Genetic Evaluation of Autism

doi:10.1016/j.spen.2008.01.005

Seminars in Pediatric Neurology

Volume 15, Issue 1, March 2008, Pages 27-31

https://doi.org/10.1016/j.spen.2008.01.005 Get rights and content

The autism spectrum disorders represent a collective of neurogenetic conditions that have in common altered socialization and communication. Much attention has been given lately to the marked increased in the reported incidence of these conditions. Significant debate also exists as to the basis of the reported increase. Regardless, clinical geneticists and pediatric neurologists alike are seeing a tremendous increase in the number of referrals for autism and related conditions. Continuing advances in genetic testing provide a moving target for the clinician in determining an appropriate diagnostic plan. In this article, we review the most recent advances in genetic testing technology and their potential application to the etiologic evaluation of patients with autism spectrum disorders.

Section snippets

Conclusion

The past several years have yielded mounting evidence of the strong genetic basis of autism. Advances in genetic technology have increased the diagnostic yield for autism spectrum disorders. Every person (family) with an ASD should be offered a genetic evaluation to determine the etiology of the condition. Before the evaluation the clinician should discuss all of the pertinent parameters of testing including cost, patient investment, diagnostic yield, and possible implications of a confirmed

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This chapter focuses on the use of chemometric models developed from infrared (IR) spectroscopic data of blood serum as an auxiliary tool for autism spectrum disorder (ASD) diagnosis. In the introductory sections the fundamentals of IR spectroscopy are shortly reviewed and brief descriptions of the different chemometric methods used in the case study described in the last section of the chapter are presented. The last section deals with the application of the described strategy to the diagnosis of ASD in children and adolescents.
Association between MTHFR gene polymorphism and susceptibility to autism spectrum disorders: Systematic review and meta-analysis
2020, Research in Autism Spectrum Disorders
Citation Excerpt :
ASD as a childhood disorder, is characterized by two major symptoms including restricted/repetitive behaviors, and social communication deficits which is combination of social and communication problems (Devlin & Scherer, 2012; Szatmari et al., 2012). During recent years, a significant increase in the reported incidence of ASD has attracted much more attention in the world (Mendelsohn & Schaefer, 2008). The global prevalence of the ASD has been estimated to be approximately 1/80–100 (Liu et al., 2011; Mendelsohn & Schaefer, 2008).
A growing number of studies have highlighted the potential link between MTHFR gene polymorphisms and autism spectrum disorder (ASD), however, the results are conflictive. Therefore, this meta-analysis was conducted to find a persuasive answer for possible association or lack of association between MTHFR gene polymorphism and ASD risk.
Systematic search was conducted in PubMed, Web of Science, and Scopus considering the association between MTHFR gene (C677 T and A1298C) polymorphisms and the risk of ASD prior to Jun 2019.
A total of 17 studies for C677T and 8 studies for A1298C MTHFR gene polymorphism recognized eligible. The pooled results suggested a significant association between C677T SNP and ASD risk under dominant model (OR = 1.47, 95%CI = 1.13–2.93, REM), allelic model (OR = 1.37, 95% CI = 1.08–1.74, REM), and CT vs CC model (OR = 1.45, 95% CI = 1.13–1.85, REM). Moreover, the pooled results of subgroup analysis confirmed increased risk of ASD in Caucasians across all genetic models except recessive model. Besides, in spite of no significant association between A1298C SNP and ASD in overall population, subgroup analysis revealed that presence of A1298C SNP decrease risk of ASD in Caucasians.
This meta-analysis suggested a significant association between MTHFR gene polymorphism (C677T and A1298C) and ASD risk.
Artificial intelligence analysis of newborn leucocyte epigenomic markers for the prediction of autism
2019, Brain Research
Citation Excerpt :
ASD is known to be highly heterogeneous in both clinical presentation and etiology. There is evidence of a strong genetic component (Mendelsohn and Schaefer, 2008; Betancur, 2011). Classic genetic changes, such as gene mutations, translocations, inversions, and copy number variations play a major role in the genetic etiology of ASD (Mefford et al., 2012; Reddy, 2005).
Epigenetic modification appears to be important in the pathogenesis of Autism and Autism spectrum disorder (ASD). Early detection and intervention is known to correlate with improved long-term outcomes. There is thus intense scientific interest in the disease pathogenesis and early prediction. Our goal was to investigate the epigenetic basis of classic autism and identify early biomarkers. Cytosine (‘CpG’) methylation was measured genome-wide in 14 autism cases and 10 controlsusing the Infinium HumanMethylation450 BeadChip assay. Six Machine Learning/Artificial Intelligence (AI) platforms including Deep-Learning (DL) were then used for autism prediction. Ingenuity Pathway Analysis (IPA) was further used to interrogate autism pathogenesis by identifying over-represented biological pathways. Highly significant CpG methylation changes were found in 230 loci (249 genes). Using only individual markers meeting a stringent p-value threshold criterion (p < 5 x 10^-8), achieved an AUC (95% CI) = 1.0 (0.80–1.00) with 97.5% sensitivity and 100.0% specificity. Conventional regression analysis using 3 CpG markers yielded an AUC (95% CI) = 1.00 (1.00–1.00) with 100.0% sensitivity and specificity each. Epigenetic dysregulation was identified in several important candidate genes including some previously linked to autism development e.g.: EIF4E, FYN, SHANK1 and VIM. We found epigenetic dysregulation of pathways involved in neuroinflammation signaling, synaptic long term potentiation, serotonin degradation, mTOR signaling and signaling by Rho-Family GTPases. Blood epigenomics and AI techniques achieved accurate newborn prediction of autism. Our results provide further evidence in support of a significant role of epigenetic alteration in autism pathogenesis.
