DANA C. CRAWFORD, PHD
Associate Director for Population and Diversity Research
Dana Crawford, PhD, is Professor in the Department of Population and Quantitative Health Sciences and Associate Director for Population and Diversity Research in the Cleveland Institute for Computational Biology. She also has a secondary appointment in the Department of Genetics and Genome Sciences. Dr. Crawford received her Ph.D. at Emory University in genetics and molecular biology in 2000 and then trained as a post-doctoral fellow as an Epidemic Intelligence Service Officer at the Centers for Disease Control and Prevention (2000–2002) and as a senior fellow at the University of Washington’s Department of Genome Sciences (2002–2006). Prior to her most current position, Dr. Crawford spent eight years as tenure-track faculty in the Department of Molecular Physiology and Biophysics and Investigator in the Center for Human Genetics Research at Vanderbilt University. As a genetic epidemiologist at CWRU, Dr. Crawford’s broad research interests include applying genetic variation data to large-scale epidemiologic and clinical cohorts to better understand human genotype-phenotype associations with an emphasis on diverse populations.
- Cooke Bailey, JN, Bush, WS, Crawford, DC. Editorial: The Importance of Diversity in Precision Medicine Research. Front Genet 2020; 11 : 875. PubMed PMID:33005167 PubMed Central PMC7479241.
- Ong, E, Wang, LL, Schaub, J, O'Toole, JF, Steck, B, Rosenberg, AZ, Dowd, F, Hansen, J, Barisoni, L, Jain, S et al.. Modelling kidney disease using ontology: insights from the Kidney Precision Medicine Project. Nat Rev Nephrol 2020; 16 (11): 686-696. PubMed PMID:32939051 .
- Karunamuni, RA, Huynh-Le, MP, Fan, CC, Thompson, W, Eeles, RA, Kote-Jarai, Z, Muir, K, UKGPCS Collaborators, Lophatananon, A, Tangen, CM et al.. African-specific improvement of a polygenic hazard score for age at diagnosis of prostate cancer. Int J Cancer 2020; : . PubMed PMID:32930425 .
- McDonough, CW, Babcock, K, Chucri, K, Crawford, DC, Bian, J, Modave, F, Cooper-DeHoff, RM, Hogan, WR. Optimizing identification of resistant hypertension: Computable phenotype development and validation. Pharmacoepidemiol Drug Saf 2020; : . PubMed PMID:32844549 .
- Darst, BF, Wan, P, Sheng, X, Bensen, JT, Ingles, SA, Rybicki, BA, Nemesure, B, John, EM, Fowke, JH, Stevens, VL et al.. A Germline Variant at 8q24 Contributes to Familial Clustering of Prostate Cancer in Men of African Ancestry. Eur Urol 2020; 78 (3): 316-320. PubMed PMID:32409115 .
- Pendergrass, SA, Buyske, S, Jeff, JM, Frase, A, Dudek, S, Bradford, Y, Ambite, JL, Avery, CL, Buzkova, P, Deelman, E et al.. A phenome-wide association study (PheWAS) in the Population Architecture using Genomics and Epidemiology (PAGE) study reveals potential pleiotropy in African Americans. PLoS One 2019; 14 (12): e0226771. PubMed PMID:31891604 PubMed Central PMC6938343.
- Crawford, DC, Lin, J, Cooke Bailey, JN, Kinzy, T, Sedor, JR, O'Toole, JF, Bush, WS. Frequency of ClinVar Pathogenic Variants in Chronic Kidney Disease Patients Surveyed for Return of Research Results at a Cleveland Public Hospital. Pac Symp Biocomput 2020; 25 : 575-586. PubMed PMID:31797629 PubMed Central PMC6931908.
- Bush, WS, Cooke Bailey, JN, Beno, MF, Crawford, DC. Bridging the Gaps in Personalized Medicine Value Assessment: A Review of the Need for Outcome Metrics across Stakeholders and Scientific Disciplines. Public Health Genomics 2019; 22 (1-2): 16-24. PubMed PMID:31454805 PubMed Central PMC6752968.
- Halladay, CW, Hadi, T, Anger, MD, Greenberg, PB, Sullivan, JM, Konicki, PE, Peachey, NS, Igo, RP Jr, Iyengar, SK, Wu, WC et al.. Genetically-guided algorithm development and sample size optimization for age-related macular degeneration cases and controls in electronic health records from the VA Million Veteran Program. AMIA Jt Summits Transl Sci Proc 2019; 2019 : 153-162. PubMed PMID:31258967 PubMed Central PMC6568141.
- Crawford, DC, Cooke Bailey, JN, Briggs, FBS. Mind the gap: resources required to receive, process and interpret research-returned whole genome data. Hum Genet 2019; 138 (7): 691-701. PubMed PMID:31161416 PubMed Central PMC6767905.
Characterization of the Metabochip in diverse populations from the International HapMap Project in the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) project.
Crawford DC, Goodloe R, Brown-Gentry K, Wilson S, Roberson J, Gillani NB, Ritchie MD, Dilks HH, Bush WS,. Genome-wide association studies (GWAS) have identified hundreds of genomic regions associated with common human disease and quantitative traits. A major research avenue for mature genotype-phenotype associations is the identification of the true risk or functional variant for […]
Enabling high-throughput genotype-phenotype associations in the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) project as part of the Population Architecture using Genomics and Epidemiology (PAGE) study.
Bush WS, Boston J, Pendergrass SA, Dumitrescu L, Goodloe R, Brown-Gentry K, Wilson S, McClellan B, Torstenson E, Basford MA, Spencer KL, Ritchie MD, Crawford DC,. Genetic association studies have rapidly become a major tool for identifying the genetic basis of common human diseases. The advent of cost-effective genotyping coupled with large collections of samples […]
Dana on Twitter
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Thanks for the shoutout @wakibbe! For those interested in this topic, please consider contributing your work to a new call for papers co-organized by @genome_gov NHGRI's Dr. Lucia Hindorff: tinyurl.com/y69qwcz9 twitter.com/wakibbe/status…