Lea Starita
Research
A barrier to fully realizing the promise of genome-guided precision medicine is the massive number of Variants of Certain Significance (VUS) that are identified by genetic testing. Variants are designated VUS when there is insufficient evidence to classify them as pathogenic or benign and, importantly, they can’t be used to guide clinical decisions. VUS are confusing to patients, maddening to doctors and exacerbate the inequities in genetic medicine because they are more likely to be identified in individuals from underserved populations.
The main goal of the Starita lab is to put an end to Variants of Uncertain Significance (VUS) to make genetic medicine more informative, equitable and impactful. Our lab has shown that multiplexed assays of variant effect (MAVE) can powerfully inform variant classification to move VUS to more definitive classifications. To continue toward this goal, my current research program has four main directions: 1) scaling existing MAVEs for broad application, 2) developing new MAVE technology to unlock access to new and more informative phenotypes, and 3) working with local and international partners to develop guidelines for clinical translation and 4) working with clinical partners to build resources to increase MAVE uptake in the clinic.
Dr. Starita is also the co-director of the Brotman Baty Advanced Technology lab (BAT-lab). The BAT-Lab allows researchers at UW and beyond to access cutting edge genomic technologies, find support for ambitious projects and we power the Seattle Flu Alliance.
Highlighted publications
Starita LM, Ahituv N, Dunham MJ, Kitzman JO, Roth FP, Seelig G, Shendure J, Fowler DM. Variant Interpretation: Functional Assays to the Rescue. Am J Hum Genet. 2017 Sep 7;101(3):315-325. doi: 10.1016/j.ajhg.2017.07.014. PMID: 28886340; PMCID: PMC5590843.
Findlay GM, Daza RM, Martin B, Zhang MD, Leith AP, Gasperini M, Janizek JD, Huang X, Starita LM,* Shendure J*. Accurate classification of BRCA1 variants with saturation genome editing. Nature. 2018 Oct;562(7726):217-222. doi: 10.1038/s41586-018-0461-z. Epub 2018 Sep 12. PMID: 30209399; PMCID: PMC6181777.
Fayer S, Horton C, Dines JN, Rubin AF, Richardson ME, McGoldrick K, Hernandez F, Pesaran T, Karam R, Shirts BH, Fowler DM,* Starita LM,* Closing the gap: Systematic integration of multiplexed functional data resolves variants of uncertain significance in BRCA1, TP53, and PTEN. Am J Hum Genet. 2021 Dec 2;108(12):2248-2258. doi: 10.1016/j.ajhg.2021.11.001. Epub 2021 Nov 17. PMID: 34793697; PMCID: PMC8715144.
Srivatsan S, Heidl S, Pfau B, Martin BK, Han PD, Zhong W, van Raay K, McDermot E, Opsahl J, Gamboa L, Smith N, Truong M, Cho S, Barrow KA, Rich LM, Stone J, Wolf CR, McCulloch DJ, Kim AE, Brandstetter E, Sohlberg SL, Ilcisin M, Geyer RE, Chen W, Gehring J; Seattle Flu Study Investigators, Kosuri S, Bedford T, Rieder MJ, Nickerson DA, Chu HY, Konnick EQ, Debley JS, Shendure J, Lockwood CM,* Starita LM,* SwabExpress: An End-to-End Protocol for Extraction-Free COVID-19 Testing. Clin Chem. 2021 Dec 30;68(1):143-1e52. doi: 10.1093/clinchem/hvab132. PMID: 34286830; PMCID: PMC8406859.
Florence M. Chardon, Chase C. Suiter, Riza M. Daza, Nahum T. Smith, Phoebe Parrish, Troy McDiarmid, Jean-Benoît Lalanne, Beth Martin, Diego Calderon, Amira Ellison, Alice H. Berger, Jay Shendure, Lea M. Starita A multiplex, prime editing framework for identifying drug resistance variants at scale. bioRxiv 2023.07.27.550902; doi: https://doi.org/10.1101/2023.07.27.550902
Please find the full list here: Google Scholar profile