Bio

Seth is a Postdoctoral Fellow in the Translational Genomics of Diabetes lab located at Stanford Research Park under the supervision of Professor Anna Gloyn. Seth completed a B.E. in Applied Mathematics before studying a PhD at the University of Exeter with Dr Richard Oram where he researched the use of genetics to predict common autoimmune disorders. Seth studied at the Alan Turing Institute in London where he used machine learning and artificial intelligence methods to predict autoimmunity and has worked collaboratively to improve screening of Type 1 diabetes from birth. Seth's postdoctoral studies focus on using genetic, transcriptomic and epigenetic data to understand the mechanisms by which both Type 1 and Type 2 diabetes occur in the human pancreas. He is also interested in ways to quantify genetic risk such as polygenic risk scores and their application in both research and clinic.

Honors & Awards

  • Larry L. Hillblom Postdoctoral Fellowship, Larry L. Hillblom Foundation (2024)
  • Skills Enrichment Secondment, The Alan Turing Institute (2019)
  • Diabetes UK PhD Studentship, Diabetes UK (2018)

Professional Education

  • Doctor of Philosophy, University of Exeter, Human Genetics (2021)
  • Bachelor of Engineering (Honors), University of Bristol, Applied Mathematics (2016)

Stanford Advisors

Contact

  • Academic
    ssharp@stanford.edu
    University - Scholar Department: Pediatrics Position: Postdoctoral Scholar

Additional Info

All Publications

  • Type 1 Diabetes Genetic Risk in 109,954 Veterans With Adult-Onset Diabetes: The Million Veteran Program (MVP). Diabetes care Yang, P. K., Jackson, S. L., Charest, B. R., Cheng, Y. J., Sun, Y. V., Raghavan, S., Litkowski, E. M., Legvold, B. T., Rhee, M. K., Oram, R. A., Kuklina, E. V., Vujkovic, M., Reaven, P. D., Cho, K., Leong, A., Wilson, P. W., Zhou, J., Miller, D. R., Sharp, S. A., Staimez, L. R., North, K. E., Highland, H. M., Phillips, L. S. 2024

    Abstract

    To characterize high type 1 diabetes (T1D) genetic risk in a population where type 2 diabetes (T2D) predominates.Characteristics typically associated with T1D were assessed in 109,594 Million Veteran Program participants with adult-onset diabetes, 2011-2021, who had T1D genetic risk scores (GRS) defined as low (0 to <45%), medium (45 to <90%), high (90 to <95%), or highest (≥95%).T1D characteristics increased progressively with higher genetic risk (P < 0.001 for trend). A GRS ≥ 90% was more common with diabetes diagnoses before age 40 years, but 95% of those participants were diagnosed at age ≥40 years, and they resembled T2D in mean age (64.3 years) and BMI (32.3 kg/m2). Compared with the low risk group, the highest-risk group was more likely to have diabetic ketoacidosis (low 0.9% vs. highest GRS 3.7%), hypoglycemia prompting emergency visits (3.7% vs. 5.8%), outpatient plasma glucose <50 mg/dL (7.5% vs. 13.4%), a shorter median time to start insulin (3.5 vs. 1.4 years), use of a T1D diagnostic code (16.3% vs. 28.1%), low C-peptide levels if tested (1.8% vs. 32.4%), and glutamic acid decarboxylase antibodies (6.9% vs. 45.2%), all P < 0.001.Characteristics associated with T1D were increased with higher genetic risk, and especially with the top 10% of risk. However, the age and BMI of those participants resemble people with T2D, and a substantial proportion did not have diagnostic testing or use of T1D diagnostic codes. T1D genetic screening could be used to aid identification of adult-onset T1D in settings in which T2D predominates.

    View details for DOI 10.2337/dc23-1927

    View details for PubMedID 38608262

https://orcid.org/0000-0002-0607-9990