Transcriptomics-based network medicine approach identifies metformin as a repurposable drug for atrial fibrillation

Network Medicine: A Potential Approach for Virtual Drug Screening

Traditional drug screening methods typically focus on a single protein target and exhibit limited efficiency due to the multifactorial nature of most diseases, which result from disturbances within complex networks of protein-protein interactions rather than single gene abnormalities. Addressing this limitation requires a comprehensive drug screening strategy. Network medicine is rooted in systems biology and provides a comprehensive framework for understanding disease mechanisms, prevention, and therapeutic innovations. This approach not only explores the associations between various diseases but also quantifies the relationships between disease genes and drug targets within interactome networks, thus facilitating the prediction of drug-disease relationships and enabling the screening of therapeutic drugs for specific complex diseases. An increasing body of research supports the efficiency and utility of network-based strategies in drug screening. This review highlights the transformative potential of network medicine in virtual therapeutic screening for complex diseases, offering novel insights and a robust foundation for future drug discovery endeavors.

Northwestern University resource and education development initiatives to advance collaborative artificial intelligence across the learning health system

Introduction

The rapid development of artificial intelligence (AI) in healthcare has exposed the unmet need for growing a multidisciplinary workforce that can collaborate effectively in the learning health systems. Maximizing the synergy among multiple teams is critical for Collaborative AI in Healthcare.

Methods

We have developed a series of data, tools, and educational resources for cultivating the next generation of multidisciplinary workforce for Collaborative AI in Healthcare. We built bulk-natural language processing pipelines to extract structured information from clinical notes and stored them in common data models. We developed multimodal AI/machine learning (ML) tools and tutorials to enrich the toolbox of the multidisciplinary workforce to analyze multimodal healthcare data. We have created a fertile ground to cross-pollinate clinicians and AI scientists and train the next generation of AI health workforce to collaborate effectively.

Results

Our work has democratized access to unstructured health information, AI/ML tools and resources for healthcare, and collaborative education resources. From 2017 to 2022, this has enabled studies in multiple clinical specialties resulting in 68 peer-reviewed publications. In 2022, our cross-discipline efforts converged and institutionalized into the Center for Collaborative AI in Healthcare.

Conclusions

Our Collaborative AI in Healthcare initiatives has created valuable educational and practical resources. They have enabled more clinicians, scientists, and hospital administrators to successfully apply AI methods in their daily research and practice, develop closer collaborations, and advanced the institution-level learning health system.

Repurposing Metformin for the Treatment of Atrial Fibrillation: Current Insights

Metformin is an orally effective anti-hyperglycemic drug that despite being introduced over 60 years ago is still utilized by an estimated 120 to 150 million people worldwide for the treatment of type 2 diabetes (T2D). Metformin is used off-label for the treatment of polycystic ovary syndrome (PCOS) and for pre-diabetes and weight loss. Metformin is a safe, inexpensive drug with side effects mostly limited to gastrointestinal issues. Prospective clinical data from the United Kingdom Prospective Diabetes Study (UKPDS), completed in 1998, demonstrated that metformin not only has excellent therapeutic efficacy as an anti-diabetes drug but also that good glycemic control reduced the risk of micro- and macro-vascular complications, especially in obese patients and thereby reduced the risk of diabetes-associated cardiovascular disease (CVD). Based on a long history of clinical use and an excellent safety record metformin has been investigated to be repurposed for numerous other diseases including as an anti-aging agent, Alzheimer's disease and other dementias, cancer, COVID-19 and also atrial fibrillation (AF). AF is the most frequently diagnosed cardiac arrythmia and its prevalence is increasing globally as the population ages. The argument for repurposing metformin for AF is based on a combination of retrospective clinical data and in vivo and in vitro pre-clinical laboratory studies. In this review, we critically evaluate the evidence that metformin has cardioprotective actions and assess whether the clinical and pre-clinical evidence support the use of metformin to reduce the risk and treat AF.

