Timothy P. Ryan

Caenorhabditis elegans in Parkinson's disease drug discovery: Addressing an unmet medical need

It has been over forty years since dopamine neuron degeneration in the substantia nigra and Lewy body formation within surviving cells were described as the pathological hallmarks of Parkinsons disease (PD). Although research in the intervening decades particularly in the last twenty-five years has yielded a variety of robust animal models and invaluable mechanistic insights into PD-associated neuronal dysfunction and cell death, therapeutic agents have not been forthcoming to alter the course of PD. Recently, the screening of experimental therapeutics for PD has been pursued through the use of genetically tractable models, such as the nematode Caenorhabditis elegans. This simple worm remarkably recapitulates the basic cellular and molecular pathways associated with PD, is amenable to facile genetic methods, and through the use of high-throughput screening technologies, provides powerful new opportunities for the in vivo identification of therapeutic targets. In this review we briefly describe the utility that the C. elegans model system may have for PD drug discovery.

Strategic applications of toxicogenomics in early drug discovery

Productivity issues facing the pharmaceutical industry are numerous, and the current challenges come in the face of an aging population and a demand for new and better medications. These challenges call for improvement in the drug discovery and development process, which paradoxically comes on the heels of remarkable scientific advances and in an era of great opportunity in medical science. Despite these advances, the pharmaceutical industry has yet to translate breakthroughs in new technologies, including genomics, into new drug therapies for unmet medical needs. The strategic application of toxicogenomics to the earliest stages of a drug discovery program offers a valuable opportunity to identify potential safety hurdles earlier than is the norm today. We propose that using genomics predictively (in vitro to predict outcomes in vivo and short-term studies in vivo to predict safety issues in longer studies) can assist in reducing inefficiency in the current paradigm, which is still heavily weighted on traditional endpoints from lengthy in vivo studies. Implementation of these strategies will assist in solving the current pharmaceutical pipeline productivity dilemma of long cycle times and unacceptable attrition rates in the preclinical drug discovery process.

Pulmonary Ferritin: Differential Effects of Hyperoxic Lung Injury on Subunit mRNA Levels

Ferritin is an iron storage protein that is regulated at the transcriptional and transcriptional levels, resulting in a complex mixture of tissue- and condition-specific isoforms. The protein shell of ferritin is composed of 24 subunits of two types (heavy or light), which are encoded by two distinct and independently regulated genes. In the present studies, the isoform profile for lung ferritin differed from other tissues (liver, spleen, and heart) as determined by isoelectric focusing (IEF) and polyacrylamide gel electrophoresis (PAGE). Lung ferritin was composed of equal amounts of heavy and light subunits. Differences in isoform profiles were the result of tissue-specific differential expression of the ferritin subunit genes as demonstrated by Northern blot analyses. Like heart ferritin, lung ferritin exhibited a low iron content that did not increase extensively in response to iron challenge, which contrasts with ferritins isolated from liver or spleen. When animals were exposed to hyperoxic conditions (95% oxygen for up to 60 h), ferritin heavy subunit mRNA levels did not markedly change at any of the investigated time points. In contrast, ferritin light subunit mRNA increased severalfold in response to hyperoxic exposure. Investigation of the cytoplasmic distribution of ferritin mRNA showed that a substantial portion was associated with the ribonucleoprotein (RNP) fraction of the cytosol, suggesting that a pool of untranslated ferritin mRNA exists in the lung. Upon hyperoxic insult, all ferritin light subunit mRNA pools (RNP, monosomal, polysomal) were elevated, although a specific shift from RNP to polysomal pools was not evident. Therefore, the increase in translatable ferritin mRNA in response to hyperoxia resulted from transcriptional rather than specific translational activation. The observed pattern of light chain-specific transcriptional induction of ferritin is consistent with the hypothesis that hyperoxic lung injury is at least partially iron mediated.

