MetHealth Team wins Startup of the Year

MetHealth Team wins Startup of the Year

There is keen interest across the field of obesity in identifying approaches that move “beyond BMI” in identifying risk and complications for people living with obesity. We are pleased to introduce Fiona McGillicuddy, PhD, Assistant Professor in the Cardiometabolic Research Group, University College Dublin School of Medicine

Fiona, congratulations to you and the MetHealth team on winning the University College Dublin Startup of the Year award

Thank you so much Sheree – I feel really privileged to have won the competition. This project has been a passion of mine for many years, so it was nice to have the judges on the day validate that there is a major unmet need in the healthcare setting to identify people with obesity who are at highest risk of complications in a timely manner; and critically to move away from that ‘one size fits all approach’ to managing patients with obesity.

We know at this point that people living with obesity vary widely in terms of their risk of developing complications. It is also now widely accepted that BMI is not particularly helpful to identify the highest-risk patients – indeed 10% of people within the ‘optimal weight’ category are also at extremely high-risk of heart disease (metabolically unhealthy lean). What we are really lacking are tests to identify the highest risk patients that are non-invasive. I’m particularly interested in identifying people who are at the highest risk of developing ‘cardiometabolic disease’ including liver disease, diabetes, insulin resistance and heart disease. Early identification of these patients will enable timely intervention and preventative management within this population – this could ultimately be life-saving.

Please describe your novel product and approach, and tell us how it will change the obesity space

My group are specifically developing a novel high-throughput high-density lipoprotein (HDL) proteomics assay that can accurately risk stratify patients with obesity according to their metabolic health status. Most people are aware that HDL-cholesterol (HDL-C) is widely used as a biomarker for cardiometabolic disease – however measurement of cholesterol alone on these particles is a massive over-simplification of an extremely complex lipoprotein particle. What most people don’t realise is that HDL carries over 100 different proteins within their cargo – this is known as the ‘HDL proteome’. My group have previously shown that the proteins that attach to HDL are remarkably modulated in obesity in preclinical studies with accumulation of liver-derived pro-inflammatory proteins and loss of anti-inflammatory proteins on HDL particles. These effects are importantly completely independent of HDL-C levels. We were also able to show that the HDL proteome could track changes within the liver proteome and mirror dysmetabolism in the liver. This was extremely exciting as HDL particles circulate in the blood and are therefore easily accessible via a simple blood-test. We subsequently showed that this paradigm also happens in human obesity (patent filed) – when we collated our data into a scoring algorithm we could show that the HDL proteome outperformed all the current biomarkers of cardiometabolic health (triglycerides, HDL-C, blood pressure, glucose etc). Our data to date suggests the reason the HDL proteome is so sensitive is due to its ability to detect liver inflammation. Over 70% of HDL particles are made by and secreted from the liver so it is perhaps not surprising that the HDL proteome could be a powerful biomarker for liver disease. However isolating HDL from serum is a laborious process and measuring over 70 proteins on a given lipoprotein particle would once upon a time have been unimaginable. Within the MetHealth project we have developed a new method to isolate HDL from serum in a high throughput manner and developed a targeted proteomics assay that can measure over 70 HDL-associated proteins in any given sample. We also have a scoring algorithm generated for metabolic health status and hope to expand this scoring algorithm to include other cardiometabolic complications in particular liver disease and heart disease.

Are there specific obesity related complications your approach may help with?

Our major focus at the moment is on using the HDL proteome as a biomarker for liver disease in obesity. Obesity is rapidly becoming the leading cause of liver transplant in western society. There is a major unmet need in healthcare setting for better biomarkers of liver disease, in particular for early stages of non-alcoholic steatohepatitis (NASH) which if caught early is reversible. Indeed, we have no true appreciation of the prevalence of NASH in society due to the lack of a good screening tool. In addition, drugs to specifically target NASH are a major unmet need but recruitment of patients into clinical trials has been very challenging due to lack of a non-invasive test to identify suitable trial participants. The only way to currently diagnose NASH is through an invasive liver biopsy. These are time-consuming, expensive, painful for the patient, unreliable and associated with bleeding complications. While non-invasive imaging techniques such as fibroscan are now available they are limited in their ability to detect early stages of NASH (excellent for picking up fibrosis). Our clinical data indicates that the HDL proteome will be particularly useful to identify patients who are at the early stages of NASH prior to onset of liver fibrosis/failure. Inflammation is a classic hallmark of NASH but biomarkers of liver inflammation have been difficult to identify. The HDL proteome is an ideal biomarker as it gives us a signal for both inflammation and dysmetabolism from the liver (immunometabolism marker) – it is the combination of changes in liver metabolism and liver inflammation that I think will be particularly powerful within our assay.

We hope that our technology will help address some of these key public health questions around the prevalence of NASH, improve the patient experience by eliminating the need for invasive liver biopsies, help healthcare screen their patients for NASH and enable timely intervention in the highest risk patients. Our clinical data suggests that significant weight-loss after bariatric surgery can reverse adverse changes within the HDL proteome observed in obesity; in turn there is an 88% lower risk of progression to major adverse liver outcomes after bariatric surgery. With the emergence of the new era of obesity medications, and bariatric surgery, and greater understanding of obesity pathophysiology, I think we are at an extremely exciting time in obesity management. Pushing pre-diabetes and NASH into remission can (and should) finally be a cornerstone of obesity management prior to onset of pancreas and liver failure – biomarkers such as the HDL proteome will ultimately be able to guide patients with obesity onto their optimal and personalised care pathways to mitigate their long-term risk of developing life-limiting complications. I hope to have a small role to play on this exciting journey towards better patient care and outcomes for people living with obesity.

Excellent news! Thank you Fiona, and good luck to you and the team as you take the product to the next phase of development!