The genomic revolution stands eager to answer the age-old medical question, “nature versus nurture”. In a sense, we know that the symptom of disease we see in patients results from both, only with the advancing technology to sequence DNA have we begun to uncover the genetics half of the equation. For chronic diseases like type 2 diabetes, a better understanding of the genetics underlying it could lead to better therapies and maybe even prevention. For years, clinicians recognized that not all type 2 diabetic patients were the same. This study identified five genetic groups for the disease which matched the clinical picture of test subjects.
Type 2 diabetes develops mostly in adults (although childhood incidence is increasing) when the body is no longer able to keep glucose levels in a safe range. Either sufficient insulin is not produced or insulin resistance occurs in which higher levels of insulin are required to lower glucose in the blood. Five genetic clusters were uncovered in this study and the genes in each matched with the clinical picture for those patients.
While direct clinical application lies in the future, we hope this could be used to guide which therapy is best for each type 2 diabetic patient rather than the trial and error approach by most conventional doctors. Knowing the patient’s genetics could help those with diabetes to start with the right therapy targeted at their root cause. Knowing a patient’s genetics could also guide what tests are used to screen non-diabetic patients for early signs of the disease. Functional MD’s like myself would then target these specific disease mechanisms with natural therapies like berberine and others. Knowing a patient’s genetic could prevent disease and maintain the healthy abundant life we desire for our patients.
Miriam S. Udler, Jaegil Kim, Marcin von Grotthuss, Sílvia Bonàs-Guarch, Joanne B. Cole, Joshua Chiou, Michael Boehnke, Markku Laakso, Gil Atzmon, Benjamin Glaser, Josep M. Mercader, Kyle Gaulton, Jason Flannick, Gad Getz, Jose C. Florez. Type 2 diabetes genetic loci informed by multi-trait associations point to disease mechanisms and subtypes: A soft clustering analysis. PLOS Medicine, 2018; 15 (9): e1002654 DOI: 10.1371/journal.pmed.1002654