Loss of epigenetic information as a cause of mammalian aging

All living things experience an increase in entropy, manifested as a loss of genetic and epigenetic information. In yeast, epigenetic information is lost over time due to the relocalization of chromatin-modifying proteins to DNA breaks, causing cells to lose their identity, a hallmark of yeast aging. Using a system called "ICE" (inducible changes to the epigenome), we find that the act of faithful DNA repair advances aging at physiological, cognitive, and molecular levels, including erosion of the epigenetic landscape, cellular exdifferentiation, senescence, and advancement of the DNA methylation clock, which can be reversed by OSK-mediated rejuvenation. These data are consistent with the information theory of aging, which states that a loss of epigenetic information is a reversible cause of aging.

Emerging Role of Translational Digital Biomarkers Within Home Cage Monitoring Technologies in Preclinical Drug Discovery and Development

In drug discovery and development, traditional assessment of human patients and preclinical subjects occurs at limited time points in potentially stressful surroundings (i.e., the clinic or a test arena), which can impact data quality and welfare. However, recent advances in remote digital monitoring technologies enable the assessment of human patients and preclinical subjects across multiple time points in familiar surroundings. The ability to monitor a patient throughout disease progression provides an opportunity for more relevant and efficient diagnosis as well as improved assessment of drug efficacy and safety. In preclinical in vivo animal models, these digital technologies allow for continuous, longitudinal, and non-invasive monitoring in the home environment. This manuscript provides an overview of digital monitoring technologies for use in preclinical studies including their history and evolution, current engagement through use cases, and impact of digital biomarkers (DBs) on drug discovery and the 3Rs. We also discuss barriers to implementation and strategies to overcome them. Finally, we address data consistency and technology standards from the perspective of technology providers, end-users, and subject matter experts. Overall, this review establishes an improved understanding of the value and implementation of digital biomarker (DB) technologies in preclinical research.

Nonclinical endpoint assessment utilizing a digital vivarium cloud platform in an ovarian cancer xenograft model

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Background: Translation of preclinical data is highly dependent on the validity of the metrics for assessing disease progression and endpoint in mouse oncology models. A digital cloud platform would provide an objective and non-invasive technology allowing real-time assessment of several parameters including motion, breathing, and activity. Here, we hypothesize digital metrics can serve to predict endpoint in an ovarian cancer xenograft model with ascites, thereby improving analysis and interpretation of therapeutic efficacy data and improved adherence to the Three Rs. Methods: Six groups of athymic mice were intraperitoneally inoculated with increasing numbers of ES-2 ovarian cancer cells or control and housed in the Vium Digital Vivarium. Leveraging Vium’s readily accessible videographic and electronic records we retrospectively analyzed night time motion data using the ROC curve on GraphPad Prism and R programming. The following parameters were defined: motion loss post induction (MLPI) and motion loss from endpoint (MLFE). These were in turn compared to the conventional parameters (ie, number of tumor nodules, tumor weight, volume of ascites, and clinical signs) in terms of predicting disease and endpoint. Results: MLPI showed significantly high correlation with endpoint when graphed on a linear regression plot (R2= 0.8671; p< 0.0001), while the conventional metrics showed low correlations with endpoint: number of tumor nodules (R2= 0.1334; p= 0.1133); volume of ascites (R2= 0.2524; p= 0.0240); tumor weight (R2= 0.1162; p= 0.1413). We also showed that MLFE was significantly higher than the days from onset of first clinical sign to endpoint. Analysis of additional digital metrics are underway. Conclusions: The results support the improved ability of a digital platform to predict endpoint over conventional metrics, and earlier than manually-recorded clinical signs. These results are important as they not only provide an objective parameter to enhance study interpretation, but they also reduce the time to humane endpoint. Additionally, the continuously recorded digital metrics increase statistical power, which can be leveraged to potentially reduce the number of animals required per study.