Diquat-dependent protein carbonyl formation: Identification of lipid-dependent and lipid-independent pathways

In a previous report on diquat-dependent oxidative damage in rat hepatic microsomes, protein oxidation, as measured by protein carbonyl (PC) formation, was observed in addition to lipid peroxidation (LP). Both phenomena were antioxidant sensitive. Inhibition of PC formation was somewhat surprising given the proposed mechanism of metal-catalyzed protein oxidation. Studies reported here examined diquat-dependent PC formation in greater detail. In rat hepatic microsomes, diquat-dependent thiobarbituric acid-reactive substances (TBARS) and PC formation were time and concentration dependent. In this system, LP was inhibited completely by U-74006F or U-78517G, whereas PC formation was inhibited only partially by these antioxidants. In an essentially lipid-free system consisting of purified rat hepatic cytochrome P450 reductase, BSA and an NADPH-generating system, PC formation was also observed, but was not antioxidant-sensitive. Under these conditions, minimal diquat-dependent TBARS formation was observed. The observation of relative antioxidant insensitivity is consistent with H2O2 (generated during the diquat redox cycle) catalyzing protein oxidation via a site-specific, metal-catalyzed mechanism. Thus, different pathways would appear to be involved in diquat-dependent PC formation in lipid-containing and lipid-free systems. Carbon tetrachloride induces LP following reductive activation to the trichloromethyl free radical, a pathway not directly involving H2O2 generation. In the microsomal system, CCl4 induced TBARS and PC formation, both of which were completely inhibitable by antioxidants. Taken together, these data suggest that diquat induces PC formation by lipid-dependent (antioxidant-sensitive) and lipid-independent (antioxidant-insensitive) pathways. In microsomes, both pathways contribute to diquat-dependent PC formation. Data for the lipid-independent pathway are consistent with the mechanism of metal-catalyzed protein oxidation proposed by Stadtman and colleagues (reviewed in Free Radic Biol Med 9: 315-325, 1990), while the lipid-dependent pathway is likely secondary to LP itself--via a Michael-type addition reaction between hydroxyalkenals and protein sulfhydryl groups, amino groups or other protein nucleophiles. The latter pathway is also responsible for carbon tetrachloride-dependent PC formation. Additional studies are in progress to further characterize the lipid-independent mechanism.

Kainic Acid-induced F-344 Rat model of Mesial Temporal Lobe Epilepsy: Gene Expression and Canonical Pathways

Mesial temporal lobe epilepsy (MTLE) is a severe neurological condition of unknown pathogenesis for which several animal models have been developed. To obtain a better understanding of the underlying molecular mechanisms and identify potential biomarkers of lesion progression, we used a rat kainic acid (KA) treatment model of MTLE coupled with global gene expression analysis to examine temporal (four hours, days 3, 14, or 28) gene regulation relative to hippocampal histopathological changes. The authors recommend reviewing the companion histopathology paper (Sharma et al. 2008) to get a better understanding of the work presented here. Analysis of filtered gene expression data using Ingenuity Pathways Analysis (Ingenuity Systems, http://www.ingenuity.com) revealed that a number of genes pertaining to neuronal plasticity (RhoA, Rac1, Cdc42, BDNF, and Trk), neurodegeneration (Caspase3, Calpain 1, Bax, a Cytochrome c, and Smac/Diablo), and inflammation/immune-response pathways (TNF-α, CCL2, Cox2) were modulated in a temporal fashion after KA treatment. Expression changes for selected genes known to have a role in neuronal plasticity were subsequently validated by quantitative polymerase chain reaction (qPCR). Notably, canonical pathway analysis revealed that a number of genes within the axon guidance signaling canonical pathway were up-regulated from Days 3 to 28, which correlated with aberrant mossy fiber (MF) sprouting observed histologically beginning at Day 6. Importantly, analysis of the gene expression data also identified potential biomarkers for monitoring neurodegeneration (Cox2) and neuronal/synaptic plasticity (Kalrn).

Gene expression analysis in a canine model of X-linked Alport syndrome

Chronic kidney disease (CKD) often culminates in renal failure as a consequence of progressive interstitial fibrosis and is an important cause of illness and death in dogs. Identification of disease biomarkers and gene expression changes will yield valuable information regarding the specific biological pathways involved in disease progression. Toward these goals, gene expression changes in the renal cortex of dogs with X-linked Alport syndrome (XLAS) were examined using microarray technology. Extensive changes in inflammatory, metabolic, immune, and extracellular matrix biology were revealed in affected dogs. Statistical analysis showed 133 genes that were robustly induced or repressed in affected animals relative to age-matched littermates. Altered expression of numerous major histocompatibility complex (MHC) molecules suggests that the immune system plays a significant role in XLAS. Increased expression of COL4A1 and TIMP-1 at the end stage of disease supports the suggestion that expression increases in association with progression of fibrosis and confirms an observation of increased COL4A1 protein expression. Clusterin may function as one of the primary defenses of the renal cortex against progressive injury in dogs with XLAS, as demonstrated here by increased CLU gene expression. Cellular mechanisms that function during excess oxidative stress might also act to deter renal damage, as evidenced by alterations in gene expression of SOD1, ACO1, FDXR, and GPX1. This investigation provides a better understanding of interstitial fibrosis pathogenesis, and potential biomarkers for early detection, factors that are essential to discovering more effective treatments thereby reducing clinical illness and death due to CKD.

