| Literature DB >> 26441683 |
Carmem Gottfried1, Victorio Bambini-Junior2, Fiona Francis3, Rudimar Riesgo4, Wilson Savino5.
Abstract
Autism spectrum disorder (ASD) involves a complex interplay of both genetic and environmental risk factors, with immune alterations and synaptic connection deficiency in early life. In the past decade, studies of ASD have substantially increased, in both humans and animal models. Immunological imbalance (including autoimmunity) has been proposed as a major etiological component in ASD, taking into account increased levels of pro-inflammatory cytokines observed in postmortem brain from patients, as well as autoantibody production. Also, epidemiological studies have established a correlation of ASD with family history of autoimmune diseases; associations with major histocompatibility complex haplotypes and abnormal levels of immunological markers in the blood. Moreover, the use of animal models to study ASD is providing increasing information on the relationship between the immune system and the pathophysiology of ASD. Herein, we will discuss the accumulating literature for ASD, giving special attention to the relevant aspects of factors that may be related to the neuroimmune interface in the development of ASD, including changes in neuroplasticity.Entities:
Keywords: autism; environmental risk factors; neuroimmune interactions; rodent models; valproic acid
Year: 2015 PMID: 26441683 PMCID: PMC4563148 DOI: 10.3389/fpsyt.2015.00121
Source DB: PubMed Journal: Front Psychiatry ISSN: 1664-0640 Impact factor: 4.157
Selected genes altered in ASD, correlated with immune function.
| Gene | Protein | Function |
|---|---|---|
| Receptor tyrosine kinase (MET) | ||
| Phosphatase and tensin homolog (PTEN) | ||
| Tuberous sclerosis complex-1 (TSC1) | Promote IL-12 increase and M2-macrophage conversion | |
| Tuberous sclerosis complex-2 (TSC2) | ||
| Major histocompatibility complex type II (MHC-II) | ||
| Macrophage migration inhibitory factor (MIF) | Guide and control of immune response | |
| Complement component 4B (C4B) |
Anatomical studies of brains from individual with ASD.
| Phenotype | Brain area | Method | Studied | Age (autism) | Sex | Reference |
|---|---|---|---|---|---|---|
| Macrocephaly | Head | Head circumference | 9.7 ± 5.4 years (3–47 years) | 5.9M:1F | ( | |
| Neuron number | DL-PFC and M-PFC | Postmortem | 2–16 years | Male | ( | |
| WM volume | Head | MRI | 41 boys (13 autistic, 14 DLD, 14 normal control); 22 girls (7 DLD, 15 normal controls) | 9.0 0.9 years (autistic), 8.2 1.6 years (DLD), and 9.1 1.2 years (controls) | Males and females | ( |
| GM volume, Gyral thickness | Head-temporal and parietal lobes affected | MRI | 8–12 years | Male | ( | |
| PV interneurons | DLPFC | Postmortem | 30–44 years | Male | ( | |
| Minicolumns | Prefrontal (area 9) and Temporal (areas 21, 22) lobe | Postmortem | 5–28 years | – | ( | |
| Neuron migration disorders | Brain | Postmortem | 4–62 years | 9 males 4 females | ( | |
| Cell density cortical layers | ACC | Postmortem | ( | |||
| Cortical layers | PCC FFG | Postmortem | 19–54 years (PCC), 14–32 years (FFG) | Male | ( | |
| Dendritic spines | Frontal, temporal and parietal (layer II), layer V (temporal) | Postmortem Golgi | 10–45 years | Males | ( | |
| Gray-white matter boundary | STG, DL-frontal, and DL-parietal | 10–45 years | Males | ( | ||
| Axons | ACC, OFC, LPFC | Postmortem | 30–44 years | 4 male, 1 female | ( | |
| Corpus callosum | CC | MRI | Meta-analysis (10 studies) | Male >74% | ( | |
| Corpus callosum | CC | MRI | 16–54 years | Males and females (3) | ( | |
| Brain development | White matter | DTI (prospective, longitudinal) | 6–24 months | Males and females | ( | |
| Brain | White matter (CC) | DTI (prospective, longitudinal) | 3–41 years | Males | ( | |
| Brain | White matter (CC) | DTI | 7–33 years | Males | ( | |
| Brain | White matter and activation (ACC) | DTI and fMRI | 20–40 years | Males and females (2) | ( | |
| Brain | White matter (arcuate) | DTI | 6–13 years | Males and females (2) | ( | |
| Brain | White matter (several areas) | DTI | 11–18 years | Males and females (1) | ( | |
| Brain | Theory of mind areas | fMRI | 15–35 years | Males and females (2) | ( | |
| Brain | Several areas | MRI/DTI | 6–12 years | Males and females (2) | ( | |
| Brain | Language and spatial | fMRI | Mean 22.5 years | Males and females (1) | ( | |
| Brain | Working memory face recognition | fMRI | 24.5 ± 10.2 years | Males | ( | |
| Brain | Reading comprehension | fMRI | – | – | ( | |
| Brain | Resting state | fMRI | 15–52 years | Males | ( | |
| Brain | Resting state | fMRI | 13–17 years | Males and females (2) | ( | |
| Brain | Executive function (Tower of London task), CC size | fMRI | 27.1 ± 11.9 years | Males and females (1) | ( | |
| Brain | Resting state | fMRI | 26 ± 5.93 years | Males and females (1) | ( | |
| Brain | Source recognition task | fMRI | 14–43 years | Males | ( | |
| Brain | Face processing | fMRI | 23.5 ± 7.8 years | – | ( |
Altered cytokines in autism spectrum disorder (ASD).