Metabolic remodelling in atrial fibrillation: manifestations, mechanisms and clinical implications

Atrial fibrillation (AF) is a continually growing health-care burden that often presents together with metabolic disorders, including diabetes mellitus and obesity. Current treatments often fall short of preventing AF and its adverse outcomes. Accumulating evidence suggests that metabolic disturbances can promote the development of AF through structural and electrophysiological remodelling, but the underlying mechanisms that predispose an individual to AF are aetiology-dependent, thus emphasizing the need for tailored therapeutic strategies to treat AF that target an individual's metabolic profile. AF itself can induce changes in glucose, lipid and ketone metabolism, mitochondrial function and myofibrillar energetics (as part of a process referred to as 'metabolic remodelling'), which can all contribute to atrial dysfunction. In this Review, we discuss our current understanding of AF in the setting of metabolic disorders, as well as changes in atrial metabolism that are relevant to the development of AF. We also describe the potential of available and emerging treatment strategies to target metabolic remodelling in the setting of AF and highlight key questions and challenges that need to be addressed to improve outcomes in these patients.

DReAmocracy: A Method to Capitalise on Prior Drug Discovery Efforts to Highlight Candidate Drugs for Repurposing

In the area of drug research, several computational drug repurposing studies have highlighted candidate repurposed drugs, as well as clinical trial studies that have tested/are testing drugs in different phases. To the best of our knowledge, the aggregation of the proposed lists of drugs by previous studies has not been extensively exploited towards generating a dynamic reference matrix with enhanced resolution. To fill this knowledge gap, we performed weight-modulated majority voting of the modes of action, initial indications and targeted pathways of the drugs in a well-known repository, namely the Drug Repurposing Hub. Our method, DReAmocracy, exploits this pile of information and creates frequency tables and, finally, a disease suitability score for each drug from the selected library. As a testbed, we applied this method to a group of neurodegenerative diseases (Alzheimer's, Parkinson's, Huntington's disease and Multiple Sclerosis). A super-reference table with drug suitability scores has been created for all four neurodegenerative diseases and can be queried for any drug candidate against them. Top-scored drugs for Alzheimer's Disease include agomelatine, mirtazapine and vortioxetine; for Parkinson's Disease, they include apomorphine, pramipexole and lisuride; for Huntington's, they include chlorpromazine, fluphenazine and perphenazine; and for Multiple Sclerosis, they include zonisamide, disopyramide and priralfimide. Overall, DReAmocracy is a methodology that focuses on leveraging the existing drug-related experimental and/or computational knowledge rather than a predictive model for drug repurposing, offering a quantified aggregation of existing drug discovery results to (1) reveal trends in selected tracks of drug discovery research with increased resolution that includes modes of action, targeted pathways and initial indications for the investigated drugs and (2) score new candidate drugs for repurposing against a selected disease.

A network-based drug prioritization and combination analysis for the MEK5/ERK5 pathway in breast cancer

BACKGROUND

Prioritizing candidate drugs based on genome-wide expression data is an emerging approach in systems pharmacology due to its holistic perspective for preclinical drug evaluation. In the current study, a network-based approach was proposed and applied to prioritize plant polyphenols and identify potential drug combinations in breast cancer. We focused on MEK5/ERK5 signalling pathway genes, a recently identified potential drug target in cancer with roles spanning major carcinogenesis processes.

RESULTS

By constructing and identifying perturbed protein-protein interaction networks for luminal A breast cancer, plant polyphenols and drugs from transcriptome data, we first demonstrated their systemic effects on the MEK5/ERK5 signalling pathway. Subsequently, we applied a pathway-specific network pharmacology pipeline to prioritize plant polyphenols and potential drug combinations for use in breast cancer. Our analysis prioritized genistein among plant polyphenols. Drug combination simulations predicted several FDA-approved drugs in breast cancer with well-established pharmacology as candidates for target network synergistic combination with genistein. This study also highlights the concept of target network enhancer drugs, with drugs previously not well characterised in breast cancer being prioritized for use in the MEK5/ERK5 pathway in breast cancer.

