Variations in serotoninergic signaling have been related to behavioral outcomes. Alterations in the genome, such as DNA methylation and histone modifications, are affected by serotonin neurotransmission. The amygdala is an important brain region involved in emotional responses and impulsivity, which receives serotoninergic input. In addition, studies suggest that the serotonin transporter gene network may interact with the environment and influence the risk for psychiatric disorders. We propose to investigate whether/how interactions between the exposure to early life adversity and serotonin transporter gene network in the amygdala associate with behavioral disorders. We constructed a co-expression-based polygenic risk score (ePRS) reflecting variations in the function of the serotonin transporter gene network in the amygdala and investigated its interaction with postnatal adversity on attention problems in two independent cohorts from Canada and Singapore. We also described how interactions between ePRS-5-HTT and postnatal adversity exposure predict brain gray matter density and variation in DNA methylation across the genome. We observed that the expression-based polygenic risk score, reflecting the function of the amygdala 5-HTT gene network, interacts with postnatal adversity, to predict attention and hyperactivity problems across both cohorts. Also, both postnatal adversity score and amygdala ePRS-5-HTT score, as well as their interaction, were observed to be associated with variation in DNA methylation across the genome. Variations in gray matter density in brain regions linked to attentional processes were also correlated to our ePRS score. These results confirm that the amygdala 5-HTT gene network is strongly associated with ADHD-related behaviors, brain cortical density, and epigenetic changes in the context of adversity in young children.
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http://dx.doi.org/10.3389/fnins.2020.00198 | DOI Listing |
Gigascience
January 2025
School of Computer Science, Hunan University of Technology, Zhuzhou 412007, Hunan, China.
Background: The accurate deciphering of spatial domains, along with the identification of differentially expressed genes and the inference of cellular trajectory based on spatial transcriptomic (ST) data, holds significant potential for enhancing our understanding of tissue organization and biological functions. However, most of spatial clustering methods can neither decipher complex structures in ST data nor entirely employ features embedded in different layers.
Results: This article introduces STMSGAL, a novel framework for analyzing ST data by incorporating graph attention autoencoder and multiscale deep subspace clustering.
JAMA Pediatr
January 2025
Department of Medicine, University of Florida, Gainesville.
Importance: Cell and gene therapies are revolutionizing the treatment landscape for children and adults with rare diseases and can be life-changing for patients and their families. Successful implementation of these new therapies into clinical practice depends on their accessibility and affordability, particularly through publicly funded Medicaid agencies, which cover many children and adults with rare diseases.
Objective: To provide a framework to broadly assess cell and gene therapies, evaluate payment options, and ensure equitable access through the lens of publicly funded Medicaid programs.
Neurology
January 2025
The Dubowitz Neuromuscular Centre, Developmental Neurosciences Department, University College London, Great Ormond Street Institute of Child Health, United Kingdom.
Background And Objectives: Safety and efficacy of IV onasemnogene abeparvovec has been demonstrated for patients with spinal muscular atrophy (SMA) weighing <8.5 kg. SMART was the first clinical trial to evaluate onasemnogene abeparvovec for participants weighing 8.
View Article and Find Full Text PDFDiscov Oncol
January 2025
Graduate School of Qinghai University, Xining, 810000, Qinghai Province, People's Republic of China.
The occurrence and progression of breast cancer (BCa) are complex processes involving multiple factors and multiple steps. The tumor microenvironment (TME) plays an important role in this process, but the functions of immune components and stromal components in the TME require further elucidation. In this study, we obtained the RNA-seq data of 1086 patients from The Cancer Genome Atlas (TCGA) database.
View Article and Find Full Text PDFDiscov Oncol
January 2025
Department of Medical Imaging, Shenzhen Longhua District Key Laboratory of Neuroimaging, Shenzhen Longhua District Central Hospital, Shenzhen, 518110, China.
Background: Glioblastoma multiforme (GBM) is a highly aggressive brain cancer with poor prognosis and limited treatment options. Despite advances in understanding its molecular mechanisms, effective therapeutic strategies remain elusive due to the tumor's genetic complexity and heterogeneity.
Methods: This study employed a comprehensive analysis approach integrating 113 machine learning algorithms with Mendelian Randomization (MR) analysis to investigate the molecular underpinnings of GBM.
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