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.
Recent Publications
- Zhu, Y, Ikuzwe Sindikubwabo, AB, Bradford, Y, Salowe, R, Caruth, L, Pham, K, Moksha, L, Vrathasha, V, Aibo, MI, Lee, R et al.. Multimodal Prediction of Primary Open-Angle Glaucoma Using Polygenic Risk Scores and Clinical Features in a High-Risk African Ancestry Cohort. medRxiv 2025; : . PubMed PMID:41256151 PubMed Central PMC12622094.
- Venkatesh, R, Cardone, KM, Bradford, Y, Moore, AK, Kumar, R, Moore, JH, Shen, L, Kim, D, Ritchie, MD. Integrative multi-omics approaches identify molecular pathways and improve Alzheimer's disease risk prediction. Alzheimers Dement 2025; 21 (11): e70886. PubMed PMID:41231230 PubMed Central PMC12614089.
- Sokolow, R, Bhattacharya, A, Kissas, G, Thompson, EW, Beeche, C, Swago, S, Zhang, D, Viswanadha, M, Morse, C, Chirinos, J et al.. Reduced order computational fluid dynamic simulations in the thoracic aorta are associated with disease recorded in a medical biobank. Sci Rep 2025; 15 (1): 39203. PubMed PMID:41213979 PubMed Central PMC12603325.
- Huffman, JE, Gaziano, L, Al Sayed, ZR, Judy, RL, Raffield, LM, Biddinger, KJ, Charest, B, Chopra, A, Gagnon, D, Guo, X et al.. An African ancestry-specific nonsense variant in CD36 is associated with a higher risk of dilated cardiomyopathy. Nat Genet 2025; 57 (11): 2682-2690. PubMed PMID:41174181 PubMed Central PMC12597818.
- Kumar, R, Romano, JD, Ritchie, MD. CASTER-DTA: equivariant graph neural networks for predicting drug-target affinity. Brief Bioinform 2025; 26 (5): . PubMed PMID:41139314 PubMed Central PMC12554097.
- Li, R, Benz, L, Duan, R, Denny, JC, Hakonarson, H, Mosley, JD, Smoller, JW, Wei, WQ, Lumley, T, Ritchie, MD et al.. A one-shot, lossless algorithm for cross-cohort learning in mixed-outcomes analysis. Patterns (N Y) 2025; 6 (9): 101321. PubMed PMID:41040961 PubMed Central PMC12485519.
- Rajagopalan, A, Nguyen, TA, Guare, LA, Garao Rico, AL, Venkatesh, R, Caruth, L, Regeneron Genetics Center, Penn Medicine BioBank, Verma, A, Ritchie, MD et al.. DRIVE-KG: Enhancing variant-phenotype association discovery in understudied complex diseases using heterogeneous knowledge graphs. medRxiv 2025; : . PubMed PMID:40894144 PubMed Central PMC12393615.
- Venkatesh, R, Cherlin, T, Penn Medicine BioBank, Ritchie, MD, Guerraty, MA, Verma, SS. Integrating Imaging-Derived Clinical Endotypes with Plasma Proteomics and External Polygenic Risk Scores Enhances Coronary Microvascular Disease Risk Prediction. medRxiv 2025; : . PubMed PMID:40894134 PubMed Central PMC12393626.
- Tavolinejad, H, Beeche, C, Dib, MJ, Pourmussa, B, Damrauer, SM, DePaolo, J, Azzo, JD, Salman, O, Duda, J, Gee, J et al.. Ascending Aortic Dimensions and Body Size: Allometric Scaling, Normative Values, and Prognostic Performance. JACC Cardiovasc Imaging 2025; : . PubMed PMID:40844449 .
- Kim, YG, Nam, Y, Westbrook, TM, Joo, J, Woerner, J, Deo, R, Ritchie, MD, Kim, D. Protein risk scores enable precise prediction of cardiovascular events in chronic kidney disease patients. medRxiv 2025; : . PubMed PMID:40778120 PubMed Central PMC12330408.
