HKUMed Leads in Synergising Global Clinical Trials Data: Reviewing Cardiovascular Drug Safety and Novel Clinical Applications

A research team led by the Department of Medicine, under the School of Clinical Medicine, LKS Faculty of Medicine of the University of Hong Kong (HKUMed), has synergised impacts of worldwide clinical trial data through a series of meta-analyses on GLP‑1 receptor agonists, an emerging cardiometabolic drug, offering in-depth insights into its safety profile and novel therapeutic potential in treating cardiovascular diseases. The study found that there was no definite risk of ischaemic optic neuropathy associated with GLP-1 agonist use in patients with diabetes or heart diseases. It also revealed that cardiac patients with obesity may improve the long-term success rate of curative catheter ablation for atrial fibrillation by adopting various weightcontrol measures, along with appropriate medication. These findings will help frontline clinicians perform more comprehensive risk‑benefit assessments before prescribing medications.

HKUMed study finds no clear link between GLP‑1 use and ischaemic optic neuropathy, and shows that obese cardiac patients may improve long‑term atrial fibrillation ablation outcomes through weight control along with appropriate medication. Photo source: HKUMed

Data from over 80,000 patients show no significant optic nerve risk from GLP-1 therapy

GLP-1 receptor agonists are an emerging class of therapeutics for treating obesity, diabetes and cardiometabolic diseases. As their clinical use continues to expand, concerns about their potential side effects have emerged. Previous research indicated a possible link between GLP-1 receptor agonists and ischaemic optic neuropathy, a serious ocular complication that can cause sudden, painless vision loss and visual field defects, particularly among individuals with diabetes and hypertension. However, evidence regarding this risk has remained inconsistent and at times conflicting.

In view of this, HKUMed conducted a meta-analysis to evaluate the safety profile and therapeutic potential of GLP-1 receptor agonists. The team analysed global clinical trial data comprising more than 80,000 patients with diabetes and heart disease, representing the largest sample size examined in this field to date. The findings showed no significant association between the use of GLP-1 receptor agonists and the risk of adverse vision-threatening complications, providing clearer evidence for formulating clinical treatment plans and enabling doctors to comprehensively assess the benefits and risks of these medications.

Integrated weight management and medication improve surgical success

Obesity increases the risk of developing cardiovascular diseases, such as atrial fibrillation (AF), which is the most common cardiac arrhythmia encountered in clinical practice and can result in life-threatening complications, including stroke and heart failure. In another study, the team analysed data from 5,415 patients with atrial fibrillation and found that for individuals with obesity, every 1% reduction in weight was associated with a 6.3% reduction in the relative risk in AF recurrence after catheter ablation. This highlights that sustained weight control is a critical factor in operative success.

Cardiac patients with obesity may improve the long-term success rate of catheter ablation for atrial fibrillation though a holistic approach to weight control, including adopting a healthier lifestyle and incorporating other clinical interventions, together with GLP-1 receptor agonists. Optimal treatment outcomes require patients to adopt a comprehensive cardiovascular risk management strategy, rather than relying solely on medication.

The findings were published in the latest issue of Diabetes Care, which is the journal of the American Diabetes Association, and were presented at the European Heart Rhythm Association Congress in Vienna in 2025.

Data‑driven insights help doctors evaluate new drugs

Lead investigator Dr Will Chan Yap-hang, Clinical Assistant Professor, Department of Medicine, School of Clinical Medicine, HKUMed, said, ‘Our meta-analysis of clinical trial data provides important evidence regarding both the safety profile and novel use of GLP-1 receptor agonists in cardiovascular patients. This will help doctors more comprehensively evaluate the potential risks and benefits of prescribing these medications. However, this research does not completely rule out the possibility of rare adverse complications. Clinicians must exercise careful judgement based on each patient’s condition. It is essential not to overemphasise the potential benefits while overlooking the associated risks, and to always assess the situation holistically.’

