Genetics and epigenetics of autism spectrum disorder—current evidence in the field

Wiśniowiecka‐Kowalnik, Barbara; Nowakowska, Beata

doi:10.1007/s13353-018-00480-w

Cited by 163 publications

(122 citation statements)

References 109 publications

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“…At any rate, these observations point to the fact that when considering the disrupted processes of the different ASD phenotypes we should not only look at the CNS but at other systems as well. Thus, this is an important evidence supporting the polygenic model that assumes that ASD is the result of rare and common variants combination [56].…”

Section: Discussionsupporting

confidence: 60%

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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: 60%

“…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: 54%

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

Gialloreti¹,

Enea²,

Micco³

et al. 2020

Preprint

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“…Unfortunately, there are no published investigations of genomic associations with sensory sensitivity, and sample sizes for GWAS studies of ASD lag far behind those of schizophrenia and other neuropsychiatric traits, with only a handful of genome-wide significant loci identified so far [24]. By contrast, rare mutations in hundreds of different genes have been linked to ASD, and such rare genetic variation is thought to be a major contributor to the condition [60]. It is possible that common genetic variation plays a smaller role in ASD than schizophrenia, and that even with a more powerful GWAS the number of significant loci would remain low [61].…”

Section: Discussionmentioning

confidence: 99%

Investigating genetic links between grapheme–colour synaesthesia and neuropsychiatric traits

Tilot

Vino

Kučera

et al. 2019

Phil. Trans. R. Soc. B

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Synaesthesia is a neurological phenomenon affecting perception, where triggering stimuli (e.g. letters and numbers) elicit unusual secondary sensory experiences (e.g. colours). Family-based studies point to a role for genetic factors in the development of this trait. However, the contributions of common genomic variation to synaesthesia have not yet been investigated. Here, we present the SynGenes cohort, the largest genotyped collection of unrelated people with grapheme–colour synaesthesia ( n = 723). Synaesthesia has been associated with a range of other neuropsychological traits, including enhanced memory and mental imagery, as well as greater sensory sensitivity. Motivated by the prior literature on putative trait overlaps, we investigated polygenic scores derived from published genome-wide scans of schizophrenia and autism spectrum disorder (ASD), comparing our SynGenes cohort to 2181 non-synaesthetic controls. We found a very slight association between schizophrenia polygenic scores and synaesthesia (Nagelkerke's R 2 = 0.0047, empirical p = 0.0027) and no significant association for scores related to ASD (Nagelkerke's R 2 = 0.00092, empirical p = 0.54) or body mass index ( R 2 = 0.00058, empirical p = 0.60), included as a negative control. As sample sizes for studying common genomic variation continue to increase, genetic investigations of the kind reported here may yield novel insights into the shared biology between synaesthesia and other traits, to complement findings from neuropsychology and brain imaging. This article is part of a discussion meeting issue ‘Bridging senses: novel insights from synaesthesia'.

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“…4 When we compared ASD prevalence in PA vs the general population, we found a much higher prevalence of ASD in PA (21% compared to 1.7% in the general population (1 in 59 15 ), indicating that a diagnosis of PA is a risk factor to develop ASD and consistent with an increased risk of ASD in patients affected by other monogenic syndromes, like Fragile-X-syndrome, Rett syndrome or Duchenne muscular dystrophy. 16 Our data raise the possibility that the quantitative exposure to high PPA levels in brain over time may be more relevant for an ASD diagnosis in PA patients than the intensity of the acute insult per se. In this regard, Waisbren et al 17 also suggested that the number of metabolic crises in UCDs is not as closely associated with the neuropsychological outcomes as the number of years of exposure to abnormal levels of toxic metabolites.…”

Section: The Pa Population Is At An Increased Risk To Be Diagnosed mentioning

confidence: 74%

High prevalence of self‐reported autism spectrum disorder in the Propionic Acidemia Registry

2019

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Propionic Acidemia (PA) is characterized by the accumulation of propionic acid (PPA), its toxic derivatives, and ammonia. The disease causes multiorgan damage, especially in heart, pancreas, and brain; seizures and intellectual disability are often described. Some PA children also show autism spectrum disorders (ASD). In this study, we have compiled data from 62 individuals from the Propionic Acidemia International Patient Registry and compared it to the published literature on the prevalence of autism in PA. The PA registry shows a significant proportion of ASD diagnoses that is consistent with the combined prevalence reported in the literature. It also shows that ASD in PA is gender balanced and it is diagnosed at older ages (median age 8 years) than in the national registry for autism (median age 4.3 years), which raises the possibility, among others, of PA specific risk factors affecting the natural history of ASD. Data from patient registries provide valuable information on studying the mechanisms involved in a rare disease, although more outreach effort must be done to increase participation and consistency in data entry.

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Genetics and epigenetics of autism spectrum disorder—current evidence in the field

Cited by 163 publications

References 109 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

Investigating genetic links between grapheme–colour synaesthesia and neuropsychiatric traits

High prevalence of self‐reported autism spectrum disorder in the Propionic Acidemia Registry

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