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Identification and Characterization of Genetic Components in Autism Spectrum Disorders 2020

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A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Genetics and Genomics".

Deadline for manuscript submissions: closed (30 January 2021) | Viewed by 94301

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Prof. Dr. Merlin G. Butler

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Departments of Psychiatry & Behavioral Sciences and Pediatrics, University of Kansas Medical Center, Kansas City, KS 66160, USA
Interests: Prader-Willi syndrome; fragile X syndrome; microdeletion syndromes; autism spectrum disorders; genetics of autism; obesity and intellectual disability; chromosomal microarray analysis; next generation sequencing; delineation of rare genetic disorders; genotype-phenotype relationships
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Dear Colleagues,

This journal issue is dedicated to the study of autism due to genetic factors, and will publish a collection of original research or review articles and studies related to this topic. Highlights in the field of autism research and the early identification and characterization of genetic components will be addressed. Autism spectrum disorders (ASD) are neurobehavioral disorders characterized by three behavioral domains and currently affect about 1% of children; they are, however, on the rise. Significant genetic contributions, factors and mechanisms underlie the causation of ASD. About 50% of individuals are diagnosed with chromosomal abnormalities, submicroscopic deletions or duplications, single gene disorders or variants and metabolic disturbances. The advancement of genetic technology with high resolution structural and microarrays with bioinformatics has led to the identification of well over 800 genes contributing to or associated with ASD. Further, next generation sequencing and other advances in diagnosing ASD at an early age may lead to potential pharmaceutical intervention/treatment that may vary from patient to patient depending on the specific structural and genomic findings, disturbed pathways and function with the associated characteristics of autism. New discoveries and the continued identification of candidate genes will be addressed, as will genotype–phenotype correlations. Evaluations requiring the use of advanced genetic testing options will be discussed along with psychiatric/behavioral co-morbidities, and a better delineation of ASD and approaches to treatment.

Prof. Dr. Merlin G. Butler
Guest Editor

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Keywords

microarray
next generation sequencing
copy number variants (CNVs)
candidate genes
candidate genes
gene polymorphisms and variants
single gene disorders associated with ASD
epigenetics
genetic causation
gene expression
non-coding RNAs
biomarkers
treatment

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Research

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24 pages, 2793 KiB

Open AccessArticle

Genomic, Clinical, and Behavioral Characterization of 15q11.2 BP1-BP2 Deletion (Burnside-Butler) Syndrome in Five Families

by Isaac Baldwin, Robin L. Shafer, Waheeda A. Hossain, Sumedha Gunewardena, Olivia J. Veatch, Matthew W. Mosconi and Merlin G. Butler

Int. J. Mol. Sci. 2021, 22(4), 1660; https://doi.org/10.3390/ijms22041660 - 7 Feb 2021

Cited by 11 | Viewed by 4843

Abstract

The 15q11.2 BP1-BP2 deletion (Burnside-Butler) syndrome is emerging as the most common cytogenetic finding in patients with neurodevelopmental or autism spectrum disorders (ASD) presenting for microarray genetic testing. Clinical findings in Burnside-Butler syndrome include developmental and motor delays, congenital abnormalities, learning and behavioral problems, and abnormal brain findings. To better define symptom presentation, we performed comprehensive cognitive and behavioral testing, collected medical and family histories, and conducted clinical genetic evaluations. The 15q11.2 BP1-BP2 region includes the TUBGCP5, CYFIP1, NIPA1, and NIPA2 genes. To determine if additional genomic variation outside of the 15q11.2 region influences expression of symptoms in Burnside-Butler syndrome, whole-exome sequencing was performed on the parents and affected children for the first time in five families with at least one parent and child with the 15q1l.2 BP1-BP2 deletion. In total, there were 453 genes with possibly damaging variants identified across all of the affected children. Of these, 99 genes had exclusively de novo variants and 107 had variants inherited exclusively from the parent without the deletion. There were three genes (APBB1, GOLGA2, and MEOX1) with de novo variants that encode proteins evidenced to interact with CYFIP1. In addition, one other gene of interest (FAT3) had variants inherited from the parent without the deletion and encoded a protein interacting with CYFIP1. The affected individuals commonly displayed a neurodevelopmental phenotype including ASD, speech delay, abnormal reflexes, and coordination issues along with craniofacial findings and orthopedic-related connective tissue problems. Of the 453 genes with variants, 35 were associated with ASD. On average, each affected child had variants in 6 distinct ASD-associated genes (

