Reduced CD4 T Lymphocytes in Lymph Nodes of the Mouse Model of Autism Induced by Valproic Acid

Aug 17, 2018·
Diego Baronio
Guilherme Bauer-Negrini
Guilherme Bauer-Negrini
,
Kamila Castro
,
Gustavo Della-Flora Nunes
,
Rudimar Riesgo
,
Daniella Arêas Mendes-da-Cruz
,
Wilson Savino
,
Carmem Gottfried
,
Victorio Bambini-Junior
· 0 min read
DOI
Abstract
Objective: Considering the potential role of lymphocytes in the pathophysiology of autism spectrum disorder (ASD), we aimed to evaluate possible alterations of T cell pools in the lymphoid organs of an animal model of autism induced by valproic acid (VPA). Pregnant Swiss mice received a single intraperitoneal injection of 600 mg/kg of VPA (VPA group) or saline (control group) on day 11 of gestation. Male offspring were euthanized on postnatal day 60 for removal of thy-muses, spleens, and a pool of inguinal, axillary and brachial lymph nodes. Cellularity was evaluated, and flow cytometry analysis was performed on cell suspensions incubated with the mouse antibodies anti-CD3-FITC, anti-CD4-PE, and anti-CD8-PE-Cy7. We observed that the prenatal exposure to VPA induced a reduction in the numbers of CD3+CD4+ T cells in their lymph nodes when compared to the control animals. This was specific since it was not seen in the thymus or spleen. The consistent decrease in the number of CD4+ T cells in subcutaneous lymph nodes of mice from the animal model of autism may be related to the allergic symptoms frequently observed in ASD. Further research is necessary to characterize the immunological patterns in ASD and the connection with the pathophysiology of this disorder.
Type
Publication
Neuroimmunomodulation
Status
Peer-reviewed
publications
Guilherme Bauer-Negrini
Authors
Biomedical Data Scientist
Computational neuroscientist working at the intersection of machine learning, biomedical imaging, and human genetics in neurodegenerative disease. My work applies deep learning to high-dimensional medical images, harmonizes imaging measurements across sites and acquisition protocols, and integrates imaging with genomic, proteomic, and longitudinal clinical data to characterise Alzheimer’s disease and related dementias, with particular focus on fluid and imaging biomarkers of neurodegeneration.