Title: Identifying Windows of Susceptibility by Temporal Gene Analysis.

Authors: Bennett, Kristin P; Brown, Elisabeth M; Santos, Hannah De Los; Poegel, Matthew; Kiehl, Thomas R; Patton, Evan W; Norris, Spencer; Temple, Sally; Erickson, John; McGuinness, Deborah L; Boles, Nathan C

Published In Sci Rep, (2019 02 26)

Abstract: Increased understanding of developmental disorders of the brain has shown that genetic mutations, environmental toxins and biological insults typically act during developmental windows of susceptibility. Identifying these vulnerable periods is a necessary and vital step for safeguarding women and their fetuses against disease causing agents during pregnancy and for developing timely interventions and treatments for neurodevelopmental disorders. We analyzed developmental time-course gene expression data derived from human pluripotent stem cells, with disease association, pathway, and protein interaction databases to identify windows of disease susceptibility during development and the time periods for productive interventions. The results are displayed as interactive Susceptibility Windows Ontological Transcriptome (SWOT) Clocks illustrating disease susceptibility over developmental time. Using this method, we determine the likely windows of susceptibility for multiple neurological disorders using known disease associated genes and genes derived from RNA-sequencing studies including autism spectrum disorder, schizophrenia, and Zika virus induced microcephaly. SWOT clocks provide a valuable tool for integrating data from multiple databases in a developmental context with data generated from next-generation sequencing to help identify windows of susceptibility.

PubMed ID: 30809014

MeSH Terms: No MeSH terms associated with this publication