\bar{x}

= 6.33, sd = 3.01). In addition, 32 genes with variants were included on clinical testing panels from Clinical Laboratory Improvement Amendments (CLIA) approved and accredited commercial laboratories reflecting other observed phenotypes. Notably, the dataset analyzed in this study was small and reported results will require validation in larger samples as well as functional follow-up. Regardless, we anticipate that results from our study will inform future research into the genetic factors influencing diverse symptoms in patients with Burnside-Butler syndrome, an emerging disorder with a neurodevelopmental behavioral phenotype. Full article

(This article belongs to the Special Issue Identification and Characterization of Genetic Components in Autism Spectrum Disorders 2020)

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19 pages, 2679 KiB

Open AccessArticle

An Automated Functional Annotation Pipeline That Rapidly Prioritizes Clinically Relevant Genes for Autism Spectrum Disorder

by Olivia J. Veatch, Merlin G. Butler, Sarah H. Elsea, Beth A. Malow, James S. Sutcliffe and Jason H. Moore

Int. J. Mol. Sci. 2020, 21(23), 9029; https://doi.org/10.3390/ijms21239029 - 27 Nov 2020

Cited by 1 | Viewed by 2642

Abstract

Human genetic studies have implicated more than a hundred genes in Autism Spectrum Disorder (ASD). Understanding how variation in implicated genes influence expression of co-occurring conditions and drug response can inform more effective, personalized approaches for treatment of individuals with ASD. Rapidly translating this information into the clinic requires efficient algorithms to sort through the myriad of genes implicated by rare gene-damaging single nucleotide and copy number variants, and common variation detected in genome-wide association studies (GWAS). To pinpoint genes that are more likely to have clinically relevant variants, we developed a functional annotation pipeline. We defined clinical relevance in this project as any ASD associated gene with evidence indicating a patient may have a complex, co-occurring condition that requires direct intervention (e.g., sleep and gastrointestinal disturbances, attention deficit hyperactivity, anxiety, seizures, depression), or is relevant to drug development and/or approaches to maximizing efficacy and minimizing adverse events (i.e., pharmacogenomics). Starting with a list of all candidate genes implicated in all manifestations of ASD (i.e., idiopathic and syndromic), this pipeline uses databases that represent multiple lines of evidence to identify genes: (1) expressed in the human brain, (2) involved in ASD-relevant biological processes and resulting in analogous phenotypes in mice, (3) whose products are targeted by approved pharmaceutical compounds or possessing pharmacogenetic variation and (4) whose products directly interact with those of genes with variants recommended to be tested for by the American College of Medical Genetics (ACMG). Compared with 1000 gene sets, each with a random selection of human protein coding genes, more genes in the ASD set were annotated for each category evaluated (p ≤ 1.99 × 10⁻²). Of the 956 ASD-implicated genes in the full set, 18 were flagged based on evidence in all categories. Fewer genes from randomly drawn sets were annotated in all categories (x = 8.02, sd = 2.56, p = 7.75 × 10⁻⁴). Notably, none of the prioritized genes are represented among the 59 genes compiled by the ACMG, and 78% had a pathogenic or likely pathogenic variant in ClinVar. Results from this work should rapidly prioritize potentially actionable results from genetic studies and, in turn, inform future work toward clinical decision support for personalized care based on genetic testing. Full article

(This article belongs to the Special Issue Identification and Characterization of Genetic Components in Autism Spectrum Disorders 2020)

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19 pages, 1415 KiB

Open AccessArticle

Tracing Autism Traits in Large Multiplex Families to Identify Endophenotypes of the Broader Autism Phenotype

by Krysta J. Trevis, Natasha J. Brown, Cherie C. Green, Paul J. Lockhart, Tarishi Desai, Tanya Vick, Vicki Anderson, Emmanuel P. K. Pua, Melanie Bahlo, Martin B. Delatycki, Ingrid E. Scheffer and Sarah J. Wilson

Int. J. Mol. Sci. 2020, 21(21), 7965; https://doi.org/10.3390/ijms21217965 - 27 Oct 2020

