transforming-growth-factor-beta and Autistic-Disorder

To differentiate between conditions of health and disease, current pathway enrichment analysis methods detect the differential expression of distinct biological pathways. System-level model-driven approaches, however, are lacking. Here we present a new methodology that uses a dynamic model to suggest a unified subsystem to better differentiate between diseased and healthy conditions. Our methodology includes the following steps: 1) detecting connections between relevant differentially expressed pathways; 2) construction of a unified in silico model, a stochastic Petri net model that links these distinct pathways; 3) model execution to predict subsystem activation; and 4) enrichment analysis of the predicted subsystem. We apply our approach to the TGF-beta regulation of the autophagy system implicated in autism. Our model was constructed manually, based on the literature, to predict, using model simulation, the TGF-beta-to-autophagy active subsystem and downstream gene expression changes associated with TGF-beta, which go beyond the individual findings derived from literature. We evaluated the in silico predicted subsystem and found it to be co-expressed in the normative whole blood human gene expression data. Finally, we show our subsystem's gene set to be significantly differentially expressed in two independent datasets of blood samples of ASD (autistic spectrum disorders) individuals as opposed to controls. Our study demonstrates that dynamic pathway unification can define a new refined subsystem that can significantly differentiate between disease conditions.

Topics: Autism Spectrum Disorder; Autistic Disorder; Autophagy; Humans; Transforming Growth Factor beta

Neuronal activity is altered in several neurological and psychiatric diseases. Upon depolarization not only neurotransmitters are released but also cytokines and other activators of signaling cascades. Unraveling their complex implication in transcriptional control in receiving cells will contribute to understand specific central nervous system (CNS) pathologies and will be of therapeutically interest. In this study we depolarized mature hippocampal neurons in vitro using KCl and revealed increased release not only of brain-derived neurotrophic factor (BDNF) but also of transforming growth factor beta (TGFB). Neuronal activity together with BDNF and TGFB controls transcription of DNA modifying enzymes specifically members of the DNA-damage-inducible (Gadd) family, Gadd45a, Gadd45b, and Gadd45g. MeDIP followed by massive parallel sequencing and transcriptome analyses revealed less DNA methylation upon KCl treatment. Psychiatric disorder-related genes, namely Tshz1, Foxn3, Jarid2, Per1, Map3k5, and Arc are transcriptionally activated and demethylated upon neuronal activation. To analyze whether misexpression of Gadd45 family members are associated with psychiatric diseases, we applied unpredictable chronic mild stress (UCMS) as established model for depression to mice. UCMS led to reduced expression of Gadd45 family members. Taken together, our data demonstrate that Gadd45 family members are new putative targets for UCMS treatments.

Topics: Animals; Autistic Disorder; Brain-Derived Neurotrophic Factor; Cell Cycle Proteins; Cells, Cultured; Chronic Disease; Depressive Disorder; Disease Models, Animal; DNA Methylation; Hippocampus; Male; Mice, Inbred BALB C; Mice, Inbred C57BL; Neurons; Nuclear Proteins; Protein Serine-Threonine Kinases; Receptor, Transforming Growth Factor-beta Type I; Receptors, Transforming Growth Factor beta; Signal Transduction; Stress, Psychological; Synaptic Transmission; Transcriptome; Transforming Growth Factor beta