Dr. Marylyn Ritchie is Professor in the Department of Biochemistry and Molecular Biology and Director, Center for Systems Genomics at the Pennsylvania State University. Dr. Ritchie is also Director of the new Biomedical and Translational Informatics at Geisinger Clinic. Dr. Ritchie’s research interests as a statistical geneticist include the development and application of novel statistical and computational methods to identify genetic variants associated with human diseases. Dr. Ritchie’s lab places a special emphasis on the development of methods to detect gene-gene interactions, gene-environment interactions, and network/pathway effects associated with disease. Dr. Ritchie has extensive experience in Big Data science and the use of electronic health records in genomic research. Dr. Ritchie has been the electronic MEdical Records & GEnomics (eMERGE) Coordinating Center genomics lead for the past eight years. Dr. Ritchie’s other accomplishments include being named Genome Technology’s “Rising Young Investigator” (2006), a Sloan Research Fellow (2010), and a Kavli Frontiers in Sciences fellow by the National Academy of Science (2011-2014). Dr. Ritchie was most recently named Thomas Reuters Most Highly Cited Researchers in 2014.
- Bergmeijer, TO, Yasmina, A, Vos, GJA, Janssen, PWA, Hackeng, CM, Kelder, JC, Verma, SS, Ritchie, MD, Gong, L, Klein, TE et al.. Effect of CYP3A4*22 and PPAR-α Genetic Variants on Platelet Reactivity in Patients Treated with Clopidogrel and Lipid-Lowering Drugs Undergoing Elective Percutaneous Coronary Intervention. Genes (Basel) 2020; 11 (9): . PubMed PMID:32932966 .
- Kember, RL, Merikangas, AK, Verma, SS, Verma, A, Judy, R, Regeneron Genetics Center, Damrauer, SM, Ritchie, MD, Rader, DJ, Bućan, M et al.. Polygenic Risk of Psychiatric Disorders Exhibits Cross-trait Associations in Electronic Health Record Data From European Ancestry Individuals. Biol. Psychiatry 2020; : . PubMed PMID:32919613 .
- Leonard, MA, Cindi, Z, Bradford, Y, Bourgi, K, Koethe, J, Turner, M, Norwood, J, Woodward, B, Erdem, H, Basham, R et al.. Efavirenz Pharmacogenetics and Weight Gain following Switch to Integrase Inhibitor-containing Regimens. Clin. Infect. Dis. 2020; : . PubMed PMID:32829410 .
- Verma, SS, Bergmeijer, TO, Gong, L, Reny, JL, Lewis, JP, Mitchell, BD, Alexopoulos, D, Aradi, D, Altman, RB, Bliden, K et al.. Genomewide Association Study of Platelet Reactivity and Cardiovascular Response in Patients Treated With Clopidogrel: A Study by the International Clopidogrel Pharmacogenomics Consortium. Clin. Pharmacol. Ther. 2020; : . PubMed PMID:32472697 .
- Moore, JH, Barnett, I, Boland, MR, Chen, Y, Demiris, G, Gonzalez-Hernandez, G, Herman, DS, Himes, BE, Hubbard, RA, Kim, D et al.. Ideas for how informaticians can get involved with COVID-19 research. BioData Min 2020; 13 : 3. PubMed PMID:32419848 PubMed Central PMC7216865.
- Murray, MF, Kenny, EE, Ritchie, MD, Rader, DJ, Bale, AE, Giovanni, MA, Abul-Husn, NS. COVID-19 outcomes and the human genome. Genet. Med. 2020; 22 (7): 1175-1177. PubMed PMID:32393819 .
- Li, R, Chen, Y, Ritchie, MD, Moore, JH. Electronic health records and polygenic risk scores for predicting disease risk. Nat. Rev. Genet. 2020; 21 (8): 493-502. PubMed PMID:32235907 .
- Lucas, AM, Palmiero, NE, McGuigan, J, Passero, K, Zhou, J, Orie, D, Ritchie, MD, Hall, MA. CLARITE Facilitates the Quality Control and Analysis Process for EWAS of Metabolic-Related Traits. Front Genet 2019; 10 : 1240. PubMed PMID:31921293 PubMed Central PMC6930237.
- Joo, YY, Actkins, K, Pacheco, JA, Basile, AO, Carroll, R, Crosslin, DR, Day, F, Denny, JC, Velez Edwards, DR, Hakonarson, H et al.. A Polygenic and Phenotypic Risk Prediction for Polycystic Ovary Syndrome Evaluated by Phenome-Wide Association Studies. J. Clin. Endocrinol. Metab. 2020; 105 (6): . PubMed PMID:31917831 PubMed Central PMC7453038.
- 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.