Gary Tse 謝家偉

  • Clinical Assistant Professorship in 2016 at Chinese University of Hong Kong


Current Appointments

Visiting Professor, Faculty of Health and Medical Sciences, University of Surrey, Guildford

United Kingdom

Distinguished Professor, Department of Cardiology, The Second Hospital, Tianjin Medical University, Tianjin

Principal Investigator, Tianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular Disease, Tianjin Institute of Cardiology, Tianjin

Honorary Professor, Xiamen Cardiovascular Hospital, Xiamen University, Xiamen, Fujian

Guest Professor, Department of Cardiology, The First Affiliated Hospital, Dalian Medical University, Dalian, Liaoning

Principal Investigator, Cardiovascular Analytics Group, Hong Kong

People's Republic of China


Qualifications

BA (Hons.) (Cantab.), MBBS (Imperial), MA (Cantab.), MPH (Manc.), MHM (UNSW), PhD (Cantab.), MFPH (UK), FAcadMEd, FESC, FACC, FSCAI, FHRS, FRCP (Glasg, Edin, Lond), FRCPCH, FFPH


Biography

After studying triple science and double mathematics at A-Level, with Advanced Extension Awards in Chemistry and Physics, Tse started his medical science training at Cambridge in 2005. He is now a fully trained clinician-scientist. With a strong interest in physics and mathematics since a young age, his current strategy is the application of advanced mathematical and statistical analyses to improve risk stratification in cardiovascular diseases.

Tse returned to China in 2015 as an academic. He established the Laboratory of Cardiovascular Physiology and Cardiovascular Analytics Group for pre-clinical and clinical research, respectively. In 2019, he was appointed to The Distinguished Professorship in Cardiology by the Tianjin Institute of Cardiology. He holds a Guest Professorship in Cardiovascular Medicine at The First Affiliated Hospital of Dalian Medical University and an Honorary Professorship at the Xiamen Cardiovascular Hospital of Xiamen University. 

He took a sabbatical to pursue a six-month advanced fellowship training at the Department of Cardiac Electrophysiology of the Xiamen Cardiovascular Hospital, where he focused on catheter ablation of atrial and supraventricular arrhythmias. 

Since then, he has returned to Tianjin Medical University, where he holds a full professorial appointment, directing cardiovascular research as Principal Investigator at its Key Laboratory. Tse has provided input on strategic planning at the institutional level under the direction of senior management. Through successfully leading and managing international studies with collaborative efforts, his team continues to deliver sustained and impactful research output. He has also developed experience in project and personnel management. In particular, his team's ethos is the bilateral nature of mentorship, where each team member plays an important role and is encouraged to develop his or her full potential.

He is currently a Visiting Professor at the Faculty of Health and Medical Sciences and a Fellow of the Institute of Advanced Studies, University of Surrey, Guildford, United Kingdom.

For excellence in teaching and medical education, Tse was voted by medical students for the Medical Clerkship Exemplary Teaching Award, and subsequently elected to the Fellowship of the UK Academy of Medical Educators.


Prior Appointments

Clinical Fellow, Department of Cardiac Electrophysiology, Xiamen Cardiovascular Hospital, Xiamen University, Xiamen, Fujian

Research Scientist, School of Life Sciences, Faculty of Science, The Chinese University of Hong Kong, Hong Kong

Principal Investigator, Laboratory of Cardiovascular Electrophysiology, Li Ka Shing Institute of Health Sciences, Hong Kong

People's Republic of China


Research

Gary Tse's Research page is detailed below:

https://sites.google.com/view/garytse86/home


COVID-19

1. Tse, G.*, Zhou, J.*, Lee, S., Wong, W.T., Li, X., Liu, T., Cao, Z., Zeng, D.D., Wai, A.K.C., Wong, I.C.K., Cheung, B.M.Y., Zhang, Q. (2021) Relationship between angiotensin-converting enzyme inhibitors or angiotensin receptor blockers and COVID-19 incidence or severe disease. Journal of Hypertension. https://doi.org/10.1097/HJH.0000000000002866. 5-year impact factor: 4.5.