Circulating microRNA and automated motion analysis as novel methods of assessing chemotherapy-induced peripheral neuropathy in mice

Chemotherapy-induced peripheral neuropathy (CiPN) is a serious adverse effect in the clinic, but nonclinical assessment methods in animal studies are limited to labor intensive behavioral tests or semi-quantitative microscopic evaluation. Hence, microRNA (miRNA) biomarkers and automated in-life behavioral tracking were assessed for their utility as non-invasive methods. To address the lack of diagnostic biomarkers, we explored miR-124, miR-183 and miR-338 in a CiPN model induced by paclitaxel, a well-known neurotoxic agent. In addition, conventional and Vium's innovative Digital Vivarium technology-based in-life behavioral tests and postmortem microscopic examination of the dorsal root ganglion (DRG) and the sciatic nerve were performed. Terminal blood was collected on days 8 or 16, after 20 mg/kg paclitaxel was administered every other day for total of 4 or 7 doses, respectively, for plasma miRNA quantification by RT-qPCR. DRG and sciatic nerve samples were collected from mice sacrificed on day 16 for miRNA quantification. Among the three miRNAs analyzed, only miR-124 was statistically significantly increased (5 fold and 10 fold on day 8 and day 16, respectively). The increase in circulating miR-124 correlated with cold allodynia and axonal degeneration in both DRG and sciatic nerve. Automated home cage motion analysis revealed for the first time that nighttime motion was significantly decreased (P < 0.05) in paclitaxel-dosed animals. Although both increase in circulating miR-124 and decrease in nighttime motion are compelling, our results provide positive evidence warranting further testing using additional peripheral nerve toxicants and diverse experimental CiPN models.

Real-time detection of LPS induced cytokine-storm using Vium Smart Housing

The objective of this study was to use Vium Smart Housing to determine if in-life digital readouts (e.g. changes in motion and breathing rate) can correlate with cytokine response profiles in an LPS-induced mouse model of endotoxemia. Real-time detection of cytokine release has the potential to reduce or eliminate the need for expensive blood sampling and biochemical analyses. Eighty Balb/c mice were injected with 5 mg/kg of UltraPure LPS (E. coli 0111:B4, Invivogen) or vehicle control. Subjects were housed in Vium’s Digital Vivarium, where sensors and a HD camera coupled with computer vision, data algorithms, and cloud capabilities allow for continuous monitoring of animals and collection of automated metrics such as motion, % time running on wheel and breathing rate. All study data is available in real-time. As early as 1 hr post-LPS administration, breathing rate increased from baseline, peaked 7 hours post-induction (8.7%±3.5% vehicle vs 39.5±3.1% LPS treated) and remained elevated relative to vehicle for over 24 hrs (p&lt;0.05). Breathing rate changes were accompanied by decreased motion as early as 1 hr post-LPS administration, peaked at 2 hours post-induction (28.73%±53.2% vehicle vs –82.69%±1.72% LPS treated), and remained decreased for over 24 hrs (p&lt;0.05). Increased breathing positively correlated, while decreased motion negatively correlated with plasma levels of TNFα, and IL-10 at 1.5 hrs, and IL-6, IL-1B, and IFN-γ levels at 6 hrs post-LPS (p&lt;0.05). We found that Vium’s automated metrics was able to detect onset of LPS-induced endotoxemia in real-time. This could be used to 1) screen compounds that prevent immune responses or alternatively 2) to identify cytokine release syndrome when screening immuno-oncology candidates.

Development of the Digital Arthritis Index, a Novel Metric to Measure Disease Parameters in a Rat Model of Rheumatoid Arthritis

Despite a broad spectrum of anti-arthritic drugs currently on the market, there is a constant demand to develop improved therapeutic agents. Efficient compound screening and rapid evaluation of treatment efficacy in animal models of rheumatoid arthritis (RA) can accelerate the development of clinical candidates. Compound screening by evaluation of disease phenotypes in animal models facilitates preclinical research by enhancing understanding of human pathophysiology; however, there is still a continuous need to improve methods for evaluating disease. Current clinical assessment methods are challenged by the subjective nature of scoring-based methods, time-consuming longitudinal experiments, and the requirement for better functional readouts with relevance to human disease. To address these needs, we developed a low-touch, digital platform for phenotyping preclinical rodent models of disease. As a proof-of-concept, we utilized the rat collagen-induced arthritis (CIA) model of RA and developed the Digital Arthritis Index (DAI), an objective and automated behavioral metric that does not require human-animal interaction during the measurement and calculation of disease parameters. The DAI detected the development of arthritis similar to standard in vivo methods, including ankle joint measurements and arthritis scores, as well as demonstrated a positive correlation to ankle joint histopathology. The DAI also determined responses to multiple standard-of-care (SOC) treatments and nine repurposed compounds predicted by the SMarTR^TM Engine to have varying degrees of impact on RA. The disease profiles generated by the DAI complemented those generated by standard methods. The DAI is a highly reproducible and automated approach that can be used in-conjunction with standard methods for detecting RA disease progression and conducting phenotypic drug screens.

