Risk and Protective Environmental Factors Associated with Autism Spectrum Disorder: Evidence-Based Principles and Recommendations

Gialloreti, Leonardo Emberti; Mazzone, Luigi; Benvenuto, Arianna; Fasano, Alessio; Alcon, Alicia Garcia; Kraneveld, Aletta D.; Moavero, Romina; Raz, Raul; Riccio, Maria Pia; Siracusano, Martina; Zachor, Ditza A.; Marini, Marina; Curatolo, Paolo

doi:10.3390/jcm8020217

Cited by 89 publications

(79 citation statements)

References 169 publications

(197 reference statements)

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“…They could not be included in any cluster. These ndings further support an ASD heterogeneity, as it may indicate that the clinical phenotype might be also the outcome of genetic common variants that could interact with a main mutation and/or with epigenetic [56] or environmental factors [57].…”

Section: Discussionsupporting

confidence: 55%

A novel data-driven approach reveals gene networks and biological processes underlying autism

Gialloreti¹,

Enea²,

Micco³

et al. 2020

Preprint

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Background: Developments in gene-hunting techniques identified several ASD associated genes. The considerable significance of cluster analysis associated with gene network studies has led to reveal many disrupted key pathways in ASD, even if its genetic underpinnings remain a challenging task. This study aims to determine, through a novel data-driven approach, how networks of mutated genes impact biological processes underlying autism. Methods: We analyzed the VariCarta dataset, which presents more than 200,000 genomic variant events collected from 13,069 people with ASD. Firstly, we created a whole-genome and an exome sequencing subset. Then, for each subset we compared pairwise patients of each group to build “patient similarity matrices”. Hierarchical-agglomerative-clustering and heatmap were performed to identify clusters of patients with common occurrences of gene networks within these matrices. The subsequent enrichment analysis (EA) highlighted biological processes that might be impacted by the mutated genes of each subgroup. Results: Considering the whole-genome matrix, we identified three main genetic clusters of ASD patients, each one characterized by a network of shared genetic variants. We isolated 11,609 genetic variants shared by at least two subjects in each cluster; 4,187 of these variants (36.1%) were common to the three clusters. Only 331 patients (2.5%) shared none or very few mutated genes with anyone else. The EA highlighted common or cluster-specific biological processes related to the variants. Most of the common abnormal processes were involved in neuron projections guidance and morphogenesis, cell junctions and synapse assembly. Exome sequencing alone was not effectual in identifying ASD subgroups. Limitations: Caution is warranted when interpreting our results, as we did not compare them with a control group and did not verify if the identified subgroups where actually associated with different phenotypes. Future work will have to ascertain the strength and reproducibility of these results. Conclusions: Itemizing not just single mutated genes, but also gene networks and specific biological processes that characterize different ASD subpopulations might allow to better understand which networks of genetic variants play a major role in the etiopathology of ASD. The proposed methodology may represent a novel approach to help disentangle ASD complexity and an instrument to boost more focused genotype-phenotype studies.

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Section: Discussionsupporting

confidence: 55%

A novel data-driven approach reveals gene networks and biological processes underlying autism

Gialloreti¹,

Enea²,

Micco³

et al. 2020

Preprint

Self Cite

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“…Available knowledge of risk factors associated with autism can facilitate the identification of at-risk individuals or subgroups during different periods of development. Various risk factors (fig 1, A) converge onto plausible biological mechanisms during pregnancy or around birth that can lead to autism in childhood 313233. The presence of protective factors can also modify trajectories; yet, much less is known about protective factors in autism and those proposed likely exert their influence by moderating risk factors, eg, female sex moderating genetic risk 34…”

Section: Defining Risk and Resilience In Autismmentioning

confidence: 99%

“…Each factor has been independently associated with the risk of autism with some degree of consistency across studies 31. Each group of factors converges on to a plausible causal mechanism shared with other developmental conditions and/or is well grounded in animal models 313233. Such mechanisms are challenging to investigate directly in autism because of the time lag between their influence on fetal development and a confirmed diagnosis starting at age 3.…”

Section: Risk Factorsmentioning

confidence: 99%

“…These effects can be seen later in life in some of the children with autism by measuring cytokine concentration in peripheral blood72; in one study altered concentrations were associated with more behavior problems in children with autism 73. Maternal health offers important opportunities for augmenting protective factors during pregnancy, such as supplementing folic acid and vitamin D 32. However, given the equivocal evidence for their association with reduced risk of autism,31 these factors are best viewed as protective for neurodevelopment in general and not specific to autism.…”

Section: Risk Factorsmentioning

confidence: 99%

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Linking risk factors and outcomes in autism spectrum disorder: is there evidence for resilience?