CONCLUSION

This study proposes a computational framework for drug prioritization and combination with the MEK5/ERK5 signaling pathway in breast cancer. The method is flexible and provides the scientific community with a robust method that can be applied to other complex diseases.

Zbtb16 increases susceptibility of atrial fibrillation in type 2 diabetic mice via Txnip-Trx2 signaling

Atrial fibrillation (AF) is the most prevalent sustained cardiac arrhythmia, and recent epidemiological studies suggested type 2 diabetes mellitus (T2DM) is an independent risk factor for the development of AF. Zinc finger and BTB (broad-complex, tram-track and bric-a-brac) domain containing 16 (Zbtb16) serve as transcriptional factors to regulate many biological processes. However, the potential effects of Zbtb16 in AF under T2DM condition remain unclear. Here, we reported that db/db mice displayed higher AF vulnerability and Zbtb16 was identified as the most significantly enriched gene by RNA sequencing (RNA-seq) analysis in atrium. In addition, thioredoxin interacting protein (Txnip) was distinguished as the key downstream gene of Zbtb16 by Cleavage Under Targets and Tagmentation (CUT&Tag) assay. Mechanistically, increased Txnip combined with thioredoxin 2 (Trx2) in mitochondrion induced excess reactive oxygen species (ROS) release, calcium/calmodulin-dependent protein kinase II (CaMKII) overactivation, and spontaneous Ca2+ waves (SCWs) occurrence, which could be inhibited through atrial-specific knockdown (KD) of Zbtb16 or Txnip by adeno-associated virus 9 (AAV9) or Mito-TEMPO treatment. High glucose (HG)-treated HL-1 cells were used to mimic the setting of diabetic in vitro. Zbtb16-Txnip-Trx2 signaling-induced excess ROS release and CaMKII activation were also verified in HL-1 cells under HG condition. Furthermore, atrial-specific Zbtb16 or Txnip-KD reduced incidence and duration of AF in db/db mice. Altogether, we demonstrated that interrupting Zbtb16-Txnip-Trx2 signaling in atrium could decrease AF susceptibility via reducing ROS release and CaMKII activation in the setting of T2DM.

Palmitoylation of PKCδ by ZDHHC5 in hypothalamic microglia presents as a therapeutic target for fatty liver disease

The hypothalamus plays a fundamental role in controlling lipid metabolism through neuroendocrine signals. However, there are currently no available drug targets in the hypothalamus that can effectively improve human lipid metabolism. In this study, we found that the antimalarial drug artemether (ART) significantly improved lipid metabolism by specifically inhibiting microglial activation in the hypothalamus of high-fat diet-induced mice. Mechanically, ART protects the thyrotropin-releasing hormone (TRH) neurons surrounding microglial cells from inflammatory damage and promotes the release of TRH into the peripheral circulation. As a result, TRH stimulates the synthesis of thyroid hormone (TH), leading to a significant improvement in hepatic lipid disorders. Subsequently, we employed a biotin-labeled ART chemical probe to identify the direct cellular target in microglial cells as protein kinase Cδ (PKCδ). Importantly, ART directly targeted PKCδ to inhibit its palmitoylation modification by blocking the binding of zinc finger DHHC-type palmitoyltransferase 5 (ZDHHC5), which resulted in the inhibition of downstream neuroinflammation signaling. In vivo, hypothalamic microglia-specific PKCδ knockdown markedly impaired ART-dependent neuroendocrine regulation and lipid metabolism improvement in mice. Furthermore, single-cell transcriptomics analysis in human brain tissues revealed that the level of PKCδ in microglia positively correlated with individuals who had hyperlipemia, thereby highlighting a clinical translational value. Collectively, these data suggest that the palmitoylation of microglial PKCδ in the hypothalamus plays a role in modulating peripheral lipid metabolism through hypothalamus-liver communication, and provides a promising therapeutic target for fatty liver diseases.

Effects of hydroxychloroquine on atrial electrophysiology in in silico wild-type and PITX2+/- atrial cardiomyocytes

BACKGROUND

Hydroxychloroquine (HCQ) is commonly used in the treatment of autoimmune diseases and increases the risk of QT interval prolongation. However, it is unclear how HCQ affects atrial electrophysiology and the risk of atrial fibrillation (AF).