Novel approaches to assess therapeutic efficacy in the MRL/lpr model of lupus

Spontaneous genetic models of systemic lupus erythematosus (SLE), such as MRL/lpr and NZB/W F1 mice, are commonly used to assess therapeutic efficacy. Therapies are evaluated against several reliable standard measures, including proteinuria, anti-dsDNA, skin lesions, splenomegaly, nephritis, and survival. We hypothesize that continuous monitoring of behavioral and physiologic parameters will provide additional meaningful data to assess disease and efficacy. Here, we treated MRL/lpr mice with two reference compounds, cyclophosphamide (CP: 25mg/kg, IP, weekly) and dexamethasone (DEX: 2mg/kg, IP, 3× week). Throughout the experiment, mice were housed in Vium’s Digital Vivarium, which provides continuous monitoring and assessment of behavioral and physiologic measures using a network of cameras and sensors. Digital metrics and standard measures were displayed and analyzed in near real-time, through an online interface. Group disease profiles were compared using automatically generated breathing rate and motion metrics, in addition to standard measures. Proteinuria, body weight, and spleen size showed disease establishment in MRL/lpr mice as early as 16 weeks of age, which was ameliorated by CP or DEX (p’s &lt; 0.03). Breathing rate significantly increased in MRL/lpr vehicle-treated mice as early as 13 weeks of age, while nighttime motion significantly decreased in MRL/lpr vehicle-treated mice by 14 weeks. Changes in breathing rate and motion detected in MRL/lpr mice were rescued by administration of CP or DEX (p’s &lt; 0.0001). Our results demonstrate that continuous measurement of breathing rate and motion are useful additional measures for evaluating disease severity and therapeutic efficacy in the MRL/lpr murine model of SLE.

An Integrative Bioinformatics Approach Identifies In Vivo Validated Drug Candidates with Novel Mechanisms of Action in Rheumatoid Arthritis

Rheumatoid arthritis (RA) is an area of active drug development, with over 100 candidates in clinical trials. However, most act on a small number of immunomodulatory targets. Drug candidates that act through new targets or mechanisms could expand treatment options for RA. We applied a data-driven bioinformatics approach and in vivo screen to identify and test new drug candidates and targets that could form the basis of future drug development in RA.

A computational model of RA was constructed by integrating patient gene expression data, molecular interactions, chemical structures, and clinical drug-disease associations. Candidates were scored based on their predicted efficacy in the computational model. FDA-approved treatments for RA were significantly enriched among the top-ranked candidates. Ten high scoring novel candidates were then screened in the collagen-induced arthritis model of RA in rats. Therapeutic treatment with three candidates significantly reduced ankle size, alleviated limb inflammation, improved joint histopathology, and reduced mobility impairments tracked by a novel digital motion endpoint. These candidates are currently approved for metabolic, allergic, and psychiatric indications, and do not act on common RA therapeutic targets. However, links between known candidate pharmacology and pathological processes in RA suggest hypothetical mechanisms that could contribute to efficacy.

Future studies will inform the druggable targets, pathways, and mechanisms that could contribute to each candidate’s efficacy in RA. The candidates could themselves be modified and optimized to increase efficacy in RA. Novel targets identified in these studies could also be the basis of new drug discovery initiatives.

Gld2-catalyzed 3' monoadenylation of miRNAs in the hippocampus has no detectable effect on their stability or on animal behavior

Gld2, a noncanonical cytoplasmic poly(A) polymerase, interacts with the RNA binding protein CPEB1 to mediate polyadenylation-induced translation in dendrites of cultured hippocampal neurons. Depletion of Gld2 from the hippocampus leads to a deficit in long-term potentiation evoked by theta burst stimulation. At least in mouse liver and human primary fibroblasts, Gld2 also 3' monoadenylates and thereby stabilizes specific miRNAs, which enhance mRNA translational silencing and eventual destruction. These results suggest that Gld2 would be likely to monoadenylate and stabilize miRNAs in the hippocampus, which would produce measurable changes in animal behavior. We now report that using Gld2 knockout mice, there are detectable alterations in specific miRNA monoadenylation in the hippocampus when compared to wild type, but that these modifications produce no detectable effect on miRNA stability. Moreover, we surprisingly find no overt change in animal behavior when comparing Gld2 knockout to wild-type mice. These data indicate that miRNA monoadenylation-mediated stability is cell type-specific and that monoadenylation has no measurable effect on higher cognitive function.

