With over 15 years of experience as a biostatistician, Huashi Li has worked with researchers and clinicians on a variety of projects including asthma, chronic obstructive pulmonary disease (COPD), COVID-19, and clinical trial data. She has performed genetic analyses of candidate genes, genome-wide array data, whole-genome sequencing data, and RNAseq and microarray gene expression data using genetic association, differential gene expression analysis, and eQTL approaches in the Severe Asthma Research Program (SARP). She has also analyzed subpopulations and intermediate outcome measures in the COPD study (SPIROMICS), the NHLBI Trans-Omics for Precision Medicine (TOPMed) study, the UK Biobank study, and the All of Us Research Program. She investigated subphenotypes of asthma using unsupervised cluster analysis in SARP, applied identified SARP clinical clusters in AstraZeneca clinical trial data, and identified the most biologic (anti-IL-5Rα monoclonal antibody) efficacious subgroups of patients. She investigated endotypes of asthma using traditional classification (age-onset of asthma and atopy) and biomarkers (IL-6, FeNO, blood eosinophils, and CC16), which further revealed more homogeneous asthma subtypes with underlying pathophysiological mechanisms.
- BS Biology, Minzu University of China, Beijing, China
- MS Statistics, Michigan State University, East Lansing, MI