annotation, 4,189 had at least one predicted ontology using top 40 co-expressed genes for prediction analysis. For the remaining 1,531 genes without GO predictions or annotations, ~17% (257 genes) had sufficient co-expression data yet no statistically significantly overrepresented ontologies, suggesting their regulation may be more complex.

Absence of genomic hypomethylation or regulation of cytosine-modifying enzymes with aging in male and female mice

BackgroundChanges to the epigenome with aging, and DNA modifications in particular, have been proposed as a central regulator of the aging process, a predictor of mortality, and a contributor to the pathogenesis of age-related diseases. In the central nervous system, control of learning and memory, neurogenesis, and plasticity require changes in cytosine methylation and hydroxymethylation. Although genome-wide decreases in methylation with aging are often reported as scientific dogma, primary research reports describe decreases, increases, or lack of change in methylation and hydroxymethylation and their principle regulators, DNA methyltransferases and ten-eleven translocation dioxygenases in the hippocampus. Furthermore, existing data are limited to only male animals.ResultsThrough examination of the hippocampus in young, adult, and old male and female mice by antibody-based, pyrosequencing, and whole-genome oxidative bisulfite sequencing methods, we provide compelling evidence that contradicts the genomic hypomethylation theory of aging. We also demonstrate that expression of DNA methyltransferases and ten-eleven translocation dioxygenases is not differentially regulated with aging or between the sexes, including the proposed cognitive aging regulator DNMT3a2. Using oxidative bisulfite sequencing that discriminates methylation from hydroxymethylation and by cytosine (CG and non-CG) context, we observe sex differences in average CG methylation and hydroxymethylation of the X chromosome, and small age-related differences in hydroxymethylation of CG island shores and shelves, and methylation of promoter regions.ConclusionThese findings clarify a long-standing misconception of the epigenomic response to aging and demonstrate the need for studies of base-specific methylation and hydroxymethylation with aging in both sexes.