2. Zhou, J., Lee, S., Wang, X., Li, Y., Wu, W.K.K., Liu, T., Cao, Z., Zeng, D.D., Leung, K.S.K., Wai, A.K.C., Wong, I.C.K., Cheung, B.M.Y., Zhang, Q.*, Tse, G.* (2021) Development of a multivariable prediction model for severe COVID-19 disease: a population-based study from Hong Kong. NPJ Digital Medicine. https://doi.org/10.1038/s41746-021-00433-4.

3. Zhou, J., Lee, S., Guo, C.L., Chang, C., Liu, T., Leung, K.S.K., Wai, A.K.C., Cheung, B.M.Y., Tse, G.*, Zhang, Q.* (2021) Anticoagulant or antiplatelet use and severe COVID-19 disease: a propensity score matched territory-wide study. Pharmacological Research. 105473. PMID: 33524539. https://doi.org/10.1016/j.phrs.2021.105473. 5-year impact factor: 5.6.

4. Zhou, J., Wang, X., Lee, S., Wu, W.K.K., Cheung, B.M.Y., Zhang, Q.*, Tse, G.* (2020) Proton pump inhibitor or famotidine use and severe COVID-19 disease: a propensity score-matched territory-wide study. Gut. gutjnl-2020-323668. PMID: 33277346. https://doi.org/10.1136/gutjnl-2020-323668. 5-year impact factor: 17.8.

5. Li, X., Guan, B., Su, T., Liu, W., Chen, M., Bin Waleed, K., Guan, X., Tse, G.*, Zhu, Z.* Impact of cardiovascular disease and cardiac injury on in-hospital mortality in patients with COVID-19: a systematic review and meta-analysis. (2020) Heart. 27:heartjnl-2020-317062. PMID: 32461330. https://doi.org/10.1136/heartjnl-2020-317062. 5-year impact factor: 5.4.

6. Wang, Y., Tse, G., Li, G., Lip, G.Y.H., Liu, T. (2020) ACE Inhibitors and Angiotensin II Receptor Blockers May Have Different Impact on Prognosis of COVID-19. Journal of the American College of Cardiology. 76(17):2041. PMID: 33092742. https://doi.org/10.1016/j.jacc.2020.07.068. 5-year impact factor: 19.0.


Cardiac Arrhythmias and Sudden Cardiac Death

1. Tse, G.*, Zhou, J., Lee, S., Liu, T., Bazoukis, G., Mililis, P., Wong, I.C.K., Chen, C., Xia, Y., Kamakura, T., Aiba, T., Kusano, K., Zhang, Q., Letsas, K.P. (2020) Incorporating latent variables using nonnegative matrix factorization improves risk stratification in Brugada syndrome. Journal of the American Heart Association. e012714. PMID: 33170070. https://doi.org/10.1161/JAHA.119.012714. 5-year impact factor: 5.1.

2. Lee, S., Zhou, J., Li, K.H.C., Leung, K.S.K., Lakhani, I., Liu, T., Wong, I.C.K., Mok, N.S., Mak, C., Jeevaratnam, K., Zhang, Q.*, Tse, G.* (2021) Territory-wide Cohort Study of Brugada Syndrome in Hong Kong: Predictors of Long-Term Outcomes Using Random Survival Forests and Non-Negative Matrix Factorisation. Open Heart. 8(1):e001505. PMID: 33547222. https://doi.org/10.1136/openhrt-2020-001505. 5-year impact factor: 2.6.

3. Tse, G., Lee, S., Li, A., Chang, D., Li, G., Zhou, J., Liu, T., Zhang, Q. (2021). Automated electrocardiogram analysis identifies novel predictors of ventricular arrhythmias in Brugada syndrome. Frontiers in Cardiovascular Medicine. 7:618254. PMID: 33521066. https://doi.org/10.3389/fcvm.2020.618254. Impact factor: 3.9.

4. Tse, G., Lee, S., Mok, N.S., Liu, T., Chang, D. (2020) Incidence and Predictors of Atrial Fibrillation in a Chinese Cohort of Brugada Syndrome. International Journal of Cardiology. S0167-5273(20)31954-9. PMID: 32387420. https://doi.org/10.1016/j.ijcard.2020.05.007. 5-year impact factor: 4.0.

