Publications
Excited to share our latest commentary in Nature Reviews Drug Discovery! We delve into the challenges and advancements in using new approach methods for predicting drug effects from model systems. We focus on human-derived iPSCs and the integration of AI tools, and the field’s aim to enhance the accuracy and reliability of preclinical drug testing.
Tackling the challenges of new approach methods for predicting drug effects from model systems
Paul D.Pang, Syed Mukhtar Ahmed, Masataka Nishiga, Norman L Stockbridge, Joseph C Wu
Congratulations to Greenstone for co-publishing in Nature Biomedical Engineering
Tachycardia-induced metabolic rewiring as a driver of contractile dysfunction.
Tu C, Caudal A, Liu Y, Gorgodze N, Zhang H, Lam CK, Dai Y, Zhang A, Wnorowski A, Wu MA, Yang H, Abilez OJ, Lyu X, Narayan SM, Mestroni L, Taylor MRG, Recchia FA, Wu JC. Nat Biomed Eng. 2023 Nov 27.
Congrats to Greenstone for co-publishing in Circulation
Studying Long QT Syndrome Caused by NAA10 Genetic Variants Using Patient-Derived Induced Pluripotent Stem Cells. Belbachir N, Wu Y, Shen M, Zhang SL, Zhang JZ, Liu C, Knollmann BC, Lyon GJ, Ma N, Wu JC. Circulation. 2023 Nov 14;148(20):1598-1601.
Congrats to Greenstone for co-publishing in Nature Cardiovascular Research.
Statins improve endothelial function via suppression of epigenetic-driven EndMT.
Liu C, Shen M, Tan WLW, Chen IY, Liu Y, Yu X, Yang H, Zhang A, Liu Y, Zhao MT, Ameen M, Zhang M, Gross ER, Qi LS, Sayed N, Wu JC. Nat Cardiovasc Res. 2023 May;2(5):467-485. doi: 10.1038/s44161-023-00267-1. Epub 2023 May 8. PMID: 37693816
For nearly a century, animal testing was the sole method for assessing drug safety and efficacy before advancing to human clinical trials. However, with the historically low success rate of just 9.6% for drugs entering phase I clinical trials, there’s a noticeable gap in the accuracy of animal-based tests predicting human responses. To address this, the FDA Modernization Act 2.0, passed in late 2022, paves the way for incorporating advanced non-animal testing methods into the drug approval process. This act endorses cutting-edge alternatives like cell-based approaches (e.g., human induced pluripotent stem cells, organoids), microphysiologic systems, and computer-driven methodologies, such as AI and machine learning. These innovative methods, like the “clinical trials in a dish,” aim to better replicate human variability, making drug testing more predictive of human outcomes and potentially improving the drug approval success rate.
Statins designed to lower cholesterol have long been noted to work in mysterious ways to improve other aspects of cardiovascular health. A Stanford Medicine and Greenstone Biosciences-led study by Prof Joseph Wu and colleagues uncover how they do it.
Using new genetic tools to study statins in human cells and mice, Stanford Medicine researchers and collaborators have uncovered how the cholesterol-lowering drugs protect the cells that line blood vessels.
The findings provide new insight into statins’ curiously wide-ranging benefits, for conditions ranging from arteriosclerosis to diabetes, that have long been observed in the clinic.
“The study gives us an understanding, at a very deep mechanistic level, of why statins have such a positive effect outside of reducing LDL,” said professor of medicine Joseph Wu, MD, PhD, referring to low-density lipoprotein, or “bad” cholesterol. “Given how many people take statins, I think the implications are pretty profound.”
Statins are the most prescribed medications in the country, with more than 40 million Americans taking them. Developed in the 1980s from compounds found in mold and fungi, statins target an enzyme that regulates cholesterol production in the liver. But clinical trials have shown that they also seem to safeguard against cardiovascular disease beyond their ability to lower cholesterol.
Heart failure patients who take statins, for example, are less likely to suffer a second heart attack. They have also been shown to prevent the clogging of arteries, reduce inflammation and even lower cancer risk. Yet these underlying mechanisms are poorly understood.
“Statins were invented to lower cholesterol by targeting the liver. But we didn’t know the targets or the pathways in the cardiovascular system,” said Chun Liu, PhD, an instructor at the Stanford Cardiovascular Institute and co-lead author of the study published May 8 in Nature Cardiovascular Research. Mengcheng Shen, PhD, and Wilson Tan, PhD, postdoctoral scholars at the Stanford Cardiovascular Institute, are the other co-lead authors, and Wu is the senior author.
Hints from a dish
To take a closer look at statins’ effect on blood vessels, Liu and colleagues tested a common statin, simvastatin, on lab-grown human endothelial cells derived from induced pluripotent stem cells. Endothelial cells make up the lining of blood vessels, but in many diseases they transform into a different cell type, known as mesenchymal cells, which are poor substitutes.
“Mesenchymal cells are less functional and make tissues stiffer so they cannot relax or contract correctly,” Liu said.
The researchers suspected that statins could reduce this harmful transition. Indeed, endothelial cells treated with simvastatin in a dish formed more capillary-like tubes, a sign of their enhanced ability to grow into new blood vessels.
RNA sequencing of the treated cells offered few clues. The researchers saw some changes in gene expression, but they “didn’t find anything interesting,” Liu said.
It was not until they employed a newer technique called ATAC-seq that the role of statins became apparent. ATAC-seq reveals what happens at the epigenetic level, meaning the changes to gene expression that do not involve changes to the genetic sequence.
