Sarah A. Pendergrass, PhD, MS

Dr. Sarah Pendergrass is Assistant (Investigator I) Professor in the Biomedical and Translational Informatics Program at Geisinger Health System.  Dr. Pendergrass is a genetic bioinformatician who focuses on high-throughput data analysis and data-mining approaches to studying complex human diseases and traits.  Dr. Pendergrass has extensive experience in using both epidemiologic and clinic-based resources to perform phenome-wide association studies (PheWAS) to identify cross-phenotype associations and pleiotropy.  Dr. Pendergrass also develops software tools to visualize complex data.  In recognition for her innovative work, Dr. Pendergrass was named one of Genome Technology’s PIs of Tomorrow (2013).

Recent Publications

  1. Hall, MA, Wallace, J, Lucas, AM, Bradford, Y, Verma, SS, Müller-Myhsok, B, Passero, K, Zhou, J, McGuigan, J, Jiang, B et al.. Novel EDGE encoding method enhances ability to identify genetic interactions. PLoS Genet 2021; 17 (6): e1009534. PubMed PMID:34086673 PubMed Central PMC8208534.
  2. Gorski, M, Jung, B, Li, Y, Matias-Garcia, PR, Wuttke, M, Coassin, S, Thio, CHL, Kleber, ME, Winkler, TW, Wanner, V et al.. Meta-analysis uncovers genome-wide significant variants for rapid kidney function decline. Kidney Int 2021; 99 (4): 926-939. PubMed PMID:33137338 PubMed Central PMC8010357.
  3. Palmer, MR, Kim, DS, Crosslin, DR, Stanaway, IB, Rosenthal, EA, Carrell, DS, Cronkite, DJ, Gordon, A, Du, X, Li, YK et al.. Loci identified by a genome-wide association study of carotid artery stenosis in the eMERGE network. Genet Epidemiol 2021; 45 (1): 4-15. PubMed PMID:32964493 PubMed Central PMC7891640.
  4. Veatch, OJ, Bauer, CR, Keenan, BT, Josyula, NS, Mazzotti, DR, Bagai, K, Malow, BA, Robishaw, JD, Pack, AI, Pendergrass, SA et al.. Characterization of genetic and phenotypic heterogeneity of obstructive sleep apnea using electronic health records. BMC Med Genomics 2020; 13 (1): 105. PubMed PMID:32711518 PubMed Central PMC7382070.
  5. Cava, W, Bauer, C, Moore, JH, Pendergrass, SA. Interpretation of machine learning predictions for patient outcomes in electronic health records. AMIA Annu Symp Proc 2019; 2019 : 572-581. PubMed PMID:32308851 PubMed Central PMC7153071.
  6. Zhang, Y, Ho, K, Keaton, JM, Hartzel, DN, Day, F, Justice, AE, Josyula, NS, Pendergrass, SA, Actkins, K, Davis, LK et al.. A genome-wide association study of polycystic ovary syndrome identified from electronic health records. Am J Obstet Gynecol 2020; 223 (4): 559.e1-559.e21. PubMed PMID:32289280 .
  7. 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.
  8. Tin, A, Marten, J, Halperin Kuhns, VL, Li, Y, Wuttke, M, Kirsten, H, Sieber, KB, Qiu, C, Gorski, M, Yu, Z et al.. Target genes, variants, tissues and transcriptional pathways influencing human serum urate levels. Nat Genet 2019; 51 (10): 1459-1474. PubMed PMID:31578528 PubMed Central PMC6858555.
  9. Teumer, A, Li, Y, Ghasemi, S, Prins, BP, Wuttke, M, Hermle, T, Giri, A, Sieber, KB, Qiu, C, Kirsten, H et al.. Genome-wide association meta-analyses and fine-mapping elucidate pathways influencing albuminuria. Nat Commun 2019; 10 (1): 4130. PubMed PMID:31511532 PubMed Central PMC6739370.
  10. Zhang, Y, Poler, SM, Li, J, Abedi, V, Pendergrass, SA, Williams, MS, Lee, MTM. Dissecting genetic factors affecting phenylephrine infusion rates during anesthesia: a genome-wide association study employing EHR data. BMC Med 2019; 17 (1): 168. PubMed PMID:31455332 PubMed Central PMC6712853.
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The Pendergrass Lab Website

Curriculum Vitae