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. Graham, SE, Clarke, SL, Wu, KH, Kanoni, S, Zajac, GJM, Ramdas, S, Surakka, I, Ntalla, I, Vedantam, S, Winkler, TW et al.. Author Correction: The power of genetic diversity in genome-wide association studies of lipids. Nature 2023; 618 (7965): E19-E20. PubMed PMID:37237109 PubMed Central PMC10355188.
  2. Gorski, M, Rasheed, H, Teumer, A, Thomas, LF, Graham, SE, Sveinbjornsson, G, Winkler, TW, Günther, F, Stark, KJ, Chai, JF et al.. Genetic loci and prioritization of genes for kidney function decline derived from a meta-analysis of 62 longitudinal genome-wide association studies. Kidney Int 2022; 102 (3): 624-639. PubMed PMID:35716955 PubMed Central PMC10034922.
  3. Winkler, TW, Rasheed, H, Teumer, A, Gorski, M, Rowan, BX, Stanzick, KJ, Thomas, LF, Tin, A, Hoppmann, A, Chu, AY et al.. Differential and shared genetic effects on kidney function between diabetic and non-diabetic individuals. Commun Biol 2022; 5 (1): 580. PubMed PMID:35697829 PubMed Central PMC9192715.
  4. Piekos, JA, Hellwege, JN, Zhang, Y, Torstenson, ES, Jarvik, GP, Dikilitas, O, Kullo, IJ, Schaid, DJ, Crosslin, DR, Pendergrass, SA et al.. Uterine fibroid polygenic risk score (PRS) associates and predicts risk for uterine fibroid. Hum Genet 2022; 141 (11): 1739-1748. PubMed PMID:35226188 PubMed Central PMC9420161.
  5. Graham, SE, Clarke, SL, Wu, KH, Kanoni, S, Zajac, GJM, Ramdas, S, Surakka, I, Ntalla, I, Vedantam, S, Winkler, TW et al.. The power of genetic diversity in genome-wide association studies of lipids. Nature 2021; 600 (7890): 675-679. PubMed PMID:34887591 PubMed Central PMC8730582.
  6. 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.
  7. 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.
  8. 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.
  9. 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.
  10. 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.
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The Pendergrass Lab Website

Curriculum Vitae