5. Tse, G.*, Lee, S., Liu, T., Yuen, H.C., Wong, I.C.K., Mak, C., Mok, N.S., Wong, W.T. (2020) Identification of novel SCN5A single nucleotide polymorphisms in Brugada syndrome: a territory-wide study from Hong Kong. Frontiers in Physiology. 11:574590. PMID: 33071830. https://doi.org/10.3389/fphys.2020.574590. 5-year impact factor: 3.9.

6. Lee, S., Zhou, J., Liu, T., Letsas, K.P., Hothi, S.S., Vassiliou, V., Li, G., Baranchuk, A., Chang, D., Zhang, Q., Tse, G.* (2020) Temporal variability in electrocardiographic indices in subjects with Brugada patterns. Frontiers in Physiology. 11:953. https://doi.org/10.3389/fphys.2020.00953. 5-year impact factor: 3.9.

7. Tse, G., Lee, S., Zhou, Liu, T., Wong, I.C.K., Mak, C., Mok, N.S., Jeevaratnam, K., Zhang, Q., Cheng, S.H., Wong, W.T. (2021) Territory-wide Chinese cohort of long QT syndrome: random survival forest and Cox analyses. Frontiers in Cardiovascular Medicine. 8:608592. PMID: 33614747. https://doi.org/10.3389/fcvm.2021.608592. Impact factor: 3.9.

8 Chen, C., Zhou, J., Yu, H., Zhang, Q., Lin, Y., Li, D., Yang, Y., Wang, Y., Tse, G.*, Xia, Y.* (2020) Identification of important risk factors for all-cause mortality of acquired long QT syndrome patients using random survival forests and non-negative matrix factorization. Heart Rhythm. S1547-5271(20)31033-X. PMID: 33127541. https://doi.org/10.1016/j.hrthm.2020.10.022. 5-year impact factor: 4.8.


Cardiovascular Risk

1. Zhang, N, Tse, G., Liu, T. (2021) Neutrophil-lymphocyte ratio in the immune checkpoint inhibitors-related atherosclerosis. European Heart Journal. PMID: 33748846. https://doi.org/10.1093/eurheartj/ehab158. 5-year impact factor: 20.1.

2. Guo, S., Tse, G., Liu, T. (2020) Cardioprotective strategies to prevent trastuzumab-induced cardiotoxicity. Lancet. 15;395(10223):491-492. PMID: 32061289. https://doi.org/10.1016/S0140- 6736(19)32549-8. Impact factor: 59.

3. Ju, C., Lai, R.W.C., Li, K.H.C., Hung, J.K.F., Lai, J.C.N., Ho, J., Liu, Y., Tsoi, M.F., Liu, T., Cheung, B.M.Y., Wong, I.C.K., Tam, L.S., Tse, G.* (2019) Comparative cardiovascular risk in users versus non- users of xanthine oxidase inhibitors and febuxostat versus allopurinol users. Rheumatology. PMID: 31873735. https://doi.org/10.1093/rheumatology/kez576. Impact factor: 5.7.

4. Roever, L., Tse, G., Versaci, F., Biondi-Zoccai, G. (2019) Admission glucagon-like peptide-1 levels in acute myocardial infarction: is this really a new biomarker of cardiovascular risk? European Heart Journal. PMID: 31834367. https://doi.org/10.1093/eurheartj/ehz868. Impact factor: 25.

5. Tse, G., Gong, M., Li, G., Wong, S.H., Wu, W.K.K., Wong, W.T., Roever, L., Lee, A.P.W., Lip, G.Y.H., Wong, M.C.S., Liu, T. (2018) Genotype-guided warfarin dosing vs. conventional dosing strategies: a systematic review and meta-analysis of randomized controlled trials. British Journal of Clinical Pharmacology. 84(9):1868-1882. PMID: 29704269. https://doi.org/10.1111/bcp.13621. 5-year impact factor: 4.2.

6. Tse, G.*, Gong, M., Wong, S.H., Wu, W.K.K., Bazoukis, G., Lampropoulos, K., Wong, W.T., Xia, Y., Wong, M.C.S., Liu, T., Woo, J. (2017) Frailty and clinical outcomes in advanced heart failure patients undergoing left ventricular assist device implantation: a systematic review and meta-analysis. Journal of the American Medical Directors Association. pii: S1525-8610(17)30545-5. PMID: 29129497.http://dx.doi.org/10.1016/j.jamda.2017.09.022. Impact factor: 5. 