| Cytokines | Level compared to control group | Source | Evaluated subjects | Reference |
|---|---|---|---|---|
| IL-1β | ↑ | Plasma | Children with ASD | ( |
| ↑ | Plasma | Children with ASD | ( | |
| ↑ | Plasma | Adults with severe ASD | ( | |
| ↑ | Blood cells | Children with ASD | ( | |
| ↑ (TLR2 or TLR4 stimulation) | Blood cells | Children with ASD | ( | |
| ↓ (TLR-9 stimulation) | Blood cells | Children with ASD | ( | |
| IL-6 | ↑ | Plasma | Children with ASD | ( |
| ↑ | Plasma | Adults with severe autism | ( | |
| ↑ | Blood cells | Children with ASD | ( | |
| ↑ (TLR2 or TLR4 stimulation) | Blood cells | Children with ASD | ( | |
| ↓ (TLR-9 stimulation) | Blood cells | Children with ASD | ( | |
| ↑ | Lymphoblasts | Children with ASD | ( | |
| ↑ | Cerebellum (postmortem) | Children with ASD | ( | |
| ↑ | Brain (postmortem) | ASD subjects (children and adults) | ( | |
| ↑ | Brain (postmortem) | ASD subjects (children and adults) | ( | |
| IL-12 P40 | ↑ | Plasma | Children with ASD | ( |
| CCL2 | ↑ | Brain (postmortem) | ASD subjects (children and adults) | ( |
| Plasma | Children with ASD | ( | ||
| TNF-α | ↑ | CSF | Children with ASD | ( |
| Brain (postmortem) | Children with ASD | ( | ||
| IFN-γ | Serum (mid-gestational) | Mothers giving birth to child with ASD | ( | |
| ↑ | Whole blood and serum | Children with ASD | ( | |
| Brain (postmortem) | ASD subjects (children and adults) | ( | ||
| TGF-β1 | ↓ | Plasma | Children with ASD (Lower levels correlated with more severe behavioral scores) | ( |
| ↓ | Serum | Adults with ASD | ( | |
| BDNF | ↑ | Brain (postmortem) | ASD subjects (children and adults) | ( |
| ↑ | Plasma | Children with ASD | ( | |
IK, interleukin; IFN, interferon; TGF, transforming growth factor; TLR, toll-like receptors.
Figure 1Evidence for neuroimmune interactions in autism spectrum disorder (ASD). Blood and postmortem brain alterations in individuals with ASD. (1) Antibody production in blood against brain antigens. (2) Brain cell infiltration of Th1 lymphocytes, monocytes and mast cells. (3) Increase in blood brain barrier (BBB) permeability. (4) Increase in IgG and IgM levels. (5) Less antioxidant defenses. (6) Changes in cytokine levels. (7) Decrease in cell adhesion molecules, such as Selectins and PCAM-1. 8. Increase in oxidative stress. All these alterations can promote neuroinflammation, followed by neuron–glial response and brain connectivity dysfunction that ultimately can influence behavioral features in ASD. GSH, glutathione; GPx, glutathione peroxidase; NO, nitric oxide; Th, T-helper; OS, oxidative stress; CCL2, C–C motif chemokine 2.
