Cell-free RNA as a biomarker of the complications and long-term outcomes of obesity
Description: Obesity is a major health concern worldwide due to its ever-increasing prevalence and the socioeconomic burden of its cardiometabolic complications such as diabetes, dyslipidemia, fatty liver disease and cardiovascular disease. There is increasing interest in pharmaceutical (GLP-1 and GLP-1/GIP receptor agonists) and surgical treatment (bariatric surgery) of obesity with the former leading to a median weight loss of 16% and the latter to 30%. However, the response of patients to an obesity treatment or surgery is highly variable and there are no clear-cut predictive factors or known mechanisms to be implicated in this response. It is estimated that about 580,000 patients undergo a bariatric surgery per year world-wide and 15-35% do not reach the expected weight loss. ?ariatric surgery is an invasive procedure that entails some risks and of course increased health care costs (not only for the surgery per se but also for the lifelong follow-up). Therefore, it would be ideal to know which patients are at high risk of not reaching the weight loss goals. This group of patients could begin with other treatments/interventions before resorting to surgery or would have a stricter follow-up after the surgery. Herein we propose the development of a novel set of transcriptomic biomarkers based on liquid biopsies (blood draw) that enable the classification of subjects based on response to obesity surgery and secondarily based on the presence/absence of metabolic comorbidities. Our overarching hypothesis is that we can identify dynamic transcriptomic changes in cell-free RNA (cfRNA) that can predict the response to surgery for these patients and the presence of comorbidities. cfRNA profiling by high-throughput transcriptomics is in the early stages of research applications in the field of metabolic diseases. The advantage of using cfRNA is that it is a highly dynamic molecule that reflects processes that are ongoing in human cells. There is a number of processes by which cfRNA is introduced in the bloodstream including exosomes or can reflect oxidative stress, inflammation and cell death. cfRNA can also provide information about the tissue of origin of RNA molecules as they can be tissue-specific. Therefore, identification of transcriptomic changes of cfRNAs can provide mechanistic explanations as well as serving as biomarkers. The following specific aims will be pursued in this proposed research by applying transcriptomic profiling in cfRNAs in serum from obese patients undergoing bariatric surgery: Aim 1: To identify unique cfRNA signatures that could predict the body weight evolution after bariatric surgery. Hypothesis 1: Patterns of cfRNA expression can distinguish between subjects that reach or not the expected target of excess weight loss after bariatric surgery. Aim 2: To compare the cfRNA profiles in obese patients with or without specific metabolic comorbidities. Hypothesis 2: Specific patterns of cfRNA profiles expression could predict the presence or absence of an obesity-related comorbidityThe main expected discoveries are the development of a prediction model of the outcomes of bariatric surgery that includes cfRNA biomarkers and also the correlation of certain cfRNA profiles with the presence of metabolic comorbidities of obesity. This will not only be the first research study of cfRNAs in the outcomes of obesity but has also the potential to identify cfRNAs in obese subjects that are related to cardiometabolic complications of obesity so as not only to get some mechanistic insights but also to intervene/treat early where needed.
Amount: CHF 100,000
Funding type: grant
Funder scheme: Spark
Start date: 2023-12-01
End date: 2024-11-30
Investigator: Chartoumpekis, Dionysios
Institution: University of Lausanne – LA
Funded outputs count: 1
Funder award ID: 220825
OpenAlex ID: G2864436937