Closing the 'phenotype gap' in precision medicine: improving what we measure to understand complex disease mechanisms

Advocating for Generalizability: Accepting Inherent Variability in Translation of Animal Research Outcomes

Advancing scientific discovery requires investigators to embrace research practices that increase transparency and disclosure about materials, methods, and outcomes. Several research advocacy and funding organizations have produced guidelines and recommended practices to enhance reproducibility through detailed and rigorous research approaches; however, confusion around vocabulary terms and a lack of adoption of suggested practices have stymied successful implementation. Although reproducibility of research findings cannot be guaranteed due to extensive inherent variables in attempts at experimental repetition, the scientific community can advocate for generalizability in the application of data outcomes to ensure a broad and effective impact on the comparison of animals to translation within human research. This report reviews suggestions, based upon work with National Institutes of Health advisory groups, for improving rigor and transparency in animal research through aspects of experimental design, statistical assessment, and reporting factors to advocate for generalizability in the application of comparative outcomes between animals and humans.

Zebrafish as a Mainstream Model for In Vivo Systems Pharmacology and Toxicology

Pharmacology and toxicology are part of a much broader effort to understand the relationship between chemistry and biology. While biomedicine has necessarily focused on specific cases, typically of direct human relevance, there are real advantages in pursuing more systematic approaches to characterizing how health and disease are influenced by small molecules and other interventions. In this context, the zebrafish is now established as the representative screenable vertebrate and, through ongoing advances in the available scale of genome editing and automated phenotyping, is beginning to address systems-level solutions to some biomedical problems. The addition of broader efforts to integrate information content across preclinical model organisms and the incorporation of rigorous analytics, including closed-loop deep learning, will facilitate efforts to create systems pharmacology and toxicology with the ability to continuously optimize chemical biological interactions around societal needs. In this review, we outline progress toward this goal.

Plasmodium knowlesi - Clinical Isolate Genome Sequencing to Inform Translational Same-Species Model System for Severe Malaria

Malaria is responsible for unacceptably high morbidity and mortality, especially in Sub-Saharan African Nations. Malaria is caused by member species' of the genus Plasmodium and despite concerted and at times valiant efforts, the underlying pathophysiological processes leading to severe disease are poorly understood. Here we describe zoonotic malaria caused by Plasmodium knowlesi and the utility of this parasite as a model system for severe malaria. We present a method to generate long-read third-generation Plasmodium genome sequence data from archived clinical samples using the MinION platform. The method and technology are accessible, affordable and data is generated in real-time. We propose that by widely adopting this methodology important information on clinically relevant parasite diversity, including multiple gene family members, from geographically distinct study sites will emerge. Our goal, over time, is to exploit the duality of P. knowlesi as a well-used laboratory model and human pathogen to develop a representative translational model system for severe malaria that is informed by clinically relevant parasite diversity.

Focusing Heart Failure Research on Myocardial Fibrosis to Prioritize Translation

Heart failure (HF) has traditionally been defined by symptoms of fluid accumulation and poor perfusion, but it is now recognized that specific HF classifications hold prognostic and therapeutic relevance. Specifically, HF with reduced ejection fraction is characterized by reduced left ventricular systolic pump function and dilation and HF with preserved ejection fraction is characterized primarily by abnormal left ventricular filling (diastolic failure) with relatively preserved left ventricular systolic function. These forms of HF are distributed equally among patients with HF and likely require distinctly different strategies to mitigate the morbidity, mortality, and medical resource utilization of this disease. In particular, HF is a significant medical issue within the US Department of Veterans Affairs (VA) hospital system and constitutes a major translational research priority for the VA. Because a common underpinning of both HF with reduced ejection fraction and HF with preserved ejection fraction seems to be changes in the structure and function of the myocardial extracellular matrix, a conference was convened sponsored by the VA, entitled, "Targeting Myocardial Fibrosis in Heart Failure" to explore the extracellular matrix as a potential therapeutic target and to propose specific research directions. The conference was conceptually framed around the hypothesis that although HF with reduced ejection fraction and HF with preserved ejection fraction clearly have distinct mechanisms, they may share modifiable pathways and biological mediators in common. Inflammation and extracellular matrix were identified as major converging themes. A summary of our discussion on unmet challenges and possible solutions to move the field forward, as well as recommendations for future research opportunities, are provided.

Strategies for targeting the cardiac sarcomere: avenues for novel drug discovery

Introduction: Heart failure remains one of the largest clinical challenges in the United States. Researchers have continually searched for more effective heart failure treatments that target the cardiac sarcomere but have found few successes despite numerous expensive cardiovascular clinical trials. Among many reasons, the high failure rate of cardiovascular clinical trials may be partly due to incomplete characterization of a drug candidate's complex interaction with cardiac physiology.Areas covered: In this review, the authors address the issue of preclinical cardiovascular studies of sarcomere-targeting heart failure therapies. The authors consider inherent tradeoffs made between mechanistic transparency and physiological fidelity for several relevant preclinical techniques at the atomic, molecular, heart muscle fiber, whole heart, and whole-organism levels. Thus, the authors suggest a comprehensive, bottom-up approach to preclinical cardiovascular studies that fosters scientific rigor and hypothesis-driven drug discovery.Expert opinion: In the authors' opinion, the implementation of hypothesis-driven drug discovery practices, such as the bottom-up approach to preclinical cardiovascular studies, will be imperative for the successful development of novel heart failure treatments. However, additional changes to clinical definitions of heart failure and current drug discovery culture must accompany the bottom-up approach to maximize the effectiveness of hypothesis-driven drug discovery.