Metabolically-inactive glucagon-like peptide-1(9-36)amide confers selective protective actions against post-myocardial infarction remodelling

BACKGROUND: Glucagon-like peptide-1 (GLP-1) therapies are routinely used for glycaemic control in diabetes and their emerging cardiovascular actions have been a major recent research focus. In addition to GLP-1 receptor activation, the metabolically-inactive breakdown product, GLP-1(9-36)amide, also appears to exert notable cardiovascular effects, including protection against acute cardiac ischaemia. Here, we specifically studied the influence of GLP-1(9-36)amide on chronic post-myocardial infarction (MI) remodelling, which is a major driver of heart failure progression.

METHODS: Adult female C57BL/6 J mice were subjected to permanent coronary artery ligation or sham surgery prior to continuous infusion with GLP-1(9-36)amide or vehicle control for 4 weeks.

RESULTS: Infarct size was similar between groups with no effect of GLP-1(9-36)amide on MI-induced cardiac hypertrophy, although modest reduction of in vitro phenylephrine-induced H9c2 cardiomyoblast hypertrophy was observed. Whilst echocardiographic systolic dysfunction post-MI remained unchanged, diastolic dysfunction (decreased mitral valve E/A ratio, increased E wave deceleration rate) was improved by GLP-1(9-36)amide treatment. This was associated with modulation of genes related to extracellular matrix turnover (MMP-2, MMP-9, TIMP-2), although interstitial fibrosis and pro-fibrotic gene expression were unaltered by GLP-1(9-36)amide. Cardiac macrophage infiltration was also reduced by GLP-1(9-36)amide together with pro-inflammatory cytokine expression (IL-1β, IL-6, MCP-1), whilst in vitro studies using RAW264.7 macrophages revealed global potentiation of basal pro-inflammatory and tissue protective cytokines (e.g. IL-1β, TNF-α, IL-10, Fizz1) in the presence of GLP-1(9-36)amide versus exendin-4.

CONCLUSIONS: These data suggest that GLP-1(9-36)amide confers selective protection against post-MI remodelling via preferential preservation of diastolic function, most likely due to modulation of infiltrating macrophages, indicating that this often overlooked GLP-1 breakdown product may exert significant actions in this setting which should be considered in the context of GLP-1 therapy in patients with cardiovascular disease.

Embracing an integromic approach to tissue biomarker research in cancer: Perspectives and lessons learned

Modern approaches to biomedical research and diagnostics targeted towards precision medicine are generating ‘big data’ across a range of high-throughput experimental and analytical platforms. Integrative analysis of this rich clinical, pathological, molecular and imaging data represents one of the greatest bottlenecks in biomarker discovery research in cancer and other diseases. Following on from the publication of our successful framework for multimodal data amalgamation and integrative analysis, Pathology Integromics in Cancer (PICan), this article will explore the essential elements of assembling an integromics framework from a more detailed perspective. PICan, built around a relational database storing curated multimodal data, is the research tool sitting at the heart of our interdisciplinary efforts to streamline biomarker discovery and validation. While recognizing that every institution has a unique set of priorities and challenges, we will use our experiences with PICan as a case study and starting point, rationalizing the design choices we made within the context of our local infrastructure and specific needs, but also highlighting alternative approaches that may better suit other programmes of research and discovery. Along the way, we stress that integromics is not just a set of tools, but rather a cohesive paradigm for how modern bioinformatics can be enhanced. Successful implementation of an integromics framework is a collaborative team effort that is built with an eye to the future and greatly accelerates the processes of biomarker discovery, validation and translation into clinical practice.