Dr Chew Weng Cheng

Profile

Dr Cheng is a Mautner BHF Career Development fellow based within the Leeds Institute of Cardiovascular and Metabolic Medicine (LICAMM). He obtained a first-class honour in Bachelor of Biomedical Science in January 2015. Following his undergraduate degree, he studied a doctoral degree in infection and immunity jointly awarded by the University of Liverpool and Chulalongkorn University (Thailand). Subsequently, he arrived at the University of Leeds (December 2018 – November 2021) as a post-doctoral researcher to work on heart failure with and without diabetes. In March 2021, Cheng was awarded an inaugural fellowship – Mautner BHF Career Development fellowship as a first step to establish his own research group.

Cheng has experience and interested in using multi-omics big data approaches for better understanding of single- and multi-disease phenomena with a view to reducing the suffering from common communicable and non-communicable diseases. He has experience in these approaches through his work on vaccine candidates for malaria; Plasmodium vivax and his recent work on heart failure with and without diabetes. Through these apparently independent areas of work he has seen an important opportunity for a research strategy bringing together understanding of infectious and cardiovascular diseases.

Research interests

Cheng made progress with his recent exciting work on COVID-19 and identified a gene known to be important in mechanical properties of the endothelial cell membrane.Transient Receptor Potential Cation Channel of Subfamily C Family 1 (TRPC1) is suggested to mediate mechanical responses of membranes, which could be relevant to infection. Excitingly, he found that there are significant previously unknown links for ion channels with cardiometabolic diseases. Based on this foundation, Cheng aims to build a new research group focused on the novel hypothesis that genes regulating membrane mechanical properties are factors determining co-susceptibilities to infections and cardiometabolic diseases and risk of more severe outcomes. He will test this hypothesis using big data genetic approaches and then explore further by iterative more in-depth big data analysis combined with wet laboratory experiments performed with collaborators using patient tissue samples.

Qualifications

• BSc Hons
• PhD

Professional memberships

• Physiological Society
• Biophysical Society

Student education

Tutor for Introduction to Medical Sciences (IMS) module. I supervise undergraduate and postgraduate students. 

Research groups and institutes

• Leeds Institute of Cardiovascular and Metabolic Medicine
• Discovery and Translational Science
• Multidisciplinary Cardiovascular Research Centre