Corticothalamic Axons Are Essential for Retinal Ganglion Cell Axon Targeting to the Mouse Dorsal Lateral Geniculate Nucleus

Retinal ganglion cells (RGCs) relay information about the outside world to multiple subcortical targets within the brain. This information is either used to dictate reflexive behaviors or relayed to the visual cortex for further processing. Many subcortical visual nuclei also receive descending inputs from projection neurons in the visual cortex. Most areas receive inputs from layer 5 cortical neurons in the visual cortex but one exception is the dorsal lateral geniculate nucleus (dLGN), which receives layer 6 inputs and is also the only RGC target that sends direct projections to the cortex. Here we ask how visual system development and function changes in mice that develop without a cortex. We find that the development of a cortex is essential for RGC axons to terminate in the dLGN, but is not required for targeting RGC axons to other subcortical nuclei. RGC axons also fail to target to the dLGN in mice that specifically lack cortical layer 6 projections to the dLGN. Finally, we show that when mice develop without a cortex they can still perform a number of vision-dependent tasks.

SIGNIFICANCE STATEMENT

The dorsal lateral geniculate nucleus (dLGN) is a sensory thalamic relay area that receives feedforward inputs from retinal ganglion cells (RGCs) in the retina, and feed back inputs from layer 6 neurons in the visual cortex. In this study we examined genetically manipulated mice that develop without a cortex or without cortical layer 6 axonal projections, and find that RGC axons fail to project to the dLGN. Other RGC recipient areas, such as the superior colliculus and suprachiasmatic nucleus, are targeted normally. These results provide support for a new mechanism of target selection that may be specific to the thalamus, whereby descending cortical axons provide an activity that promotes feedforward targeting of RGC axons to the dLGN.

Digital Vivarium™ Platform Enables Automated Drug Efficacy Assessment Correlated with Pathology in Rheumatoid Arthritis

Current methods for evaluating new therapeutics in rodent disease models and improving understanding of disease mechanisms are frequently labor-intensive and require the same technician to perform key measurements for consistency. To address these limitations, we established a novel Digital Vivarium™ platform, which monitors subjects continuously for disease and health-related endpoints, without human interaction, to evaluate drug efficacy. As a proof of principal, we validated automated disease scoring in a standard model of arthritis with an algorithm that captures salient motion metrics during the animals’ active period to compute an arthritis score. This Digital Arthritis Index™ score reproducibly correlated to disease pathology and was better at detecting mild disease pathology as compared to joint swelling across standard-of-care compounds including Methotrexate, Etanercept, and Dexamethasone. Additional health endpoints, include breathing rate, overall activity, and circadian rhythms, are also monitored continuously and stored in auditable electronic and videographic records. The platform was then used to screen 9 re- purposed drugs at appropriate dose ranges for efficacy. Study-specific disease and health endpoints are available real-time remotely over the internet to enable rapid decisions. Our results demonstrate a low-touch digital platform that will pave new ways for more rapid, reproducible, drug discovery and evaluation, not only for RA, but also more broadly in other autoimmune diseases such as MS and Lupus, as well as outside of immunology such as cancer, CNS and toxicology.

One-carbon metabolism in neurodevelopmental disorders: using broad-based nutraceutics to treat cognitive deficits in complex spectrum disorders

Folate and choline, two nutrients involved in the one-carbon metabolic cycle, are intimately involved in regulating DNA integrity, synthesis, biogenic amine synthesis, and methylation. In this review, we discuss evidence that folate and choline play an important role in normal cognitive development, and that altered levels of these nutrients during periods of high neuronal proliferation and synaptogenesis can result in diminished cognitive function. We also discuss the use of these nutrients as therapeutic agents in a spectrum of developmental disorders in which intellectual disability is a prominent feature, such as in Fragile-X, Rett syndrome, Down syndrome, and Autism spectrum disorders. A survey of recent literature suggests that nutritional supplements have mild, but generally consistent, effects on improving cognition. Intervening with supplements earlier rather than later during development is more effective in improving cognitive outcomes. Given the mild improvements seen after treatments using nutrients alone, and the importance of the genetic profile of parents and offspring, we suggest that using nutraceutics early in development and in combination with other therapeutics are likely to have positive impacts on cognitive outcomes in a broad spectrum of complex neurodevelopmental disorders.