Cited by 3 | Viewed by 3833

Abstract

Families comprising many individuals with Autism Spectrum Disorders (ASD) may carry a dominant predisposing mutation. We implemented rigorous phenotyping of the “Broader Autism Phenotype” (BAP) in large multiplex ASD families using a novel endophenotype approach for the identification and characterisation of distinct BAP endophenotypes. We evaluated ASD/BAP features using standardised tests and a semi-structured interview to assess social, intellectual, executive and adaptive functioning in 110 individuals, including two large multiplex families (Family A: 30; Family B: 35) and an independent sample of small families (n = 45). Our protocol identified four distinct psychological endophenotypes of the BAP that were evident across these independent samples, and showed high sensitivity (97%) and specificity (82%) for individuals classified with the BAP. Patterns of inheritance of identified endophenotypes varied between the two large multiplex families, supporting their utility for identifying genes in ASD. Full article

(This article belongs to the Special Issue Identification and Characterization of Genetic Components in Autism Spectrum Disorders 2020)

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23 pages, 2648 KiB

Open AccessArticle

Phenotypic Subtyping and Re-Analysis of Existing Methylation Data from Autistic Probands in Simplex Families Reveal ASD Subtype-Associated Differentially Methylated Genes and Biological Functions

by Elizabeth C. Lee and Valerie W. Hu

Int. J. Mol. Sci. 2020, 21(18), 6877; https://doi.org/10.3390/ijms21186877 - 19 Sep 2020

Cited by 9 | Viewed by 3398

Abstract

Autism spectrum disorder (ASD) describes a group of neurodevelopmental disorders with core deficits in social communication and manifestation of restricted, repetitive, and stereotyped behaviors. Despite the core symptomatology, ASD is extremely heterogeneous with respect to the severity of symptoms and behaviors. This heterogeneity presents an inherent challenge to all large-scale genome-wide omics analyses. In the present study, we address this heterogeneity by stratifying ASD probands from simplex families according to the severity of behavioral scores on the Autism Diagnostic Interview-Revised diagnostic instrument, followed by re-analysis of existing DNA methylation data from individuals in three ASD subphenotypes in comparison to that of their respective unaffected siblings. We demonstrate that subphenotyping of cases enables the identification of over 1.6 times the number of statistically significant differentially methylated regions (DMR) and DMR-associated genes (DAGs) between cases and controls, compared to that identified when all cases are combined. Our analyses also reveal ASD-related neurological functions and comorbidities that are enriched among DAGs in each phenotypic subgroup but not in the combined case group. Moreover, relational gene networks constructed with the DAGs reveal signaling pathways associated with specific functions and comorbidities. In addition, a network comprised of DAGs shared among all ASD subgroups and the combined case group is enriched in genes involved in inflammatory responses, suggesting that neuroinflammation may be a common theme underlying core features of ASD. These findings demonstrate the value of phenotype definition in methylomic analyses of ASD and may aid in the development of subtype-directed diagnostics and therapeutics. Full article

(This article belongs to the Special Issue Identification and Characterization of Genetic Components in Autism Spectrum Disorders 2020)

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Review

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22 pages, 1147 KiB

Open AccessReview

An Overview of the Main Genetic, Epigenetic and Environmental Factors Involved in Autism Spectrum Disorder Focusing on Synaptic Activity

by Elena Masini, Eleonora Loi, Ana Florencia Vega-Benedetti, Marinella Carta, Giuseppe Doneddu, Roberta Fadda and Patrizia Zavattari

Int. J. Mol. Sci. 2020, 21(21), 8290; https://doi.org/10.3390/ijms21218290 - 5 Nov 2020

Cited by 125 | Viewed by 19932

Abstract

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that affects social interaction and communication, with restricted interests, activity and behaviors. ASD is highly familial, indicating that genetic background strongly contributes to the development of this condition. However, only a fraction of the total number of genes thought to be associated with the condition have been discovered. Moreover, other factors may play an important role in ASD onset. In fact, it has been shown that parental conditions and in utero and perinatal factors may contribute to ASD etiology. More recently, epigenetic changes, including DNA methylation and micro RNA alterations, have been associated with ASD and proposed as potential biomarkers. This review aims to provide a summary of the literature regarding ASD candidate genes, mainly focusing on synapse formation and functionality and relevant epigenetic and environmental aspects acting in concert to determine ASD onset. Full article