Pre-clinical research summary

In collaboration with Prof. Jack Wong and Prof. Tong Liu's research groups, Tse's team focuses on investigating the pathophysiology of atrial and ventricular arrhythmias, which are important conditions leading to thromboembolic events and sudden cardiac death, respectively. They have unravelled the novel mechanisms by which immunosuppressive, anti-lipidemic and anti-diabetic medications exert protective effects against atrial fibrillation (Liu,..., Tse, Li and Liu, Cardiovasc Ther. 2017 Oct;35(5)). Using a combination of genetic, pharmacological, biochemical and imaging approaches, the team has identified reductions in oxidative stress and prevention of mitochondrial dysfunction are critical to achieve reverse remodelling of the atria (Zhang,...Tse, Li and Liu, J Am Heart Assoc. 2017 May 15;6(5). pii: e005945; Yang,...Tse, Li and Liu, J Am Heart Assoc. 2018 May 2;7(10):e008807; Shao et al., Cardiovasc Diabetol. 2019,18(1):165. doi: 10.1186/s12933-019-0964-4; Wang...Tse, Li, Liu, Fu., J Physiol Biochem. 2020 Oct 21. doi: 10.1007/s13105-020-00769-7).

Using Langendorff mouse models (reviewed in Yeo,...and Tse, J Basic Clin Physiol Pharmacol. 2017 May 1;28(3):191-200), his team has elucidated the relative contributions of gap junction and sodium channel function to cardiac conduction, and the relationship between conduction, repolarization, their heterogeneities, and dynamic substrates of electrical restitution to atrial and ventricular arrhythmogenicity. Of note, his team was the first to validate the use of the S1S2 protocol against the gold standard of dynamic pacing for assessing electrical restitution in mice. With The team's recent efforts have focused on the use of time-domain, frequency-domain and non-linear analysis to interrogate data derived from action potential time series (Tse et al., Front Physiol. 2018 9:1578). Under the directions of Prof. Kamalan Jeevaratnam's group in the United Kingdom, it was found that three dimensional restitution analysis of sinus rhythm electrocardiograms followed by application of the k-NN classifier algorithm with matching using synthetic minority oversampling technique could be used to predict paroxysmal atrial fibrillation in equine athletes (Huang, Alexeenko, Huang, Tse, Marr and Jeevaratnam, Function. 2020. doi:10.1093/function/zqaa031).


Clinical research summary

In collaboration with local and international groups, Tse's team utilizes clinical data to better define disease life course and epidemiology of cardiac arrhythmias. Using insights from their pre-clinical programme, they have identified key electrocardiographic (ECG) predictors that can aid risk stratification in stroke. They have validated that atrial remodelling can be detected using the ECG and P-wave parameters reflecting atrial electrical dysfunction can predict future onset and recurrence of atrial fibrillation (AF) (Tse et al., Int J Cardiol. 2017), and more importantly stroke events independently of AF (He, Tse et al., Stroke. 2017 Aug;48(8):2066-2072). Recently, the team applied a decision tree learning approach, demonstrating that incorporation of individual and non-linear interaction variables between P-wave area and age significantly improved prediction of incident atrial fibrillation (Tse et al., Front. Bioeng. Biotechnol. 2020). They subsequently discovered that a multi-task Gaussian process learning model significantly improved the predictive performance for adverse outcomes such as atrial fibrillation, transient ischaemic attack/stroke and all-cause mortality compared to logistic regression and decision tree learning (Tse et al., Eur J Clin Invest, 2020; Tse et al., ESC Heart Failure, 2020).

