Cutting-edge research: machine learning identifies early predictors of type 1 diabetes CellCellPress machinelearning AI ML typeonediabetes type1diabetes T1D diabetes
By Susha Cheriyedath, M.Sc.Jul 3 2023Reviewed by Lily Ramsey, LLM In a study recently published in the Cell Reports Medicine Journal, scientists utilized plasma protein proteomics to identify proteins associated with the onset of type 1 diabetes.
What is type 1 diabetes? Type 1 diabetes is an autoimmune disorder estimated to affect 20 million people worldwide and is responsible for reducing life expectancy in patients by 11 years. It is characterized by the body's rejection and destruction of β cells due to the development of autoantibodies against the individual's pancreatic islet proteins, a process termed "seroconversion." A cure for this condition does not yet exist.
Analysis of these proteins may increase researchers' predictive powers and provide healthcare practitioners with viable means to treat T1D in the future. Unfortunately, many previous studies have been unable to systematically validate their study participants, thereby confounding the interpretation of results.
Thirty-six thousand two hundred fifty-two peptides from 1,720 proteins were thus identified, of which the 376 proteins that had the highest coefficient of variance and were repeated most often were used for statistical analyses. These proteins were overexpressed in coagulation and complement cascade-related processes, known to cooccur with T1D-related nutrient digestion and absorption, inflammatory signaling, blood clotting, and cellular metabolism.
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