Identifying Windows of Susceptibility by Temporal Gene Analysis

Overview

Journal Sci Rep

Specialty Science

Date 2019 Feb 28

PMID 30809014

Citations 7

Authors

Kristin P Bennett

Elisabeth M Brown

Hannah De Los Santos

Matthew Poegel

Thomas R Kiehl

Evan W Patton

Spencer Norris

Sally Temple

John Erickson

Deborah L McGuinness

Nathan C Boles

Affiliations

Soon will be listed here.

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.

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