(This article belongs to the Special Issue Identification and Characterization of Genetic Components in Autism Spectrum Disorders 2020)

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33 pages, 3650 KiB

Open AccessReview

Proteomics and Metabolomics Approaches towards a Functional Insight onto AUTISM Spectrum Disorders: Phenotype Stratification and Biomarker Discovery

by Maria Vittoria Ristori, Stefano Levi Mortera, Valeria Marzano, Silvia Guerrera, Pamela Vernocchi, Gianluca Ianiro, Simone Gardini, Giuliano Torre, Giovanni Valeri, Stefano Vicari, Antonio Gasbarrini and Lorenza Putignani

Int. J. Mol. Sci. 2020, 21(17), 6274; https://doi.org/10.3390/ijms21176274 - 30 Aug 2020

Cited by 44 | Viewed by 8617

Abstract

Autism spectrum disorders (ASDs) are neurodevelopmental disorders characterized by behavioral alterations and currently affect about 1% of children. Significant genetic factors and mechanisms underline the causation of ASD. Indeed, many affected individuals are diagnosed with chromosomal abnormalities, submicroscopic deletions or duplications, single-gene disorders or variants. However, a range of metabolic abnormalities has been highlighted in many patients, by identifying biofluid metabolome and proteome profiles potentially usable as ASD biomarkers. Indeed, next-generation sequencing and other omics platforms, including proteomics and metabolomics, have uncovered early age disease biomarkers which may lead to novel diagnostic tools and treatment targets that may vary from patient to patient depending on the specific genomic and other omics findings. The progressive identification of new proteins and metabolites acting as biomarker candidates, combined with patient genetic and clinical data and environmental factors, including microbiota, would bring us towards advanced clinical decision support systems (CDSSs) assisted by machine learning models for advanced ASD-personalized medicine. Herein, we will discuss novel computational solutions to evaluate new proteome and metabolome ASD biomarker candidates, in terms of their recurrence in the reviewed literature and laboratory medicine feasibility. Moreover, the way to exploit CDSS, performed by artificial intelligence, is presented as an effective tool to integrate omics data to electronic health/medical records (EHR/EMR), hopefully acting as added value in the near future for the clinical management of ASD. Full article

(This article belongs to the Special Issue Identification and Characterization of Genetic Components in Autism Spectrum Disorders 2020)

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18 pages, 622 KiB

Open AccessReview

Clinical Assessment, Genetics, and Treatment Approaches in Autism Spectrum Disorder (ASD)

by Ann Genovese and Merlin G. Butler

Int. J. Mol. Sci. 2020, 21(13), 4726; https://doi.org/10.3390/ijms21134726 - 2 Jul 2020

Cited by 131 | Viewed by 41315

Abstract

Autism spectrum disorder (ASD) consists of a genetically heterogenous group of neurobehavioral disorders characterized by impairment in three behavioral domains including communication, social interaction, and stereotypic repetitive behaviors. ASD affects more than 1% of children in Western societies, with diagnoses on the rise due to improved recognition, screening, clinical assessment, and diagnostic testing. We reviewed the role of genetic and metabolic factors which contribute to the causation of ASD with the use of new genetic technology. Up to 40 percent of individuals with ASD are now diagnosed with genetic syndromes or have chromosomal abnormalities including small DNA deletions or duplications, single gene conditions, or gene variants and metabolic disturbances with mitochondrial dysfunction. Although the heritability estimate for ASD is between 70 and 90%, there is a lower molecular diagnostic yield than anticipated. A likely explanation may relate to multifactorial causation with etiological heterogeneity and hundreds of genes involved with a complex interplay between inheritance and environmental factors influenced by epigenetics and capabilities to identify causative genes and their variants for ASD. Behavioral and psychiatric correlates, diagnosis and genetic evaluation with testing are discussed along with psychiatric treatment approaches and pharmacogenetics for selection of medication to treat challenging behaviors or comorbidities commonly seen in ASD. We emphasize prioritizing treatment based on targeted symptoms for individuals with ASD, as treatment will vary from patient to patient based on diagnosis, comorbidities, causation, and symptom severity. Full article

(This article belongs to the Special Issue Identification and Characterization of Genetic Components in Autism Spectrum Disorders 2020)