Minor compensatory changes in SAGE Mdr1a (P-gp), Bcrp, and Mrp2 knockout rats do not detract from their utility in the study of transporter-mediated pharmacokinetics.

Mdr1a-, Bcrp-, and Mrp2-knockout rats are a more practical species for absorption, distribution, metabolism, and excretion (ADME) studies than murine models and previously demonstrated expected alterations in the pharmacokinetics of various probe substrates. At present, gene expression and pathology changes were systematically studied in the small intestine, liver, kidney, and brain tissue from male SAGE Mdr1a, Bcrp, and Mrp2 knockout rats versus wild-type Sprague-Dawley controls. Gene expression data supported the relevant knockout genotype. As expected, Mrp2 knockout rats were hyperbilirubinemic and exhibited upregulation of hepatic Mrp3. Overall, few alterations were observed within 112 ADME-relevant genes. The two potentially most consequential changes were upregulation of intestinal carboxylesterase in Mdr1a knockouts and catechol-O-methyltransferase in all tissues of Bcrp knockout rats. Previously reported upregulation of hepatic Mdr1b P-glycoprotein in proprietary Wistar Mdr1a knockout rats was not observed in the SAGE counterpart investigated herein. Relative liver and kidney weights were 22–53% higher in all three knockouts, with microscopic increases in hepatocyte size in Mdr1a and Mrp2 knockout rats and glomerular size in Bcrp and Mrp2 knockouts. Increased relative weight of clearing organs is quantitatively consistent with reported increases in the clearance of drugs that are not substrates of the knocked-out transporter. Overall, SAGE knockout rats demonstrated modest compensatory changes, which do not preclude their general application to study transporter-mediated pharmacokinetics. However, until future studies elucidate the magnitude of functional change, caution is warranted in rare instances of extensive metabolism by catechol-O-methyltransferase in Bcrp knockouts and intestinal carboxylesterase in Mdr1a knockout rats, specifically for molecules with free catechol groups and esters subject to gut-wall hydrolysis.

Co-Prescription Trends in a Large Cohort of Subjects Predict Substantial Drug-Drug Interactions

Pharmaceutical prescribing and drug-drug interaction data underlie recommendations on drug combinations that should be avoided or closely monitored by prescribers. Because the number of patients taking multiple medications is increasing, a comprehensive view of prescribing patterns in patients is important to better assess real world pharmaceutical response and evaluate the potential for multi-drug interactions. We obtained self-reported prescription data from NHANES surveys between 1999 and 2010, and confirm the previously reported finding of increasing drug use in the elderly. We studied co-prescription drug trends by focusing on the 2009-2010 survey, which contains prescription data on 690 drugs used by 10,537 subjects. We found that medication profiles were unique for individuals aged 65 years or more, with ≥98 unique drug regimens encountered per 100 subjects taking 3 or more medications. When drugs were viewed by therapeutic class, it was found that the most commonly prescribed drugs were not the most commonly co-prescribed drugs for any of the 16 drug classes investigated. We cross-referenced these medication lists with drug interaction data from Drugs.com to evaluate the potential for drug interactions. The number of drug alerts rose proportionally with the number of co-prescribed medications, rising from 3.3 alerts for individuals prescribed 5 medications to 11.7 alerts for individuals prescribed 10 medications. We found 22% of elderly subjects taking both a substrate and inhibitor of a given cytochrome P450 enzyme, and 4% taking multiple inhibitors of the same enzyme simultaneously. By examining drug pairs prescribed in 0.1% of the population or more, we found low agreement between co-prescription rate and co-discussion in the literature. These data show that prescribing trends in treatment could drive a large extent of individual variability in drug response, and that current pairwise approaches to assessing drug-drug interactions may be inadequate for predicting real world outcomes.

