Mycotoxin Exposure and Autism: A Systematic Review of Molecular Mechanism

2020 ◽  
Vol 13 ◽  
Author(s):  
Yılmaz Serkan ◽  
Utku Beyazit ◽  
Aynur Bütün Ayhan

Background and objective: Exposure to mycotoxins may delay and/or negatively influence the development of neurological, gastrointestinal and inflammatory mechanisms in individuals with Autism Spectrum Disorder (ASD). Therefore, there is a need to address the possible links between mycotoxins and the risk and prevalence of ASD to increase the understanding of the molecular mechanism underlying these links. In this context, the aim of this study was to investigate the molecular mechanism underpinning mycotoxin exposure and autism. Methods: The study was based on a systematic approach which focused on the possible associations between mycotoxins and ASD in addition to the role of the mycotoxins on the risk and prevalence of ASD. The systematic review included all molecular mechanism studies examining mycotoxin exposure and autism, and was not limited to a specific period of time. A search was performed on the PubMed, Web of Science, Scopus, and Google Scholar databases. Results: The investigation of the literature revealed that a total number of 11 studies with a specific focus on the molecular mechanism of mycotoxin exposure and autism were published between 2008 and 2019. Out of these studies, 7 were research and 4 were review articles. In almost all the articles, possible links between mycotoxins and ASD were revealed. Conclusion: The examination of the given studies provided data related to the links between mycotoxins and ASD. However, evidence related to these links needs to be investigated in larger samples, while the effects of separate mycotoxins and their metabolisms should also be examined.

2019 ◽  
Vol 40 (6) ◽  
pp. 1421-1454 ◽  
Author(s):  
Tamar Kalandadze ◽  
Valentina Bambini ◽  
Kari-Anne B. Næss

AbstractIndividuals with autism spectrum disorder (ASD) often experience difficulty in comprehending metaphors compared to individuals with typical development (TD). However, there is a large variation in the results across studies, possibly related to the properties of the metaphor tasks. This preregistered systematic review and meta-analysis (a) explored the properties of the metaphor tasks used in ASD research, and (b) investigated the group difference between individuals with ASD and TD on metaphor comprehension, as well as the relationship between the task properties and any between-study variation. A systematic search was undertaken in seven relevant databases. Fourteen studies fulfilled our predetermined inclusion criteria. Across tasks, we detected four types of response format and a great variety of metaphors in terms of familiarity, syntactic structure, and linguistic context. Individuals with TD outperformed individuals with ASD on metaphor comprehension (Hedges’ g = −0.63). Verbal explanation response format was utilized in the study showing the largest effect size in the group comparison. However, due to the sparse experimental manipulations, the role of task properties could not be established. Future studies should consider and report task properties to determine their role in metaphor comprehension, and to inform experimental paradigms as well as educational assessment.


Cells ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 1976
Author(s):  
Bianka Hoxha ◽  
Malvina Hoxha ◽  
Elisa Domi ◽  
Jacopo Gervasoni ◽  
Silvia Persichilli ◽  
...  

Folic acid has been identified to be integral in rapid tissue growth and cell division during fetal development. Different studies indicate folic acid’s importance in improving childhood behavioral outcomes and underline its role as a modifiable risk factor for autism spectrum disorders. The aim of this systematic review is to both elucidate the potential role of folic acid in autism spectrum disorders and to investigate the mechanisms involved. Studies have pointed out a potential beneficial effect of prenatal folic acid maternal supplementation (600 µg) on the risk of autism spectrum disorder onset, but opposite results have been reported as well. Folic acid and/or folinic acid supplementation in autism spectrum disorder diagnosed children has led to improvements, both in some neurologic and behavioral symptoms and in the concentration of one-carbon metabolites. Several authors report an increased frequency of serum auto-antibodies against folate receptor alpha (FRAA) in autism spectrum disorder children. Furthermore, methylene tetrahydrofolate reductase (MTHFR) polymorphisms showed a significant influence on ASD risk. More clinical trials, with a clear study design, with larger sample sizes and longer observation periods are necessary to be carried out to better evaluate the potential protective role of folic acid in autism spectrum disorder risk.


2021 ◽  
Vol 15 ◽  
Author(s):  
Ala Seif ◽  
Carly Shea ◽  
Susanne Schmid ◽  
Ryan A. Stevenson

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that affects one in 66 children in Canada. The contributions of changes in the cortex and cerebellum to autism have been studied for decades. However, our understanding of brainstem contributions has only started to emerge more recently. Disruptions of sensory processing, startle response, sensory filtering, sensorimotor gating, multisensory integration and sleep are all features of ASD and are processes in which the brainstem is involved. In addition, preliminary research into brainstem contribution emphasizes the importance of the developmental timeline rather than just the mature brainstem. Therefore, the purpose of this systematic review is to compile histological, behavioral, neuroimaging, and electrophysiological evidence from human and animal studies about brainstem contributions and their functional implications in autism. Moreover, due to the developmental nature of autism, the review pays attention to the atypical brainstem development and compares findings based on age. Overall, there is evidence of an important role of brainstem disruptions in ASD, but there is still the need to examine the brainstem across the life span, from infancy to adulthood which could lead the way for early diagnosis and possibly treatment of ASD.


