Subgroups of Diabetes

Precision Medicine in Type 2 Diabetes

A novel approach for precision medicine for diabetes involves classifying newly diagnosed type 2 diabetes patients into data-driven subphenotypes based on their clinical characteristics (e.g., age at diagnosis, body mass index, HbA1c, HOMA2-IR, HOMA2-B). These subphenotypes vary in their genetic profile, presentation, responses to antihyperglycemic medication and risk of diabetes-related complications. However, reasons such as unavailability of HOMA2 indices in routinely collected clinical data, scarcity of data on subphenotypes derived from non-European populations, non-replicable cut-points for clinical variables and hard cluster assignment ignoring multifactorial nature of diabetes, preclude the widespread translation of this phenotyping approach from cohort studies to clinical practice.

This is ongoing work with Dr. KM Venkat Narayan, Dr. Joyce C. Ho and Zhongyu Li.

Challenges in defining subphenotypes for type 2 diabetes.


  1. Varghese 2023 Lancet Diabetes & Endocrinology Correspondence on Replicability of subphenotypes
  2. Varghese 2023 Primary Care Diabetes Brief Report on Ethnic Differences of subphenotypes
  3. Varghese 2021 Diabetes Technology & Therapeutics on CGM-derived profiles

Getting Involved

These projects are ideal for advanced masters or doctoral students who want hands-on experience with cohort studies and electronic health record data.

If you are interested in adult-onset type 2 diabetes:

  1. Classify subphenotypes of newly diagnosed adult type 2 diabetes from cohort studies using variables available in electronic health records
  2. Visualize distribution of subphenotypes in EHR systems by county, race-ethnicity, sex, and age groups
  3. Describe trends in prescribed medications, clinical parameters, and risk of complications among EHR-derived newly diagnosed type 2 diabetes subphenotypes.
  4. Develop a ‘2-year risk’ multi-class prediction model for phenotype membership using electronic health records from two clinical research networks and evaluate domain generalization

If you are interested in youth-onset type 2 diabetes:

  1. Develop a novel classification of newly diagnosed, youth-onset type 2 diabetes using clinical characteristics from cohort studies, and compare the classification with adult-onset subphenotypes
  2. Describe the longitudinal association of T2DM subphenotypes among youth-onset type 2 diabetes and Michigan Neuropathy Screening Instrument (MNSI) scores
  3. Describe the association of youth-onset T2DM subphenotypes and distal symmetric polyneuropathy phenotypes based on the Michigan Neuropathy Screening Instrument (MNSI)