Moreover, his team has identified ECG predictors for ventricular arrhythmic and sudden cardiac death events in rare congenital ion channelopathies and more prevalent conditions of ischemic heart disease and myocardial infarction. These include fragmentation of the QRS complex (Meng et al., Front Physiol. 2017 Sep 12;8:678) and prolonged Tpeak-Tend intervals (Tse et al. Heart Rhythm. 2017 Aug;14(8):1131-1137), reflecting increased dispersion of conduction velocities and increased spatial dispersion of repolarization, respectively (reviewed in Tse et al., Europace. 2017 May 1;19(5):712-721). Tse is currently working with his team to establish multi-center arrhythmia cohorts, such as Brugada syndrome and long QT syndrome, utilizing the full capabilities of cutting edge machine learning techniques to perform higher dimensional analysis on multi-modality data sets. In a multi-national study involving China, Japan and Greece, the team found that incorporating latent features between risk variables significantly improved arrhythmic risk prediction in Brugada syndrome (Tse et al., Journal of the American Heart Association 2020, DOI: 10.1161/JAHA.119.012714). In collaboration with Dalian Medical University, the team found that mortality prediction in patients with acquired long QT syndrome was more accurate using both random survival forests (RSF) and non-negative matrix factorization (NMF) compared to RSF and Cox regression models (Chen, ... Tse*, Xia*, Heart Rhythm 2020, S1547-5271(20)31033-X).

Tse's group makes use of population- and registry-based data to examine the epidemiology, disease outcomes (Wang...Tse, EuroIntervention. 2020 Jan 28. pii: EIJ-D-19-00225) and comparative drug effects in different cardiovascular conditions (Ju...Tse, Rheumatology (Oxford) 2020. pii: kez576) and to create score-based systems with advanced machine learning techniques for improving risk stratification (Li...Tse, Atherosclerosis 2020, 301:30-36). His team also further provided epidemiological evidence on the cancer-metabolic link, reporting important relationships between serum insulin levels and lymph node metastases in endometrial cancer (Mu...Tse, Cancer Medicine 2018. 7(4):1519-1527).

Finally, in collaboration with international investigators, Tse publishes high-quality systematic reviews and meta-analyses on cardiovascular epidemiology, thereby providing a scientific basis for evidence-based practice in clinical medicine (e.g. Tse et al., J Am Med Dir Assoc 2017, 18(12):1097.e1-1097; Tse et al., Int J Cardiol 2018. 250:152-156; Lakhani...Tse, Metabolism 2018. 83:11-17; Chi...Tse, JACC Clinical Electrophysiology 2018 4(9):1214-1223; Tse et al. Br J Clin Pharmacol. 2018 Sep;84(9):1868-1882).


Service and Output

Together, Tse and his team have published in the Lancet, European Heart Journal, Journal of the American College of Cardiology, Journal of the American Medical Directors Association, Circulation: Arrhythmia and Electrophysiology, Circulation: Cardiovascular Imaging, International Journal of Cardiology, European Journal of Clinical Investigation, ESC Heart Failure, Stroke, Gut, Heart, Journal of the American Heart Association, Heart Rhythm, Europace, Journal of Arrhythmia and JACC: Clinical Electrophysiology. Their research has been recognized by conferences organized by learned societies, including the Gordon Research Conferences, European Cardiac Arrhythmia Society, Heart Rhythm Society and Europace. Tse has served as chairman/co-chairman of five national meetings, such as the NSFC-RGC Conference in Calcium Signalling, and The Joint Inaugural Clinical and Translational Cardiology Conference). 

Tse serves on the editorial board of Current Hypertension Reviews, Cardio-Oncology, Journal of Electrocardiology, Oxford Medical Case Reports, Biomedical Reports, International Journal of Cardiology Heart & Vasculature, Frontiers in Physiology, Section of Cardiac Electrophysiology and Frontiers in Cardiovascular Medicine, Section of Cardiac Rhythmology. He is a regular academic reviewer for > 40 international journals in cardiology, cardiac electrophysiology, cardiovascular biology and epidemiology. He is an International Council Member, International Society of Electrocardiology (ISE), and Nucleus Committee Member, Young Community of the ISE; Co-Director, International Health Informatics Study Network (IHISN): a research collaborative network involving >25 academics from 6 countries. He also served as Abstract Reviewer for European Society of Cardiology Congress and external expert reviewer for funding bodies from the UK (Medical Research Council, Rosetrees Trust) and New Zealand (Auckland Medical Research Foundation).

Tse has attracted approximately $12 RMB million research-related funding as a principal applicant and co-applicant. In recognition of contributions to the understanding of cardiac electrophysiology, Tse was recently awarded the ECG Bayés Award by the International Congress of Electrocardiology for the best research output by a young investigator.