Niha Zubair, Phd Email & Phone Number

Harmonizing and merging data across various sources (genetic, blood, lifestyle, demographics). Conducting statistical analysis to validate this dataset. This dataset is now being used in analyses to develop products/insights for patients.Using research and data from genome-wide association analysis to create novel polygenic scores to inform patients of diet, lifestyle, and supplement changes that may benefit their health.Developing a health questionnaire (that can interact with genetic and lab data). Also creating internal logic for health recommendations for patients.Cross-departmental collaborations with software engineers, computer scientists, clinicians, UX designers, and marketing.

Acquired by Atrium Innovations.Performed statistical and machine-learning analysis of multi-omic health data with the goal of optimizing clinical and dietary supplement recommendations.Worked specifically with blood biomarker, genetic, and lifestyle data for product development and research.

Greater Seattle Area

First authored a seminal peer-reviewed research paper: “Genetic Predisposition Impacts Clinical Changes in a Lifestyle Coaching Program” Zubair, N., Conomos, M.P., Hood, L. et al. Scientific Reports. (2019). Translated data-driven results, from statistical and machine-learning analyses, to clinicalimplementation.Developed evidence-based clinical recommendation system to evaluate interventions suitable for clients.Produced and wrote clinical content for clients’ dashboards and blog.

Applied statistical methods to research how genetic, biomarker, and lifestyle factors influence colorectal cancer and cardiovascular disease risk.Led the data harmonization team for the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO); helped build and maintain a large standardized and comprehensive database of epidemiologic, tumor, survival, and biomarker variables in over 50,000 individuals.Designed algorithms to transform data in a consistent manner.

Greater Seattle Area

Research focused on the interplay between genetic, biomarker, and lifestyle factors on colorectal cancer and cardiovascular disease; analyzed and interpreted high-dimensional genetic data.Led and designed the most ethnically diverse genetic association study on lipid biomarkers in over 50,000 individuals from 9 cohorts; received an award from the American Heart Association for this research.Curated genetic variants from OMIM, ClinVar, and multi-ethnic fine-mapping studies to help design the Illumina Multi-Ethnic Genotyping Array (MEGA).Predicted cancer survival of individuals with rare and common genetic risk variants.Tools/Skills: regression analysis, Cox proportional hazard based models, Bayesian methods for meta- analysis, parallel computing, and genetic analysis; used R, Stata, and Metasoft.

Analyzed the impact of diet, lifestyle, and genetic factors on cardiovascular and inflammatory biomarkers using advanced statistical techniques.Tools/Skills: regression analysis, cluster analysis, principal components, factor analysis, genetic analysis, and instrumental variable; used Stata, SAS, Mplus, and PLINK.

Studied reproductive rates using nonlinear discrete population models.Tools/Skills: topology, nonlinear discrete population models, and regression analysis; used Matlab, Java, and GIS.

Doctor Of Philosophy (Ph.D.), Nutritional Epidemiology

Dissertation Thesis: Novel Approach to Examine the Interactive Role of Dietary, Lifestyle, and Genetic Factors on Cardiometabolic Risk.

Bachelor’S Degree, Mathematics

Activities and Societies: Phi Beta KappaHonors Thesis: Reproduction Rate Strategies in White-Footed Mice Took classes in mathematics.