Dr. Fatimah Jackson received her Ph.D., M.A., and B.A. (cum laude with Distinction in all Subjects) from Cornell University. She is currently Professor of Biology and Director of the W. Montague Cobb Research Laboratory at Howard University and Professor Emerita at the University of Maryland. Dr. Jackson has published extensively on population substructure in peoples of African descent, differential expressions of health disparities, and human-plant coevolution. She is the recipient of numerous national and international prizes and awards including the Norgan Award (Annals of Human Biology), the Ernest E. Just Prize in Medical and Public Health Research (Avery Research Institute and Medical College of South Carolina) and has been Coined by Rear Admiral Dr. Helena Mishoe, National Institutes of Health, NHLBI and US Public Health Service.


In heterogeneous, stratified populations, a major problem in the search for causes of chronic disease is not knowing in which subgroups to look for relevant genetic, cultural/behavioral, and environmental disease triggers. PSNA provides a systematic strategy to identify the most probable microethnic groups (MEGs) for understanding specific disease-associated traits. METHODS: PSNA relies on the identification and the computer assisted correlation analysis of multiple permutated disease-associated phenotypes to tease out the MEGS most likely to express the most salient phenotypic initiators of chronic disease. The top 5% of these correlations are identified as targets for further study and linked to their affiliated MEGs. RESULTS: This technique identifies the MEGs most likely to have specific disease-relevant cultural behaviors, candidate susceptibility and resistance genes, and candidate non-genetic biological factors and produces a MEG-specific algorithm of chronic disease risk. The application of PSNA reduces the time to detection of factors responsible for the initiation and course of a chronic disease and a ranking of these factors in the initiation of the chronic disease process. Examples from renopathology and cardiovascular disease are provided. CONCLUSION: PSNA is a superior alternative to the usual approaches in that it focuses on population substructure and includes an extensive evaluation of phenotypic traits associated with a specific chronic disease within the local microsettings of specific MEGS.

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