Biology subjects

Krontira, A. C.

Publications and source records attributed to Krontira, A. C..

3 recordsLinked to original sources

bioRxiv2024

Chronic exposure to glucocorticoids amplifies inhibitory neuron cell fate during human neurodevelopment in organoids

Disruptions in the tightly regulated process of human brain development have been linked to increased risk for brain and mental illnesses. While the genetic contribution to these diseases is well established, important environmental factors have been less studied at molecular and cellular levels. In this study, we used single-cell and cell-type-specific techniques to investigate the effect of glucocorticoid (GC) exposure, a mediator of antenatal environmental risk, on gene regulation and lineage specification in unguided human neural organoids. We characterized the transcriptional response to chronic GC exposure during neural differentiation and studied the underlying gene regulatory networks by integrating single-cell transcriptomics-with chromatin accessibility data. We found lasting cell type-specific changes that included autism risk genes and several transcription factors associated with neurodevelopment. Chronic GCs influenced lineage specification primarily by priming the inhibitory neuron lineage through key transcription factors like PBX3. We provide evidence for convergence of genetic and environmental risk factors through a common mechanism of altering lineage specification.

neuroscience↗

bioRxiv2022

Temporal regulation of ZBTB16 expression by glucocorticoids alters human cortical neurogenesis

Glucocorticoids are important for proper organ maturation and their levels are tightly regulated during development. Here we use human cerebral organoids and mice to study cell-type specific effects of glucocorticoids on neurogenesis. We show that glucocorticoids increase a specific type of basal progenitors (co-expressing PAX6 and EOMES) that has been shown to drive cortical expansion in gyrified species. This effect is mediated via the transcription factor ZBTB16 and leads to increased production of neurons. A phenome-wide mendelian randomization analysis of an enhancer variant that moderates glucocorticoid-induced ZBTB16 levels, reveals causal relationships with higher educational attainment and altered brain structure. The relationship with postnatal cognition is supported by data from a prospective pregnancy cohort. This study provides a novel cellular and molecular pathway for the effects of glucocorticoids on human neurogenesis that relates to lasting postnatal phenotypes.

neuroscience↗

bioRxiv2022

DiffBrainNet: differential analyses add new insights into the response to glucocorticoids at the level of genes, networks and brain regions

Genome-wide gene expression analyses are invaluable tools for increasing our knowledge of biological and disease processes, allowing a hypothesis-free comparison of gene expression profiles across experimental groups, tissues and cell types. Traditionally, transcriptomic data analysis has focused on gene-level effects found by differential expression. In recent years, network analysis has emerged as an important additional level of investigation, providing information on molecular connectivity, especially for diseases associated with a large number of linked effects of smaller magnitude, like neuropsychiatric disorders and their risk factors, including stress. In this manuscript, we describe how combined differential expression and prior-knowledge-based differential network analysis can be used to explore complex datasets. As an example, we analyze the transcriptional responses following administration of the glucocorticoid/stress hormone receptor agonist dexamethasone in C57Bl/6 mice, in 8 brain regions important for stress processing: the prefrontal cortex, the amygdala, the paraventricular nucleus of the hypothalamus, the cerebellar cortex, and sub regions of the hippocampus: the dorsal and ventral Cornu Ammonis 1, the dorsal and ventral dentate gyrus. By applying a combination of differential network- and differential expression-analyses, we find that these explain distinct but complementary aspects and biological mechanisms of the responses to the stimulus. In addition, network analysis identifies new differentially connected partners of important genes and can be used to generate hypotheses on specific molecular pathways affected. With this work, we provide an analysis framework and a publicly available resource for the study of the transcriptional landscape of the mouse brain: DiffBrainNet (http://diffbrainnet.psych.mpg.de), which can identify molecular pathways important for basic functioning and response to glucocorticoids in a brain-region specific manner.

genomics↗