2021 ◽  
Vol 13 (9) ◽  
pp. 5097
Author(s):  
Irene Gómez-Marí ◽  
Pilar Sanz-Cervera ◽  
Raúl Tárraga-Mínguez

The increasing number of students with autism spectrum disorder (ASD) in mainstream education environments require teachers to know how to identify their needs, being capable to adapt their education processes and make their inclusion easier. The purpose of this study is to conduct a systematic review about teachers’ knowledge of ASD, including teachers from any stage and specialization. The research has been conducted from four databases (Web of Science, Scopus, PsycInfo and Google Scholar) during the period of 2015–2020. In total, 25 articles were analyzed. The results show that, in general, teachers’ knowledge of ASD is poor. It depends on the education stage (being higher in early childhood teachers and in university professors), prior training and possible prior contact with students with ASD.


2020 ◽  
Vol 29 (2) ◽  
pp. 890-902
Author(s):  
Lynn Kern Koegel ◽  
Katherine M. Bryan ◽  
Pumpki Lei Su ◽  
Mohini Vaidya ◽  
Stephen Camarata

Purpose The purpose of this systematic review was to identify parent education procedures implemented in intervention studies focused on expressive verbal communication for nonverbal (NV) or minimally verbal (MV) children with autism spectrum disorder (ASD). Parent education has been shown to be an essential component in the habilitation of individuals with ASD. Parents of individuals with ASD who are NV or MV may particularly benefit from parent education in order to provide opportunities for communication and to support their children across the life span. Method ProQuest databases were searched between the years of 1960 and 2018 to identify articles that targeted verbal communication in MV and NV individuals with ASD. A total of 1,231 were evaluated to assess whether parent education was implemented. We found 36 studies that included a parent education component. These were reviewed with regard to (a) the number of participants and participants' ages, (b) the parent education program provided, (c) the format of the parent education, (d) the duration of the parent education, (e) the measurement of parent education, and (f) the parent fidelity of implementation scores. Results The results of this analysis showed that very few studies have included a parent education component, descriptions of the parent education programs are unclear in most studies, and few studies have scored the parents' implementation of the intervention. Conclusions Currently, there is great variability in parent education programs in regard to participant age, hours provided, fidelity of implementation, format of parent education, and type of treatment used. Suggestions are made to provide both a more comprehensive description and consistent measurement of parent education programs.


2018 ◽  
Vol 19 (5) ◽  
pp. 454-459 ◽  
Author(s):  
Francielly Mourao Gasparotto ◽  
Francislaine Aparecida dos Reis Lívero ◽  
Sara Emilia Lima Tolouei Menegati ◽  
Arquimedes Gasparotto Junior

2019 ◽  
Author(s):  
Sun Jae Moon ◽  
Jin Seub Hwang ◽  
Rajesh Kana ◽  
John Torous ◽  
Jung Won Kim

BACKGROUND Over the recent years, machine learning algorithms have been more widely and increasingly applied in biomedical fields. In particular, its application has been drawing more attention in the field of psychiatry, for instance, as diagnostic tests/tools for autism spectrum disorder. However, given its complexity and potential clinical implications, there is ongoing need for further research on its accuracy. OBJECTIVE The current study aims to summarize the evidence for the accuracy of use of machine learning algorithms in diagnosing autism spectrum disorder (ASD) through systematic review and meta-analysis. METHODS MEDLINE, Embase, CINAHL Complete (with OpenDissertations), PsyINFO and IEEE Xplore Digital Library databases were searched on November 28th, 2018. Studies, which used a machine learning algorithm partially or fully in classifying ASD from controls and provided accuracy measures, were included in our analysis. Bivariate random effects model was applied to the pooled data in meta-analysis. Subgroup analysis was used to investigate and resolve the source of heterogeneity between studies. True-positive, false-positive, false negative and true-negative values from individual studies were used to calculate the pooled sensitivity and specificity values, draw SROC curves, and obtain area under the curve (AUC) and partial AUC. RESULTS A total of 43 studies were included for the final analysis, of which meta-analysis was performed on 40 studies (53 samples with 12,128 participants). A structural MRI subgroup meta-analysis (12 samples with 1,776 participants) showed the sensitivity at 0.83 (95% CI-0.76 to 0.89), specificity at 0.84 (95% CI -0.74 to 0.91), and AUC/pAUC at 0.90/0.83. An fMRI/deep neural network (DNN) subgroup meta-analysis (five samples with 1,345 participants) showed the sensitivity at 0.69 (95% CI- 0.62 to 0.75), the specificity at 0.66 (95% CI -0.61 to 0.70), and AUC/pAUC at 0.71/0.67. CONCLUSIONS Machine learning algorithms that used structural MRI features in diagnosis of ASD were shown to have accuracy that is similar to currently used diagnostic tools.


Author(s):  
Huaimin Yi ◽  
Yajun Han ◽  
Mengxin Li ◽  
Jiong Wang ◽  
Liping Yang

Sign in / Sign up

Export Citation Format

Share Document