METHODS

We quantitatively examined the potential atrial arrhythmogenic effects of HCQ on AF using a computational model of human atrial cardiomyocytes. We measured atrial electrophysiological markers after systematically varying HCQ concentrations.

RESULTS

The HCQ concentrations were positively correlated with the action potential duration (APD), resting membrane potential, refractory period, APD alternans threshold, and calcium transient alternans threshold (p < 0.05). By contrast, HCQ concentrations were inversely correlated with the maximum upstroke velocity and calcium transient amplitude (p < 0.05). When the therapeutic concentration (Cmax) of HCQ was applied, HCQ increased APD90 by 1.4% in normal sinus rhythm, 1.8% in wild-type AF, and 2.6% in paired-like homeodomain transcription factor 2 (PITX2)+/- AF, but did not affect the alternans thresholds. The overall in silico results suggest no significant atrial arrhythmogenic effects of HCQ at Cmax, instead implying a potential antiarrhythmic role of low-dose HCQ in AF. However, at an HCQ concentration of fourfold Cmax, a rapid pacing rate of 4 Hz induced prominent APD alternans, particularly in the PITX2+/- AF model.

CONCLUSION

Our in silico analysis suggests a potential antiarrhythmic role of low-dose HCQ in AF. Concomitant PITX2 mutations and high-dose HCQ treatments may increase the risk of AF, and this potential genotype/dose-dependent arrhythmogenic effect of HCQ should be investigated further.

Recent Advances in Antiarrhythmic Drug Therapy

Cardiac arrhythmias remain a common cause of death and disability. Antiarrhythmic drugs (AADs) and antiarrhythmic agents remain a cornerstone of current cardiac arrhythmia management, despite moderate efficacy and the potential for significant adverse proarrhythmic effects. Due to conceptual, regulatory and financial considerations, the number of novel antiarrhythmic targets and agents in the development pipeline has decreased substantially during the last few decades. However, several promising candidates remain and there are exciting developments in repurposing and reformulating already existing drugs for indications related to cardiac arrhythmias. This review discusses the key conceptual considerations for the development of new antiarrhythmic agents, summarizes new compounds and formulations currently in clinical development for rhythm control of atrial fibrillation, and highlights the potential for drug repurposing. Finally, future directions in AAD development are discussed. Together with an ever-increasing understanding of the molecular mechanisms underlying cardiac arrhythmias, these components support a cautiously optimistic outlook towards improved pharmacological treatment opportunities for patients suffering from cardiac arrhythmias.

Reviewing Atrial Fibrillation Pathophysiology from a Network Medicine Perspective: The Relevance of Structural Remodeling, Inflammation, and the Immune System

Atrial fibrillation (AF) is the most common type of sustained arrhythmia. The numerous gaps concerning the knowledge of its mechanism make improving clinical management difficult. As omics technologies allow more comprehensive insight into biology and disease at a molecular level, bioinformatics encompasses valuable tools for studying systems biology, as well as combining and modeling multi-omics data and networks. Network medicine is a subarea of network biology where disease traits are considered perturbations within the interactome. With this approach, potential disease drivers can be revealed, and the effect of drugs, novel or repurposed, used alone or in combination, may be studied. Thus, this work aims to review AF pathology from a network medicine perspective, helping researchers to comprehend the disease more deeply. Essential concepts involved in network medicine are highlighted, and specific research applying network medicine to study AF is discussed. Additionally, data integration through literature mining and bioinformatics tools, with network building, is exemplified. Together, all of the data show the substantial role of structural remodeling, the immune system, and inflammation in this disease etiology. Despite this, there are still gaps to be filled about AF.