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Other

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21 pages, 25769 KiB

Open AccessCase Report

40-Hz Auditory Steady-State Response (ASSR) as a Biomarker of Genetic Defects in the SHANK3 Gene: A Case Report of 15-Year-Old Girl with a Rare Partial SHANK3 Duplication

by Anastasia K. Neklyudova, Galina V. Portnova, Anna B. Rebreikina, Victoria Yu Voinova, Svetlana G. Vorsanova, Ivan Y. Iourov and Olga V. Sysoeva

Int. J. Mol. Sci. 2021, 22(4), 1898; https://doi.org/10.3390/ijms22041898 - 14 Feb 2021

Cited by 9 | Viewed by 4732

Abstract

SHANK3 encodes a scaffold protein involved in postsynaptic receptor density in glutamatergic synapses, including those in the parvalbumin (PV)+ inhibitory neurons—the key players in the generation of sensory gamma oscillations, such as 40-Hz auditory steady-state response (ASSR). However, 40-Hz ASSR was not studied in relation to SHANK3 functioning. Here, we present a 15-year-old girl (SH01) with previously unreported duplication of the first seven exons of the SHANK3 gene (22q13.33). SH01’s electroencephalogram (EEG) during 40-Hz click trains of 500 ms duration binaurally presented with inter-trial intervals of 500–800 ms were compared with those from typically developing children (n = 32). SH01 was diagnosed with mild mental retardation and learning disabilities (F70.88), dysgraphia, dyslexia, and smaller vocabulary than typically developing (TD) peers. Her clinical phenotype resembled the phenotype of previously described patients with 22q13.33 microduplications (≈30 reported so far). SH01 had mild autistic symptoms but below the threshold for ASD diagnosis and microcephaly. No seizures or MRI abnormalities were reported. While SH01 had relatively preserved auditory event-related potential (ERP) with slightly attenuated P1, her 40-Hz ASSR was totally absent significantly deviating from TD’s ASSR. The absence of 40-Hz ASSR in patients with microduplication, which affected the SHANK3 gene, indicates deficient temporal resolution of the auditory system, which might underlie language problems and represent a neurophysiological biomarker of SHANK3 abnormalities. Full article

(This article belongs to the Special Issue Identification and Characterization of Genetic Components in Autism Spectrum Disorders 2020)

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8 pages, 2347 KiB

Open AccessCase Report

New Cav1.2 Channelopathy with High-Functioning Autism, Affective Disorder, Severe Dental Enamel Defects, a Short QT Interval, and a Novel CACNA1C Loss-of-Function Mutation

by Dominique Endres, Niels Decher, Isabell Röhr, Kirsty Vowinkel, Katharina Domschke, Katalin Komlosi, Andreas Tzschach, Birgitta Gläser, Miriam A. Schiele, Kimon Runge, Patrick Süß, Florian Schuchardt, Kathrin Nickel, Birgit Stallmeyer, Susanne Rinné, Eric Schulze-Bahr and Ludger Tebartz van Elst

Int. J. Mol. Sci. 2020, 21(22), 8611; https://doi.org/10.3390/ijms21228611 - 15 Nov 2020

Cited by 14 | Viewed by 3451

Abstract

Complex neuropsychiatric-cardiac syndromes can be genetically determined. For the first time, the authors present a syndromal form of short QT syndrome in a 34-year-old German male patient with extracardiac features with predominant psychiatric manifestation, namely a severe form of secondary high-functioning autism spectrum disorder (ASD), along with affective and psychotic exacerbations, and severe dental enamel defects (with rapid wearing off his teeth) due to a heterozygous loss-of-function mutation in the CACNA1C gene (NM_000719.6: c.2399A > C; p.Lys800Thr). This mutation was found only once in control databases; the mutated lysine is located in the Cav1.2 calcium channel, is highly conserved during evolution, and is predicted to affect protein function by most pathogenicity prediction algorithms. L-type Cav1.2 calcium channels are widely expressed in the brain and heart. In the case presented, electrophysiological studies revealed a prominent reduction in the current amplitude without changes in the gating behavior of the Cav1.2 channel, most likely due to a trafficking defect. Due to the demonstrated loss of function, the p.Lys800Thr variant was finally classified as pathogenic (ACMG class 4 variant) and is likely to cause a newly described Cav1.2 channelopathy. Full article

(This article belongs to the Special Issue Identification and Characterization of Genetic Components in Autism Spectrum Disorders 2020)

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