About the research team

This interdisciplinary study was co-led by Dr Will Chan Yap-hang, Clinical Assistant Professor, and Professor Tse Hung-fat, Chair Professor and Department Chairperson, both from the Department of Medicine, School of Clinical Medicine, HKUMed. The first author is Ms Kathleen Li Hoi-ying. Other team members include Professor Yiu Kai-hang, Clinical Professor, Department of Medicine, and Dr Kendrick Co Shih, Clinical Associate Professor of Practice, Department of Ophthalmology, both from the School of Clinical Medicine, HKUMed.

HKUMed evaluates the safety profile and therapeutic potential of GLP-1 receptor agonists by analysing global clinical trial data comprising more than 80,000 patients with diabetes and heart disease. The research is led by Dr Will Chan Yap-hang (second right) and Professor Tse Hung-fat (middle). Photo source: HKUMed

A research team from the Department of Pharmacology and Pharmacy at the LKS Faculty of Medicine of the University of Hong Kong (HKUMed) has developed an innovative AI-based cardiovascular risk prediction tool, called CardiOmicScore. With a single blood test, the system can accurately forecast the future risk of six major cardiovascular diseases (CVDs): coronary artery disease, stroke, heart failure, atrial fibrillation, peripheral artery disease and venous thromboembolism. It can also provide early warning signals up to 15 years before clinical onset. The findings were published in Nature Communications [link to the publication].

HKUMed develops a cardiovascular risk prediction tool that can accurately predict the future risk of six major cardiovascular diseases with a single blood test. The system can provide early warning signals up to 15 years before clinical onset. The research is led by Professor Zhang Qingpeng (left).

AI-based multiomics integration reflects the body’s real-time health status

CVDs remain the leading cause of death worldwide, accounting approximately 19.8 million fatalities in 2022 alone. In routine health assessments, physicians typically evaluate cardiovascular risk based on age, blood pressure, smoking and other conventional clinical indicators. However, these measures often fail to capture subtle and early biological changes before the disease becomes clinically apparent, leading to many patients missing the optimal window for preventive intervention. Although polygenic risk scores have become popular in recent years, genetic predisposition is largely fixed at birth and does not change over time. Consequently, polygenic risk scores cannot reflect the immediate impact on health conditions resulting from lifestyle or environmental changes. This creates an urgent need for tools that can capture a person’s current biological state and provide accurate, early warnings for CVDs.

To address this problem, the HKUMed research team applied deep learning techniques to integrate multiomics data, including genomics, metabolomics and proteomics, to develop the CardiOmicScore tool. The study was based on large-scale population data from the UK Biobank, analysing 2,920 circulating proteins and 168 metabolites measured from blood samples. These molecular signals act as ‘real-time recorders’ of the body, sensitively reflecting subtle changes in the immune system, metabolism, and vascular health.

Professor Zhang Qingpeng, Associate Professor in the Department of Pharmacology and Pharmacy at HKUMed, explained, ‘Genes determine where we start—they define our baseline health risk. However, proteins and metabolites reflect our current physical health. Our AI tool is designed to decode these complex molecular signals, enabling doctors and patients to identify risks much earlier, which can potentially change the trajectory of disease through timely lifestyle modifications and early prevention.’

Accurate prediction of six major cardiovascular diseases with 15-year advance warning in high-risk groups

The results showed that CardiOmicScore transforms complex multiomics measurements into personalised risk scores with substantially improved predictive performance compared with conventional polygenic risk scores. When combined with clinical information such as age and gender, the model significantly enhanced the risk prediction accuracy of six common CVDs and can even flag elevated risk up to 15 years before symptoms appear.

This study marks a shift in precision medicine from a static, gene-centric paradigm towards a more dynamic, multiomics-based approach. In the future, a small-volume blood sample may be sufficient to generate a comprehensive cardiovascular risk profile for multiple diseases.

Professor Zhang added, ‘We aim to leverage technology to identify and prevent diseases before they develop. By shifting health management from reactive treatment to proactive prediction and intervention, we aim to create a lasting impact for both public health and individual patient care.’

About the research team

The study was led by Professor Zhang Qingpeng, Associate Professor in the Department of Pharmacology and Pharmacy, HKUMed, and the HKU Musketeers Foundation Institute of Data Science (IDS). The first author is Luo Yan from the HKU IDS.