As Bioinformatics Scientist for ADDI, Caitlin develops and incorporates bioinformatics tools into the AD Workbench (ADWB), manages data science technical workstreams, and works with the technical team to incorporate the needs of the scientific community.

An accomplished statistical geneticist, Caitlin’s area of expertise includes developing statistical models and applying them to large-scale human genetics data with phenotypes of interest ranging from BMI and ECG measurements to Huntington’s Disease and primary open angle glaucoma. Prior to joining the ADDI team, she worked as a research scientist at the University of Washington where she was a core member of the data coordinating center for TOPMed, a consortium generating whole genome sequence data for 150,000 participants across more than 80 studies. Caitlin also worked with the Cardiovascular Health Study (CHS), a cohort study started in 1989 by the University of Washington. Her projects included making computationally efficient the estimation of pairwise relatedness using more than 1 million genetic markers and 100,000+ participants, and coordinating all non-genetics omics data for 50+ projects.

Caitlin earned her PhD in Biostatistics from the University of Washington, a Master of Science in Applicable Mathematics from the London School of Economics, and a Bachelor of Science in Mathematics from Seattle University. When she’s not chasing after her 2-year-old daughter, she loves to knit.

AD Data Initiative Team

Caitlin McHugh

Erin Clark

Graham Bearden

Manny McBride

Matthew Clement

Niranjan Bose

Prabhu Ganeshan