Ayasdi’s collaborators delivered another significant win with Mt. Sinai’s Ichan School of Medicine getting published in the ultra-prestigious journal Science: Translational Medicine for their work using topological data analysis to identify previously unknown diabetes subtypes.
The paper contains breakthrough research and is a validation that precision medicine translates (no pun intended) beyond cancer. Dr. Joel Dudley, Director of Biomedical Informatics at the Icahn School of Medicine at Mount Sinai used Workbench to identify new patient subgroups, which will ultimately enable more precise diagnosis and therapies for this widespread, expensive and devastating disease.
The Icahn School of Medicine at Mount Sinai has a large database that pairs the genetic, clinical, and medical record data of over 30,000 patients. Mount Sinai’s data set is not only massive, but also complex since it contains many different data types. In addition to genomic sequencing data, it also includes information about each patient’s age, gender, height, weight, race, allergies, blood tests, diagnoses, and family history. Joel and his team used a precision medicine approach to characterize the complexity of Type 2 Diabetes patient populations based on high-dimensional electronic medical records (EMRs) and genotype data from 11,210 individuals (genetic markers and clinical data, such as blood levels and symptoms).
To learn the three distinct subgroups of T2D in patient-patient networks, click here.
