Andrew Kasarskis

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Andrew Kasarskis
Born (1972-11-02) November 2, 1972 (age 51)
Madison, Wisconsin
CitizenshipAmerican
Alma materUniversity of Kentucky
University of California, Berkeley
Scientific career
FieldsBioinformatics, genomics
InstitutionsSema4

Andrew Kasarskis (born November 2, 1972) is an American biologist. He is the Chief Data Officer (CDO) at Sema4.[1] He was previously CDO and an Executive Vice President (EVP) at the Mount Sinai Health System in New York City and, before that, vice chair of the Department of Genetics and Genomic Sciences and Co-director of the Icahn Institute for Genomics and Multiscale Biology at the Icahn School of Medicine at Mount Sinai.[2] Kasarskis is known for taking a network-based approach to biology and for directing the first medical school class offering students the opportunity to fully sequence and analyze their own genomes.[3]

Early life and education[edit]

Kasarskis completed bachelor's degrees in chemistry and biology at the University of Kentucky in 1992. In 1998, he completed his PhD in molecular and cell biology at the University of California, Berkeley, under the supervision of Kathryn Anderson.[2]

Career and research[edit]

Throughout his career in industry and academia, Kasarskis' research has focused on the use of genetic and genomic data together with high-performance computing and advanced analytical tools to address biomedical needs and improve clinical treatment.

After completing his PhD in 1998, Kasarskis worked at Stanford University for two years, contributing to the development of various genome databases. In 2000, he entered industry, working in computational biology at DoubleTwist and later Rosetta Inpharmatics (acquired by Merck Research Laboratories). His work there centered on generating and mining complex biological data sets and using that information to build, predict, and model human disease. Kasarskis also worked for Sage Bionetworks and Pacific Biosciences before returning to academia.[4]

In 2011, Kasarskis became Vice Chair of the Department of Genetics and Genomic Sciences at the Icahn School of Medicine at Mount Sinai and Co-director, along with Eric Schadt, of the Icahn Institute for Genomics and Multiscale Biology, where Kasarskis's research focuses on improving health outcomes through better data mining, and his research program includes sequencing-based pathogen surveillance; pharmacogenomics; electronic health records; and systems biology of sleep, behavior, and stress.[2] In 2019, Kasarskis was appointed Chief Data Officer and Executive Vice President of Mount Sinai Health System,[5] where he leads efforts to improve clinical data infrastructure[6] and leverage data to improve patient outcomes while accelerating research and innovation.[7][8]

Kasarskis is known for directing the first graduate course that allowed medical and PhD students to fully sequence and analyze their own genomes, along with co-instructors Michael Linderman, George Diaz, Ali Bashir, and Randi Zinberg. He has said that courses like this will be critical for training teams of people capable of performing this type of analysis in a medical setting. He chose whole genome sequencing because he expects the more limited exome sequencing will not be a relevant technological approach in the long term.[3]

Kasarskis has called for improvements to informed consent protocols in patient research based on the concept that studies involving DNA cannot fully be made anonymous. He was quoted in the journal Nature saying, "We need to move beyond an assumption that you cannot be identified from the data that exist about you and really work to make sure that we're protecting people's rights in ways that allow us to use the data that are out there for individuals' and researchers' benefit."[9]

In 2019, Kasarskis joined a five-year collaborative study with Mount Sinai Health System, Sanofi, and Sema4, aimed to provide insights into the biological mechanisms of asthma using diverse data sets such as clinical data, genomics, immunological environmental, and sensor data from devices to carryout advanced network modeling of the disease. Kasarskis reported that understanding the molecular basis of clinical subtypes of asthma in the study would enable better management of asthma and could provide opportunities to discover new treatments for the disease. [10]

In 2020, the molecular pathogen surveillance program Kasarskis had established with Dr. Harm van Bakel and others at the Mount Sinai Health System clearly demonstrated that SARS-CoV2, the virus causing COVID-19, was introduced to the New York Metropolitan Area not from Asia but predominately from Europe, with some contribution from other United States regions.[11] The ensuing research paper was published in the journal Science.[12]

Selected publications[edit]

Pharmacogenomics[edit]

