Precision Diabetes Is Slowly Becoming a Reality

Abstract

The concept of precision medicine is becoming increasingly popular. The use of big data, genomics and other “omics” like metabolomics, proteomics and transcriptomics could make the dream of personalised medicine become a reality in the near future. As far as polygenic forms of diabetes like type 2 and type 1 diabetes are concerned, interesting leads are emerging, but precision diabetes is still in its infancy. However, with regard to monogenic forms of diabetes like maturity-onset diabetes of the young and neonatal diabetes mellitus, rapid strides have been made and precision diabetes has already become part of the clinical tools used at advanced diabetes centres. In patients with some monogenic form of diabetes, if the appropriate gene defects are identified, insulin injections can be stopped and be replaced by oral sulphonylurea drugs. In the coming years, rapid advances can be expected in the field of precision diabetes, thereby making the control of diabetes more effective and hopefully leading to prevention of its complications and improvement of the quality of life of people afflicted with diabetes.

Challenges in the diagnosis of diabetes type in pediatrics

“…MODY caused by mutations in HNF1B is not responsive to sulfonylureas, and requires treatment with insulin 34 . Some types of neonatal diabetes may remit and relapse, with intermittent need for low‐dose sulfonylurea therapy; other neonatal diabetes requires long‐term high‐dose sulfonylureas or insulin therapy 36,37 . The variety of treatment approaches in monogenic diabetes highlights the tremendous advantage offered by personalized medicine, as appropriate choice of therapy becomes easier through better classification through molecular diagnosis of diabetes.…”

Prediction of the development of islet autoantibodies through integration of environmental, genetic, and metabolic markers

“…The conclusion of this work was that continued developments of such models are necessary to better understand the complexity of the disease and address long-term goals of precision diabetes. 44,45 Biomarkers hold vast potential for clinical utility both in terms of diagnosis and prognosis of disease but also in drug discovery. 46,47 An alternate strategy to regression modeling is to take a data-driven approach to allow a large collections of potential risk factors and molecular markers to be integrated into the predictive modeling.…”

“…The logistic regression model to make this prediction utilized five predictors that were selected based on known associations, such as IA‐2 antibody positivity status and hemoglobin A1c (HbA1c) level, achieving a sensitivity of 0.91 at a specificity of 0.59, yielding a ROC curve with an AUC of 0.80. The conclusion of this work was that continued developments of such models are necessary to better understand the complexity of the disease and address long‐term goals of precision diabetes 44,45 . Biomarkers hold vast potential for clinical utility both in terms of diagnosis and prognosis of disease but also in drug discovery 46,47 …”

Advances in Research on Diabetes by Human Nutriomics

“…The concept of precision medicine is becoming increasingly popular. Using large amounts of data, genomics, and other “omics”, such as metabolomics, proteomics, and transcriptomics, can make personalized medicine a reality in the near future [89]. In addition, the Metabolomics Association believes that integrating metabolomic data into precision medicine programs is timely and will provide extremely valuable new data to complement the current data [90].…”