Genome-wide screen for modulation of hepatic Apolipoprotein A-I (ApoA-I) secretion

Background: Increasing HDL-c through ApoA-I expression is hypothesized to reduce cardiovascular deaths significantly. Results: Genes that regulate hepatocyte ApoA-I secretion were identified using 21,789 siRNAs. Conclusion: Forty genes of interest were confirmed as regulators of ApoA-I production by hepatocytes. Significance: This study provides functional genomics-based data for exploring new mechanisms by which ApoA-I levels may be regulated. Control of plasma cholesterol levels is a major therapeutic strategy for management of coronary artery disease (CAD). Although reducing LDL cholesterol (LDL-c) levels decreases morbidity and mortality, this therapeutic intervention only translates into a 25–40% reduction in cardiovascular events. Epidemiological studies have shown that a high LDL-c level is not the only risk factor for CAD; low HDL cholesterol (HDL-c) is an independent risk factor for CAD. Apolipoprotein A-I (ApoA-I) is the major protein component of HDL-c that mediates reverse cholesterol transport from tissues to the liver for excretion. Therefore, increasing ApoA-I levels is an attractive strategy for HDL-c elevation. Using genome-wide siRNA screening, targets that regulate hepatocyte ApoA-I secretion were identified through transfection of 21,789 siRNAs into hepatocytes whereby cell supernatants were assayed for ApoA-I. Approximately 800 genes were identified and triaged using a convergence of information, including genetic associations with HDL-c levels, tissue-specific gene expression, druggability assessments, and pathway analysis. Fifty-nine genes were selected for reconfirmation; 40 genes were confirmed. Here we describe the siRNA screening strategy, assay implementation and validation, data triaging, and example genes of interest. The genes of interest include known and novel genes encoding secreted enzymes, proteases, G-protein-coupled receptors, metabolic enzymes, ion transporters, and proteins of unknown function. Repression of farnesyltransferase (FNTA) by siRNA and the enzyme inhibitor manumycin A caused elevation of ApoA-I secretion from hepatocytes and from transgenic mice expressing hApoA-I and cholesterol ester transfer protein transgenes. In total, this work underscores the power of functional genetic assessment to identify new therapeutic targets.

Data-driven analysis approach for biomarker discovery using molecular-profiling technologies

Abstract High-throughput molecular-profiling technologies provide rapid, efficient and systematic approaches to search for biomarkers. Supervised learning algorithms are naturally suited to analyse a large amount of data generated using these technologies in biomarker discovery efforts. The study demonstrates with two examples a data-driven analysis approach to analysis of large complicated datasets collected in high-throughput technologies in the context of biomarker discovery. The approach consists of two analytic steps: an initial unsupervised analysis to obtain accurate knowledge about sample clustering, followed by a second supervised analysis to identify a small set of putative biomarkers for further experimental characterization. By comparing the most widely applied clustering algorithms using a leukaemia DNA microarray dataset, it was established that principal component analysis-assisted projections of samples from a high-dimensional molecular feature space into a few low dimensional subspaces provides a more effective and accurate way to explore visually and identify data structures that confirm intended experimental effects based on expected group membership. A supervised analysis method, shrunken centroid algorithm, was chosen to take knowledge of sample clustering gained or confirmed by the first step of the analysis to identify a small set of molecules as candidate biomarkers for further experimentation. The approach was applied to two molecular-profiling studies. In the first study, PCA-assisted analysis of DNA microarray data revealed that discrete data structures exist in rat liver gene expression and correlated with blood clinical chemistry and liver pathological damage in response to a chemical toxicant diethylhexylphthalate, a peroxisome-proliferator-activator receptor agonist. Sixteen genes were then identified by shrunken centroid algorithm as the best candidate biomarkers for liver damage. Functional annotations of these genes revealed roles in acute phase response, lipid and fatty acid metabolism and they are functionally relevant to the observed toxicities. In the second study, 26 urine ions identified from a GC/MS spectrum, two of which were glucose fragment ions included as positive controls, showed robust changes with the development of diabetes in Zucker diabetic fatty rats. Further experiments are needed to define their chemical identities and establish functional relevancy to disease development.