Health & Medicine, Canada (Commonwealth Union) – Type 2 diabetes mellitus, a chronic metabolic disorder characterized by elevated blood sugar levels, affects millions of individuals worldwide. The increasing prevalence of this condition, closely associated with sedentary lifestyles and unhealthy dietary habits, has prompted extensive research efforts aimed at unraveling its complexities. Over the years, remarkable strides have been made in understanding the underlying mechanisms, risk factors, and potential interventions for type 2 diabetes.
The integration of artificial intelligence (AI) and machine learning techniques in diabetes research has revolutionized disease prediction and management. Advanced algorithms trained on large datasets can now analyze multifactorial factors such as genetics, lifestyle, and clinical data to predict an individual’s risk of developing diabetes. Additionally, AI-driven systems have the potential to enhance early detection, enable precision medicine approaches, and optimize treatment strategies, empowering healthcare professionals to make more informed decisions.
A global team of scientists with collaborations from Europe, Canada, and the USA have found molecules in samples obtained from 3,000 diabetic patients that may assist in personalizing treatments.
This study was conducted as a component of the European RHAPSODY project (Risk Assessment and Progression of Diabetes). They received funds from the Innovative Medicines Initiative, RHAPSODY a joint project consisting of over 100 scientists that represent twenty academic institutions, five pharmaceutical companies together with two small and medium enterprises.
The collaboration involved Guy Rutter, a researcher affiliated with the CHUM Research Centre (CRCHUM) and Imperial College London, in addition to being a professor at Université de Montréal. They worked together with Ewan R. Pearson from the University of Dundee and Leen M’t Hart from Leiden University Medical Center. Notably, Roderick C. Slieker, a member of M’t Hart’s team, served as the study’s primary author.
The findings appeared in the journal Nature Communications, which gave insights into new molecules that may assist clinical teams in forecast and tracking the decline of glucose metabolisms.
Rutter indicated in the study, that they selected to systematically assay biomarkers for diabetes progression. They are part of 3 very different molecular classes: small charged molecules (metabolites), lipids, and proteins.
Researchers indicated that sophisticated molecular tests conducted on blood samples from 3,000 people from 3 cohorts in Europe and 1 in the USA, the researchers had the ability to find that certain 20 molecules, 9 lipids, 3 metabolites as well as 11 proteins, that were linked with fast disease progression.
From the 1,300 proteins evaluated, the protein NogoR stood out from the rest.
To consolidate these findings, Rutter and his team tested the impact of an increase in NogoR blood levels on the metabolism of genetically modified mice.
“By injecting mice fed a high fat/high sugar diet, we improved their glucose tolerance. On db/db mice, a type 2 diabetes mouse model, we worsened their insulin sensitivity, i.e., their ability to regulate blood sugar levels,” explained Rutter.
“By shedding light on the signaling pathways and mechanisms involved, we might be able to inhibit this protein that kills the pancreatic cells responsible for insulin secretion, thereby slowing the progression of diabetes.”
“In our study, we were also surprised to see that the biomarkers for diabetes progression that we identified are the same as those related to diabetes risk. This suggests that the same biological process is operating in both cases,” explained Rutter.
In the not-too-distant future, the researchers envision a scenario where clinical teams can efficiently and affordably analyze these emerging biomarkers by utilizing a mere droplet of blood. This breakthrough would significantly enhance the accuracy of disease progression predictions. However, achieving this goal necessitates the advent of several technological advancements.
Right now, type 2 diabetes affects a staggering 400 million individuals across the globe. Alarming projections indicate that this number will skyrocket to over 700 million by the year 2045.