Elsabbagh

2020

BMJ

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Autism spectrum disorder (referred to here as autism) is one of several overlapping neurodevelopmental conditions that have variable impacts on different individuals. This variability results from dynamic interactions between biological and non-biological risk factors, which result in increasing differentiation between individuals over time. Although this differentiation continues well into adulthood, the infancy period is when the brain and behavior develop rapidly, and when the first signs and symptoms of autism emerge. This review discusses advances in our understanding of the causal pathways leading to autism and overlapping neurodevelopmental conditions. Research is also mapping trajectories of brain and behavioral development for some risk groups, namely later born siblings of children with autism and/or infants referred because of developmental concerns. This knowledge has been useful in improving early identification and establishing the feasibility of targeted interventions for infant risk groups before symptoms arise. However, key knowledge gaps remain, such as the discovery of protective factors (biological or environmental) that may mitigate the impact of risk. Also, the dynamic mechanisms that underlie the associations between risk factors and outcomes need further research. These include the processes of resilience, which may explain why some individuals at risk for autism achieve better than expected outcomes. Bridging these knowledge gaps would help to provide tools for early identification and intervention that reflect dynamic developmental pathways from risk to outcomes.

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“…Several studies have proven that some parental, prenatal and postnatal factors increase the risk of ASD [ 8 , 9 ]. For example, a significantly higher incidence of ASD has been observed in children having mothers without folic acid supplementation during pregnancy compared to whom had their mothers supplemented [ 10 ]. As for iron, it has been reported that its deficiency, especially during breastfeeding, could lead to an increased ASD risk [ 11 ].…”

Section: Introductionmentioning

confidence: 99%

Risk and Protective Factors in Autism Spectrum Disorders: A Case Control Study in the Lebanese Population

Gerges

Bitar

Hawat

et al. 2020

IJERPH

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Autism spectrum disorders (ASD) are among the most common childhood neurodevelopmental disorders. Identification of risk and protective factors are necessary to improve the guidance of prevention and intervention strategies. Our study aims to determine the potential risk and protective factors in ASD in the Lebanese population. Our case-control study included 100 ASD patients and 100 healthy matched controls recruited from all the Lebanese districts. The data collected from the questionnaires was analyzed using SPSS 23.0. Independent Student T-test and Chi-Square test were carried out for the bivariate analysis of the data. In addition, the variables revealing a p-value < 0.05 were used for the multivariate logistic regression analysis. Multivitamins intake, especially omega 3 and vitamin B (Odds Ratio (OR) = 0.257; 95% Confidence Interval (CI) [0.115–0.579]), rich cereal diet (OR = 0.212; 95% CI [0.089–0.510]), and supplementation in iron during pregnancy (OR = 0.229; 95% CI [0.083–0.627]) were identified as protective factors against ASD. On the other hand, stress during pregnancy (OR = 6.339; 95% CI [2.845–14.125]), the presence of ASD patients in the family (OR = 7.878; 95% CI [1.877–33.065]) and the presence of attention deficit hyperactivity disorder (ADHD) patients in the family (OR = 6.981; 95% CI [1.362–35.789]) were associated with ASD. This study shed light on risk and protective factors associated with ASD in the Lebanese population. Further rigorous research, taking into consideration these factors, is needed to assist in early detection, prevention and subsequent intervention targeting ASD and its associated comorbidities, given that our study is not experimental and does not prove causality.

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Risk and Protective Environmental Factors Associated with Autism Spectrum Disorder: Evidence-Based Principles and Recommendations

Cited by 89 publications

References 169 publications

A novel data-driven approach reveals gene networks and biological processes underlying autism

A novel data-driven approach reveals gene networks and biological processes underlying autism

Linking risk factors and outcomes in autism spectrum disorder: is there evidence for resilience?

Risk and Protective Factors in Autism Spectrum Disorders: A Case Control Study in the Lebanese Population

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