Selected findings in animal models related to ASD and immune system.
| Model | Animal | Outcome, breakthrough or major finding | Reference |
|---|---|---|---|
| – | Mouse | Suggested that animal models of autoimmunity-associated behavioral syndrome (AABS) may be a useful model for the study of CNS involvement in human autoimmune diseases, e.g., autism | ( |
| Neonatal rat infection with Borna disease virus | Rat | Abnormalities of early development; Increase locomotor activity; Increased stereotypies; Increased brain expression of mRNA for IL-1a, IL1-b, IL-6, TNF-α, and TNF-β | ( |
| MIA | Mouse | Offspring display deficits in prepulse inhibition; deficiency in exploratory behavior and deficiency in social interaction | ( |
| MIA | Mouse | Prepulse inhibition (PPI) and latent inhibition (LI) deficits were observed in the adult offspring. Coadministration of an anti-IL-6 antibody in the model of MIA prevented the behavioral changes. MIA in IL-6 knockout mice does not result in several of the behavioral changes seen in the offspring of wild-type mice after MIA | ( |
| Prenatal exposure to VPA | Rat | Increased basal level of corticosterone, decreased weight of the thymus, decreased splenocytes proliferative response to concanavaline A, lower IFN-gamma/IL-10 ratio, and increased production of NO by peritoneal macrophages | ( |
| Prenatal exposure to antibodies from mothers of children with autism | Mouse | Adult mice exposed | ( |
| MIA | Rhesus monkey | Behavioral alterations in infants monkeys were observed, e.g., disruption of prepulse inhibition. Magnetic resonance imaging (MRI) revealed a significant 8.8% increase in global white matter volume distributed across many cortical regions compared to controls | ( |
| MIA | Mouse | Pups born to maternal immune activation (MIA) mothers produce a lower rate of Ultrasonic vocalizations, decreased sociability and increased repetitive/stereotyped behavior | ( |
| MIA | Mouse | Systemic deficit in CD4(+) TCRβ(+) Foxp3(+) CD25(+) T regulatory cells, increased IL 6 and IL-17 production by CD4(+) T cells, and elevated levels of peripheral Gr-1(+) cells; hematopoietic stem cells exhibit altered myeloid lineage potential and differentiation; behaviorally abnormal MA offspring that have been irradiated and transplanted with immunologically normal bone marrow from either MIA or control offspring no longer exhibit deficits in stereotyped/repetitive and anxiety-like behaviors | ( |
| MIA | Rhesus monkey | Offspring exhibited abnormal responses to separation from their mothers, increased repetitive behaviors and inappropriately approaching and remaining in immediate proximity of an unfamiliar animal | ( |
| Prenatal exposure to antibodies from mothers of children with autism | Mouse | Offspring displayed autistic-like stereotypical behavior in both marble burying and spontaneous grooming behaviors. Additionally, small alterations in social approach behavior were observed | ( |
| MIA | Mouse | Following stimulation macrophages from offspring of poly(I:C) treated dams produced higher levels of IL-12, suggesting an increased M1 polarization. Also, macrophages from offspring of poly(I:C) treated dams exhibited a higher production of CCL3 | ( |
| MIA | Mouse | In the marble burying test of repetitive behavior, male offspring but not female offspring from both LPS and PolyIC-treated mothers showed increased marble burying | ( |
| Prenatal exposure to VPA | Mouse | VPA mice present signs of chronic glial activation in the hippocampus and the cerebellum; When they are challenged LPS, they show an exacerbated inflammatory response, increased expression of pro-inflammatory cytokines in the spleen and higher corticosterone secretion to the blood | ( |
| BTBR strain | Mouse | Levels of IgG isotypes deposited in fetal brain of BTBR mice were significantly higher than in FVB mice except for IgG1 | ( |
| BTBR strain | Mouse | Altered IgG levels were found, e.g., higher IgG1:IgG2a ratios; presence of brain-reactive IgG in the sera; levels of IgG1 deposited in the cerebellum, cortex, hippocampus or striatum of both BTBR male and female mice were significantly higher than in FVB counterpart | ( |
| MIA | Mouse | Adult LPS-treated mice offspring had an elevated percentage of interferon (IFN)-γ(+) CD4(+) T cells and interleukin (IL)-17A(+) CD4(+) T cells in the spleen, IL-17A(+) CD4(+) T cells in the liver, and CD4(+) Foxp3(+) T cells in the spleen. LPS offspring CD4(+) T cells showed increased proliferation and an enhanced survival rate | ( |
Figure 2Hypothesis for neuroimmune interactions in triggering the development of ASD. This hypothesis considers the presence of environmental risk factors during pregnancy, followed by immunoneuroendocrine response from the mother to the developing embryo/fetus. The risk factors (such as VPA) would influence central and peripheral neural responses in the context of a crosstalk with the immune system, followed by gradual changes in neural plasticity and function, resulting in behavioral impairment during development, ultimately leading to ASD.