Communicating complex genomic information: A counselling approach derived from research experience with Autism Spectrum Disorder
2018, Patient Education and Counseling
Individuals with Autism Spectrum Disorder (ASD) share characteristics (impairments in socialization and communication, and repetitive interests and behaviour), but differ in their developmental course, pattern of symptoms, and cognitive and language abilities. The development of standardized phenotyping has revealed ASD to clinically be vastly heterogeneous, ranging from milder presentations to more severe forms associated with profound intellectual disability. Some 100 genes have now been implicated in the etiology of ASD, and advances in genome-wide testing continue to yield new data at an unprecedented rate. As the translation of this data is incorporated into clinical care, genetic professionals/counsellors, as well as other health care providers, will benefit from guidelines and tools to effectively communicate such genomic information. Here, we present a model to facilitate communication regarding the complexities of ASD, where clinical and genetic heterogeneity, as well as overlapping neurological conditions are inherent. We outline an approach for counselling families about their genomic results grounded in our direct experience from counselling families participating in an ASD research study, and supported by rationale from the literature.
Urinary organophosphate insecticide metabolite concentrations during pregnancy and children's interpersonal, communication, repetitive, and stereotypic behaviors at 8 years of age: The home study
2017, Environmental Research
Citation Excerpt :
While the autistic phenotype develops and manifests in early childhood, the abnormal neural circuitry behind ASDs most likely develops in utero (London et al., 2007). Gestational exposures play an important role in ASD risk (Mendelsohn and Schaefer, 2008; Chomiak et al., 2013), but few genetic or environmental risk factors have been found to contribute definitively to ASD risk (Kalkbrenner et al., 2014). An in utero environmental exposure that may increase the risk of ASDs is the class of insecticides known as organophosphates (OP).
Prenatal exposure to organophosphate insecticides may be associated with autism spectrum disorders and related behaviors. This association may be modified by single nucleotide polymorphisms in the paraoxonase (PON1) enzyme.
We examined the relationship of prenatal organophosphate insecticide biomarkers with reciprocal social, repetitive, and stereotypic behaviors in 8-year old children, and modification of this relationship by child PON1 polymorphisms.
Among 224 pregnant women, we quantified concentrations of six nonspecific dialkyl phosphate (DAP) metabolites of organophosphate insecticides in two urine samples collected at ~16 and ~26 weeks gestation. When children were eight years old, we administered the Social Responsiveness Scale (SRS), a continuous measure of various dimensions of interpersonal behavior, communication, and repetitive/stereotypic behaviors. We estimated the association between a 10-fold increase in the sum of six DAP concentrations (ΣDAP) and SRS scores. We examined whether child PON1₁₉₂ and PON1_–108 genotypes modified this association.
After covariate adjustment, ΣDAP concentrations were not associated with SRS scores
[β=–1.2; 95% confidence interval (CI): –4.0, 1.6]. Among children with the PON1_–108TT genotype, ΣDAP concentrations were associated with 2.5-point higher (95% CI: −4.9, 9.8) SRS scores; however, the association was not different from the 1.8-point decrease (95% CI: −5.8, 2.2) among children with PON1_–108CT/CC genotypes (ΣDAP × PON1_–108 p-value =0.54). The association between ΣDAP concentrations and SRS scores was not modified by PON1₁₉₂ (ΣDAP × PON1₁₉₂ p-value =0.89).
In this cohort, prenatal urinary DAP concentrations were not associated with children's social behaviors; these associations were not modified by child PON1 genotype.
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Citation Excerpt :
Consequently, gene discovery promises to help elucidate the underlying pathophysiology of these syndromes and directed to eventually improve diagnosis, treatment, and prognosis of ASD. This strategy is highly motivated because less than 15% of diagnosed cases of autism have an underlying cause identified (Mendelsohn and Schaefer, 2008). The advent of high-throughput sequencing (HTS) of genetic data created the possibility to explore, with high precision and thorough coverage, a large volume of genetic information at one time.
Human neurons, generated from reprogrammed somatic cells isolated from live patients, bring a new perspective on the understanding of Autism Spectrum Disorders (ASD). The new technology can nicely complement other models for basic research and the development of therapeutic compounds aiming to revert or ameliorate the condition. Here, we discuss recent advances on the use of stem cells and other models to study ASDs, as well as their limitations, implications and future perspectives.