They found that the changes in gene expression stemmed from the way strings of DNA are packaged inside the cell nucleus. DNA exists in our cells not as loose strands but as a series of tight spools around proteins, together known as chromatin. Whether particular DNA sequences are exposed or hidden in these spools determines how much they are expressed.
“When we adopted the ATAC-seq technology, we were quite surprised to find a really robust epigenetic change of the chromatin,” Liu said.
ATAC-seq revealed that simvastatin-treated cells had closed chromatin structures that reduced the expression of genes that cause the endothelial-to-mesenchymal transition. Working backward, the researchers found that simvastatin prevents a protein known as YAP from entering the nucleus and opening chromatin.
The YAP protein is known to play important roles in development, such as regulating the size of our organs, but also has been implicated in the abnormal cell growth seen in cancer.
A look at diabetes
To see the drug in context, the researchers tested simvastatin on diabetic mice. Diabetes causes subtle changes to blood vessels that mimic the damage commonly seen in people who are prescribed statins — older patients who do not have a cardiovascular condition, Liu said.
They found that after eight weeks on simvastatin, the diabetic mice had significantly improved vascular function, with arteries that more easily relaxed and contracted.
“If we can understand the mechanism, we can fine-tune this drug to be more specific to rescuing vascular function,” Liu said.
The findings also provide a more detailed picture of the vascular disease process, which could help doctors identify and treat early signs of vascular damage.
“I’ve been taking statins for the past 10 years to keep my cholesterol down. I also knew it has good vascular effects. I just didn’t know how it does it,” said Wu, the Simon H. Stertzer, MD, Professor who is also the director of the Stanford Cardiovascular Institute. “This study explains how.”
Researchers from the University of North Texas and the Ohio State University College of Medicine contributed to this study.
The study was supported by funding from the National Institutes of Health (grants R01 HL130020, R01 HL150693, R01 HL163680, R01 HL145676, P01 HL141084, R01 HL141371, R01 HL126527, R01 HL15864, R01 HL161002, R01 HL155282 and 18CDA34110293), an American Heart Association SFRN grant, an AHA Career Development Award and the Tobacco-Related Disease Research Program.
Greenstone Biosciences co-founded Joseph C. Wu, and SAB James Zou writes on the relevant AI models in healthcare and how physiological data has been harnessed by AI to advance healthcare.
Abstract
Artificial Intelligence (AI) in healthcare has generated remarkable innovation and progress in the last decade. Significant advancements can be attributed to the utilization of AI to transform physiology data to advance healthcare. In this review, we will explore how past work has shaped the field and defined future challenges and directions. In particular, we focus on three areas of development. First, we give an overview of AI, with special attention to the most relevant AI models. We then detail how physiology data has been harnessed by AI to advance the main areas of healthcare such as automating existing healthcare tasks, increasing access to care, and augmenting healthcare capabilities. Finally, we discuss emerging concerns surrounding the use of individual physiology data and detail an increasingly important consideration for the field, namely the challenges of deploying AI models to achieve meaningful clinical impact.
Single-cell technology has become an indispensable tool in cardiovascular research since its first introduction in 2009. Here, we highlight the recent remarkable progress in using single-cell technology to study transcriptomic and epigenetic heterogeneity in cardiac disease and development. We then introduce the key concepts in single-cell multi-omics modalities that apply to cardiovascular research. Lastly, we discuss some of the trending concepts in single-cell technology that are expected to propel cardiovascular research to the next phase of single-cell research.
In the past decade, the application of machine learning (ML) to healthcare has helped drive the automation of physician tasks as well as enhancements in clinical capabilities and access to care. This progress has emphasized that, from model development to model deployment, data play central roles. In this Review, we provide a data-centric view of the innovations and challenges that are defining ML for healthcare. We discuss deep generative models and federated learning as strategies to augment datasets for improved model performance, as well as the use of the more recent transformer models for handling larger datasets and enhancing the modelling of clinical text. We also discuss data-focused problems in the deployment of ML, emphasizing the need to efficiently deliver data to ML models for timely clinical predictions and to account for natural data shifts that can deteriorate model performance.
Marijuana use and heart-attack risk were correlated in a large human study, Stanford scientists and their collaborators found. A molecule in soybeans may counteract these effects.
Congratulations to Greenstone for co-publishing in Nature Biomedical Engineering
Tachycardia-induced metabolic rewiring as a driver of contractile dysfunction.
Tu C, Caudal A, Liu Y, Gorgodze N, Zhang H, Lam CK, Dai Y, Zhang A, Wnorowski A, Wu MA, Yang H, Abilez OJ, Lyu X, Narayan SM, Mestroni L, Taylor MRG, Recchia FA, Wu JC. Nat Biomed Eng. 2023 Nov 27.
Since the advent of induced pluripotent stem cell (iPSC) technology a decade ago, enormous progress has been made in stem cell biology and regenerative medicine. Human iPSCs have been widely used for disease modeling, drug discovery, and cell therapy development. Novel pathological mechanisms have been elucidated, new drugs originating from iPSC screens are in the pipeline, and the first clinical trial using human iPSC-derived products has been initiated. In particular, the combination of human iPSC technology with recent developments in gene editing and three-dimensional organoids makes iPSC-based platforms even more powerful in each area of their application, including precision medicine. In this overview, we will discuss the progress in applications of iPSC technology that are particularly relevant to drug discovery and regenerative medicine, in light of the remaining challenges and the emerging opportunities in the field.