Biostatistics, Epidemiology, and Research Design Trailblazer Awardee: Kate Young
By Frontiers , Clinical and Translational Science Institute
Sep 04, 2025
Project Title: Advancements in Translational Science through Personalized Biomarker Evaluations and Cutoffs to Improve Quality and Equity in Diagnoses
Current diagnostic procedures for many diseases rely on invasive or expensive testing. For example, Alzheimer’s disease is diagnosed by examining biomarkers found in cerebral spinal fluid (CSF), which is collected through lumbar punctures, or through brain imaging, which requires expensive specialized equipment and highly trained radiologists. Physicians use these biomarkers along with clinical symptoms and medical history to determine a diagnosis. Kate Young, Ph.D., is working on a project to improve the accuracy of blood-based biomarkers, with the goal of developing less invasive, less expensive methods of detecting disease. Such a feat would ease the diagnostic process for Alzheimer’s disease. However, while blood tests are much easier to collect than CSF or neuroimaging, blood-based biomarkers for Alzheimer’s disease are currently less accurate than CSF and neuroimaging.
Recently, Young was awarded a Biostatistics, Epidemiology, and Research Design (BERD) Trailblazer award from Frontiers. This funding award supports statistical, epidemiological, and data science investigations toward novel methods development that will improve clinical and translational research inferences. In her BERD award, Young is continuing a line of research she started as a doctoral student at KU Medical Center. She wants to expand upon and improve the accuracy of current biomarker-based diagnostic testing across disorders, not solely limited to Alzheimer’s disease. To do this, Young is developing a R-based software package to define and evaluate methods to measure accuracy of biomarkers based on clinical characteristics (R is a free software suite for statistical computing and graphics that is widely used by researchers). If successful, this should allow for personalized diagnostic testing that could improve diagnostic accuracy and sensitivity across populations and within disease subgroups. For aging individuals, Young hopes that her work will be able to differentiate between varying degrees of impairment in healthy aging adults, adults with mild cognitive impairment, and adults with fully progressed Alzheimer’s disease.
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