Metformin: evidence from preclinical and clinical studies for potential novel applications in cardiovascular disease

INTRODUCTION

For a long time, metformin has been the first-line treatment for glycaemic control in type 2 diabetes, however, the results of recent cardiovascular outcome trials of sodium-glucose co-transporter 2 inhibitors and glucagon-like peptide 1 receptor agonists have caused many to question metformin's position in the guidelines. Although there are several plausible mechanisms by which metformin might have beneficial cardiovascular effects, for example its anti-inflammatory effects and metabolic properties, and numerous observational data suggesting improved cardiovascular outcomes with metformin use, the main randomised clinical trial data for metformin was published over 20 years ago. Nevertheless, the overwhelming majority of participants in contemporary type 2 diabetes trials were prescribed metformin.

AREAS COVERED

In this review we will summarise the potential mechanisms of cardiovascular benefit with metformin, before discussing clinical data in individuals with or without diabetes.

EXPERT OPINION

Metformin may have some cardiovascular benefit in patients with and without diabetes, however the majority of clinical trials were small and are before the use SGLT2 inhibitors and GLP1-RAs. Larger contemporary randomised trials with metformin evaluating its cardiovascular benefit are warranted.

Intestinal Barrier Dysfunction and Microbial Translocation in Patients with First-Diagnosed Atrial Fibrillation

BACKGROUND

According to the leaky gut concept, microbial products (e.g., lipopolysaccharide, LPS) enter the circulation and mediate pro-inflammatory immunological responses. Higher plasma LPS levels have been reported in patients with various cardiovascular diseases, but not specifically during early atrial fibrillation (AF).

METHODS

We studied data and blood samples from patients presenting with first-diagnosed AF (FDAF) (n = 80) and 20 controls.

RESULTS

Circulating biomarkers that are suggestive of mucosal inflammation (zonulin, mucosal adhesion molecule MAdCAM-1) and intestinal epithelium damage (intestinal fatty acid binding protein, IFABP) were increased in the plasma of patients with FDAF when compared to patients with chronic cardiovascular diseases but without AF. Surrogate plasma markers of increased intestinal permeability (LPS, CD14, LPS-binding protein, gut-derived LPS-neutralising IgA antibodies, EndoCAbs) were detected during early AF. A reduced ratio of IgG/IgM EndoCAbs titres indicated chronic endotoxaemia. Collagen turnover biomarkers, which corresponded to the LPS values, suggested an association of gut-derived low-grade endotoxaemia with adverse structural remodelling. The LPS concentrations were higher in FDAF patients who experienced a major adverse cardiovascular event.

CONCLUSIONS

Intestinal barrier dysfunction and microbial translocation accompany FDAF. Improving gut permeability and low-grade endotoxaemia might be a potential therapeutic approach to reducing the disease progression and cardiovascular complications in FDAF.

Human-Induced Pluripotent Stem Cell-Based Differentiation of Cardiomyocyte Subtypes for Drug Discovery and Cell Therapy

Drug attrition rates have increased over the past few years, accompanied with growing costs for the pharmaceutical industry and consumers. Lack of in vitro models connecting the results of toxicity screening assays with clinical outcomes accounts for this high attrition rate. The emergence of cardiomyocytes derived from human pluripotent stem cells provides an amenable source of cells for disease modeling, drug discovery, and cardiotoxicity screening. Functionally similar to to embryonic stem cells, but with fewer ethical concerns, induced pluripotent stem cells (iPSCs) can recapitulate patient-specific genetic backgrounds, which would be a huge revolution for personalized medicine. The generated iPSC-derived cardiomyocytes (iPSC-CMs) represent different subtypes including ventricular-, atrial-, and nodal-like cardiomyocytes. Purifying these subtypes for chamber-specific drug screening presents opportunities and challenges. In this chapter, we discuss the strategies for the purification of iPSC-CMs, the use of iPSC-CMs for drug discovery and cardiotoxicity test, and the current limitations of iPSC-CMs that should be overcome for wider and more precise cardiovascular applications.

New use for an old drug: Metformin and atrial fibrillation

Lal and colleagues¹ reported an integrative approach-combining transcriptomics, iPSCs, and epidemiological evidence-to identify and repurpose metformin, a main first-line medication for the treatment of type 2 diabetes, as an effective risk reducer for atrial fibrillation.