Does your patient have an atypical Diabetes presentation? Polygenic Risk Scores may be able to help you differentiate between Type 1 and Type 2 Diabetes.
The Science Behind Polygenic Risk Scores - Type 1 and Type 2 Diabetes
This Behind the Science blog post features summaries* of a few promising studies researchers have completed in the field of Polygenic Risk Scores (PRS). This series will provide our more clinical readers insight into some of the arenas in which PRS can provide utility, allowing for better risk stratification for various diseases. For more general patient-focused knowledge regarding the diseases on our panel, please visit our “Deep Dive” blogs on Type 1 and Type 2 Diabetes
*Please note that the following blog post includes information pulled directly from the referenced articles and may also include direct quotes from the research team or other experts. For more detailed study information, including additional methods, a discussion of study limitations, and more, please refer to the cited article(s) directly.
Research Citation: “Utility of Polygenic Scores for Differentiating Diabetes Diagnosis Among Patients With Atypical Phenotypes of Diabetes.” (2023). Billings, L.K., Shi, Z., Wei, J., Rifkin, A.S., Zheng, S.L., Helfand, B.T., Ilbawi, N., Dunnenberger, H.M., Hulick, P.J., Qamar, A., Xu, J. The Journal of Clinical Endocrinology & Metabolism. 2023; 00; 1-7. https://pubmed.ncbi.nlm.nih.gov/37560999/
Background
According to the World Health Organization and other sources, Diabetes (or, rather, complications arising from Diabetes) are a leading cause of death worldwide. As many are aware, Diabetes is a condition characterized by the body's inability to properly process glucose (or “blood sugar”) for the body’s metabolic needs. The disease has two main forms, Type 1 and Type 2. Type 1 Diabetes is less common (5-10% of all Diabetes worldwide) and results from the destruction of pancreatic β-cells and a lack of insulin production. Type 2 Diabetes is much more common (accounting for 90-95% of all cases) and results from varying degrees of insulin resistance and deficiency (i.e. the pancreas can produce insulin, but not enough, or other metabolic issues prevent appropriate utilization of the insulin).
Accurate classification of Diabetes type can, at times, be difficult, “as many patients present with atypical and overlapping characteristics of” Types 1 and 2 Diabetes. Traditional methods of classifying type include assessing age of diagnosis, body mass index (BMI), the presence or absence of autoantibodies, personal or family history of autoimmune disease, presence of diabetic ketoacidosis, and response to initial therapy of the disease. However, these methods are not always sufficient for clarifying Diabetes type.
Study Objective
To assess the clinical utility of Polygenic Scores (PRS) in differentiating Type 1 and Type 2 Diabetes among patients with atypical clinical presentation in a large population-based cohort.
Methods and Findings
Over 40,000 individuals with a Diabetes diagnosis from the UK Biobank (a large population-based cohort) were studied (N=41,787). Of those, 464 (1%) had a diagnosis of classic Type 1 Diabetes (T1D), and 15,923 (38%) had a diagnosis of classic Type 2 Diabetes (T2D). The remaining 25,400 (61%) had atypical Diabetes.
The study evaluated two published polygenic risk scores (PRS), one for T1D and one for T2D. The ability of the polygenic risk scores (PRS) to discriminate between T1D and T2D was assessed using a C-statistic (read more details on methods and statistical analysis in the article here).
Individuals with classic T1D had a significantly higher average T1D-PRS than those with classic T2D. And those with classic T2D had a significantly higher average T2D-PRS than those with classic T1D. Additionally, the performance for differentiating classic T1D and T2D was significantly higher using a combined T1D-PRS and T2D-PRS than using either PRS independently.
The researchers then used the combined T1D/T2D-PRS to predict the genetic probability of an individual having T1D versus T2D (see the Materials and Methods and Results sections of the article for details on how this was calculated. In doing this, they found that 23% of individuals previously identified as having atypical Diabetes were considered, from the PRS analysis, to have a high genetic predisposition to T1D. This was consistent with the finding that individuals with atypical Diabetes AND a high T1D-PRS had a higher rate of clinical diagnosis of T1D than patients with low T1D-PRS results. See the table below from the referenced study for additional information.
Discussion
The results of this study demonstrate that PRS may serve as “valuable tools to supplement existing clinical variables for more accurate diagnoses among atypical Diabetes patients to direct appropriate clinical management.” The authors draw attention to the fact that 63% of diabetic individuals in the UK Biobank had an atypical presentation, so the potential for PRS to help reclassify close to a quarter could be substantial.
To read the research in the August 2023 Journal of Clinical Endocrinology & Metabolism publication, please visit: https://academic.oup.com/jcem/article/109/1/107/7240445
Series Overview: Behind the Science
Welcome to Behind the Science, a blog series dedicated to providing a peek behind the curtain of the cutting-edge work happening both here at GenomicMD and also in the greater field of polygenic research. This series will supply our readers with valuable insights via curated research articles and press releases, as well as interviews with key players at our laboratory and beyond. Each post will provide an in-depth look at the roles, aspirations, and contributions that collectively drive the success of GenomicMD and polygenics research as a whole. In this series you'll find:
Join us as we explore the world of genetic testing and the inspiring individuals who are shaping the future of healthcare, one discovery at a time. Welcome to GenomicMD’s "Behind the Science" – where understanding meets innovation.
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