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Genetic Evaluation of Autism

Section snippets

Conclusion

Psychiatry Res

Semin Pediatr Neurol

J Pediatr

Genet Med

Genet Med

Genet Med

Genet Med

Int J Dev Neurosci

Pediatr Neurol

J Am Acad Child Adolesc Psychiatry

Autistic disturbances of affective contact

Nerv Child

Diagnostic and Statistical Manual of Mental Disorders Fourth Edition (DSM- IV)

Trajectory of development in adolescents and adults with autism

Ment Retard Dev Disabil Res Rev

Autism diagnostic interview-revised: A revised version of a diagnostic interview for caregivers of individuals with possible pervasive developmental disorders

J Autism Dev Disord

The autism diagnostic observation schedule-generic: A standard measure of social and communication deficits associated with the spectrum of autism

J Autism Dev Disord

Mental Health in the United States: Parental report of diagnosed autism in children aged 4-17 years–United States, 2003-2004

Morb Mortal Wkly Rep

Epidemiological surveys of autism and other pervasive developmental disorders: An update

J Autism Dev Disord

Etiologic yield of autistic spectrum disorders: A prospective study

Am J Med Genet C Semin Med Genet

The yield of the medical evaluation of children with pervasive developmental disorders

J Autism Dev Disord

Outcomes of genetic evaluation in children with pervasive developmental disorder

J Dev Behav Pediatr

The yield of laboratory investigations in children with infantile autism

J Neural Transm

Etiologic yield of autistic spectrum disorders: A prospective study

J Child Neurol

On the selection of patients with developmental delay/mental retardation and autism spectrum disorders for genetic studies

Am J Med Genet A