Gestational diabetes induces behavioral and brain gene transcription dysregulation in adult offspring

Keren Aviel-Shekler, Yara Hamshawi, Worood Sirhan, Dmitriy Getselter, Kolluru D. Srikanth, Assaf Malka, Ron Piran, Evan Elliott

Research output: Contribution to journalArticlepeer-review

29 Scopus citations

Abstract

The etiology of Autism Spectrum Disorders (ASD) includes a strong genetic component and a complicated environmental component. Recent evidence indicates that maternal diabetes, including gestational diabetes, is associated with an increased prevalence of ASD. While previous studies have looked into possible roles for maternal diabetes in neurodevelopment, there are few studies into how gestational diabetes, with no previous diabetic or metabolic phenotype, may affect neurodevelopment. In this study, we have specifically induced gestational diabetes in mice, followed by behavioral and molecular phenotyping of the mice offspring. Pregnant mice were injected with STZ a day after initiation of pregnancy. Glucose levels increased to diabetic levels between E7 and E14 in pregnancy in a subset of the pregnant animals. Male offspring of Gestational Diabetic mothers displayed increased repetitive behaviors with no dysregulation in the three-chambered social interaction test. RNA-seq analysis revealed a dysregulation in genes related to forebrain development in the frontal cortex and a dysregulation of a network of neurodevelopment and immune related genes in the striatum. Together, these results give evidence that gestational diabetes can induce changes in adulthood behavior and gene transcription in the brain.

Original languageEnglish
Article number412
JournalTranslational Psychiatry
Volume10
Issue number1
DOIs
StatePublished - 25 Nov 2020

Bibliographical note

Publisher Copyright:
© 2020, The Author(s).

Funding

We thank the Crown Center of Genomics and the Insitute of Bioinformatics at the Israel National Center for Personalized Medicine (INCPM) in the Weizmann Institute for Science for their genomic and bioinformatic support. In particular, we thank Gilgi Friedlander for her work and support toward this project. This project was funded by the Israel Science Foundation (898/17) and Teva Pharmaceuticals.

FundersFunder number
Teva Pharmaceuticals
Israel Science Foundation898/17

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