  • Smith, Catherine C.; Wang, Qi; Chin, Chen-Shan; Salerno, Sara; Damon, Lauren E.; Levis, Mark J.; Perl, Alexander E.; Travers, Kevin J.; Wang, Susana; Hunt, Jeremy P.; Zarrinkar, Patrick P.; Schadt, Eric E.; Kasarskis, Andrew; Kuriyan, John; Shah, Neil P. (2012). "Validation of ITD mutations in FLT3 as a therapeutic target in human acute myeloid leukaemia". Nature. 485 (7397): 260–263. Bibcode:2012Natur.485..260S. doi:10.1038/nature11016. PMC 3390926. PMID 22504184.
  • Kasarskis, Andrew; Yang, Xia; Schadt, Eric (2011). "Integrative genomics strategies to elucidate the complexity of drug response". Pharmacogenomics. 12 (12): 1695–1715. doi:10.2217/pgs.11.115. PMID 22118053.
  • Gargis, Amy S.; Kalman, Lisa; Berry, Meredith W.; Bick, David P.; Dimmock, David P.; Hambuch, Tina; Lu, Fei; Lyon, Elaine; Voelkerding, Karl V.; Zehnbauer, Barbara A.; Agarwala, Richa; Bennett, Sarah F.; Chen, Bin; Chin, Ephrem L H.; Compton, John G.; Das, Soma; Farkas, Daniel H.; Ferber, Matthew J.; Funke, Birgit H.; Furtado, Manohar R.; Ganova-Raeva, Lilia M.; Geigenmüller, Ute; Gunselman, Sandra J.; Hegde, Madhuri R.; Johnson, Philip L F.; Kasarskis, Andrew; Kulkarni, Shashikant; Lenk, Thomas; Liu, C S Jonathan; et al. (2012). "Assuring the quality of next-generation sequencing in clinical laboratory practice". Nature Biotechnology. 30 (11): 1033–1036. doi:10.1038/nbt.2403. PMC 3827024. PMID 23138292.

Pathogens[edit]

Complex disease[edit]

References[edit]

  1. ^ "4 hospital execs who recently left their roles for digital health companies". Retrieved June 25, 2021.
  2. ^ a b c "Andrew Kasarskis - Icahn School of Medicine at Mount Sinai". Icahn.mssm.edu. Retrieved June 10, 2013.
  3. ^ a b Nicholas Tatonetti (October 24, 2012). "Q&A: Mount Sinai's Andrew Kasarskis on Teaching Students how to Analyze their Own Genomes | Clinical Sequencing News | Sequencing". GenomeWeb. Retrieved June 10, 2013.
  4. ^ "BIOMEDIN 206: Informatics in Industry - Stanford University". Stanford.edu. Retrieved June 10, 2013.
  5. ^ "Mount Sinai Accelerates Data-driven Discovery and Patient Care with New Chief Data Officer Role | Mount Sinai - New York". Mount Sinai Health System. Retrieved September 9, 2019.
  6. ^ "Q&A: Mount Sinai Chief Data Officer Andrew Kasarskis on New Role". GenomeWeb. June 26, 2019. Retrieved September 9, 2019.
  7. ^ "Mount Sinai Accelerates Data-driven Discovery and Patient Care with New Chief Data Officer Role | Mount Sinai - New York". Mount Sinai Health System. Retrieved September 9, 2019.
  8. ^ "Mount Sinai Health System selects first chief data officer: 6 things to know". www.beckershospitalreview.com. Retrieved September 9, 2019.
  9. ^ Check Hayden, Erika (April 25, 2012). "Open-data project aims to ease the way for genomic research". Nature News. Nature.com. doi:10.1038/nature.2012.10507. S2CID 211728919. Retrieved June 10, 2013.
  10. ^ "Sanofi, Sema4, Mount Sinai Collaborate on Largest Asthma Study of Its Kind | Mount Sinai - New York". Mount Sinai Health System. Retrieved September 9, 2019.
  11. ^ Zimmer, Carl (April 9, 2020). "Most New York Coronavirus Cases Came From Europe, Genomes Show". New York Times. Retrieved June 25, 2021.
  12. ^ Gonzalez-Reiche, Ana S.; et al. (2020). "Introductions and early spread of SARS-CoV-2 in the New York City area". Science. 369 (6501): 297–301. Bibcode:2020Sci...369..297G. doi:10.1126/science.abc1917. PMC 7259823. PMID 32471856.
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