Assistant Professor

Shraddha Pai

PhD, Cold Spring Harbor Laboratory

Ontario Institute for Cancer Research
MaRS Centre, 661 University Avenue, Suite 510, Toronto, Ontario Canada M5G 0A3
Research Interests
Cancer Mechanisms and Models, Data Science and Computational Biology, Neuroscience

At a Glance

  • Genomics of brain disorders and brain cancers
  • Epigenomic origin of disease & treatment resistance; epigenetic therapies
  • Algorithm development for drug discovery and precision oncology
  • Keywords: Epigenomics; Neurodevelopmental disorders; Precision oncology; Gene regulation; Genomics; Epigenomics; Systems biology; Networks

Short Bio

Dr. Pai has an interdisciplinary background in neuroscience, disease genomics, computational biology, and systems biology. She received her B.Math. in Hon. Computer Science (Bioinformatics) from the University of Waterloo and her PhD in Biological Sciences from Cold Spring Harbor Laboratory (NY, USA), using experimental and analytic approaches to identify the brain-basis of short-term memory in rodents. Dr. Pai’s first postdoctoral fellowship was in epigenetics of human brain and mental illness at the Centre for Addiction and Mental Health in Toronto. Her second postdoctoral fellowship was at the Donnelly Centre for Cellular and Biomolecular Research in Toronto, developing machine learning methods for precision medicine. Dr. Pai is a recipient of the 2014 NARSAD Young Investigator Award, 2014 CIHR Fellowship Award, and the 2019 Donnelly Centre Research Excellence Award for Postdoctoral Fellows and Research Associates.

Research Synopsis

Genomics and epigenomics of neurodevelopmental disorders

Every embryo starts out as a single-celled organism. As it develops, DNA in each cell is tagged or untagged by covalent modifications, in patterns that stably change its transcriptional state. This process of epigenetic modification generates hundreds of diverse cell types – or multiple phenotypes – in cells with the identical genotype. Moreover, this process of alteration continues throughout the individual’s life, in response to environmental factors, developmental programs, aging, or stochastically. Epigenetic misregulation of the genome can explain various features of disease, such as monozygotic twin discordance and sexual dimorphism.

The Pai lab is interested in how epigenetic changes in developing or adult tissues can drive disease onset or cause treatment resistance. We focus on diseases putatively rooted in brain development and combine experimental and computational techniques, including histology, laser capture microdissection, flow cytometry, molecular biology, single-cell genomics and bioinformatics. Our studies focus on post mortem human fetal and adult brain, mouse fetal and  adult brain, and on tumours.

Current projects include uncovering the fetal epigenomic origins of medulloblastoma, a highly malignant childhood brain cancer in sore need of molecular therapies. We also perform computational analyses of single-cell transcriptomes from the human and mouse brains to dissect gene regulatory networks unique to the developing brain. 

Dr. Pai co-led the first epigenome-wide association study in neurons isolated from post-mortem prefrontal cortex of individuals with schizophrenia and bipolar disorder. This study led to the identification of a novel biomarker that unifies two distinctive features of psychosis: dopaminergic increase and reduced synaptic structure. The study of genomics of pediatric brain malignancies is a new and fast-evolving research area in the lab.

“Biologically-aware” Algorithms for precision medicine

Another major area of interest is in developing algorithms for drug discovery and patient stratification. Our methods combine patient genomes with prior knowledge of pathways, molecular interaction networks, tissue-specific expression, single-cell genomics, pharmacogenomics, genetic mutations in disease, and functional screens, to improve drug specificity. We previously co-developed netDx, a general-purpose patient classifier algorithm that integrates heterogenous patient data into a single model to predict clinical outcome. It adapts a recommender system model similar to that used by Netflix (“find movies like this one”) to precision medicine (“find patients like non-responders”), and uses prior knowledge of cellular pathways to organize genomic data as well as machine learning. Current projects include a collaboration with OICR’s Drug Discovery team to build a target prioritization algorithm for cancer therapeutics.

For more information please see the Pai Lab website.

Recent Publications

  • Pai S, Li P, Killinger B, Marshall L, Jia P, Liao J, Petronis A, Szabó PE, Labrie V (2019). Differential methylation of enhancer at IGF2 is associated with abnormal dopamine synthesis in major psychosis. Nature Comms. 10:2046.
  • Pai S, Hui S, Isserlin R, Shah MA, Kaka H, Bader GD. (2019). netDx: interpretable patient classification using integrated patient similarity networks. Mol Sys Biol 15:e8497
  • Pai S and Bader GD. (2018). Patient Similarity Networks for Precision Medicine. Invited review. J Mol Biol. 430 (18 Pt A); 2924.
  • Khare T, Pai S, Koncevicius K, Pal M, Kriukiene E, Liutkeviciute Z, Irimia M, Jia P, Ptak C, Xia M, Tice R, Tochigi M, Moréra S, Nazarians A, Belsham D, Wong AH, Blencowe BJ, Wang SC, Kapranov P, Kustra R, Labrie V, Klimasauskas S, Petronis A. (2012). 5-hmC in the brain is abundant in synaptic genes and shows differences at the exon-intron boundary. Nat Struct Mol Biol. 19 (10): 1037-43. Co-lead author.
  • Labrie V, Pai S, Petronis A. (2012) Epigenetics of major psychosis: progress, problems and perspectives. TiGs, invited review. 28 (9): 427-35. Co-lead author.

Honours and Awards

2019 Donnelly Centre Research Excellence award
2014 NARSAD Young Investigator award
2014 CIHR Postdoctoral Fellowship
2004-2008 Dana Foundation Fellow, WSBS
2004 NSERC Canada Graduate Scholarship